setting up bluesky firehose

.github/workflows/build_systems.yml

@@ -23,6 +23,6 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Build default package
-        run: "nixos-rebuild build --accept-flake-config --flake ./#${{ matrix.system }}"
+        run: "nixos-rebuild build --flake ./#${{ matrix.system }}"
       - name: copy to nix-cache
         run: nix copy --accept-flake-config --to unix:///host-nix/var/nix/daemon-socket/socket .#nixosConfigurations.${{ matrix.system }}.config.system.build.toplevel

.github/workflows/fix_eval_warnings.yml

@@ -0,0 +1,30 @@
+name: fix_eval_warnings
+on:
+  workflow_run:
+    workflows: ["build_systems"]
+    types: [completed]
+
+jobs:
+  check-warnings:
+    if: >-
+      github.event.workflow_run.conclusion != 'cancelled' &&
+      github.event.workflow_run.head_branch == 'main' &&
+      (github.event.workflow_run.event == 'push' || github.event.workflow_run.event == 'schedule')
+    runs-on: self-hosted
+    permissions:
+      contents: write
+      pull-requests: write
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - name: Fix eval warnings
+        env:
+          GH_TOKEN: ${{ secrets.GH_TOKEN_FOR_UPDATES }}
+        run: >-
+          nix develop .#devShells.x86_64-linux.default -c
+          python -m python.eval_warnings.main
+          --run-id "${{ github.event.workflow_run.id }}"
+          --repo "${{ github.repository }}"
+          --ollama-url "${{ secrets.OLLAMA_URL }}"
+          --run-url "${{ github.event.workflow_run.html_url }}"

.github/workflows/merge_flake_lock_update.yml

@@ -6,18 +6,24 @@ on:
 
 jobs:
   merge:
-    runs-on: self-hosted
+    runs-on: ubuntu-latest
 
     permissions:
       contents: write
       pull-requests: write
 
     steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
       - name: merge_flake_lock_update
-        run: >-
+        run: |
-          nix develop .#devShells.x86_64-linux.default -c
+          pr_number=$(gh pr list --state open --author RichieCahill --label flake_lock_update --json number --jq '.[0].number')
-          python -m python.gitea_flake_lock merge
+          echo "pr_number=$pr_number" >> $GITHUB_ENV
-          --repo "${{ github.repository }}"
+          if [ -n "$pr_number" ]; then
+            gh pr merge "$pr_number" --rebase
+          else
+            echo "No open PR found with label flake_lock_update"
+          fi
         env:
-          GITEA_TOKEN: ${{ secrets.GITEA_TOKEN }}
+          GITHUB_TOKEN: ${{ secrets.GH_TOKEN_FOR_UPDATES }}
-          GITEA_URL: https://gitea.tmmworkshop.com

.github/workflows/pytest.yml

@@ -1,13 +1,13 @@
 name: pytest
 
 on:
-  workflow_dispatch:
   push:
     branches:
       - main
   pull_request:
     branches:
       - main
+  merge_group:
 
 jobs:
   pytest:

.github/workflows/update-flake-lock.yml

@@ -6,21 +6,18 @@ on:
 
 jobs:
   lockfile:
-    runs-on: self-hosted
+    runs-on: ubuntu-latest
-    permissions:
-      actions: write
-      contents: write
-      pull-requests: write
     steps:
       - name: Checkout repository
         uses: actions/checkout@v4
+      - name: Install Nix
+        uses: DeterminateSystems/nix-installer-action@main
       - name: Update flake.lock
-        run: nix flake update
+        uses: DeterminateSystems/update-flake-lock@main
-      - name: Create or update flake.lock PR
+        with:
-        env:
+          token: ${{ secrets.GH_TOKEN_FOR_UPDATES }}
-          GITEA_TOKEN: ${{ secrets.GITEA_TOKEN }}
+          pr-title: "Update flake.lock"
-          GITEA_URL: https://gitea.tmmworkshop.com
+          pr-labels: |
-        run: >-
+            dependencies
-          nix develop .#devShells.x86_64-linux.default -c
+            automated
-          python -m python.gitea_flake_lock update
+            flake_lock_update
-          --repo "${{ github.repository }}"

.gitignore

@@ -169,7 +169,3 @@ test.*
 # Frontend build output
 frontend/dist/
 frontend/node_modules/
-
-# data from testing llms
-data/*
-.ebook_search_bm25

.vscode/settings.json

@@ -40,6 +40,7 @@
     "cgroupdriver",
     "charliermarsh",
     "Checkpointing",
+    "cloudflared",
     "codellama",
     "codezombiech",
     "compactmode",
@@ -203,7 +204,6 @@
     "peerconnection",
     "PESKYFOX",
     "PGID",
-    "pgvector",
     "pipewire",
     "pkgs",
     "plugdev",
@@ -308,7 +308,6 @@
     "usernamehw",
     "userprefs",
     "vaninventory",
-    "vdev",
     "vfat",
     "victron",
     "virt",

AGENTS.md

@@ -0,0 +1,12 @@
+## Dev environment tips
+
+- use treefmt to format all files
+- make python code ruff compliant
+- use pytest to test python code
+- always use the minimum amount of complexity
+- if judgment calls are easy to reverse make them. if not ask me first
+- Match existing code style.
+- Use builtin helpers getenv() over os.environ.get.
+- Prefer single-purpose functions over “do everything” helpers.
+- Avoid compatibility branches like PG_USER and POSTGRESQL_URL unless requested.
+- Keep helpers only if reused or they simplify the code otherwise inline.

common/global/default.nix

@@ -23,10 +23,7 @@
   boot = {
     tmp.useTmpfs = true;
     kernelPackages = lib.mkDefault pkgs.linuxPackages_6_12;
-    zfs = {
+    zfs.package = lib.mkDefault pkgs.zfs_2_4;
-      package = lib.mkDefault pkgs.zfs_2_4;
-      forceImportRoot = lib.mkDefault false;
-    };
   };
 
   hardware.enableRedistributableFirmware = true;
@@ -40,17 +37,10 @@
 
   nixpkgs = {
     overlays = builtins.attrValues outputs.overlays;
-    config = {
+    config.allowUnfree = true;
-      allowUnfree = true;
-      permittedInsecurePackages = [
-        "openssl-1.1.1w" # This is for discord-canary
-      ];
-    };
   };
 
   services = {
-    dbus.implementation = "dbus";
-
     # firmware update
     fwupd.enable = true;
 

common/global/nix.nix

@@ -34,7 +34,6 @@ in
       warn-dirty = false;
       flake-registry = ""; # disable global flake registries
       connect-timeout = 10;
-      download-buffer-size = 536870912;
       fallback = true;
     };
 

common/optional/monitoring-agent.nix

@@ -1,256 +0,0 @@
-{
-  config,
-  lib,
-  pkgs,
-  ...
-}:
-let
-  monitoringInterface = "ztwfunumly";
-  nodeTextfileDir = "/var/lib/prometheus-node-exporter-textfile";
-
-  mkProcessNameTemplate =
-    perPid: template: if perPid then "${template}:{{.PID}}:{{.StartTime}}" else template;
-
-  mkProcessMatchers = perPid: [
-    {
-      name = mkProcessNameTemplate perPid "{{.Username}}:{{.Matches.Module}}";
-      cmdline = [ "^/nix/store[^ ]*/bin/python[^ ]* -m (?P<Module>[^ ]+)" ];
-    }
-    {
-      name = mkProcessNameTemplate perPid "{{.Username}}:{{.Matches.Wrapped}}";
-      cmdline = [
-        "^/nix/store[^ ]*/bin/python[^ ]* /nix/store[^ ]*/bin/\\.?(?P<Wrapped>[^ /]+?)(?:-wrapped)?(?:\\s|$)"
-      ];
-    }
-    {
-      name = mkProcessNameTemplate perPid "{{.Username}}:{{.Matches.Wrapped}}";
-      cmdline = [
-        "^/nix/store[^ ]*/bin/node /nix/store[^ ]*-(?P<Wrapped>[A-Za-z0-9._+-]+)-[0-9][^ /]*/"
-      ];
-    }
-    {
-      name = mkProcessNameTemplate perPid "{{.Username}}:{{.Matches.Wrapped}}";
-      cmdline = [ "^/nix/store[^ ]*/(?:bin/|lib/[^ ]*/)?\\.?(?P<Wrapped>[^ /]+?)(?:-wrapped)?(?:\\s|$)" ];
-    }
-    {
-      name = mkProcessNameTemplate perPid "{{.Username}}:{{.ExeBase}}";
-      cmdline = [ ".+" ];
-    }
-  ];
-
-  perPidConfig = pkgs.writeText "process-exporter-per-pid.yaml" (
-    builtins.toJSON {
-      process_names = mkProcessMatchers true;
-    }
-  );
-
-  zpoolLatencyScript = pkgs.writeShellScript "zpool-latency-exporter" ''
-        set -euo pipefail
-
-        out_dir=${lib.escapeShellArg nodeTextfileDir}
-        host=${lib.escapeShellArg config.networking.hostName}
-        tmp_file="$(mktemp "$out_dir/zpool.prom.XXXXXX")"
-        trap 'rm -f "$tmp_file"' EXIT
-
-        pools="$(zpool list -H -o name | paste -sd, -)"
-
-        cat >"$tmp_file" <<'EOF'
-    # HELP zpool_iostat_total_wait_read_ns Average total read wait time reported by zpool iostat.
-    # TYPE zpool_iostat_total_wait_read_ns gauge
-    # HELP zpool_iostat_total_wait_write_ns Average total write wait time reported by zpool iostat.
-    # TYPE zpool_iostat_total_wait_write_ns gauge
-    # HELP zpool_iostat_disk_wait_read_ns Average disk read wait time reported by zpool iostat.
-    # TYPE zpool_iostat_disk_wait_read_ns gauge
-    # HELP zpool_iostat_disk_wait_write_ns Average disk write wait time reported by zpool iostat.
-    # TYPE zpool_iostat_disk_wait_write_ns gauge
-    # HELP zpool_iostat_syncq_wait_read_ns Average synchronous queue read wait time reported by zpool iostat.
-    # TYPE zpool_iostat_syncq_wait_read_ns gauge
-    # HELP zpool_iostat_syncq_wait_write_ns Average synchronous queue write wait time reported by zpool iostat.
-    # TYPE zpool_iostat_syncq_wait_write_ns gauge
-    # HELP zpool_iostat_asyncq_wait_read_ns Average asynchronous queue read wait time reported by zpool iostat.
-    # TYPE zpool_iostat_asyncq_wait_read_ns gauge
-    # HELP zpool_iostat_asyncq_wait_write_ns Average asynchronous queue write wait time reported by zpool iostat.
-    # TYPE zpool_iostat_asyncq_wait_write_ns gauge
-    EOF
-
-        zpool iostat -Hplvy -y 1 1 | awk -F '\t' -v host="$host" -v pools="$pools" '
-          function esc(str, out) {
-            out = str
-            gsub(/\\/, "\\\\", out)
-            gsub(/"/, "\\\"", out)
-            return out
-          }
-
-          function emit(metric, pool, vdev, value) {
-            if (value == "" || value == "-") {
-              return
-            }
-
-            printf "%s{host=\"%s\",pool=\"%s\",vdev=\"%s\"} %s\n",
-              metric,
-              esc(host),
-              esc(pool),
-              esc(vdev),
-              value
-          }
-
-          BEGIN {
-            split(pools, pool_names, ",")
-            for (idx in pool_names) {
-              if (pool_names[idx] != "") {
-                known_pools[pool_names[idx]] = 1
-              }
-            }
-          }
-
-          NF == 0 {
-            next
-          }
-
-          {
-            row_name = $1
-
-            if (row_name in known_pools) {
-              current_pool = row_name
-              current_vdev = "_pool"
-            } else if (current_pool == "") {
-              next
-            } else {
-              current_vdev = row_name
-            }
-
-            emit("zpool_iostat_total_wait_read_ns", current_pool, current_vdev, $8)
-            emit("zpool_iostat_total_wait_write_ns", current_pool, current_vdev, $9)
-            emit("zpool_iostat_disk_wait_read_ns", current_pool, current_vdev, $10)
-            emit("zpool_iostat_disk_wait_write_ns", current_pool, current_vdev, $11)
-            emit("zpool_iostat_syncq_wait_read_ns", current_pool, current_vdev, $12)
-            emit("zpool_iostat_syncq_wait_write_ns", current_pool, current_vdev, $13)
-            emit("zpool_iostat_asyncq_wait_read_ns", current_pool, current_vdev, $14)
-            emit("zpool_iostat_asyncq_wait_write_ns", current_pool, current_vdev, $15)
-          }
-        ' >>"$tmp_file"
-
-        mv "$tmp_file" "$out_dir/zpool.prom"
-        trap - EXIT
-  '';
-in
-{
-  networking.firewall.interfaces.${monitoringInterface}.allowedTCPPorts = [
-    9100
-    9134
-    9256
-    9257
-    9633
-  ];
-
-  services.prometheus.exporters = {
-    node = {
-      enable = true;
-      enabledCollectors = [
-        "pressure"
-        "processes"
-        "systemd"
-      ];
-      extraFlags = [ "--collector.textfile.directory=${nodeTextfileDir}" ];
-    };
-
-    process = {
-      enable = true;
-      user = "root";
-      group = "root";
-      settings.process_names = mkProcessMatchers false;
-      extraFlags = [
-        "-gather-smaps=false"
-        "-remove-empty-groups=true"
-        "-threads=false"
-      ];
-    };
-
-    smartctl.enable = true;
-    zfs.enable = true;
-  };
-
-  programs.atop = {
-    enable = true;
-    atopService.enable = true;
-    atopRotateTimer.enable = true;
-    atopacctService.enable = true;
-    settings.interval = 30;
-  };
-
-  systemd = {
-    services = {
-      prometheus-process-pid-exporter = {
-        description = "Prometheus process exporter with per-PID naming";
-        wantedBy = [ "multi-user.target" ];
-        after = [ "network.target" ];
-        serviceConfig = {
-          ExecStart = ''
-            ${pkgs.prometheus-process-exporter}/bin/process-exporter \
-              --web.listen-address 0.0.0.0:9257 \
-              --config.path ${perPidConfig} \
-              -children=false \
-              -gather-smaps=false \
-              -remove-empty-groups=true \
-              -threads=false
-          '';
-          User = "root";
-          Group = "root";
-          Restart = "always";
-          WorkingDirectory = "/tmp";
-          CapabilityBoundingSet = [ "" ];
-          DeviceAllow = [ "" ];
-          LockPersonality = true;
-          MemoryDenyWriteExecute = true;
-          NoNewPrivileges = true;
-          PrivateDevices = true;
-          PrivateTmp = true;
-          ProtectClock = true;
-          ProtectControlGroups = true;
-          ProtectHome = true;
-          ProtectHostname = true;
-          ProtectKernelLogs = true;
-          ProtectKernelModules = true;
-          ProtectKernelTunables = true;
-          ProtectSystem = "strict";
-          RemoveIPC = true;
-          RestrictAddressFamilies = [
-            "AF_INET"
-            "AF_INET6"
-          ];
-          RestrictNamespaces = true;
-          RestrictRealtime = true;
-          RestrictSUIDSGID = true;
-          SystemCallArchitectures = "native";
-          UMask = "0077";
-        };
-      };
-
-      zpool-latency-exporter = {
-        description = "Exports ZFS latency metrics for node_exporter textfile collection";
-        after = [ "zfs-import.target" ];
-        requires = [ "zfs-import.target" ];
-        path = [
-          config.boot.zfs.package
-          pkgs.coreutils
-          pkgs.gawk
-        ];
-        serviceConfig = {
-          Type = "oneshot";
-          ExecStart = zpoolLatencyScript;
-        };
-      };
-    };
-
-    timers.zpool-latency-exporter = {
-      wantedBy = [ "timers.target" ];
-      timerConfig = {
-        OnBootSec = "2m";
-        OnUnitActiveSec = "60s";
-        Unit = "zpool-latency-exporter.service";
-      };
-    };
-
-    tmpfiles.rules = [ "d ${nodeTextfileDir} 0755 root root - -" ];
-  };
-}

common/optional/syncthing_base.nix

@@ -12,7 +12,7 @@
       brain.id = "SSCGIPI-IV3VYKB-TRNIJE3-COV4T2H-CDBER7F-I2CGHYA-NWOEUDU-3T5QAAN"; # cspell:disable-line
       ipad.id = "KI76T3X-SFUGV2L-VSNYTKR-TSIUV5L-SHWD3HE-GQRGRCN-GY4UFMD-CW6Z6AX"; # cspell:disable-line
       jeeves.id = "ICRHXZW-ECYJCUZ-I4CZ64R-3XRK7CG-LL2HAAK-FGOHD22-BQA4AI6-5OAL6AG"; # cspell:disable-line
-      phone.id = "JPVQKQW-CFXOJXT-Q5G5F3H-QIDHDRE-GKHPTQB-GXZUQSP-U7FR7F7-INP3AAH"; # cspell:disable-line
+      phone.id = "TBRULKD-7DZPGGZ-F6LLB7J-MSO54AY-7KLPBIN-QOFK6PX-W2HBEWI-PHM2CQI"; # cspell:disable-line
       rhapsody-in-green.id = "ASL3KC4-3XEN6PA-7BQBRKE-A7JXLI6-DJT43BY-Q4WPOER-7UALUAZ-VTPQ6Q4"; # cspell:disable-line
     };
   };

common/optional/update.nix

@@ -4,7 +4,7 @@
     flags = [ "--accept-flake-config" ];
     randomizedDelaySec = "1h";
     persistent = true;
-    flake = "git+https://gitea.tmmworkshop.com/richie/dotfiles?ref=main";
+    flake = "github:RichieCahill/dotfiles";
     allowReboot = true;
     dates = "Sat *-*-* 06:00:00";
   };

docs/zfs_failed_root_import_recovry.md

@@ -1,76 +0,0 @@
-# ZFS failed root import recovery
-
-## Fast path
-
-If the machine fails to boot because ZFS refuses to import `root_pool`:
-
-### GRUB
-
-1. At the bootloader menu, select the normal NixOS entry.
-2. Press `e`.
-3. Find the line that starts with `linux`.
-4. Append this to the end of that line:
-
-```text
-zfs_force=1
-```
-
-5. Boot once with `Ctrl+x` or `F10`.
-
-### systemd-boot
-
-1. At the bootloader menu, highlight the normal NixOS entry.
-2. Press `e`.
-3. Append this to the end of the options line:
-
-```text
-zfs_force=1
-```
-
-4. Press `Enter` to boot once.
-
-## After boot
-
-Run:
-
-```bash
-sudo zpool status
-sudo zpool import
-journalctl -b | rg "ZFS|zfs|import|root_pool"
-```
-
-## Expected result
-
-`sudo zpool status` should show `root_pool` as `ONLINE`.
-
-## Reboot test
-
-Run:
-
-```bash
-sudo reboot
-```
-
-Do not add `zfs_force=1` the second time.
-
-## If it still fails
-
-Boot once more with:
-
-```text
-zfs_force=1
-```
-
-Then run:
-
-```bash
-sudo zpool status -v
-sudo zpool history | tail -n 50
-journalctl -b | rg "ZFS|zfs|import|root_pool"
-```
-
-## Notes
-
-- Root pool name is `root_pool`.
-- This is a one-time recovery path after disk moves, controller changes, dirty exports, or interrupted imports.
-- Some hosts also need the LUKS unlock USB key inserted before boot.

flake.lock

@@ -8,11 +8,11 @@
       },
       "locked": {
         "dir": "pkgs/firefox-addons",
-        "lastModified": 1781150628,
+        "lastModified": 1773979456,
-        "narHash": "sha256-b4mp8l3qWuSCyYYo9HSngDtcB3PpecYiOXjULrjwwlw=",
+        "narHash": "sha256-9kBMJ5IvxqNlkkj/swmE8uK1Sc7TL/LIRUI958m7uBM=",
         "owner": "rycee",
         "repo": "nur-expressions",
-        "rev": "753319310f4673a2dabbfab87482187b40bf9bac",
+        "rev": "81e28f47ac18d9e89513929c77e711e657b64851",
         "type": "gitlab"
       },
       "original": {
@@ -29,11 +29,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1781189114,
+        "lastModified": 1774007980,
-        "narHash": "sha256-5inaamLgUMWy+MOBE9ChF9QAF1o/74LFuHkI0W/9rqc=",
+        "narHash": "sha256-FOnZjElEI8pqqCvB6K/1JRHTE8o4rer8driivTpq2uo=",
         "owner": "nix-community",
         "repo": "home-manager",
-        "rev": "486595d2cf49cfcd649b58a284fa11ac0e34da22",
+        "rev": "9670de2921812bc4e0452f6e3efd8c859696c183",
         "type": "github"
       },
       "original": {
@@ -43,15 +43,12 @@
       }
     },
     "nixos-hardware": {
-      "inputs": {
-        "nixpkgs": "nixpkgs"
-      },
       "locked": {
-        "lastModified": 1781168557,
+        "lastModified": 1774018263,
-        "narHash": "sha256-LOnLQ2tpYF9gqIDDr3+j3DbpJJr/QCH6zPRT2GzEUOE=",
+        "narHash": "sha256-HHYEwK1A22aSaxv2ibhMMkKvrDGKGlA/qObG4smrSqc=",
         "owner": "nixos",
         "repo": "nixos-hardware",
-        "rev": "6358ff76821101c178e3ab4919a62799bfe3652e",
+        "rev": "2d4b4717b2534fad5c715968c1cece04a172b365",
         "type": "github"
       },
       "original": {
@@ -63,24 +60,27 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1767892417,
+        "lastModified": 1773821835,
-        "narHash": "sha256-8bW3q88CEg2u4hSP66Vf4lpbLonHz7hqDNBMcCY7E9U=",
+        "narHash": "sha256-TJ3lSQtW0E2JrznGVm8hOQGVpXjJyXY2guAxku2O9A4=",
-        "rev": "3497aa5c9457a9d88d71fa93a4a8368816fbeeba",
+        "owner": "nixos",
-        "type": "tarball",
+        "repo": "nixpkgs",
-        "url": "https://releases.nixos.org/nixos/unstable/nixos-26.05pre924538.3497aa5c9457/nixexprs.tar.xz"
+        "rev": "b40629efe5d6ec48dd1efba650c797ddbd39ace0",
+        "type": "github"
       },
       "original": {
-        "type": "tarball",
+        "owner": "nixos",
-        "url": "https://channels.nixos.org/nixos-unstable/nixexprs.tar.xz"
+        "ref": "nixos-unstable",
+        "repo": "nixpkgs",
+        "type": "github"
       }
     },
     "nixpkgs-master": {
       "locked": {
-        "lastModified": 1781229721,
+        "lastModified": 1774051532,
-        "narHash": "sha256-ORvqDbb/LYxiJljGIejapjkc/kJbVote2N1WSb9W45I=",
+        "narHash": "sha256-d3CGMweyYIcPuTj5BKq+1Lx4zwlgL31nVtN647tOZKo=",
         "owner": "nixos",
         "repo": "nixpkgs",
-        "rev": "173d0ad7a974f8543a9ab01d2271b2e290341b33",
+        "rev": "8620c0b5cc8fbe76502442181be1d0514bc3a1b7",
         "type": "github"
       },
       "original": {
@@ -106,28 +106,12 @@
         "type": "github"
       }
     },
-    "nixpkgs_2": {
-      "locked": {
-        "lastModified": 1781074563,
-        "narHash": "sha256-md8WlXOlfnIeHeOScMTTHFyf2d6iaTwPl2apR5EQ3P4=",
-        "owner": "nixos",
-        "repo": "nixpkgs",
-        "rev": "9ae611a455b90cf061d8f332b977e387bda8e1ca",
-        "type": "github"
-      },
-      "original": {
-        "owner": "nixos",
-        "ref": "nixos-unstable",
-        "repo": "nixpkgs",
-        "type": "github"
-      }
-    },
     "root": {
       "inputs": {
         "firefox-addons": "firefox-addons",
         "home-manager": "home-manager",
         "nixos-hardware": "nixos-hardware",
-        "nixpkgs": "nixpkgs_2",
+        "nixpkgs": "nixpkgs",
         "nixpkgs-master": "nixpkgs-master",
         "nixpkgs-stable": "nixpkgs-stable",
         "sops-nix": "sops-nix",
@@ -141,11 +125,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1780547341,
+        "lastModified": 1773889674,
-        "narHash": "sha256-Gq8KNx5A7hBB3uGJaj6eQfLDIz5YdLu92gqBcvHvoUo=",
+        "narHash": "sha256-+ycaiVAk3MEshJTg35cBTUa0MizGiS+bgpYw/f8ohkg=",
         "owner": "Mic92",
         "repo": "sops-nix",
-        "rev": "9ed65852b6257fbeae4355bc24ecfea307ca759a",
+        "rev": "29b6519f3e0780452bca0ac0be4584f04ac16cc5",
         "type": "github"
       },
       "original": {

frontend/.gitignore

@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?

overlays/default.nix

@@ -17,41 +17,16 @@
 
   python-env = final: _prev: {
     my_python = final.python314.withPackages (
-      ps:
+      ps: with ps; [
-      let
-        bm25s = ps.buildPythonPackage rec {
-          pname = "bm25s";
-          version = "0.3.9";
-          pyproject = true;
-
-          src = final.fetchPypi {
-            inherit pname version;
-            hash = "sha256-iVxnnZUrfeg1XttfPhpiCh4vKU0dQrkZvwghzOLi9Zc=";
-          };
-
-          build-system = [ ps.setuptools ];
-          dependencies = with ps; [
-            numpy
-            scipy
-          ];
-
-          pythonImportsCheck = [ "bm25s" ];
-        };
-      in
-      with ps;
-      [
         alembic
         apprise
         apscheduler
-        beautifulsoup4
+        confluent-kafka
-        ebooklib
         fastapi
         fastapi-cli
         httpx
         mypy
-        numpy
         orjson
-        pgvector
         polars
         psycopg
         pydantic
@@ -65,10 +40,8 @@
         scalene
         sqlalchemy
         sqlalchemy
-        bm25s
         tenacity
         textual
-        tiktoken
         tinytuya
         typer
         websockets

pyproject.toml

@@ -26,7 +26,6 @@ dependencies = [
 [project.scripts]
 database = "python.database_cli:app"
 van-inventory = "python.van_inventory.main:serve"
-whisper-transcribe = "python.tools.whisper.transcribe:main"
 
 [dependency-groups]
 dev = [
@@ -51,7 +50,6 @@ lint.ignore = [
     "COM812", # (TEMP) conflicts when used with the formatter
     "ISC001", # (TEMP) conflicts when used with the formatter
     "S603",   # (PERM) This is known to cause a false positive
-    "S607",   # (PERM) This is becoming a consistent annoyance
 ]
 
 [tool.ruff.lint.per-file-ignores]
@@ -80,10 +78,15 @@ lint.ignore = [
 "python/congress_tracker/**" = [
     "TC003", # (perm) this creates issues because sqlalchemy uses these at runtime
 ]
-
+"python/eval_warnings/**" = [
+    "S607", # (perm) gh and git are expected on PATH in the runner environment
+]
 "python/alembic/**" = [
     "INP001", # (perm) this creates LSP issues for alembic
 ]
+"python/signal_bot/**" = [
+    "D107", # (perm) class docstrings cover __init__
+]
 
 [tool.ruff.lint.pydocstyle]
 convention = "google"

python/alembic/data_science_dev/versions/2026_03_24-adding_failedingestion_2f43120e3ffc.py

@@ -0,0 +1,50 @@
+"""adding FailedIngestion.
+
+Revision ID: 2f43120e3ffc
+Revises: f99be864fe69
+Create Date: 2026-03-24 23:46:17.277897
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import sqlalchemy as sa
+from alembic import op
+
+from python.orm import DataScienceDevBase
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+# revision identifiers, used by Alembic.
+revision: str = "2f43120e3ffc"
+down_revision: str | None = "f99be864fe69"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+schema = DataScienceDevBase.schema_name
+
+
+def upgrade() -> None:
+    """Upgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table(
+        "failed_ingestion",
+        sa.Column("raw_line", sa.Text(), nullable=False),
+        sa.Column("error", sa.Text(), nullable=False),
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_failed_ingestion")),
+        schema=schema,
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table("failed_ingestion", schema=schema)
+    # ### end Alembic commands ###

python/alembic/data_science_dev/versions/2026_03_25-attach_partitions_to_posts.py

@@ -0,0 +1,80 @@
+"""Attach all partition tables to the posts parent table.
+
+Alembic autogenerate creates partition tables as standalone tables but does not
+emit the ALTER TABLE ... ATTACH PARTITION statements needed for PostgreSQL to
+route inserts to the correct partition.
+
+Revision ID: a1b2c3d4e5f6
+Revises: 605b1794838f
+Create Date: 2026-03-25 10:00:00.000000
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+from alembic import op
+from sqlalchemy import text
+
+from python.orm import DataScienceDevBase
+from python.orm.data_science_dev.posts.partitions import (
+    PARTITION_END_YEAR,
+    PARTITION_START_YEAR,
+    iso_weeks_in_year,
+    week_bounds,
+)
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+# revision identifiers, used by Alembic.
+revision: str = "a1b2c3d4e5f6"
+down_revision: str | None = "605b1794838f"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+schema = DataScienceDevBase.schema_name
+
+ALREADY_ATTACHED_QUERY = text("""
+    SELECT inhrelid::regclass::text
+    FROM pg_inherits
+    WHERE inhparent = :parent::regclass
+""")
+
+
+def upgrade() -> None:
+    """Attach all weekly partition tables to the posts parent table."""
+    connection = op.get_bind()
+    already_attached = {
+        row[0]
+        for row in connection.execute(
+            ALREADY_ATTACHED_QUERY, {"parent": f"{schema}.posts"}
+        )
+    }
+
+    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
+        for week in range(1, iso_weeks_in_year(year) + 1):
+            table_name = f"posts_{year}_{week:02d}"
+            qualified_name = f"{schema}.{table_name}"
+            if qualified_name in already_attached:
+                continue
+            start, end = week_bounds(year, week)
+            start_str = start.strftime("%Y-%m-%d %H:%M:%S")
+            end_str = end.strftime("%Y-%m-%d %H:%M:%S")
+            op.execute(
+                f"ALTER TABLE {schema}.posts "
+                f"ATTACH PARTITION {qualified_name} "
+                f"FOR VALUES FROM ('{start_str}') TO ('{end_str}')"
+            )
+
+
+def downgrade() -> None:
+    """Detach all weekly partition tables from the posts parent table."""
+    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
+        for week in range(1, iso_weeks_in_year(year) + 1):
+            table_name = f"posts_{year}_{week:02d}"
+            op.execute(
+                f"ALTER TABLE {schema}.posts "
+                f"DETACH PARTITION {schema}.{table_name}"
+            )

python/alembic/env.py

@@ -3,6 +3,7 @@
 from __future__ import annotations
 
 import logging
+import re
 import sys
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Literal

python/alembic/richie/versions/2026_03_29-removed_ds_table_from_richie_db_c8a794340928.py

@@ -1,187 +0,0 @@
-"""removed ds table from richie DB.
-
-Revision ID: c8a794340928
-Revises: 6b275323f435
-Create Date: 2026-03-29 15:29:23.643146
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-import sqlalchemy as sa
-from alembic import op
-from sqlalchemy.dialects import postgresql
-
-from python.orm import RichieBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "c8a794340928"
-down_revision: str | None = "6b275323f435"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = RichieBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_table("vote_record", schema=schema)
-    op.drop_index(op.f("ix_vote_congress_chamber"), table_name="vote", schema=schema)
-    op.drop_index(op.f("ix_vote_date"), table_name="vote", schema=schema)
-    op.drop_index(op.f("ix_legislator_bioguide_id"), table_name="legislator", schema=schema)
-    op.drop_table("legislator", schema=schema)
-    op.drop_table("vote", schema=schema)
-    op.drop_index(op.f("ix_bill_congress"), table_name="bill", schema=schema)
-    op.drop_table("bill", schema=schema)
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table(
-        "vote",
-        sa.Column("congress", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("chamber", sa.VARCHAR(), autoincrement=False, nullable=False),
-        sa.Column("session", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("number", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("vote_type", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("question", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("result", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("result_text", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("vote_date", sa.DATE(), autoincrement=False, nullable=False),
-        sa.Column("yea_count", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("nay_count", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("not_voting_count", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("present_count", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("bill_id", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("id", sa.INTEGER(), autoincrement=True, nullable=False),
-        sa.Column(
-            "created",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.Column(
-            "updated",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.ForeignKeyConstraint(["bill_id"], [f"{schema}.bill.id"], name=op.f("fk_vote_bill_id_bill")),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_vote")),
-        sa.UniqueConstraint(
-            "congress",
-            "chamber",
-            "session",
-            "number",
-            name=op.f("uq_vote_congress_chamber_session_number"),
-            postgresql_include=[],
-            postgresql_nulls_not_distinct=False,
-        ),
-        schema=schema,
-    )
-    op.create_index(op.f("ix_vote_date"), "vote", ["vote_date"], unique=False, schema=schema)
-    op.create_index(op.f("ix_vote_congress_chamber"), "vote", ["congress", "chamber"], unique=False, schema=schema)
-    op.create_table(
-        "vote_record",
-        sa.Column("vote_id", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("legislator_id", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("position", sa.VARCHAR(), autoincrement=False, nullable=False),
-        sa.ForeignKeyConstraint(
-            ["legislator_id"],
-            [f"{schema}.legislator.id"],
-            name=op.f("fk_vote_record_legislator_id_legislator"),
-            ondelete="CASCADE",
-        ),
-        sa.ForeignKeyConstraint(
-            ["vote_id"], [f"{schema}.vote.id"], name=op.f("fk_vote_record_vote_id_vote"), ondelete="CASCADE"
-        ),
-        sa.PrimaryKeyConstraint("vote_id", "legislator_id", name=op.f("pk_vote_record")),
-        schema=schema,
-    )
-    op.create_table(
-        "legislator",
-        sa.Column("bioguide_id", sa.TEXT(), autoincrement=False, nullable=False),
-        sa.Column("thomas_id", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("lis_id", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("govtrack_id", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("opensecrets_id", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("fec_ids", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("first_name", sa.VARCHAR(), autoincrement=False, nullable=False),
-        sa.Column("last_name", sa.VARCHAR(), autoincrement=False, nullable=False),
-        sa.Column("official_full_name", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("nickname", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("birthday", sa.DATE(), autoincrement=False, nullable=True),
-        sa.Column("gender", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("current_party", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("current_state", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("current_district", sa.INTEGER(), autoincrement=False, nullable=True),
-        sa.Column("current_chamber", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("id", sa.INTEGER(), autoincrement=True, nullable=False),
-        sa.Column(
-            "created",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.Column(
-            "updated",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_legislator")),
-        schema=schema,
-    )
-    op.create_index(op.f("ix_legislator_bioguide_id"), "legislator", ["bioguide_id"], unique=True, schema=schema)
-    op.create_table(
-        "bill",
-        sa.Column("congress", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("bill_type", sa.VARCHAR(), autoincrement=False, nullable=False),
-        sa.Column("number", sa.INTEGER(), autoincrement=False, nullable=False),
-        sa.Column("title", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("title_short", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("official_title", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("status", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("status_at", sa.DATE(), autoincrement=False, nullable=True),
-        sa.Column("sponsor_bioguide_id", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("subjects_top_term", sa.VARCHAR(), autoincrement=False, nullable=True),
-        sa.Column("id", sa.INTEGER(), autoincrement=True, nullable=False),
-        sa.Column(
-            "created",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.Column(
-            "updated",
-            postgresql.TIMESTAMP(timezone=True),
-            server_default=sa.text("now()"),
-            autoincrement=False,
-            nullable=False,
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_bill")),
-        sa.UniqueConstraint(
-            "congress",
-            "bill_type",
-            "number",
-            name=op.f("uq_bill_congress_type_number"),
-            postgresql_include=[],
-            postgresql_nulls_not_distinct=False,
-        ),
-        schema=schema,
-    )
-    op.create_index(op.f("ix_bill_congress"), "bill", ["congress"], unique=False, schema=schema)
-    # ### end Alembic commands ###

python/alembic/richie/versions/2026_06_03-adding_audiobook_libreary_metadata_d7864d1ffc17.py

@@ -1,93 +0,0 @@
-"""adding audiobook libreary metadata.
-
-Revision ID: d7864d1ffc17
-Revises: c8a794340928
-Create Date: 2026-06-03 20:24:09.200837
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-import sqlalchemy as sa
-from alembic import op
-
-from python.orm import RichieBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "d7864d1ffc17"
-down_revision: str | None = "c8a794340928"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = RichieBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table(
-        "audiobook_author",
-        sa.Column("name", sa.String(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_audiobook_author")),
-        sa.UniqueConstraint("name", name=op.f("uq_audiobook_author_name")),
-        schema=schema,
-    )
-    op.create_table(
-        "audiobook_series",
-        sa.Column("name", sa.String(), nullable=False),
-        sa.Column("author_id", sa.Integer(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["author_id"],
-            [f"{schema}.audiobook_author.id"],
-            name=op.f("fk_audiobook_series_author_id_audiobook_author"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_audiobook_series")),
-        sa.UniqueConstraint("author_id", "name", name=op.f("uq_audiobook_series_author_id")),
-        schema=schema,
-    )
-    op.create_table(
-        "audiobook",
-        sa.Column("title", sa.String(), nullable=False),
-        sa.Column("author_id", sa.Integer(), nullable=False),
-        sa.Column("series_id", sa.Integer(), nullable=True),
-        sa.Column("series_index", sa.Integer(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["author_id"],
-            [f"{schema}.audiobook_author.id"],
-            name=op.f("fk_audiobook_author_id_audiobook_author"),
-            ondelete="CASCADE",
-        ),
-        sa.ForeignKeyConstraint(
-            ["series_id"],
-            [f"{schema}.audiobook_series.id"],
-            name=op.f("fk_audiobook_series_id_audiobook_series"),
-            ondelete="SET NULL",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_audiobook")),
-        schema=schema,
-    )
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_table("audiobook", schema=schema)
-    op.drop_table("audiobook_series", schema=schema)
-    op.drop_table("audiobook_author", schema=schema)
-    # ### end Alembic commands ###

python/alembic/richie/versions/2026_06_10-add_ebook_search_tables_2db132cace1a.py

@@ -1,200 +0,0 @@
-"""add ebook search tables.
-
-Revision ID: 2db132cace1a
-Revises: b3c60cc5beb5
-Create Date: 2026-06-10 22:10:54.379159
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-import pgvector
-import sqlalchemy as sa
-from alembic import op
-
-from python.orm import RichieBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "2db132cace1a"
-down_revision: str | None = "b3c60cc5beb5"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = RichieBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_table(
-        "ebook_embedding_model",
-        sa.Column("name", sa.String(), nullable=False),
-        sa.Column("dimension", sa.Integer(), nullable=False),
-        sa.Column("is_default", sa.Boolean(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_embedding_model")),
-        sa.UniqueConstraint("name", name=op.f("uq_ebook_embedding_model_name")),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_source",
-        sa.Column("title", sa.String(), nullable=False),
-        sa.Column("author", sa.String(), nullable=True),
-        sa.Column("language", sa.String(), nullable=True),
-        sa.Column("publisher", sa.String(), nullable=True),
-        sa.Column("identifier", sa.String(), nullable=True),
-        sa.Column("file_path", sa.String(), nullable=False),
-        sa.Column("file_sha256", sa.String(length=64), nullable=False),
-        sa.Column("file_mtime", sa.DateTime(timezone=True), nullable=False),
-        sa.Column("file_size", sa.BigInteger(), nullable=False),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_source")),
-        sa.UniqueConstraint("file_path", name=op.f("uq_ebook_source_file_path")),
-        sa.UniqueConstraint("file_sha256", name=op.f("uq_ebook_source_file_sha256")),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_chapter",
-        sa.Column("source_id", sa.Integer(), nullable=False),
-        sa.Column("spine_index", sa.Integer(), nullable=False),
-        sa.Column("title", sa.String(), nullable=True),
-        sa.Column("href", sa.String(), nullable=True),
-        sa.Column("id", sa.Integer(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["source_id"],
-            [f"{schema}.ebook_source.id"],
-            name=op.f("fk_ebook_chapter_source_id_ebook_source"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_chapter")),
-        sa.UniqueConstraint("source_id", "spine_index", name=op.f("uq_ebook_chapter_source_id")),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_chunk",
-        sa.Column("source_id", sa.Integer(), nullable=False),
-        sa.Column("chapter_id", sa.Integer(), nullable=True),
-        sa.Column("chunk_index", sa.Integer(), nullable=False),
-        sa.Column("text", sa.String(), nullable=False),
-        sa.Column("token_start", sa.Integer(), nullable=False),
-        sa.Column("token_count", sa.Integer(), nullable=False),
-        sa.Column("page_label", sa.String(), nullable=True),
-        sa.Column("content_sha256", sa.String(length=64), nullable=False),
-        sa.Column("search_text", sa.String(), nullable=False),
-        sa.Column("id", sa.BigInteger(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["chapter_id"],
-            [f"{schema}.ebook_chapter.id"],
-            name=op.f("fk_ebook_chunk_chapter_id_ebook_chapter"),
-            ondelete="SET NULL",
-        ),
-        sa.ForeignKeyConstraint(
-            ["source_id"],
-            [f"{schema}.ebook_source.id"],
-            name=op.f("fk_ebook_chunk_source_id_ebook_source"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_chunk")),
-        sa.UniqueConstraint("source_id", "chunk_index", name="uq_ebook_chunk_source_id_chunk_index"),
-        sa.UniqueConstraint("source_id", "content_sha256", name="uq_ebook_chunk_source_id_content_sha256"),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_chunk_embedding_1024",
-        sa.Column("chunk_id", sa.BigInteger(), nullable=False),
-        sa.Column("model_id", sa.Integer(), nullable=False),
-        sa.Column("embedding", pgvector.sqlalchemy.vector.VECTOR(dim=1024), nullable=False),
-        sa.Column("id", sa.BigInteger(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["chunk_id"],
-            [f"{schema}.ebook_chunk.id"],
-            name=op.f("fk_ebook_chunk_embedding_1024_chunk_id_ebook_chunk"),
-            ondelete="CASCADE",
-        ),
-        sa.ForeignKeyConstraint(
-            ["model_id"],
-            [f"{schema}.ebook_embedding_model.id"],
-            name=op.f("fk_ebook_chunk_embedding_1024_model_id_ebook_embedding_model"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_chunk_embedding_1024")),
-        sa.UniqueConstraint("chunk_id", "model_id", name=op.f("uq_ebook_chunk_embedding_1024_chunk_id")),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_chunk_embedding_2560",
-        sa.Column("chunk_id", sa.BigInteger(), nullable=False),
-        sa.Column("model_id", sa.Integer(), nullable=False),
-        sa.Column("embedding", pgvector.sqlalchemy.vector.VECTOR(dim=2560), nullable=False),
-        sa.Column("id", sa.BigInteger(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["chunk_id"],
-            [f"{schema}.ebook_chunk.id"],
-            name=op.f("fk_ebook_chunk_embedding_2560_chunk_id_ebook_chunk"),
-            ondelete="CASCADE",
-        ),
-        sa.ForeignKeyConstraint(
-            ["model_id"],
-            [f"{schema}.ebook_embedding_model.id"],
-            name=op.f("fk_ebook_chunk_embedding_2560_model_id_ebook_embedding_model"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_chunk_embedding_2560")),
-        sa.UniqueConstraint("chunk_id", "model_id", name=op.f("uq_ebook_chunk_embedding_2560_chunk_id")),
-        schema=schema,
-    )
-    op.create_table(
-        "ebook_chunk_embedding_4096",
-        sa.Column("chunk_id", sa.BigInteger(), nullable=False),
-        sa.Column("model_id", sa.Integer(), nullable=False),
-        sa.Column("embedding", pgvector.sqlalchemy.vector.VECTOR(dim=4096), nullable=False),
-        sa.Column("id", sa.BigInteger(), nullable=False),
-        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
-        sa.ForeignKeyConstraint(
-            ["chunk_id"],
-            [f"{schema}.ebook_chunk.id"],
-            name=op.f("fk_ebook_chunk_embedding_4096_chunk_id_ebook_chunk"),
-            ondelete="CASCADE",
-        ),
-        sa.ForeignKeyConstraint(
-            ["model_id"],
-            [f"{schema}.ebook_embedding_model.id"],
-            name=op.f("fk_ebook_chunk_embedding_4096_model_id_ebook_embedding_model"),
-            ondelete="CASCADE",
-        ),
-        sa.PrimaryKeyConstraint("id", name=op.f("pk_ebook_chunk_embedding_4096")),
-        sa.UniqueConstraint("chunk_id", "model_id", name=op.f("uq_ebook_chunk_embedding_4096_chunk_id")),
-        schema=schema,
-    )
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_table("ebook_chunk_embedding_4096", schema=schema)
-    op.drop_table("ebook_chunk_embedding_2560", schema=schema)
-    op.drop_table("ebook_chunk_embedding_1024", schema=schema)
-    op.drop_table("ebook_chunk", schema=schema)
-    op.drop_table("ebook_chapter", schema=schema)
-    op.drop_table("ebook_source", schema=schema)
-    op.drop_table("ebook_embedding_model", schema=schema)
-    # ### end Alembic commands ###

python/alembic/richie/versions/2026_06_10-updated_series_index_to_float_and_added__b3c60cc5beb5.py

@@ -1,63 +0,0 @@
-"""updated series_index to float and added UniqueConstraint to audiobook and audiobook_author.
-
-Revision ID: b3c60cc5beb5
-Revises: d7864d1ffc17
-Create Date: 2026-06-10 20:02:43.073725
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-import sqlalchemy as sa
-from alembic import op
-
-from python.orm import RichieBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "b3c60cc5beb5"
-down_revision: str | None = "d7864d1ffc17"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = RichieBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.alter_column(
-        "audiobook",
-        "series_index",
-        existing_type=sa.INTEGER(),
-        type_=sa.Float(),
-        existing_nullable=False,
-        schema=schema,
-    )
-    op.create_unique_constraint(
-        op.f("uq_audiobook_author_id"),
-        "audiobook",
-        ["author_id", "series_id", "title"],
-        schema=schema,
-        postgresql_nulls_not_distinct=True,
-    )
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_constraint(op.f("uq_audiobook_author_id"), "audiobook", schema=schema, type_="unique")
-    op.alter_column(
-        "audiobook",
-        "series_index",
-        existing_type=sa.Float(),
-        type_=sa.INTEGER(),
-        existing_nullable=False,
-        schema=schema,
-    )
-    # ### end Alembic commands ###

python/alembic/richie/versions/2026_06_13-add_1024_ebook_embedding_cosine_index_c460105682d2.py

@@ -1,54 +0,0 @@
-"""add 1024 ebook embedding cosine index.
-
-Revision ID: c460105682d2
-Revises: 2db132cace1a
-Create Date: 2026-06-13 19:53:45.680289
-
-"""
-
-from __future__ import annotations
-
-from typing import TYPE_CHECKING
-
-from alembic import op
-
-from python.orm import RichieBase
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-# revision identifiers, used by Alembic.
-revision: str = "c460105682d2"
-down_revision: str | None = "2db132cace1a"
-branch_labels: str | Sequence[str] | None = None
-depends_on: str | Sequence[str] | None = None
-
-schema = RichieBase.schema_name
-
-
-def upgrade() -> None:
-    """Upgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.create_index(
-        "ix_ebook_chunk_embedding_1024_embedding_cosine",
-        "ebook_chunk_embedding_1024",
-        ["embedding"],
-        unique=False,
-        schema=schema,
-        postgresql_using="hnsw",
-        postgresql_ops={"embedding": "vector_cosine_ops"},
-    )
-    # ### end Alembic commands ###
-
-
-def downgrade() -> None:
-    """Downgrade."""
-    # ### commands auto generated by Alembic - please adjust! ###
-    op.drop_index(
-        "ix_ebook_chunk_embedding_1024_embedding_cosine",
-        table_name="ebook_chunk_embedding_1024",
-        schema=schema,
-        postgresql_using="hnsw",
-        postgresql_ops={"embedding": "vector_cosine_ops"},
-    )
-    # ### end Alembic commands ###

python/alembic/signal_bot/versions/2026_03_17-seprating_signal_bot_database_6eaf696e07a5.py

@@ -0,0 +1,100 @@
+"""seprating signal_bot database.
+
+Revision ID: 6eaf696e07a5
+Revises:
+Create Date: 2026-03-17 21:35:37.612672
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import postgresql
+
+from python.orm import SignalBotBase
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+# revision identifiers, used by Alembic.
+revision: str = "6eaf696e07a5"
+down_revision: str | None = None
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+schema = SignalBotBase.schema_name
+
+
+def upgrade() -> None:
+    """Upgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table(
+        "dead_letter_message",
+        sa.Column("source", sa.String(), nullable=False),
+        sa.Column("message", sa.Text(), nullable=False),
+        sa.Column("received_at", sa.DateTime(timezone=True), nullable=False),
+        sa.Column(
+            "status", postgresql.ENUM("UNPROCESSED", "PROCESSED", name="message_status", schema=schema), nullable=False
+        ),
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_dead_letter_message")),
+        schema=schema,
+    )
+    op.create_table(
+        "role",
+        sa.Column("name", sa.String(length=50), nullable=False),
+        sa.Column("id", sa.SmallInteger(), nullable=False),
+        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_role")),
+        sa.UniqueConstraint("name", name=op.f("uq_role_name")),
+        schema=schema,
+    )
+    op.create_table(
+        "signal_device",
+        sa.Column("phone_number", sa.String(length=50), nullable=False),
+        sa.Column("safety_number", sa.String(), nullable=True),
+        sa.Column(
+            "trust_level",
+            postgresql.ENUM("VERIFIED", "UNVERIFIED", "BLOCKED", name="trust_level", schema=schema),
+            nullable=False,
+        ),
+        sa.Column("last_seen", sa.DateTime(timezone=True), nullable=False),
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_signal_device")),
+        sa.UniqueConstraint("phone_number", name=op.f("uq_signal_device_phone_number")),
+        schema=schema,
+    )
+    op.create_table(
+        "device_role",
+        sa.Column("device_id", sa.Integer(), nullable=False),
+        sa.Column("role_id", sa.SmallInteger(), nullable=False),
+        sa.Column("id", sa.Integer(), nullable=False),
+        sa.Column("created", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.Column("updated", sa.DateTime(timezone=True), server_default=sa.text("now()"), nullable=False),
+        sa.ForeignKeyConstraint(
+            ["device_id"], [f"{schema}.signal_device.id"], name=op.f("fk_device_role_device_id_signal_device")
+        ),
+        sa.ForeignKeyConstraint(["role_id"], [f"{schema}.role.id"], name=op.f("fk_device_role_role_id_role")),
+        sa.PrimaryKeyConstraint("id", name=op.f("pk_device_role")),
+        sa.UniqueConstraint("device_id", "role_id", name="uq_device_role_device_role"),
+        schema=schema,
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table("device_role", schema=schema)
+    op.drop_table("signal_device", schema=schema)
+    op.drop_table("role", schema=schema)
+    op.drop_table("dead_letter_message", schema=schema)
+    # ### end Alembic commands ###

python/alembic/signal_bot/versions/2026_03_18-test_66bdd532bcab.py

@@ -0,0 +1,72 @@
+"""test.
+
+Revision ID: 66bdd532bcab
+Revises: 6eaf696e07a5
+Create Date: 2026-03-18 19:21:14.561568
+
+"""
+
+from __future__ import annotations
+
+from typing import TYPE_CHECKING
+
+import sqlalchemy as sa
+from alembic import op
+from sqlalchemy.dialects import postgresql
+
+from python.orm import SignalBotBase
+
+if TYPE_CHECKING:
+    from collections.abc import Sequence
+
+# revision identifiers, used by Alembic.
+revision: str = "66bdd532bcab"
+down_revision: str | None = "6eaf696e07a5"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+schema = SignalBotBase.schema_name
+
+
+def upgrade() -> None:
+    """Upgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.alter_column(
+        "dead_letter_message",
+        "status",
+        existing_type=postgresql.ENUM("UNPROCESSED", "PROCESSED", name="message_status", schema=schema),
+        type_=sa.Enum("UNPROCESSED", "PROCESSED", name="message_status", native_enum=False),
+        existing_nullable=False,
+        schema=schema,
+    )
+    op.alter_column(
+        "signal_device",
+        "trust_level",
+        existing_type=postgresql.ENUM("VERIFIED", "UNVERIFIED", "BLOCKED", name="trust_level", schema=schema),
+        type_=sa.Enum("VERIFIED", "UNVERIFIED", "BLOCKED", name="trust_level", native_enum=False),
+        existing_nullable=False,
+        schema=schema,
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    """Downgrade."""
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.alter_column(
+        "signal_device",
+        "trust_level",
+        existing_type=sa.Enum("VERIFIED", "UNVERIFIED", "BLOCKED", name="trust_level", native_enum=False),
+        type_=postgresql.ENUM("VERIFIED", "UNVERIFIED", "BLOCKED", name="trust_level", schema=schema),
+        existing_nullable=False,
+        schema=schema,
+    )
+    op.alter_column(
+        "dead_letter_message",
+        "status",
+        existing_type=sa.Enum("UNPROCESSED", "PROCESSED", name="message_status", native_enum=False),
+        type_=postgresql.ENUM("UNPROCESSED", "PROCESSED", name="message_status", schema=schema),
+        existing_nullable=False,
+        schema=schema,
+    )
+    # ### end Alembic commands ###

python/api/main.py

@@ -9,9 +9,9 @@ import typer
 import uvicorn
 from fastapi import FastAPI
 
+from python.api.middleware import ZstdMiddleware
 from python.api.routers import contact_router, views_router
 from python.common import configure_logger
-from python.fastapi_tools import ZstdMiddleware
 from python.orm.common import get_postgres_engine
 
 logger = logging.getLogger(__name__)

python/api/middleware.py

@@ -1,4 +1,4 @@
-"""Zstd response compression middleware."""
+"""Middleware for the FastAPI application."""
 
 from compression import zstd
 from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint

python/api/routers/contact.py

@@ -9,7 +9,7 @@ from pydantic import BaseModel
 from sqlalchemy import select
 from sqlalchemy.orm import selectinload
 
-from python.fastapi_tools.db import DbSession
+from python.api.dependencies import DbSession
 from python.orm.richie.contact import Contact, ContactRelationship, Need, RelationshipType
 
 TEMPLATES_DIR = Path(__file__).parent.parent / "templates"

python/api/routers/views.py

@@ -9,7 +9,7 @@ from fastapi.templating import Jinja2Templates
 from sqlalchemy import select
 from sqlalchemy.orm import Session, selectinload
 
-from python.fastapi_tools.db import DbSession
+from python.api.dependencies import DbSession
 from python.orm.richie.contact import Contact, ContactRelationship, Need, RelationshipType
 
 TEMPLATES_DIR = Path(__file__).parent.parent / "templates"

python/data_science/__init__.py

@@ -0,0 +1,3 @@
+"""Data science CLI tools."""
+
+from __future__ import annotations

python/data_science/bluesky_ids.py

@@ -0,0 +1,104 @@
+"""Utilities for converting Bluesky identifiers to numeric database IDs.
+
+Handles DID-to-user_id hashing, TID-to-post_id decoding, and AT-URI parsing.
+"""
+
+from __future__ import annotations
+
+import hashlib
+
+TID_CHARSET = "234567abcdefghijklmnopqrstuvwxyz"
+_TID_LENGTH = 13
+_BIGINT_MASK = 0x7FFFFFFFFFFFFFFF
+_AT_URI_SEGMENT_COUNT = 3
+
+
+def did_to_user_id(did: str) -> int:
+    """Convert a DID string to a deterministic 63-bit integer for user_id.
+
+    Uses SHA-256, truncated to 63 bits (positive signed BigInteger range).
+    Collision probability is negligible at Bluesky's scale (~tens of millions of users).
+
+    Args:
+        did: A Bluesky DID string, e.g. "did:plc:abc123".
+
+    Returns:
+        A positive 63-bit integer suitable for BigInteger storage.
+    """
+    digest = hashlib.sha256(did.encode()).digest()
+    return int.from_bytes(digest[:8], "big") & _BIGINT_MASK
+
+
+def tid_to_integer(tid: str) -> int:
+    """Decode a Bluesky TID (base32-sortbase) into a 64-bit integer for post_id.
+
+    TIDs are 13-character, base32-sortbase encoded identifiers that encode a
+    microsecond timestamp plus a clock ID. They are globally unique by construction.
+
+    Args:
+        tid: A 13-character TID string, e.g. "3abc2defghijk".
+
+    Returns:
+        A positive integer suitable for BigInteger storage.
+
+    Raises:
+        ValueError: If the TID is malformed (wrong length or invalid characters).
+    """
+    if len(tid) != _TID_LENGTH:
+        message = f"TID must be {_TID_LENGTH} characters, got {len(tid)}: {tid!r}"
+        raise ValueError(message)
+
+    result = 0
+    for char in tid:
+        index = TID_CHARSET.find(char)
+        if index == -1:
+            message = f"Invalid character {char!r} in TID {tid!r}"
+            raise ValueError(message)
+        result = result * 32 + index
+    return result
+
+
+def parse_at_uri(uri: str) -> tuple[str, str, str]:
+    """Parse an AT-URI into its components.
+
+    Args:
+        uri: An AT-URI string, e.g. "at://did:plc:abc123/app.bsky.feed.post/3abc2defghijk".
+
+    Returns:
+        A tuple of (did, collection, rkey).
+
+    Raises:
+        ValueError: If the URI doesn't have the expected format.
+    """
+    stripped = uri.removeprefix("at://")
+    parts = stripped.split("/", maxsplit=2)
+    if len(parts) != _AT_URI_SEGMENT_COUNT:
+        message = f"Expected {_AT_URI_SEGMENT_COUNT} path segments in AT-URI, got {len(parts)}: {uri!r}"
+        raise ValueError(message)
+    return parts[0], parts[1], parts[2]
+
+
+def post_id_from_uri(uri: str) -> int:
+    """Extract and decode the post_id (TID) from an AT-URI.
+
+    Args:
+        uri: An AT-URI pointing to a post.
+
+    Returns:
+        The post_id as an integer.
+    """
+    _did, _collection, rkey = parse_at_uri(uri)
+    return tid_to_integer(rkey)
+
+
+def user_id_from_uri(uri: str) -> int:
+    """Extract and hash the user_id (DID) from an AT-URI.
+
+    Args:
+        uri: An AT-URI pointing to a post.
+
+    Returns:
+        The user_id as an integer.
+    """
+    did, _collection, _rkey = parse_at_uri(uri)
+    return did_to_user_id(did)

python/data_science/bluesky_transform.py

@@ -0,0 +1,143 @@
+"""Transform Bluesky Jetstream messages into rows matching the Posts table schema."""
+
+from __future__ import annotations
+
+import json
+import logging
+from datetime import datetime
+
+from python.data_science.bluesky_ids import (
+    did_to_user_id,
+    post_id_from_uri,
+    tid_to_integer,
+    user_id_from_uri,
+)
+
+logger = logging.getLogger(__name__)
+
+INSTANCE = "bsky"
+POST_COLLECTION = "app.bsky.feed.post"
+EMBED_RECORD_TYPE = "app.bsky.embed.record"
+EMBED_RECORD_WITH_MEDIA_TYPE = "app.bsky.embed.recordWithMedia"
+
+
+def transform_jetstream_post(message: dict) -> dict:
+    """Transform a Jetstream commit message into a dict matching Posts table columns.
+
+    Expects a Jetstream message with kind=commit, operation=create,
+    collection=app.bsky.feed.post.
+
+    Args:
+        message: The full Jetstream JSON message.
+
+    Returns:
+        A dict with keys matching the Posts table columns.
+    """
+    did = message["did"]
+    commit = message["commit"]
+    record = commit["record"]
+
+    row: dict = {
+        "post_id": tid_to_integer(commit["rkey"]),
+        "user_id": did_to_user_id(did),
+        "instance": INSTANCE,
+        "date": datetime.fromisoformat(record["createdAt"]),
+        "text": record.get("text", ""),
+        "langs": _extract_langs(record),
+        "like_count": 0,
+        "reply_count": 0,
+        "repost_count": 0,
+        "reply_to": None,
+        "replied_author": None,
+        "thread_root": None,
+        "thread_root_author": None,
+        "repost_from": None,
+        "reposted_author": None,
+        "quotes": None,
+        "quoted_author": None,
+        "labels": _extract_labels(record),
+        "sent_label": None,
+        "sent_score": None,
+    }
+
+    _extract_reply_refs(record, row)
+    _extract_quote_refs(record, row)
+
+    return row
+
+
+def is_post_create(message: dict) -> bool:
+    """Check if a Jetstream message is a post creation event.
+
+    Args:
+        message: The full Jetstream JSON message.
+
+    Returns:
+        True if this is a create commit for app.bsky.feed.post.
+    """
+    if message.get("kind") != "commit":
+        return False
+    commit = message.get("commit", {})
+    return commit.get("operation") == "create" and commit.get("collection") == POST_COLLECTION
+
+
+def _extract_langs(record: dict) -> str | None:
+    """Extract langs array as a JSON string, or None if absent."""
+    langs = record.get("langs")
+    if langs is None:
+        return None
+    return json.dumps(langs)
+
+
+def _extract_labels(record: dict) -> str | None:
+    """Extract self-labels as a JSON string, or None if absent."""
+    labels_obj = record.get("labels")
+    if labels_obj is None:
+        return None
+    values = labels_obj.get("values", [])
+    if not values:
+        return None
+    label_strings = [label.get("val", "") for label in values]
+    return json.dumps(label_strings)
+
+
+def _extract_reply_refs(record: dict, row: dict) -> None:
+    """Populate reply_to, replied_author, thread_root, thread_root_author from record.reply."""
+    reply = record.get("reply")
+    if reply is None:
+        return
+
+    parent = reply.get("parent", {})
+    parent_uri = parent.get("uri")
+    if parent_uri:
+        row["reply_to"] = post_id_from_uri(parent_uri)
+        row["replied_author"] = user_id_from_uri(parent_uri)
+
+    root = reply.get("root", {})
+    root_uri = root.get("uri")
+    if root_uri:
+        row["thread_root"] = post_id_from_uri(root_uri)
+        row["thread_root_author"] = user_id_from_uri(root_uri)
+
+
+def _extract_quote_refs(record: dict, row: dict) -> None:
+    """Populate quotes and quoted_author from embed record references."""
+    embed = record.get("embed")
+    if embed is None:
+        return
+
+    embed_type = embed.get("$type", "")
+
+    if embed_type == EMBED_RECORD_TYPE:
+        _set_quote_from_record(embed.get("record", {}), row)
+    elif embed_type == EMBED_RECORD_WITH_MEDIA_TYPE:
+        inner_record = embed.get("record", {}).get("record", {})
+        _set_quote_from_record(inner_record, row)
+
+
+def _set_quote_from_record(record_ref: dict, row: dict) -> None:
+    """Set quotes and quoted_author from a record reference object."""
+    uri = record_ref.get("uri")
+    if uri and POST_COLLECTION in uri:
+        row["quotes"] = post_id_from_uri(uri)
+        row["quoted_author"] = user_id_from_uri(uri)

python/data_science/firehose_consumer.py

@@ -0,0 +1,203 @@
+"""Kafka consumer that ingests Bluesky posts into the partitioned Posts table.
+
+Consumes Jetstream messages from Kafka, transforms them into Posts rows,
+and batch-inserts them into PostgreSQL with manual offset commits.
+
+Usage:
+    firehose-consumer
+    firehose-consumer --kafka-servers kafka:9092 --batch-size 500
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import signal
+from os import getenv
+from threading import Event
+from typing import Annotated
+
+import typer
+from confluent_kafka import Consumer, KafkaError, KafkaException
+from sqlalchemy.orm import Session
+
+from python.data_science.bluesky_transform import is_post_create, transform_jetstream_post
+from python.data_science.ingest_posts import ingest_batch
+from python.orm.common import get_postgres_engine
+from python.orm.data_science_dev.posts.failed_ingestion import FailedIngestion
+
+logger = logging.getLogger(__name__)
+
+DEFAULT_TOPIC = "bluesky.firehose.posts"
+DEFAULT_KAFKA_SERVERS = "localhost:9092"
+DEFAULT_GROUP_ID = "bluesky-posts-ingestor"
+DEFAULT_BATCH_SIZE = 500
+POLL_TIMEOUT_SECONDS = 5.0
+
+shutdown_event = Event()
+
+app = typer.Typer(help="Consume Bluesky posts from Kafka and ingest into PostgreSQL.")
+
+
+@app.command()
+def main(
+    kafka_servers: Annotated[str, typer.Option(help="Kafka bootstrap servers")] = "",
+    topic: Annotated[str, typer.Option(help="Kafka topic to consume from")] = "",
+    group_id: Annotated[str, typer.Option(help="Kafka consumer group ID")] = "",
+    batch_size: Annotated[int, typer.Option(help="Messages per DB insert batch")] = DEFAULT_BATCH_SIZE,
+) -> None:
+    """Consume Bluesky posts from Kafka and ingest into the partitioned posts table."""
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s %(levelname)s %(message)s",
+        datefmt="%H:%M:%S",
+    )
+
+    servers = kafka_servers or getenv("KAFKA_BOOTSTRAP_SERVERS", DEFAULT_KAFKA_SERVERS)
+    topic_name = topic or getenv("BLUESKY_FIREHOSE_TOPIC", DEFAULT_TOPIC)
+    group = group_id or getenv("KAFKA_GROUP_ID", DEFAULT_GROUP_ID)
+
+    signal.signal(signal.SIGTERM, _handle_shutdown)
+    signal.signal(signal.SIGINT, _handle_shutdown)
+
+    consumer = _create_consumer(servers, group)
+    consumer.subscribe([topic_name])
+
+    engine = get_postgres_engine(name="DATA_SCIENCE_DEV")
+    total_inserted = 0
+
+    logger.info("Starting firehose consumer: topic=%s group=%s batch_size=%d", topic_name, group, batch_size)
+
+    try:
+        with Session(engine) as session:
+            while not shutdown_event.is_set():
+                inserted = _consume_batch(consumer, session, batch_size)
+                total_inserted += inserted
+                if inserted > 0:
+                    logger.info("Batch inserted %d rows (total: %d)", inserted, total_inserted)
+    except KafkaException:
+        logger.exception("Fatal Kafka error")
+    finally:
+        logger.info("Closing consumer (total inserted: %d)", total_inserted)
+        consumer.close()
+
+
+def _consume_batch(consumer: Consumer, session: Session, batch_size: int) -> int:
+    """Poll a batch of messages, transform, and insert into the database.
+
+    Args:
+        consumer: The Kafka consumer instance.
+        session: SQLAlchemy database session.
+        batch_size: Maximum number of messages to consume per batch.
+
+    Returns:
+        Number of rows successfully inserted.
+    """
+    messages = consumer.consume(num_messages=batch_size, timeout=POLL_TIMEOUT_SECONDS)
+    if not messages:
+        return 0
+
+    rows: list[dict] = []
+    for message in messages:
+        error = message.error()
+        if error is not None:
+            if error.code() == KafkaError._PARTITION_EOF:  # noqa: SLF001 — confluent-kafka exposes this as a pseudo-private constant; no public alternative exists
+                continue
+            logger.error("Consumer error: %s", error)
+            continue
+
+        row = _safe_transform(message.value(), session)
+        if row is not None:
+            rows.append(row)
+
+    if not rows:
+        consumer.commit(asynchronous=False)
+        return 0
+
+    inserted = ingest_batch(session, rows)
+    consumer.commit(asynchronous=False)
+    return inserted
+
+
+def _safe_transform(raw_value: bytes | None, session: Session) -> dict | None:
+    """Transform a Kafka message value into a Posts row, logging failures.
+
+    Args:
+        raw_value: Raw message bytes from Kafka.
+        session: SQLAlchemy session for logging failures.
+
+    Returns:
+        A transformed row dict, or None if transformation failed.
+    """
+    if raw_value is None:
+        return None
+
+    try:
+        message = json.loads(raw_value)
+    except (json.JSONDecodeError, UnicodeDecodeError):
+        logger.exception("Failed to decode Kafka message")
+        _log_failed_ingestion(session, raw_value, "JSON decode error")
+        return None
+
+    if not is_post_create(message):
+        return None
+
+    try:
+        return transform_jetstream_post(message)
+    except (KeyError, ValueError, TypeError):
+        logger.exception("Failed to transform Jetstream message")
+        _log_failed_ingestion(session, raw_value, "Transform error")
+        return None
+
+
+def _log_failed_ingestion(session: Session, raw_value: bytes, error: str) -> None:
+    """Log a failed ingestion to the FailedIngestion table.
+
+    Args:
+        session: SQLAlchemy session.
+        raw_value: The raw message bytes.
+        error: Description of the error.
+    """
+    try:
+        session.add(
+            FailedIngestion(
+                raw_line=raw_value.decode(errors="replace")[:10000],
+                error=error,
+            )
+        )
+        session.commit()
+    except Exception:
+        session.rollback()
+        logger.exception("Failed to log ingestion failure")
+
+
+def _create_consumer(servers: str, group: str) -> Consumer:
+    """Create a configured Kafka consumer.
+
+    Args:
+        servers: Kafka bootstrap servers string.
+        group: Consumer group ID.
+
+    Returns:
+        A configured confluent_kafka.Consumer.
+    """
+    config = {
+        "bootstrap.servers": servers,
+        "group.id": group,
+        "auto.offset.reset": "earliest",
+        "enable.auto.commit": False,
+        "max.poll.interval.ms": 300000,
+        "fetch.min.bytes": 1024,
+        "session.timeout.ms": 30000,
+    }
+    return Consumer(config)
+
+
+def _handle_shutdown(_signum: int, _frame: object) -> None:
+    """Signal handler to trigger graceful shutdown."""
+    logger.info("Shutdown signal received")
+    shutdown_event.set()
+
+
+if __name__ == "__main__":
+    app()

python/data_science/firehose_producer.py

@@ -0,0 +1,230 @@
+"""Bluesky Jetstream firehose to Kafka producer.
+
+Connects to the Bluesky Jetstream WebSocket API with zstd compression,
+filters for post creation events, and produces them to a Kafka topic.
+
+Usage:
+    firehose-producer
+    firehose-producer --kafka-servers kafka:9092 --topic bluesky.firehose.posts
+"""
+
+from __future__ import annotations
+
+import json
+import logging
+import signal
+from os import getenv
+from threading import Event
+from typing import Annotated
+
+import typer
+from compression import zstd
+from confluent_kafka import KafkaError, KafkaException, Producer
+from websockets.exceptions import ConnectionClosed
+from websockets.sync.client import connect
+
+logger = logging.getLogger(__name__)
+
+JETSTREAM_URL = "wss://jetstream2.us-east.bsky.network/subscribe"
+DEFAULT_TOPIC = "bluesky.firehose.posts"
+DEFAULT_KAFKA_SERVERS = "localhost:9092"
+POLL_INTERVAL = 100
+POST_COLLECTION = "app.bsky.feed.post"
+
+shutdown_event = Event()
+
+app = typer.Typer(help="Stream Bluesky firehose posts into Kafka.")
+
+
+@app.command()
+def main(
+    kafka_servers: Annotated[str, typer.Option(help="Kafka bootstrap servers")] = "",
+    topic: Annotated[str, typer.Option(help="Kafka topic to produce to")] = "",
+    collections: Annotated[str, typer.Option(help="Comma-separated collections to subscribe to")] = POST_COLLECTION,
+) -> None:
+    """Connect to Bluesky Jetstream and produce post events to Kafka."""
+    logging.basicConfig(
+        level=logging.INFO,
+        format="%(asctime)s %(levelname)s %(message)s",
+        datefmt="%H:%M:%S",
+    )
+
+    servers = kafka_servers or getenv("KAFKA_BOOTSTRAP_SERVERS", DEFAULT_KAFKA_SERVERS)
+    topic_name = topic or getenv("BLUESKY_FIREHOSE_TOPIC", DEFAULT_TOPIC)
+
+    signal.signal(signal.SIGTERM, _handle_shutdown)
+    signal.signal(signal.SIGINT, _handle_shutdown)
+
+    producer = _create_producer(servers)
+    cursor: int | None = None
+
+    logger.info("Starting firehose producer → %s on %s", topic_name, servers)
+
+    while not shutdown_event.is_set():
+        try:
+            cursor = _stream_loop(producer, topic_name, collections, cursor)
+        except (ConnectionClosed, OSError):
+            logger.exception("WebSocket disconnected, reconnecting")
+        except KafkaException:
+            logger.exception("Kafka error, reconnecting")
+
+        if not shutdown_event.is_set():
+            logger.info("Reconnecting in 5 seconds (cursor=%s)", cursor)
+            shutdown_event.wait(timeout=5)
+
+    logger.info("Shutting down, flushing producer")
+    producer.flush(timeout=30)
+    logger.info("Producer shutdown complete")
+
+
+def _stream_loop(
+    producer: Producer,
+    topic: str,
+    collections: str,
+    cursor: int | None,
+) -> int | None:
+    """Connect to Jetstream and stream messages to Kafka until disconnected.
+
+    Args:
+        producer: The Kafka producer instance.
+        topic: Kafka topic name.
+        collections: Comma-separated AT Protocol collections to subscribe to.
+        cursor: Optional microsecond timestamp to resume from.
+
+    Returns:
+        The last processed time_us cursor value.
+    """
+    url = _build_jetstream_url(collections, cursor)
+    logger.info("Connecting to %s", url)
+
+    message_count = 0
+    last_cursor = cursor
+
+    with connect(url, additional_headers={"Accept-Encoding": "zstd"}) as websocket:
+        logger.info("Connected to Jetstream")
+
+        while not shutdown_event.is_set():
+            try:
+                raw_frame = websocket.recv(timeout=10)
+            except TimeoutError:
+                producer.poll(0)
+                continue
+
+            text = _decode_frame(raw_frame)
+            message = json.loads(text)
+
+            time_us = message.get("time_us")
+            if time_us is not None:
+                last_cursor = time_us
+
+            if not _is_post_create(message):
+                continue
+
+            did = message.get("did", "")
+
+            try:
+                producer.produce(
+                    topic,
+                    key=did.encode(),
+                    value=text.encode() if isinstance(text, str) else text,
+                    callback=_delivery_callback,
+                )
+            except BufferError:
+                logger.warning("Producer buffer full, flushing")
+                producer.flush(timeout=10)
+                producer.produce(
+                    topic,
+                    key=did.encode(),
+                    value=text.encode() if isinstance(text, str) else text,
+                    callback=_delivery_callback,
+                )
+
+            message_count += 1
+            if message_count % POLL_INTERVAL == 0:
+                producer.poll(0)
+
+            if message_count % 10000 == 0:
+                logger.info("Produced %d messages (cursor=%s)", message_count, last_cursor)
+
+    return last_cursor
+
+
+def _build_jetstream_url(collections: str, cursor: int | None) -> str:
+    """Build the Jetstream WebSocket URL with query parameters.
+
+    Args:
+        collections: Comma-separated collection names.
+        cursor: Optional microsecond timestamp for resumption.
+
+    Returns:
+        The full WebSocket URL.
+    """
+    params = ["compress=true"]
+    for raw_collection in collections.split(","):
+        cleaned = raw_collection.strip()
+        if cleaned:
+            params.append(f"wantedCollections={cleaned}")
+    if cursor is not None:
+        params.append(f"cursor={cursor}")
+    return f"{JETSTREAM_URL}?{'&'.join(params)}"
+
+
+def _decode_frame(frame: str | bytes) -> str:
+    """Decode a WebSocket frame, decompressing zstd if binary.
+
+    Jetstream with compress=true sends zstd-compressed binary frames.
+
+    Args:
+        frame: Raw WebSocket frame data.
+
+    Returns:
+        The decoded JSON string.
+    """
+    if isinstance(frame, bytes):
+        return zstd.decompress(frame).decode()
+    return frame
+
+
+def _is_post_create(message: dict) -> bool:
+    """Check if a Jetstream message is a post creation commit."""
+    if message.get("kind") != "commit":
+        return False
+    commit = message.get("commit", {})
+    return commit.get("operation") == "create" and commit.get("collection") == POST_COLLECTION
+
+
+def _create_producer(servers: str) -> Producer:
+    """Create a configured Kafka producer.
+
+    Args:
+        servers: Kafka bootstrap servers string.
+
+    Returns:
+        A configured confluent_kafka.Producer.
+    """
+    config = {
+        "bootstrap.servers": servers,
+        "linger.ms": 50,
+        "batch.size": 65536,
+        "compression.type": "zstd",
+        "acks": "all",
+        "retries": 5,
+        "retry.backoff.ms": 500,
+    }
+    return Producer(config)
+
+
+def _delivery_callback(error: KafkaError | None, _message: object) -> None:
+    """Log delivery failures from the Kafka producer."""
+    if error is not None:
+        logger.error("Kafka delivery failed: %s", error)
+
+
+def _handle_shutdown(_signum: int, _frame: object) -> None:
+    """Signal handler to trigger graceful shutdown."""
+    logger.info("Shutdown signal received")
+    shutdown_event.set()
+
+
+if __name__ == "__main__":
+    app()

python/data_science/ingest_posts.py

@@ -0,0 +1,247 @@
+"""Ingestion pipeline for loading JSONL post files into the weekly-partitioned posts table.
+
+Usage:
+    ingest-posts /path/to/files/
+    ingest-posts /path/to/single_file.jsonl
+    ingest-posts /data/dir/ --workers 4 --batch-size 5000
+"""
+
+from __future__ import annotations
+
+import logging
+from datetime import UTC, datetime
+from pathlib import Path  # noqa: TC003 this is needed for typer
+from typing import TYPE_CHECKING, Annotated
+
+import orjson
+import psycopg
+import typer
+
+from python.common import configure_logger
+from python.orm.common import get_connection_info
+from python.parallelize import parallelize_process
+
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
+logger = logging.getLogger(__name__)
+
+
+app = typer.Typer(help="Ingest JSONL post files into the partitioned posts table.")
+
+
+@app.command()
+def main(
+    path: Annotated[Path, typer.Argument(help="Directory containing JSONL files, or a single JSONL file")],
+    batch_size: Annotated[int, typer.Option(help="Rows per INSERT batch")] = 10000,
+    workers: Annotated[int, typer.Option(help="Parallel workers for multi-file ingestion")] = 4,
+    pattern: Annotated[str, typer.Option(help="Glob pattern for JSONL files")] = "*.jsonl",
+) -> None:
+    """Ingest JSONL post files into the weekly-partitioned posts table."""
+    configure_logger(level="INFO")
+
+    logger.info("starting ingest-posts")
+    logger.info("path=%s batch_size=%d workers=%d pattern=%s", path, batch_size, workers, pattern)
+    if path.is_file():
+        ingest_file(path, batch_size=batch_size)
+    elif path.is_dir():
+        ingest_directory(path, batch_size=batch_size, max_workers=workers, pattern=pattern)
+    else:
+        typer.echo(f"Path does not exist: {path}", err=True)
+        raise typer.Exit(code=1)
+
+    logger.info("ingest-posts done")
+
+
+def ingest_directory(
+    directory: Path,
+    *,
+    batch_size: int,
+    max_workers: int,
+    pattern: str = "*.jsonl",
+) -> None:
+    """Ingest all JSONL files in a directory using parallel workers."""
+    files = sorted(directory.glob(pattern))
+    if not files:
+        logger.warning("No JSONL files found in %s", directory)
+        return
+
+    logger.info("Found %d JSONL files to ingest", len(files))
+
+    kwargs_list = [{"path": fp, "batch_size": batch_size} for fp in files]
+    parallelize_process(ingest_file, kwargs_list, max_workers=max_workers)
+
+
+SCHEMA = "main"
+
+COLUMNS = (
+    "post_id",
+    "user_id",
+    "instance",
+    "date",
+    "text",
+    "langs",
+    "like_count",
+    "reply_count",
+    "repost_count",
+    "reply_to",
+    "replied_author",
+    "thread_root",
+    "thread_root_author",
+    "repost_from",
+    "reposted_author",
+    "quotes",
+    "quoted_author",
+    "labels",
+    "sent_label",
+    "sent_score",
+)
+
+INSERT_FROM_STAGING = f"""
+    INSERT INTO {SCHEMA}.posts ({", ".join(COLUMNS)})
+    SELECT {", ".join(COLUMNS)} FROM pg_temp.staging
+    ON CONFLICT (post_id, date) DO NOTHING
+"""  # noqa: S608
+
+FAILED_INSERT = f"""
+    INSERT INTO {SCHEMA}.failed_ingestion (raw_line, error)
+    VALUES (%(raw_line)s, %(error)s)
+"""  # noqa: S608
+
+
+def get_psycopg_connection() -> psycopg.Connection:
+    """Create a raw psycopg3 connection from environment variables."""
+    database, host, port, username, password = get_connection_info("DATA_SCIENCE_DEV")
+    return psycopg.connect(
+        dbname=database,
+        host=host,
+        port=int(port),
+        user=username,
+        password=password,
+        autocommit=False,
+    )
+
+
+def ingest_file(path: Path, *, batch_size: int) -> None:
+    """Ingest a single JSONL file into the posts table."""
+    log_trigger = max(100_000 // batch_size, 1)
+    failed_lines: list[dict] = []
+    try:
+        with get_psycopg_connection() as connection:
+            for index, batch in enumerate(read_jsonl_batches(path, batch_size, failed_lines), 1):
+                ingest_batch(connection, batch)
+                if index % log_trigger == 0:
+                    logger.info("Ingested %d batches (%d rows) from %s", index, index * batch_size, path)
+
+            if failed_lines:
+                logger.warning("Recording %d malformed lines from %s", len(failed_lines), path.name)
+                with connection.cursor() as cursor:
+                    cursor.executemany(FAILED_INSERT, failed_lines)
+                connection.commit()
+    except Exception:
+        logger.exception("Failed to ingest file: %s", path)
+        raise
+
+
+def ingest_batch(connection: psycopg.Connection, batch: list[dict]) -> None:
+    """COPY batch into a temp staging table, then INSERT ... ON CONFLICT into posts."""
+    if not batch:
+        return
+
+    try:
+        with connection.cursor() as cursor:
+            cursor.execute(f"""
+                CREATE TEMP TABLE IF NOT EXISTS staging
+                (LIKE {SCHEMA}.posts INCLUDING DEFAULTS)
+                ON COMMIT DELETE ROWS
+            """)
+            cursor.execute("TRUNCATE pg_temp.staging")
+
+            with cursor.copy(f"COPY pg_temp.staging ({', '.join(COLUMNS)}) FROM STDIN") as copy:
+                for row in batch:
+                    copy.write_row(tuple(row.get(column) for column in COLUMNS))
+
+            cursor.execute(INSERT_FROM_STAGING)
+        connection.commit()
+    except Exception as error:
+        connection.rollback()
+
+        if len(batch) == 1:
+            logger.exception("Skipping bad row post_id=%s", batch[0].get("post_id"))
+            with connection.cursor() as cursor:
+                cursor.execute(
+                    FAILED_INSERT,
+                    {
+                        "raw_line": orjson.dumps(batch[0], default=str).decode(),
+                        "error": str(error),
+                    },
+                )
+            connection.commit()
+            return
+
+        midpoint = len(batch) // 2
+        ingest_batch(connection, batch[:midpoint])
+        ingest_batch(connection, batch[midpoint:])
+
+
+def read_jsonl_batches(file_path: Path, batch_size: int, failed_lines: list[dict]) -> Iterator[list[dict]]:
+    """Stream a JSONL file and yield batches of transformed rows."""
+    batch: list[dict] = []
+    with file_path.open("r", encoding="utf-8") as handle:
+        for raw_line in handle:
+            line = raw_line.strip()
+            if not line:
+                continue
+            batch.extend(parse_line(line, file_path, failed_lines))
+            if len(batch) >= batch_size:
+                yield batch
+                batch = []
+    if batch:
+        yield batch
+
+
+def parse_line(line: str, file_path: Path, failed_lines: list[dict]) -> Iterator[dict]:
+    """Parse a JSONL line, handling concatenated JSON objects."""
+    try:
+        yield transform_row(orjson.loads(line))
+    except orjson.JSONDecodeError:
+        if "}{" not in line:
+            logger.warning("Skipping malformed line in %s: %s", file_path.name, line[:120])
+            failed_lines.append({"raw_line": line, "error": "malformed JSON"})
+            return
+        fragments = line.replace("}{", "}\n{").split("\n")
+        for fragment in fragments:
+            try:
+                yield transform_row(orjson.loads(fragment))
+            except (orjson.JSONDecodeError, KeyError, ValueError) as error:
+                logger.warning("Skipping malformed fragment in %s: %s", file_path.name, fragment[:120])
+                failed_lines.append({"raw_line": fragment, "error": str(error)})
+    except Exception as error:
+        logger.exception("Skipping bad row in %s: %s", file_path.name, line[:120])
+        failed_lines.append({"raw_line": line, "error": str(error)})
+
+
+def transform_row(raw: dict) -> dict:
+    """Transform a raw JSONL row into a dict matching the Posts table columns."""
+    raw["date"] = parse_date(raw["date"])
+    if raw.get("langs") is not None:
+        raw["langs"] = orjson.dumps(raw["langs"])
+    if raw.get("text") is not None:
+        raw["text"] = raw["text"].replace("\x00", "")
+    return raw
+
+
+def parse_date(raw_date: int) -> datetime:
+    """Parse compact YYYYMMDDHHmm integer into a naive datetime (input is UTC by spec)."""
+    return datetime(
+        raw_date // 100000000,
+        (raw_date // 1000000) % 100,
+        (raw_date // 10000) % 100,
+        (raw_date // 100) % 100,
+        raw_date % 100,
+        tzinfo=UTC,
+    )
+
+
+if __name__ == "__main__":
+    app()

python/database_cli.py

@@ -83,6 +83,20 @@ DATABASES: dict[str, DatabaseConfig] = {
         base_class_name="VanInventoryBase",
         models_module="python.orm.van_inventory.models",
     ),
+    "signal_bot": DatabaseConfig(
+        env_prefix="SIGNALBOT",
+        version_location="python/alembic/signal_bot/versions",
+        base_module="python.orm.signal_bot.base",
+        base_class_name="SignalBotBase",
+        models_module="python.orm.signal_bot.models",
+    ),
+    "data_science_dev": DatabaseConfig(
+        env_prefix="DATA_SCIENCE_DEV",
+        version_location="python/alembic/data_science_dev/versions",
+        base_module="python.orm.data_science_dev.base",
+        base_class_name="DataScienceDevBase",
+        models_module="python.orm.data_science_dev.models",
+    ),
 }
 
 

python/ebook_search/__init__.py

@@ -1 +0,0 @@
-"""EPUB search package."""

python/ebook_search/answer.py

@@ -1,57 +0,0 @@
-"""Grounded answer generation."""
-
-from __future__ import annotations
-
-import logging
-from typing import TYPE_CHECKING
-
-from python.ebook_search.llm_interface import request_chat_completion
-
-if TYPE_CHECKING:
-    from python.ebook_search.config import EbookSearchConfig
-    from python.ebook_search.search import SearchResult
-
-logger = logging.getLogger(__name__)
-
-
-def answer_query(query: str, results: list[SearchResult], config: EbookSearchConfig) -> str:
-    """Answer a question using only retrieved chunks."""
-    if not config.answer_enabled:
-        logger.info("ebook_answer_skipped_disabled")
-        return "Answer generation is disabled. Source chunks are shown below."
-
-    if not results:
-        logger.info("ebook_answer_skipped_no_results")
-        return "No relevant sources were found."
-
-    logger.info(
-        "ebook_answer_request_start base_url=%s model=%s sources=%s query_length=%s",
-        config.vllm_base_url,
-        config.chat_model,
-        len(results),
-        len(query),
-    )
-    context = "\n\n".join(
-        f"[{index}] {result.source_title}{' - ' + result.chapter_title if result.chapter_title else ''}\n{result.text}"
-        for index, result in enumerate(results, start=1)
-    )
-    content = request_chat_completion(
-        config,
-        [
-            {
-                "role": "system",
-                "content": (
-                    "Answer only from the provided context. Cite sources with bracketed numbers like [1]. "
-                    "If the context is insufficient, say so."
-                ),
-            },
-            {"role": "user", "content": f"Question:\n{query}\n\nContext:\n{context}"},
-        ],
-    )
-
-    logger.info(
-        "ebook_answer_request_complete model=%s answer_length=%s",
-        config.chat_model,
-        len(content),
-    )
-    return content or "The model returned an empty answer."

python/ebook_search/api/__init__.py

@@ -1 +0,0 @@
-"""Web and external API adapters for EPUB search."""

python/ebook_search/api/bm25_tasks.py

@@ -1,60 +0,0 @@
-"""Background BM25 refresh tasks for the web app."""
-
-from __future__ import annotations
-
-import logging
-from threading import Timer
-from typing import TYPE_CHECKING
-
-from sqlalchemy.orm import Session
-
-from python.ebook_search.bm25_corpus import load_bm25_corpus, refresh_bm25_corpus
-
-if TYPE_CHECKING:
-    from fastapi import FastAPI
-    from sqlalchemy.engine import Engine
-
-    from python.ebook_search.config import EbookSearchConfig
-
-logger = logging.getLogger(__name__)
-
-
-def schedule_bm25_refresh(app: FastAPI) -> None:
-    """Schedule a delayed BM25 corpus refresh, replacing any pending refresh."""
-    existing_timer = getattr(app.state, "bm25_refresh_timer", None)
-    if existing_timer is not None:
-        existing_timer.cancel()
-
-    timer = Timer(app.state.config.bm25_refresh_delay_seconds, refresh_bm25_for_app, args=(app,))
-    timer.daemon = True
-    timer.start()
-    app.state.bm25_refresh_timer = timer
-    logger.info(
-        "ebook_bm25_refresh_scheduled delay_seconds=%s",
-        app.state.config.bm25_refresh_delay_seconds,
-    )
-
-
-def cancel_bm25_refresh(app: FastAPI) -> None:
-    """Cancel any pending BM25 corpus refresh."""
-    existing_timer = getattr(app.state, "bm25_refresh_timer", None)
-    if existing_timer is not None:
-        existing_timer.cancel()
-        app.state.bm25_refresh_timer = None
-        logger.info("ebook_bm25_refresh_cancelled")
-
-
-def refresh_bm25_for_app(app: FastAPI) -> None:
-    """Refresh the BM25 corpus using the app engine and config."""
-    try:
-        refresh_bm25_for_engine(app.state.engine, app.state.config)
-    except Exception:
-        logger.exception("ebook_bm25_refresh_failed")
-
-
-def refresh_bm25_for_engine(engine: Engine, config: EbookSearchConfig) -> None:
-    """Refresh the BM25 corpus using a SQLAlchemy engine."""
-    with Session(engine) as session:
-        refresh_bm25_corpus(session, config)
-    load_bm25_corpus.cache_clear()
-    logger.info("ebook_bm25_corpus_cache_cleared_after_refresh")

python/ebook_search/api/main.py

@@ -1,79 +0,0 @@
-"""FastAPI HTMX app for EPUB search."""
-
-from __future__ import annotations
-
-import logging
-from contextlib import asynccontextmanager
-from typing import TYPE_CHECKING, Annotated
-
-import typer
-import uvicorn
-from fastapi import FastAPI
-from fastapi.staticfiles import StaticFiles
-from sqlalchemy.orm import Session
-
-from python.common import configure_logger
-from python.ebook_search.api.bm25_tasks import cancel_bm25_refresh
-from python.ebook_search.api.routes import admin_router, page_router, search_router
-from python.ebook_search.api.web import STATIC_DIR
-from python.ebook_search.bm25_corpus import ensure_bm25_corpus
-from python.ebook_search.config import load_config
-from python.fastapi_tools import ZstdMiddleware
-from python.orm.common import get_postgres_engine
-
-if TYPE_CHECKING:
-    from collections.abc import AsyncIterator
-
-
-logger = logging.getLogger(__name__)
-
-
-@asynccontextmanager
-async def lifespan(app: FastAPI) -> AsyncIterator[None]:
-    """Manage application startup and shutdown resources."""
-    logger.info("ebook_search_startup")
-    app.state.engine = get_postgres_engine(name="RICHIE", vector_engine=True)
-    with Session(app.state.engine) as session:
-        ensure_bm25_corpus(session, app.state.config)
-    try:
-        yield
-    finally:
-        logger.info("ebook_search_shutdown")
-        cancel_bm25_refresh(app)
-        app.state.engine.dispose()
-
-
-def create_app() -> FastAPI:
-    """Create the EPUB search web app."""
-    app = FastAPI(title="EPUB Search", lifespan=lifespan)
-    app.add_middleware(ZstdMiddleware)
-    app.mount("/static", StaticFiles(directory=STATIC_DIR), name="static")
-    app.state.config = load_config()
-    logger.info(
-        "ebook_search_config_loaded top_k=%s embedding_model=%s rerank_enabled=%s answer_enabled=%s library_paths=%s",
-        app.state.config.top_k,
-        app.state.config.embedding_model,
-        app.state.config.rerank.enabled,
-        app.state.config.answer_enabled,
-        len(app.state.config.library_paths),
-    )
-
-    app.include_router(admin_router)
-    app.include_router(page_router)
-    app.include_router(search_router)
-
-    return app
-
-
-def serve(
-    host: Annotated[str, typer.Option("--host", "-h", help="Host to bind to")] = "127.0.0.1",
-    port: Annotated[int, typer.Option("--port", "-p", help="Port to bind to")] = 8070,
-    log_level: Annotated[str, typer.Option("--log-level", "-l", help="Log level")] = "INFO",
-) -> None:
-    """Start the EPUB search server."""
-    configure_logger(log_level)
-    uvicorn.run(create_app(), host=host, port=port)
-
-
-if __name__ == "__main__":
-    typer.run(serve)

python/ebook_search/api/routes/__init__.py

@@ -1,11 +0,0 @@
-"""EPUB search web route modules."""
-
-from python.ebook_search.api.routes.admin import router as admin_router
-from python.ebook_search.api.routes.page import router as page_router
-from python.ebook_search.api.routes.search import router as search_router
-
-__all__ = [
-    "admin_router",
-    "page_router",
-    "search_router",
-]

python/ebook_search/api/routes/admin.py

@@ -1,107 +0,0 @@
-"""Admin routes for the EPUB search web UI."""
-
-from __future__ import annotations
-
-import logging
-from dataclasses import replace
-
-from fastapi import APIRouter, Request
-from fastapi.responses import HTMLResponse
-from sqlalchemy.orm import Session
-
-from python.ebook_search.api.bm25_tasks import schedule_bm25_refresh
-from python.ebook_search.api.web import templates
-from python.ebook_search.embeddings import embed_missing_chunks, embedding_model_stats
-from python.ebook_search.ingest import ingest_configured_paths
-
-logger = logging.getLogger(__name__)
-
-router = APIRouter(prefix="/admin")
-EMBED_ALL_BATCH_SIZE = 32
-
-
-@router.get("", response_class=HTMLResponse)
-def admin(request: Request) -> HTMLResponse:
-    """Render the admin page."""
-    with Session(request.app.state.engine) as session:
-        stats = embedding_model_stats(session)
-    logger.info("ebook_admin_page_loaded models=%s", len(stats))
-    return templates.TemplateResponse(request, "admin.html", {"config": request.app.state.config, "stats": stats})
-
-
-@router.post("/scan", response_class=HTMLResponse)
-def scan_library(request: Request) -> HTMLResponse:
-    """Scan configured library paths for EPUB changes."""
-    try:
-        with Session(request.app.state.engine) as session:
-            count = ingest_configured_paths(session, request.app.state.config)
-            session.commit()
-    except Exception as error:
-        logger.exception("ebook_admin_scan_failed")
-        return templates.TemplateResponse(request, "partials/error.html", {"message": str(error)}, status_code=500)
-
-    logger.info("ebook_admin_scan_complete changed_files=%s", count)
-    if count > 0:
-        schedule_bm25_refresh(request.app)
-    return templates.TemplateResponse(request, "partials/admin_status.html", {"message": f"Indexed {count} EPUBs"})
-
-
-@router.post("/embed-missing", response_class=HTMLResponse)
-def embed_missing(request: Request) -> HTMLResponse:
-    """Embed chunks missing vectors for the configured model."""
-    try:
-        with Session(request.app.state.engine) as session:
-            count = embed_missing_chunks(session, request.app.state.config)
-            session.commit()
-    except Exception as error:
-        logger.exception("ebook_admin_embed_missing_failed")
-        return templates.TemplateResponse(request, "partials/error.html", {"message": str(error)}, status_code=500)
-
-    logger.info("ebook_admin_embed_missing_complete chunks=%s", count)
-    return templates.TemplateResponse(
-        request,
-        "partials/admin_status.html",
-        {"message": f"Embedded {count} chunks"},
-    )
-
-
-@router.post("/embed-all", response_class=HTMLResponse)
-def embed_all(request: Request) -> HTMLResponse:
-    """Embed all chunks missing vectors in fixed-size batches."""
-    total = 0
-    batches = 0
-    config = replace(request.app.state.config, embedding_batch_size=EMBED_ALL_BATCH_SIZE)
-    try:
-        with Session(request.app.state.engine) as session:
-            while True:
-                count = embed_missing_chunks(session, config)
-                if count == 0:
-                    break
-                session.commit()
-                total += count
-                batches += 1
-                logger.info(
-                    "ebook_admin_embed_all_batch_complete batch=%s chunks=%s total_chunks=%s",
-                    batches,
-                    count,
-                    total,
-                )
-    except Exception as error:
-        logger.exception(
-            "ebook_admin_embed_all_failed batches=%s chunks=%s",
-            batches,
-            total,
-        )
-        return templates.TemplateResponse(
-            request,
-            "partials/error.html",
-            {"message": f"Embed all failed after {total} chunks in {batches} batches: {error}"},
-            status_code=500,
-        )
-
-    logger.info("ebook_admin_embed_all_complete batches=%s chunks=%s", batches, total)
-    return templates.TemplateResponse(
-        request,
-        "partials/admin_status.html",
-        {"message": f"Embedded {total} chunks in {batches} batches of {EMBED_ALL_BATCH_SIZE}"},
-    )

python/ebook_search/api/routes/page.py

@@ -1,57 +0,0 @@
-"""Page routes for the EPUB search web UI."""
-
-from __future__ import annotations
-
-import logging
-
-from fastapi import APIRouter, Request
-from fastapi.responses import HTMLResponse
-from sqlalchemy import select
-from sqlalchemy.orm import Session
-
-from python.ebook_search.api.web import templates
-from python.orm.richie import EbookSource
-
-logger = logging.getLogger(__name__)
-
-router = APIRouter()
-
-
-@router.get("/", response_class=HTMLResponse)
-def index(request: Request) -> HTMLResponse:
-    """Render the search page."""
-    return templates.TemplateResponse(request, "search.html", {"config": request.app.state.config})
-
-
-@router.get("/books", response_class=HTMLResponse)
-def books(request: Request) -> HTMLResponse:
-    """Render the indexed books page."""
-    with Session(request.app.state.engine) as session:
-        sources = list(session.scalars(select(EbookSource).order_by(EbookSource.title)).all())
-    logger.info("ebook_books_page_loaded count=%s", len(sources))
-    return templates.TemplateResponse(request, "books.html", {"sources": sources})
-
-
-@router.get("/books/{source_id}", response_class=HTMLResponse)
-def book_detail(source_id: int, request: Request) -> HTMLResponse:
-    """Render details for one indexed book."""
-    with Session(request.app.state.engine) as session:
-        source = session.get(EbookSource, source_id)
-        if source is not None:
-            chapter_count = len(source.chapters)
-            chunk_count = len(source.chunks)
-        else:
-            chapter_count = 0
-            chunk_count = 0
-    logger.info(
-        "ebook_book_detail_loaded source_id=%s found=%s chapters=%s chunks=%s",
-        source_id,
-        source is not None,
-        chapter_count,
-        chunk_count,
-    )
-    return templates.TemplateResponse(
-        request,
-        "book_detail.html",
-        {"chapter_count": chapter_count, "chunk_count": chunk_count, "source": source},
-    )

python/ebook_search/api/routes/search.py

@@ -1,58 +0,0 @@
-"""Search routes for the EPUB search web UI."""
-
-from __future__ import annotations
-
-import logging
-from dataclasses import replace
-from time import perf_counter
-from typing import Annotated
-
-from fastapi import APIRouter, Form, Request
-from fastapi.responses import HTMLResponse
-
-from python.ebook_search.answer import answer_query
-from python.ebook_search.api.web import templates
-from python.ebook_search.search import search_ebooks
-from python.ebook_search.timing import runtime_step_from_start
-
-logger = logging.getLogger(__name__)
-
-router = APIRouter()
-
-
-@router.post("/search", response_class=HTMLResponse)
-def search(
-    request: Request,
-    query: Annotated[str, Form()],
-    rerank: Annotated[str | None, Form()] = None,
-) -> HTMLResponse:
-    """Run a search and render HTMX results."""
-    try:
-        response = search_ebooks(request.app.state.engine, query, request.app.state.config, rerank=rerank == "true")
-    except Exception as error:
-        logger.exception("ebook_search_request_failed")
-        return templates.TemplateResponse(request, "partials/error.html", {"message": str(error)}, status_code=500)
-
-    answer_start = perf_counter()
-    if request.app.state.config.answer_enabled:
-        try:
-            answer = answer_query(query, response.results, request.app.state.config)
-        except RuntimeError as error:
-            logger.warning("ebook_answer_request_failed_falling_back error=%s", error)
-            answer = "Answer generation failed. Source chunks are still shown below."
-    else:
-        logger.info("ebook_answer_skipped_disabled")
-        answer = "Answer generation is disabled. Source chunks are shown below."
-    answer_step_name = "Answer generation" if request.app.state.config.answer_enabled else "Answer skipped"
-    response = replace(
-        response,
-        timings=(*response.timings, runtime_step_from_start(answer_step_name, answer_start)),
-    )
-
-    logger.info(
-        "ebook_search_request_complete results=%s rank_label=%s runtime_ms=%.1f",
-        len(response.results),
-        response.rank_label,
-        response.total_runtime_ms,
-    )
-    return templates.TemplateResponse(request, "partials/results.html", {"answer": answer, "response": response})

python/ebook_search/api/static/style.css

@@ -1,140 +0,0 @@
-body {
-    margin: 0;
-    background: #f7f7f4;
-    color: #202124;
-    font-family: system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
-}
-
-main {
-    max-width: 960px;
-    margin: 0 auto;
-    padding: 24px;
-}
-
-nav {
-    display: flex;
-    gap: 12px;
-    align-items: center;
-    margin-bottom: 20px;
-}
-
-nav form {
-    margin: 0;
-}
-
-.actions {
-    display: flex;
-    flex-wrap: wrap;
-    gap: 12px;
-    margin-bottom: 24px;
-}
-
-textarea {
-    display: block;
-    width: 100%;
-    margin: 8px 0 12px;
-}
-
-button {
-    padding: 8px 14px;
-}
-
-.check {
-    display: inline-flex;
-    gap: 8px;
-    align-items: center;
-    margin-right: 12px;
-}
-
-.rank-label {
-    margin-top: 24px;
-    font-weight: 700;
-}
-
-.results {
-    padding-left: 24px;
-}
-
-.meta,
-.scores,
-.status {
-    color: #626a73;
-}
-
-.scores {
-    display: flex;
-    flex-wrap: wrap;
-    gap: 8px;
-    margin: 12px 0;
-}
-
-.scores div {
-    display: inline-flex;
-    gap: 4px;
-    align-items: baseline;
-}
-
-.scores dt {
-    font-weight: 700;
-}
-
-.scores dd {
-    margin: 0;
-}
-
-.runtime {
-    margin-top: 16px;
-}
-
-.timing-chart {
-    display: grid;
-    gap: 8px;
-    padding: 0;
-    list-style: none;
-}
-
-.timing-chart li {
-    display: grid;
-    grid-template-columns: minmax(150px, 1fr) minmax(160px, 2fr) auto auto;
-    gap: 8px;
-    align-items: center;
-}
-
-.timing-bar {
-    height: 10px;
-    overflow: hidden;
-    background: #e5e5df;
-}
-
-.timing-bar span {
-    display: block;
-    height: 100%;
-    background: #3767c8;
-}
-
-.timing-value,
-.timing-remaining {
-    color: #626a73;
-    font-variant-numeric: tabular-nums;
-}
-
-table {
-    width: 100%;
-    border-collapse: collapse;
-}
-
-th,
-td {
-    padding: 8px;
-    border-bottom: 1px solid #d8d8d2;
-    text-align: left;
-}
-
-th {
-    font-weight: 700;
-}
-
-.error {
-    color: #9f1d20;
-    font-weight: 700;
-}

python/ebook_search/api/templates/admin.html

@@ -1,57 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>EPUB Admin</title>
-    <script src="https://unpkg.com/htmx.org@2.0.4"></script>
-    <link rel="stylesheet" href="/static/style.css">
-</head>
-<body>
-    <main>
-        <nav>
-            <a href="/">Search</a>
-            <a href="/books">Books</a>
-            <a href="/admin">Admin</a>
-        </nav>
-        <h1>Admin</h1>
-        <section id="admin-status"></section>
-        <section class="actions">
-            <form hx-post="/admin/scan" hx-target="#admin-status" hx-swap="innerHTML">
-                <button type="submit">Scan</button>
-            </form>
-            <form hx-post="/admin/embed-missing" hx-target="#admin-status" hx-swap="innerHTML">
-                <button type="submit">Embed</button>
-            </form>
-            <form hx-post="/admin/embed-all" hx-target="#admin-status" hx-swap="innerHTML">
-                <button type="submit">Embed all</button>
-            </form>
-        </section>
-        <section>
-            <h2>Embeddings</h2>
-            <table>
-                <thead>
-                    <tr>
-                        <th>Model</th>
-                        <th>Dimensions</th>
-                        <th>Embedded</th>
-                        <th>Missing</th>
-                        <th>Total chunks</th>
-                    </tr>
-                </thead>
-                <tbody>
-                    {% for item in stats %}
-                        <tr>
-                            <td>{{ item.model_name }}</td>
-                            <td>{{ item.dimension }}</td>
-                            <td>{{ item.embedded_chunks }}</td>
-                            <td>{{ item.missing_chunks }}</td>
-                            <td>{{ item.total_chunks }}</td>
-                        </tr>
-                    {% endfor %}
-                </tbody>
-            </table>
-        </section>
-    </main>
-</body>
-</html>

python/ebook_search/api/templates/book_detail.html

@@ -1,32 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>{% if source %}{{ source.title }}{% else %}Book not found{% endif %}</title>
-    <link rel="stylesheet" href="/static/style.css">
-</head>
-<body>
-    <main>
-        <nav>
-            <a href="/">Search</a>
-            <a href="/books">Books</a>
-            <a href="/admin">Admin</a>
-        </nav>
-        {% if source %}
-            <h1>{{ source.title }}</h1>
-            <p class="meta">{{ source.author or "Unknown author" }}</p>
-            <dl>
-                <dt>File</dt>
-                <dd>{{ source.file_path }}</dd>
-                <dt>Chapters</dt>
-                <dd>{{ chapter_count }}</dd>
-                <dt>Chunks</dt>
-                <dd>{{ chunk_count }}</dd>
-            </dl>
-        {% else %}
-            <h1>Book not found</h1>
-        {% endif %}
-    </main>
-</body>
-</html>

python/ebook_search/api/templates/books.html

@@ -1,31 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>EPUB Books</title>
-    <link rel="stylesheet" href="/static/style.css">
-</head>
-<body>
-    <main>
-        <nav>
-            <a href="/">Search</a>
-            <a href="/books">Books</a>
-            <a href="/admin">Admin</a>
-        </nav>
-        <h1>Books</h1>
-        {% if sources %}
-            <ol class="results">
-                {% for source in sources %}
-                    <li>
-                        <h2><a href="/books/{{ source.id }}">{{ source.title }}</a></h2>
-                        <p class="meta">{{ source.author or "Unknown author" }}</p>
-                    </li>
-                {% endfor %}
-            </ol>
-        {% else %}
-            <p>No EPUBs indexed.</p>
-        {% endif %}
-    </main>
-</body>
-</html>

python/ebook_search/api/templates/partials/admin_status.html

@@ -1 +0,0 @@
-<p class="status">{{ message }}</p>

python/ebook_search/api/templates/partials/error.html

@@ -1 +0,0 @@
-<p class="error">{{ message }}</p>

python/ebook_search/api/templates/partials/results.html

@@ -1,74 +0,0 @@
-<div class="rank-label">{{ response.rank_label }}</div>
-{% if response.timings %}
-    <section class="runtime">
-        <h2>Runtime</h2>
-        <p class="meta">Total {{ "%.1f"|format(response.total_runtime_ms) }} ms</p>
-        <ol class="timing-chart">
-            {% set total = response.total_runtime_ms %}
-            {% set ns = namespace(remaining=total) %}
-            {% for step in response.timings %}
-                {% set width = (step.duration_ms / total * 100) if total else 0 %}
-                {% if step.counts_toward_total %}
-                    {% set ns.remaining = ns.remaining - step.duration_ms %}
-                {% endif %}
-                <li>
-                    <span class="timing-label">{{ step.name }}</span>
-                    <span class="timing-bar"><span style="width: {{ "%.2f"|format(width) }}%"></span></span>
-                    <span class="timing-value">{{ "%.1f"|format(step.duration_ms) }} ms</span>
-                    <span class="timing-remaining">{{ "%.1f"|format([ns.remaining, 0]|max) }} ms left</span>
-                </li>
-            {% endfor %}
-        </ol>
-    </section>
-{% endif %}
-<section class="answer">
-    <h2>Answer</h2>
-    <p>{{ answer }}</p>
-</section>
-{% if response.results %}
-    <ol class="results">
-        {% for result in response.results %}
-            <li>
-                <h2>{{ result.source_title }}</h2>
-                <p class="meta">
-                    {% if result.source_author %}{{ result.source_author }}{% endif %}
-                    {% if result.chapter_title %} · {{ result.chapter_title }}{% endif %}
-                    {% if result.page_label %} · page {{ result.page_label }}{% endif %}
-                </p>
-                <p>{{ result.text }}</p>
-                <dl class="scores">
-                    <div>
-                        <dt>final</dt>
-                        <dd>{{ "%.3f"|format(result.score) }}</dd>
-                    </div>
-                    {% if result.rerank_score is not none %}
-                        <div>
-                            <dt>rerank</dt>
-                            <dd>{{ "%.3f"|format(result.rerank_score) }}</dd>
-                        </div>
-                    {% endif %}
-                    {% if result.vector_score is not none %}
-                        <div>
-                            <dt>vector cosine</dt>
-                            <dd>{{ "%.3f"|format(result.vector_score) }}</dd>
-                        </div>
-                    {% endif %}
-                    {% if result.bm25_score is not none %}
-                        <div>
-                            <dt>BM25</dt>
-                            <dd>{{ "%.6f"|format(result.bm25_score) }}</dd>
-                        </div>
-                    {% endif %}
-                    {% if result.fused_score is not none %}
-                        <div>
-                            <dt>RRF</dt>
-                            <dd>{{ "%.3f"|format(result.fused_score) }}</dd>
-                        </div>
-                    {% endif %}
-                </dl>
-            </li>
-        {% endfor %}
-    </ol>
-{% else %}
-    <p>No results.</p>
-{% endif %}

python/ebook_search/api/templates/search.html

@@ -1,30 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>EPUB Search</title>
-    <script src="https://unpkg.com/htmx.org@2.0.4"></script>
-    <link rel="stylesheet" href="/static/style.css">
-</head>
-<body>
-    <main>
-        <nav>
-            <a href="/">Search</a>
-            <a href="/books">Books</a>
-            <a href="/admin">Admin</a>
-        </nav>
-        <h1>EPUB Search</h1>
-        <form hx-post="/search" hx-target="#results" hx-swap="innerHTML">
-            <label for="query">Search</label>
-            <textarea id="query" name="query" rows="4" required></textarea>
-            <label class="check">
-                <input type="checkbox" name="rerank" value="true" {% if config.rerank.enabled %}checked{% endif %}>
-                Rerank
-            </label>
-            <button type="submit">Search</button>
-        </form>
-        <section id="results"></section>
-    </main>
-</body>
-</html>

python/ebook_search/api/web.py

@@ -1,13 +0,0 @@
-"""Shared web UI resources for EPUB search."""
-
-from __future__ import annotations
-
-from pathlib import Path
-
-from fastapi.templating import Jinja2Templates
-
-PACKAGE_DIR = Path(__file__).resolve().parent
-TEMPLATE_DIR = PACKAGE_DIR / "templates"
-STATIC_DIR = PACKAGE_DIR / "static"
-
-templates = Jinja2Templates(directory=TEMPLATE_DIR)

python/ebook_search/bm25_corpus.py

@@ -1,281 +0,0 @@
-"""Persisted BM25 corpus management."""
-
-from __future__ import annotations
-
-import json
-import logging
-import shutil
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from functools import cache
-from pathlib import Path
-from typing import TYPE_CHECKING
-
-import bm25s
-from sqlalchemy import func, select, union_all
-
-from python.orm.richie import EbookChapter, EbookChunk, EbookSource
-
-if TYPE_CHECKING:
-    from sqlalchemy.orm import Session
-
-    from python.ebook_search.config import EbookSearchConfig
-
-logger = logging.getLogger(__name__)
-MANIFEST_NAME = "manifest.json"
-REQUIRED_INDEX_FILES = frozenset(
-    {
-        "data.csc.index.npy",
-        "indices.csc.index.npy",
-        "indptr.csc.index.npy",
-        "params.index.json",
-        "vocab.index.json",
-        "corpus.jsonl",
-    }
-)
-
-
-@dataclass(frozen=True)
-class BM25Manifest:
-    """Metadata describing a persisted BM25 corpus."""
-
-    created_at: datetime
-    db_updated_at: datetime | None
-    chunk_count: int
-
-
-@dataclass(frozen=True)
-class BM25Corpus:
-    """Loaded persisted BM25 corpus and retriever."""
-
-    retriever: object | None
-    records: tuple[dict[str, object], ...]
-    manifest: BM25Manifest
-
-
-class BM25CorpusUnavailableError(RuntimeError):
-    """Raised when the persisted BM25 corpus cannot be loaded."""
-
-
-def bm25_index_path(config: EbookSearchConfig) -> Path:
-    """Return the configured BM25 index root path relative to the current working directory."""
-    path = Path(config.bm25_index_dir).expanduser()
-    if path.is_absolute():
-        return path
-    return Path.cwd() / path
-
-
-def get_current_bm25_index(index_path: Path) -> Path:
-    """Return the live BM25 index directory."""
-    current_path = index_path / "current"
-    if current_path.exists() or current_path.is_symlink():
-        return current_path
-    return index_path
-
-
-def ensure_bm25_corpus(session: Session, config: EbookSearchConfig) -> None:
-    """Create or refresh the persisted BM25 corpus when it is missing or stale."""
-    index_path = bm25_index_path(config)
-    manifest = read_bm25_manifest(index_path)
-    db_updated_at = corpus_last_updated_at(session)
-    if not bm25_index_exists(index_path, manifest):
-        logger.info("ebook_bm25_index_missing path=%s", index_path)
-        refresh_bm25_corpus(session, config, db_updated_at=db_updated_at)
-        return
-    if db_updated_at is not None and manifest is not None and manifest.created_at < db_updated_at:
-        logger.info(
-            "ebook_bm25_index_stale path=%s created_at=%s db_updated_at=%s",
-            index_path,
-            manifest.created_at.isoformat(),
-            db_updated_at.isoformat(),
-        )
-        refresh_bm25_corpus(session, config, db_updated_at=db_updated_at)
-        return
-    logger.info(
-        "ebook_bm25_index_current path=%s chunks=%s created_at=%s",
-        index_path,
-        manifest.chunk_count if manifest else 0,
-        manifest.created_at.isoformat() if manifest else None,
-    )
-
-
-def refresh_bm25_corpus(
-    session: Session,
-    config: EbookSearchConfig,
-    *,
-    db_updated_at: datetime | None = None,
-) -> BM25Manifest:
-    """Rebuild and persist the BM25 corpus from the current database chunks."""
-    index_path = bm25_index_path(config)
-    records, texts = fetch_bm25_corpus_records(session)
-    manifest = BM25Manifest(
-        created_at=datetime.now(tz=UTC),
-        db_updated_at=db_updated_at if db_updated_at is not None else corpus_last_updated_at(session),
-        chunk_count=len(records),
-    )
-    write_bm25_corpus(index_path, records, texts, manifest)
-    logger.info(
-        "ebook_bm25_index_refreshed path=%s chunks=%s created_at=%s",
-        index_path,
-        manifest.chunk_count,
-        manifest.created_at.isoformat(),
-    )
-    return manifest
-
-
-@cache
-def load_bm25_corpus(config: EbookSearchConfig) -> BM25Corpus:
-    """Load the BM25 corpus into memory once per process.
-
-    Background refresh tasks clear this cache after rebuilding the on-disk corpus.
-    """
-    index_path = bm25_index_path(config)
-    active_index_path = get_current_bm25_index(index_path)
-    logger.info("ebook_bm25_corpus_cache_load path=%s active_path=%s", index_path, active_index_path)
-    manifest = read_bm25_manifest(index_path)
-    if manifest is None or not bm25_index_exists(index_path, manifest):
-        msg = f"BM25 corpus is not available: {index_path}"
-        raise BM25CorpusUnavailableError(msg)
-    if manifest.chunk_count == 0:
-        return BM25Corpus(retriever=None, records=(), manifest=manifest)
-
-    retriever = bm25s.BM25.load(active_index_path, load_corpus=True, mmap=True)
-    records = tuple(dict(record) for record in retriever.corpus)
-    return BM25Corpus(retriever=retriever, records=records, manifest=manifest)
-
-
-def score_bm25_corpus(query: str, corpus: BM25Corpus, *, limit: int) -> list[tuple[dict[str, object], float]]:
-    """Score a query against a loaded BM25 corpus."""
-    if corpus.retriever is None or not corpus.records:
-        return []
-    k = min(limit, len(corpus.records))
-    documents, scores = corpus.retriever.retrieve(
-        bm25s.tokenize(query, show_progress=False),
-        corpus=list(corpus.records),
-        k=k,
-        show_progress=False,
-    )
-    results: list[tuple[dict[str, object], float]] = []
-    for document, score in zip(documents[0], scores[0], strict=True):
-        score_value = float(score)
-        if score_value <= 0:
-            continue
-        results.append((dict(document), score_value))
-    return results
-
-
-def fetch_bm25_corpus_records(session: Session) -> tuple[list[dict[str, object]], list[str]]:
-    """Fetch persistable BM25 corpus records and their matching index texts from the database.
-
-    search_text is only needed to build the index, so it is returned separately instead of
-    being persisted into the corpus records, which would double the corpus size.
-    """
-    statement = (
-        select(
-            EbookChunk.id.label("chunk_id"),
-            EbookChunk.text.label("text"),
-            EbookSource.title.label("source_title"),
-            EbookSource.author.label("source_author"),
-            EbookChapter.title.label("chapter_title"),
-            EbookChunk.page_label.label("page_label"),
-            EbookChunk.search_text.label("bm25_text"),
-        )
-        .select_from(EbookChunk)
-        .join(EbookSource, EbookSource.id == EbookChunk.source_id)
-        .outerjoin(EbookChapter, EbookChapter.id == EbookChunk.chapter_id)
-        .order_by(EbookChunk.id)
-    )
-    records: list[dict[str, object]] = []
-    texts: list[str] = []
-    for row in session.execute(statement).mappings():
-        record = dict(row)
-        texts.append(str(record.pop("bm25_text")))
-        records.append(record)
-    return records, texts
-
-
-def corpus_last_updated_at(session: Session) -> datetime | None:
-    """Return the latest source/chapter/chunk update timestamp relevant to BM25 text."""
-    update_times = union_all(
-        select(func.max(EbookSource.updated).label("updated")),
-        select(func.max(EbookChapter.updated).label("updated")),
-        select(func.max(EbookChunk.updated).label("updated")),
-    ).subquery()
-    return session.scalar(select(func.max(update_times.c.updated)))
-
-
-def write_bm25_corpus(
-    index_path: Path,
-    records: list[dict[str, object]],
-    texts: list[str],
-    manifest: BM25Manifest,
-) -> None:
-    """Write a BM25 corpus generation and publish it through the current symlink."""
-    index_path.mkdir(parents=True, exist_ok=True)
-
-    generations_path = index_path / "generations"
-    generations_path.mkdir(exist_ok=True)
-
-    generation_path = next_bm25_generation_path(generations_path, manifest.created_at)
-    current_path = index_path / "current"
-    next_current_path = index_path / f".current.{generation_path.name}.tmp"
-    try:
-        generation_path.mkdir()
-
-        # Empty corpora publish a manifest-only generation so startup succeeds before any chunks exist.
-        if records:
-            retriever = bm25s.BM25()
-            retriever.index(bm25s.tokenize(texts, show_progress=False), show_progress=False)
-            retriever.save(generation_path, corpus=records, show_progress=False)
-        write_bm25_manifest(generation_path, manifest)
-        next_current_path.unlink(missing_ok=True)
-        next_current_path.symlink_to(generation_path, target_is_directory=True)
-        next_current_path.replace(current_path)
-    except Exception:
-        next_current_path.unlink(missing_ok=True)
-        shutil.rmtree(generation_path, ignore_errors=True)
-        raise
-
-
-def read_bm25_manifest(index_path: Path) -> BM25Manifest | None:
-    """Read the BM25 manifest if it exists and is valid."""
-    manifest_path = get_current_bm25_index(index_path) / MANIFEST_NAME
-    if not manifest_path.exists():
-        return None
-    body = json.loads(manifest_path.read_text(encoding="utf-8"))
-    return BM25Manifest(
-        created_at=datetime.fromisoformat(str(body["created_at"])),
-        db_updated_at=datetime.fromisoformat(str(body["db_updated_at"])) if body.get("db_updated_at") else None,
-        chunk_count=int(body["chunk_count"]),
-    )
-
-
-def write_bm25_manifest(index_path: Path, manifest: BM25Manifest) -> None:
-    """Write the BM25 manifest to an index directory."""
-    body = {
-        "created_at": manifest.created_at.isoformat(),
-        "db_updated_at": manifest.db_updated_at.isoformat() if manifest.db_updated_at else None,
-        "chunk_count": manifest.chunk_count,
-    }
-    (index_path / MANIFEST_NAME).write_text(json.dumps(body, indent=2, sort_keys=True), encoding="utf-8")
-
-
-def bm25_index_exists(index_path: Path, manifest: BM25Manifest | None) -> bool:
-    """Return whether a usable persisted BM25 index exists."""
-    active_index_path = get_current_bm25_index(index_path)
-    if manifest is None or not active_index_path.is_dir():
-        return False
-    if manifest.chunk_count == 0:
-        return True
-    return all((active_index_path / file_name).exists() for file_name in REQUIRED_INDEX_FILES)
-
-
-def next_bm25_generation_path(generations_path: Path, created_at: datetime) -> Path:
-    """Return an unused dated BM25 generation path."""
-    base_name = created_at.astimezone(UTC).strftime("%Y%m%dT%H%M%S.%fZ")
-    generation_path = generations_path / base_name
-    suffix = 1
-    while generation_path.exists():
-        generation_path = generations_path / f"{base_name}.{suffix}"
-        suffix += 1
-    return generation_path

python/ebook_search/config.py

@@ -1,117 +0,0 @@
-"""Configuration for the EPUB search app."""
-
-from __future__ import annotations
-
-from dataclasses import dataclass
-from os import getenv
-
-
-def getenv_bool(name: str, *, default: bool) -> bool:
-    """Read a boolean environment variable with a default fallback."""
-    value = getenv(name)
-    if value is None:
-        return default
-    return value.strip().lower() in {"1", "true", "yes", "on"}
-
-
-def getenv_int(name: str, *, default: int) -> int:
-    """Read an integer environment variable with a default fallback."""
-    value = getenv(name)
-    if value is None or not value.strip():
-        return default
-    return int(value)
-
-
-@dataclass(frozen=True)
-class RerankConfig:
-    """vLLM reranker settings."""
-
-    enabled: bool = False
-    base_url: str = "http://192.168.90.25:8001"
-    model: str = "qwen3-reranker-06b"
-    candidates: int = 24
-    timeout_seconds: float = 30.0
-
-
-@dataclass(frozen=True)
-class EbookSearchConfig:
-    """Runtime settings for EPUB search."""
-
-    rerank: RerankConfig
-    top_k: int = 12
-    library_paths: tuple[str, ...] = ()
-    vllm_base_url: str = "https://ollama.com/v1"
-    vllm_api_key: str = "not-needed"
-    chat_model: str = "deepseek-v4-flash"
-    answer_enabled: bool = True
-    embedding_base_url: str = "http://192.168.90.25:8000/v1"
-    embedding_api_key: str = "not-needed"
-    embedding_model: str = "qwen3-embedding-0.6b"
-    embedding_batch_size: int = 32
-    bm25_index_dir: str = ".ebook_search_bm25"
-    bm25_refresh_delay_seconds: int = 60
-
-
-def load_rerank_config() -> RerankConfig:
-    """Load reranker config from environment variables."""
-    return RerankConfig(
-        enabled=getenv_bool("EBOOK_SEARCH_RERANK_ENABLED", default=False),
-        base_url=getenv("EBOOK_SEARCH_RERANK_BASE_URL", "http://192.168.90.25:8001"),
-        model=getenv("EBOOK_SEARCH_RERANK_MODEL", "qwen3-reranker-06b"),
-        candidates=getenv_int("EBOOK_SEARCH_RERANK_CANDIDATES", default=24),
-        timeout_seconds=float(getenv_int("EBOOK_SEARCH_RERANK_TIMEOUT_SECONDS", default=30)),
-    )
-
-
-def load_config() -> EbookSearchConfig:
-    """Load EPUB search config from environment variables."""
-    return EbookSearchConfig(
-        rerank=load_rerank_config(),
-        top_k=getenv_int("EBOOK_SEARCH_TOP_K", default=12),
-        library_paths=library_paths_from_env(),
-        vllm_base_url=getenv("EBOOK_SEARCH_VLLM_BASE_URL", "https://ollama.com/v1"),
-        vllm_api_key=getenv("EBOOK_SEARCH_VLLM_API_KEY") or getenv("OLLAMA_API_KEY") or "not-needed",
-        chat_model=getenv("EBOOK_SEARCH_CHAT_MODEL", "deepseek-v4-flash"),
-        answer_enabled=getenv_bool("EBOOK_SEARCH_ANSWER_ENABLED", default=True),
-        embedding_base_url=getenv("EBOOK_SEARCH_EMBEDDING_BASE_URL", "http://192.168.90.25:8000/v1"),
-        embedding_api_key=getenv("EBOOK_SEARCH_EMBEDDING_API_KEY", "not-needed"),
-        embedding_model=normalize_embedding_model(),
-        embedding_batch_size=getenv_int("EBOOK_SEARCH_EMBEDDING_BATCH_SIZE", default=32),
-        bm25_index_dir=getenv("EBOOK_SEARCH_BM25_INDEX_DIR", ".ebook_search_bm25"),
-        bm25_refresh_delay_seconds=getenv_int("EBOOK_SEARCH_BM25_REFRESH_DELAY_SECONDS", default=60),
-    )
-
-
-def normalize_embedding_model(default: str = "qwen3-embedding-0.6b") -> str:
-    """Normalize supported embedding aliases to provider model names."""
-    aliases = {
-        "Qwen3-Embedding-0.6B": "qwen3-embedding-0.6b",
-        "Qwen3-Embedding-4B": "qwen3-embedding-4b",
-        "Qwen3-Embedding-8B": "qwen3-embedding-8b",
-        "Qwen/Qwen3-Embedding-0.6B": "qwen3-embedding-0.6b",
-        "Qwen/Qwen3-Embedding-4B": "qwen3-embedding-4b",
-        "Qwen/Qwen3-Embedding-8B": "qwen3-embedding-8b",
-        "qwen3-embedding:0.6b": "qwen3-embedding-0.6b",
-        "qwen3-embedding:4b": "qwen3-embedding-4b",
-        "qwen3-embedding:8b": "qwen3-embedding-8b",
-        "qwen3-embedding-0.6b": "qwen3-embedding-0.6b",
-        "qwen3-embedding-4b": "qwen3-embedding-4b",
-        "qwen3-embedding-8b": "qwen3-embedding-8b",
-    }
-
-    model = getenv("EBOOK_SEARCH_EMBEDDING_MODEL", default)
-    standard_model = aliases.get(model)
-
-    if standard_model is None:
-        error = f"Embedding model {model} is not supported. Supported models are {aliases.keys()}"
-        raise ValueError(error)
-
-    return standard_model
-
-
-def library_paths_from_env() -> tuple[str, ...]:
-    """Read configured EPUB library paths from the environment."""
-    value = getenv("EBOOK_SEARCH_LIBRARY_PATHS")
-    if value is None:
-        return ()
-    return tuple(path for path in value.split(":") if path)

python/ebook_search/embeddings.py

@@ -1,170 +0,0 @@
-"""Embedding model helpers."""
-
-from __future__ import annotations
-
-import logging
-from dataclasses import dataclass
-from typing import TYPE_CHECKING
-
-from sqlalchemy import func, select
-from sqlalchemy.dialects.postgresql import insert
-
-from python.ebook_search.llm_interface import request_embeddings
-from python.orm.richie import (
-    EbookChunk,
-    EbookChunkEmbedding1024,
-    EbookChunkEmbedding2560,
-    EbookChunkEmbedding4096,
-    EbookEmbeddingModel,
-)
-
-logger = logging.getLogger(__name__)
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from sqlalchemy.orm import Session
-
-    from python.ebook_search.config import EbookSearchConfig
-
-MODEL_DIMENSIONS = {
-    "qwen3-embedding-0.6b": 1024,
-    "qwen3-embedding-4b": 2560,
-    "qwen3-embedding-8b": 4096,
-}
-
-
-def get_embedding_table(
-    dimension: int,
-) -> type[EbookChunkEmbedding1024 | EbookChunkEmbedding2560 | EbookChunkEmbedding4096]:
-    """Return the embedding table mapped to an embedding dimension."""
-    embedding_tables = {
-        1024: EbookChunkEmbedding1024,
-        2560: EbookChunkEmbedding2560,
-        4096: EbookChunkEmbedding4096,
-    }
-    table = embedding_tables.get(dimension)
-    if not table:
-        msg = f"Embedding dimension {dimension} is not supported"
-        raise ValueError(msg)
-    return table
-
-
-@dataclass(frozen=True)
-class EmbeddingModelStats:
-    """Embedding coverage for one model."""
-
-    model_name: str
-    dimension: int
-    embedded_chunks: int
-    total_chunks: int
-
-    @property
-    def missing_chunks(self) -> int:
-        """Return chunks missing this embedding model."""
-        return max(self.total_chunks - self.embedded_chunks, 0)
-
-
-def embed_texts(texts: Sequence[str], config: EbookSearchConfig) -> list[list[float]]:
-    """Embed text with the configured vLLM embedding model."""
-    logger.info(
-        "ebook_embed_request_start base_url=%s model=%s count=%s",
-        config.embedding_base_url,
-        config.embedding_model,
-        len(texts),
-    )
-    vectors = request_embeddings(texts, config)
-    expected_dimension = MODEL_DIMENSIONS[config.embedding_model]
-    for vector in vectors:
-        if len(vector) != expected_dimension:
-            msg = f"Expected {expected_dimension} dimensions, got {len(vector)}"
-            raise ValueError(msg)
-    logger.info(
-        "ebook_embed_request_complete model=%s count=%s dimension=%s",
-        config.embedding_model,
-        len(vectors),
-        expected_dimension,
-    )
-    return vectors
-
-
-def embed_query(query: str, config: EbookSearchConfig) -> list[float]:
-    """Embed a search query with the Qwen retrieval instruction."""
-    instructed_query = f"Instruct: Retrieve relevant passages for the query.\nQuery: {query}"
-    return embed_texts([instructed_query], config)[0]
-
-
-def ensure_embedding_models(session: Session) -> None:
-    """Ensure supported embedding model rows exist."""
-    for name, dimension in MODEL_DIMENSIONS.items():
-        existing = session.scalar(select(EbookEmbeddingModel).where(EbookEmbeddingModel.name == name))
-        if existing is None:
-            session.add(EbookEmbeddingModel(name=name, dimension=dimension, is_default=name == "qwen3-embedding-0.6b"))
-            logger.info("ebook_embedding_model_created model=%s dimension=%s", name, dimension)
-    session.flush()
-
-
-def embedding_model_stats(session: Session) -> list[EmbeddingModelStats]:
-    """Return embedding coverage counts for every supported model."""
-    total_chunks = session.scalar(select(func.count(EbookChunk.id))) or 0
-    models = {
-        model.name: model
-        for model in session.scalars(
-            select(EbookEmbeddingModel)
-            .where(EbookEmbeddingModel.name.in_(MODEL_DIMENSIONS))
-            .order_by(EbookEmbeddingModel.name)
-        )
-    }
-
-    stats: list[EmbeddingModelStats] = []
-    for model_name, dimension in MODEL_DIMENSIONS.items():
-        model = models.get(model_name)
-        embedded_chunks = 0
-        if model is not None:
-            table = get_embedding_table(dimension)
-            embedded_chunks = session.scalar(select(func.count(table.id)).where(table.model_id == model.id)) or 0
-        stats.append(
-            EmbeddingModelStats(
-                model_name=model_name,
-                dimension=dimension,
-                embedded_chunks=embedded_chunks,
-                total_chunks=total_chunks,
-            )
-        )
-    return stats
-
-
-def embed_missing_chunks(session: Session, config: EbookSearchConfig) -> int:
-    """Embed chunks missing embeddings for the configured model."""
-    ensure_embedding_models(session)
-    model = session.scalar(select(EbookEmbeddingModel).where(EbookEmbeddingModel.name == config.embedding_model))
-    if model is None:
-        supported_models = ", ".join(MODEL_DIMENSIONS)
-        msg = f"Unknown embedding model: {config.embedding_model}. Supported models: {supported_models}"
-        raise ValueError(msg)
-
-    table = get_embedding_table(model.dimension)
-    chunks = list(
-        session.scalars(
-            select(EbookChunk)
-            .outerjoin(table, (table.chunk_id == EbookChunk.id) & (table.model_id == model.id))
-            .where(table.id.is_(None))
-            .order_by(EbookChunk.id)
-            .limit(config.embedding_batch_size)
-        )
-    )
-    if not chunks:
-        logger.info("ebook_embed_missing_none model=%s", config.embedding_model)
-        return 0
-
-    logger.info("ebook_embed_missing_batch_start model=%s count=%s", config.embedding_model, len(chunks))
-    vectors = embed_texts([chunk.text for chunk in chunks], config)
-    rows = [
-        {"chunk_id": chunk.id, "model_id": model.id, "embedding": vector}
-        for chunk, vector in zip(chunks, vectors, strict=True)
-    ]
-    statement = insert(table).values(rows).on_conflict_do_nothing(index_elements=["chunk_id", "model_id"])
-    session.execute(statement)
-    session.flush()
-    logger.info("ebook_embed_missing_batch_complete model=%s count=%s", config.embedding_model, len(rows))
-    return len(rows)

python/ebook_search/epub_parse.py

@@ -1,95 +0,0 @@
-"""EPUB parsing helpers."""
-
-from __future__ import annotations
-
-import re
-from dataclasses import dataclass
-from typing import TYPE_CHECKING
-
-from bs4 import BeautifulSoup
-from ebooklib import ITEM_DOCUMENT, epub
-
-if TYPE_CHECKING:
-    from pathlib import Path
-
-WHITESPACE_RE = re.compile(r"\s+")
-
-
-@dataclass(frozen=True)
-class ParsedChapter:
-    """Text extracted from one EPUB spine document."""
-
-    title: str | None
-    href: str | None
-    text: str
-    page_labels: tuple[str, ...]
-
-
-@dataclass(frozen=True)
-class ParsedEpub:
-    """Parsed EPUB metadata and text."""
-
-    title: str
-    author: str | None
-    language: str | None
-    publisher: str | None
-    identifier: str | None
-    chapters: tuple[ParsedChapter, ...]
-
-
-def parse_epub(path: Path) -> ParsedEpub:
-    """Parse EPUB metadata and spine text."""
-    book = epub.read_epub(path)
-    chapters = []
-    for item in book.get_items_of_type(ITEM_DOCUMENT):
-        soup = BeautifulSoup(item.get_content(), "html.parser")
-        title = chapter_title(soup)
-        page_labels = tuple(extract_page_labels(soup))
-        text = clean_text(soup.get_text(" "))
-        if text:
-            chapters.append(ParsedChapter(title=title, href=item.get_name(), text=text, page_labels=page_labels))
-
-    return ParsedEpub(
-        title=metadata_value(book, "title") or path.stem,
-        author=metadata_value(book, "creator"),
-        language=metadata_value(book, "language"),
-        publisher=metadata_value(book, "publisher"),
-        identifier=metadata_value(book, "identifier"),
-        chapters=tuple(chapters),
-    )
-
-
-def metadata_value(book: epub.EpubBook, name: str) -> str | None:
-    """Return the first non-empty Dublin Core metadata value for a name."""
-    values = book.get_metadata("DC", name)
-    if not values:
-        return None
-    value = values[0][0]
-    return str(value).strip() or None
-
-
-def chapter_title(soup: BeautifulSoup) -> str | None:
-    """Extract the best available title from an EPUB document soup."""
-    heading = soup.find(["h1", "h2", "h3"])
-    if heading is None:
-        title = soup.find("title")
-        if title is None:
-            return None
-        return clean_text(title.get_text(" ")) or None
-    return clean_text(heading.get_text(" ")) or None
-
-
-def extract_page_labels(soup: BeautifulSoup) -> list[str]:
-    """Extract EPUB page-break labels from a document soup."""
-    labels: list[str] = []
-    for tag in soup.find_all(attrs={"epub:type": "pagebreak"}):
-        label = tag.get("title") or tag.get("aria-label") or tag.get_text(" ")
-        clean = clean_text(str(label))
-        if clean:
-            labels.append(clean)
-    return labels
-
-
-def clean_text(text: str) -> str:
-    """Normalize whitespace in extracted EPUB text."""
-    return WHITESPACE_RE.sub(" ", text).strip()

python/ebook_search/ingest.py

@@ -1,190 +0,0 @@
-"""EPUB ingestion into Richie DB."""
-
-from __future__ import annotations
-
-import hashlib
-import logging
-from dataclasses import dataclass
-from datetime import UTC, datetime
-from pathlib import Path
-from typing import TYPE_CHECKING
-
-import tiktoken
-from sqlalchemy import or_, select
-
-from python.ebook_search.epub_parse import parse_epub
-from python.orm.richie import EbookChapter, EbookChunk, EbookSource
-
-logger = logging.getLogger(__name__)
-DEFAULT_CHUNK_TOKENS = 700
-DEFAULT_CHUNK_OVERLAP = 100
-
-if TYPE_CHECKING:
-    from sqlalchemy.orm import Session
-
-    from python.ebook_search.config import EbookSearchConfig
-    from python.ebook_search.epub_parse import ParsedChapter
-
-
-@dataclass(frozen=True)
-class TextChunk:
-    """A token-bounded chunk of text."""
-
-    text: str
-    token_start: int
-    token_count: int
-
-
-def chunk_text(
-    text: str,
-    *,
-    chunk_tokens: int = DEFAULT_CHUNK_TOKENS,
-    overlap_tokens: int = DEFAULT_CHUNK_OVERLAP,
-) -> list[TextChunk]:
-    """Split text into overlapping token chunks."""
-    if chunk_tokens <= 0:
-        msg = "chunk_tokens must be positive"
-        raise ValueError(msg)
-    if overlap_tokens < 0 or overlap_tokens >= chunk_tokens:
-        msg = "overlap_tokens must be non-negative and smaller than chunk_tokens"
-        raise ValueError(msg)
-
-    encoding = tiktoken.get_encoding("cl100k_base")
-    tokens = encoding.encode(text)
-    if not tokens:
-        return []
-
-    chunks: list[TextChunk] = []
-    step = chunk_tokens - overlap_tokens
-    for start in range(0, len(tokens), step):
-        chunk = tokens[start : start + chunk_tokens]
-        if not chunk:
-            continue
-        chunks.append(
-            TextChunk(
-                text=encoding.decode(chunk).strip(),
-                token_start=start,
-                token_count=len(chunk),
-            )
-        )
-        if start + chunk_tokens >= len(tokens):
-            break
-    return [chunk for chunk in chunks if chunk.text]
-
-
-def ingest_configured_paths(session: Session, config: EbookSearchConfig) -> int:
-    """Ingest every EPUB found under configured library paths."""
-    count = 0
-    for library_path in config.library_paths:
-        path = Path(library_path).expanduser()
-        logger.info("ebook_ingest_path_start path=%s", path)
-        if path.is_file() and path.suffix.lower() == ".epub":
-            count += int(ingest_file(session, path))
-        elif path.is_dir():
-            for epub_path in sorted(path.rglob("*.epub")):
-                count += int(ingest_file(session, epub_path))
-        else:
-            logger.warning("ebook_ingest_path_missing path=%s", path)
-    logger.info("ebook_ingest_paths_complete changed_files=%s configured_paths=%s", count, len(config.library_paths))
-    return count
-
-
-def ingest_file(session: Session, path: Path) -> bool:
-    """Ingest one EPUB file. Return True when the database changed."""
-    resolved_path = path.expanduser().resolve()
-    logger.info("ebook_ingest_file_start path=%s", resolved_path)
-    file_hash = sha256_file(resolved_path)
-    existing = find_existing_source(session, resolved_path, file_hash)
-    if existing is not None and existing.file_sha256 == file_hash:
-        stat = resolved_path.stat()
-        existing.file_path = str(resolved_path)
-        existing.file_mtime = datetime.fromtimestamp(stat.st_mtime, tz=UTC)
-        existing.file_size = stat.st_size
-        session.flush()
-        logger.info("ebook_ingest_file_unchanged source_id=%s path=%s", existing.id, resolved_path)
-        return False
-    if existing is not None:
-        logger.info("ebook_ingest_file_replacing source_id=%s path=%s", existing.id, resolved_path)
-        session.delete(existing)
-        session.flush()
-
-    stat = resolved_path.stat()
-    parsed = parse_epub(resolved_path)
-    source = EbookSource(
-        title=parsed.title,
-        author=parsed.author,
-        language=parsed.language,
-        publisher=parsed.publisher,
-        identifier=parsed.identifier,
-        file_path=str(resolved_path),
-        file_sha256=file_hash,
-        file_mtime=datetime.fromtimestamp(stat.st_mtime, tz=UTC),
-        file_size=stat.st_size,
-    )
-    session.add(source)
-    session.flush()
-
-    chunk_index = 0
-    for spine_index, parsed_chapter in enumerate(parsed.chapters):
-        chapter = EbookChapter(
-            source_id=source.id,
-            spine_index=spine_index,
-            title=parsed_chapter.title,
-            href=parsed_chapter.href,
-        )
-        session.add(chapter)
-        session.flush()
-        chunk_index = add_chapter_chunks(session, source, chapter, parsed_chapter, chunk_index)
-
-    session.flush()
-    logger.info(
-        "ebook_ingest_file_complete source_id=%s path=%s chapters=%s chunks=%s",
-        source.id,
-        resolved_path,
-        len(parsed.chapters),
-        chunk_index,
-    )
-    return True
-
-
-def find_existing_source(session: Session, path: Path, file_hash: str) -> EbookSource | None:
-    """Find an existing source by canonical path or file hash."""
-    return session.scalar(
-        select(EbookSource).where(or_(EbookSource.file_path == str(path), EbookSource.file_sha256 == file_hash))
-    )
-
-
-def add_chapter_chunks(
-    session: Session,
-    source: EbookSource,
-    chapter: EbookChapter,
-    parsed_chapter: ParsedChapter,
-    chunk_index: int,
-) -> int:
-    """Add chunk rows for one parsed chapter and return the next chunk index."""
-    page_label = parsed_chapter.page_labels[0] if parsed_chapter.page_labels else None
-    for text_chunk in chunk_text(parsed_chapter.text):
-        session.add(
-            EbookChunk(
-                source_id=source.id,
-                chapter_id=chapter.id,
-                chunk_index=chunk_index,
-                text=text_chunk.text,
-                token_start=text_chunk.token_start,
-                token_count=text_chunk.token_count,
-                page_label=page_label,
-                content_sha256=hashlib.sha256(text_chunk.text.encode()).hexdigest(),
-                search_text=f"{source.title} {source.author or ''} {chapter.title or ''} {text_chunk.text}",
-            )
-        )
-        chunk_index += 1
-    return chunk_index
-
-
-def sha256_file(path: Path) -> str:
-    """Calculate the SHA-256 digest for a file."""
-    digest = hashlib.sha256()
-    with path.open("rb") as file:
-        for block in iter(lambda: file.read(1024 * 1024), b""):
-            digest.update(block)
-    return digest.hexdigest()

python/ebook_search/llm_interface.py

@@ -1,143 +0,0 @@
-"""LLM provider HTTP adapters."""
-
-from __future__ import annotations
-
-import logging
-from typing import TYPE_CHECKING
-
-import httpx
-
-if TYPE_CHECKING:
-    from collections.abc import Sequence
-
-    from python.ebook_search.config import EbookSearchConfig, RerankConfig
-
-logger = logging.getLogger(__name__)
-
-
-def auth_headers(api_key: str) -> dict[str, str]:
-    """Build authorization headers when an API key is configured."""
-    if api_key == "not-needed":
-        return {}
-    return {"Authorization": f"Bearer {api_key}"}
-
-
-def request_embeddings(texts: Sequence[str], config: EbookSearchConfig) -> list[list[float]]:
-    """Request embeddings from the configured OpenAI-compatible endpoint."""
-    try:
-        response = httpx.post(
-            f"{config.embedding_base_url.rstrip('/')}/embeddings",
-            headers=auth_headers(config.embedding_api_key),
-            json={"model": config.embedding_model, "input": list(texts)},
-            timeout=60,
-        )
-        response.raise_for_status()
-        return embedding_vectors_from_response(response.json())
-    except (httpx.HTTPError, ValueError, KeyError, TypeError) as error:
-        logger.exception(
-            "ebook_embed_request_failed base_url=%s model=%s count=%s",
-            config.embedding_base_url,
-            config.embedding_model,
-            len(texts),
-        )
-        msg = f"Embedding request failed. base_url={config.embedding_base_url} model={config.embedding_model}"
-        raise RuntimeError(msg) from error
-
-
-def embedding_vectors_from_response(body: object) -> list[list[float]]:
-    """Extract embedding vectors from an OpenAI-compatible embedding response."""
-    if not isinstance(body, dict):
-        msg = "Embedding response is not an object"
-        raise TypeError(msg)
-
-    data = body["data"]
-    if not isinstance(data, list):
-        msg = "Embedding response data is not a list"
-        raise TypeError(msg)
-
-    vectors: list[list[float]] = []
-    for item in data:
-        if not isinstance(item, dict):
-            msg = "Embedding item is not an object"
-            raise TypeError(msg)
-        embedding = item["embedding"]
-        if not isinstance(embedding, list):
-            msg = "Embedding value is not a list"
-            raise TypeError(msg)
-        vectors.append([float(value) for value in embedding])
-    return vectors
-
-
-def request_rerank(
-    query: str,
-    documents: Sequence[str],
-    config: RerankConfig,
-) -> object | None:
-    """Request rerank scores from the configured vLLM endpoint."""
-    payload = {
-        "model": config.model,
-        "query": query,
-        "documents": list(documents),
-    }
-    response = httpx.post(
-        f"{config.base_url.rstrip('/')}/rerank",
-        json=payload,
-        timeout=config.timeout_seconds,
-    )
-    response.raise_for_status()
-    try:
-        return response.json()
-    except ValueError:
-        logger.debug("ebook_rerank_response_invalid_json", extra={"response": response.text})
-        return None
-
-
-def request_chat_completion(
-    config: EbookSearchConfig,
-    messages: Sequence[dict[str, str]],
-) -> str:
-    """Request a chat completion from the configured OpenAI-compatible endpoint."""
-    try:
-        response = httpx.post(
-            f"{config.vllm_base_url.rstrip('/')}/chat/completions",
-            headers=auth_headers(config.vllm_api_key),
-            json={
-                "model": config.chat_model,
-                "messages": list(messages),
-                "temperature": 0,
-            },
-            timeout=60,
-        )
-        response.raise_for_status()
-        return chat_content_from_response(response.json())
-    except (httpx.HTTPError, ValueError, KeyError, TypeError) as error:
-        msg = f"Chat request failed. base_url={config.vllm_base_url} model={config.chat_model}"
-        raise RuntimeError(msg) from error
-
-
-def chat_content_from_response(body: object) -> str:
-    """Extract text content from an OpenAI-compatible chat response."""
-    if not isinstance(body, dict):
-        msg = "Chat response is not an object"
-        raise TypeError(msg)
-
-    choices = body["choices"]
-    if not isinstance(choices, list) or not choices:
-        msg = "Chat response has no choices"
-        raise ValueError(msg)
-
-    first = choices[0]
-    if not isinstance(first, dict):
-        msg = "Chat choice is not an object"
-        raise TypeError(msg)
-
-    message = first["message"]
-    if not isinstance(message, dict):
-        msg = "Chat message is not an object"
-        raise TypeError(msg)
-
-    content = message.get("content") or ""
-    if not isinstance(content, str):
-        msg = "Chat content is not text"
-        raise TypeError(msg)
-    return content

python/ebook_search/rerank.py

@@ -1,129 +0,0 @@
-"""vLLM-backed optional reranking."""
-
-from __future__ import annotations
-
-import logging
-from dataclasses import dataclass, replace
-from typing import TYPE_CHECKING
-
-from python.ebook_search.llm_interface import request_rerank
-
-if TYPE_CHECKING:
-    from python.ebook_search.config import RerankConfig
-    from python.ebook_search.search import SearchResult
-
-logger = logging.getLogger(__name__)
-RERANK_SCORE_WEIGHT = 0.7
-HYBRID_SCORE_WEIGHT = 0.3
-
-
-@dataclass(frozen=True)
-class RerankResult:
-    """A relevance score for one candidate chunk."""
-
-    chunk_id: int
-    score: float
-
-
-def rerank_chunks(query: str, candidates: list[SearchResult], config: RerankConfig) -> list[SearchResult]:
-    """Rerank candidates with a vLLM rerank endpoint."""
-    if not candidates:
-        return []
-
-    logger.info(
-        "ebook_rerank_request_start base_url=%s model=%s candidates=%s",
-        config.base_url,
-        config.model,
-        len(candidates),
-    )
-    scores = score_candidates(query, candidates, config)
-    results = sorted(
-        (
-            replace(
-                result,
-                score=final_rerank_score(result, scores[result.chunk_id].score, candidates),
-                rerank_score=scores[result.chunk_id].score,
-            )
-            for result in candidates
-        ),
-        key=lambda result: result.score,
-        reverse=True,
-    )
-    logger.info(
-        "ebook_rerank_request_complete base_url=%s model=%s candidates=%s",
-        config.base_url,
-        config.model,
-        len(results),
-    )
-    return results
-
-
-def score_candidates(
-    query: str,
-    candidates: list[SearchResult],
-    config: RerankConfig,
-) -> dict[int, RerankResult]:
-    """Score candidate chunks with the configured rerank API."""
-    body = request_rerank(query, [candidate.text for candidate in candidates], config)
-    if body is None:
-        return zero_rerank_scores(candidates)
-
-    scores = parse_vllm_scores(body, candidates)
-    for result in scores.values():
-        logger.debug("ebook_rerank_candidate_scored chunk_id=%s score=%s", result.chunk_id, result.score)
-    return scores
-
-
-def parse_vllm_scores(body: object, candidates: list[SearchResult]) -> dict[int, RerankResult]:
-    """Parse vLLM rerank scores into chunk-id keyed results."""
-    if not isinstance(body, dict):
-        logger.debug("ebook_rerank_response_not_object", extra={"response": body})
-        return zero_rerank_scores(candidates)
-
-    results = body.get("results") or body.get("data")
-    if not isinstance(results, list):
-        logger.debug("ebook_rerank_response_missing_results", extra={"response": body})
-        return zero_rerank_scores(candidates)
-
-    scores = zero_rerank_scores(candidates)
-    for item in results:
-        if not isinstance(item, dict):
-            continue
-        index = item.get("index")
-        score = item.get("relevance_score", item.get("score"))
-        if not isinstance(index, int) or index < 0 or index >= len(candidates):
-            continue
-        if not isinstance(score, int | float):
-            continue
-        chunk_id = candidates[index].chunk_id
-        scores[chunk_id] = RerankResult(chunk_id=chunk_id, score=clamp_score(float(score)))
-    return scores
-
-
-def zero_rerank_scores(candidates: list[SearchResult]) -> dict[int, RerankResult]:
-    """Return zero relevance scores for all candidate chunks."""
-    return {candidate.chunk_id: RerankResult(chunk_id=candidate.chunk_id, score=0.0) for candidate in candidates}
-
-
-def clamp_score(score: float) -> float:
-    """Clamp a rerank score into the supported 0.0 to 1.0 range."""
-    return min(max(score, 0.0), 1.0)
-
-
-def final_rerank_score(result: SearchResult, rerank_score: float, candidates: list[SearchResult]) -> float:
-    """Combine rerank relevance with normalized hybrid retrieval evidence."""
-    return (RERANK_SCORE_WEIGHT * rerank_score) + (HYBRID_SCORE_WEIGHT * normalized_hybrid_score(result, candidates))
-
-
-def normalized_hybrid_score(result: SearchResult, candidates: list[SearchResult]) -> float:
-    """Normalize a candidate hybrid score against the rerank candidate set."""
-    hybrid_scores = [
-        candidate.fused_score if candidate.fused_score is not None else candidate.score for candidate in candidates
-    ]
-    low = min(hybrid_scores)
-    high = max(hybrid_scores)
-    if high == low:
-        return 1.0
-
-    score = result.fused_score if result.fused_score is not None else result.score
-    return (score - low) / (high - low)

python/ebook_search/search.py

@@ -1,383 +0,0 @@
-"""Hybrid search orchestration."""
-
-from __future__ import annotations
-
-import logging
-import re
-from concurrent.futures import ThreadPoolExecutor
-from dataclasses import dataclass, replace
-from typing import TYPE_CHECKING
-
-from pgvector.sqlalchemy import Vector
-from sqlalchemy import literal, select
-from sqlalchemy.orm import Session
-
-from python.ebook_search.bm25_corpus import (
-    BM25CorpusUnavailableError,
-    load_bm25_corpus,
-    score_bm25_corpus,
-)
-from python.ebook_search.embeddings import MODEL_DIMENSIONS, embed_query, get_embedding_table
-from python.ebook_search.rerank import rerank_chunks
-from python.ebook_search.timing import RuntimeStep, timed_result
-from python.orm.richie import (
-    EbookChapter,
-    EbookChunk,
-    EbookEmbeddingModel,
-    EbookSource,
-)
-
-if TYPE_CHECKING:
-    from collections.abc import Mapping
-
-    from sqlalchemy.engine import Engine
-
-    from python.ebook_search.config import EbookSearchConfig
-
-logger = logging.getLogger(__name__)
-BM25_CANDIDATE_LIMIT = 120
-
-
-@dataclass(frozen=True)
-class SearchResult:
-    """One source chunk returned by search."""
-
-    chunk_id: int
-    text: str
-    source_title: str
-    score: float = 0.0
-    vector_score: float | None = None
-    bm25_score: float | None = None
-    fused_score: float | None = None
-    rerank_score: float | None = None
-    source_author: str | None = None
-    chapter_title: str | None = None
-    page_label: str | None = None
-    rank_source: str = "Hybrid"
-
-
-@dataclass(frozen=True)
-class SearchResponse:
-    """Search output for the UI."""
-
-    query: str
-    results: list[SearchResult]
-    rank_label: str
-    timings: tuple[RuntimeStep, ...] = ()
-
-    @property
-    def total_runtime_ms(self) -> float:
-        """Return total measured runtime for the response."""
-        return sum(step.duration_ms for step in self.timings if step.counts_toward_total)
-
-
-@dataclass(frozen=True)
-class RetrievalResponse:
-    """Parallel retrieval output for vector and BM25 candidates."""
-
-    vector_results: list[SearchResult]
-    lexical_results: list[SearchResult]
-    timings: tuple[RuntimeStep, ...]
-
-
-def search_ebooks(
-    engine: Engine,
-    query: str,
-    config: EbookSearchConfig,
-    *,
-    rerank: bool = False,
-) -> SearchResponse:
-    """Run hybrid vector/BM25 search and optional reranking."""
-    if not query.strip():
-        logger.info("ebook_search_empty_query")
-        return SearchResponse(query=query, results=[], rank_label="Hybrid")
-
-    logger.info("ebook_search_start query_length=%s rerank=%s", len(query), rerank)
-    timings: list[RuntimeStep] = []
-    bm25_query, timing = timed_result("BM25 query preparation", retrieval_query_from_text, query)
-    timings.append(timing)
-    retrieval, timing = timed_result(
-        "Hybrid retrieval",
-        parallel_retrieval,
-        engine,
-        query,
-        bm25_query,
-        config,
-    )
-    timings.extend(retrieval.timings)
-    timings.append(timing)
-    fused, timing = timed_result(
-        "Reciprocal rank fusion",
-        reciprocal_rank_fusion,
-        retrieval.vector_results,
-        retrieval.lexical_results,
-    )
-    timings.append(timing)
-    if config.rerank.enabled and rerank:
-        response, timing = timed_result("Rerank", apply_rerank, query, fused, config)
-    else:
-        response, timing = timed_result("Rerank skipped", skip_rerank, query, fused, config)
-    timings.append(timing)
-    response = replace(response, timings=tuple(timings))
-    logger.info(
-        "ebook_search_complete vector_candidates=%s lexical_candidates=%s "
-        "fused_candidates=%s returned=%s rank_label=%s runtime_ms=%.1f",
-        len(retrieval.vector_results),
-        len(retrieval.lexical_results),
-        len(fused),
-        len(response.results),
-        response.rank_label,
-        response.total_runtime_ms,
-    )
-    return response
-
-
-def parallel_retrieval(
-    engine: Engine,
-    vector_query: str,
-    bm25_query: str,
-    config: EbookSearchConfig,
-) -> RetrievalResponse:
-    """Run vector and BM25 candidate retrieval concurrently with separate database sessions."""
-    with ThreadPoolExecutor(max_workers=2, thread_name_prefix="ebook-search") as executor:
-        vector_future = executor.submit(
-            timed_result,
-            "Embedding + vector search",
-            vector_candidates,
-            engine,
-            vector_query,
-            config,
-        )
-        bm25_future = executor.submit(
-            timed_result,
-            "BM25 search",
-            bm25_candidates,
-            bm25_query,
-            config,
-        )
-        vector_results, vector_timing = vector_future.result()
-        lexical_results, lexical_timing = bm25_future.result()
-
-    logger.info(
-        "ebook_parallel_retrieval_complete vector_candidates=%s lexical_candidates=%s",
-        len(vector_results),
-        len(lexical_results),
-    )
-    return RetrievalResponse(
-        vector_results=vector_results,
-        lexical_results=lexical_results,
-        timings=(
-            replace(vector_timing, counts_toward_total=False),
-            replace(lexical_timing, counts_toward_total=False),
-        ),
-    )
-
-
-def skip_rerank(
-    query: str,
-    candidates: list[SearchResult],
-    config: EbookSearchConfig,
-) -> SearchResponse:
-    """Return fused hybrid results without reranking."""
-    logger.info("ebook_rerank_skipped candidates=%s", len(candidates))
-    return SearchResponse(query=query, results=candidates[: config.top_k], rank_label="Hybrid")
-
-
-def apply_rerank(
-    query: str,
-    candidates: list[SearchResult],
-    config: EbookSearchConfig,
-) -> SearchResponse:
-    """Rerank already-fused hybrid candidates."""
-    reranked = rerank_chunks(query, candidates[: config.rerank.candidates], config.rerank)
-    logger.info(
-        "ebook_rerank_complete input_candidates=%s returned=%s",
-        min(len(candidates), config.rerank.candidates),
-        len(reranked),
-    )
-    return SearchResponse(
-        query=query,
-        results=[replace(result, rank_source="Hybrid + rerank") for result in reranked[: config.top_k]],
-        rank_label="Hybrid + rerank",
-    )
-
-
-def vector_candidates(engine: Engine, query: str, config: EbookSearchConfig) -> list[SearchResult]:
-    """Return pgvector cosine candidates for a natural-language query."""
-    with Session(engine) as session:
-        model = session.scalar(select(EbookEmbeddingModel).where(EbookEmbeddingModel.name == config.embedding_model))
-        if model is None:
-            msg = f"Embedding model is not registered: {config.embedding_model}"
-            raise ValueError(msg)
-
-        expected_dimension = MODEL_DIMENSIONS[config.embedding_model]
-        if model.dimension != expected_dimension:
-            msg = f"Model row dimension {model.dimension} does not match configured dimension {expected_dimension}"
-            raise ValueError(msg)
-
-        embedding = embed_query(query, config)
-        limit = max(config.rerank.candidates, config.top_k) * 4
-        embedding_table = get_embedding_table(model.dimension)
-
-        embedding_param = literal(embedding, type_=Vector(model.dimension))
-        distance = embedding_table.embedding.op("<=>")(embedding_param)
-        score = (literal(1.0) - distance).label("score")
-        statement = (
-            select(
-                EbookChunk.id.label("chunk_id"),
-                EbookChunk.text.label("text"),
-                EbookSource.title.label("source_title"),
-                EbookSource.author.label("source_author"),
-                EbookChapter.title.label("chapter_title"),
-                EbookChunk.page_label.label("page_label"),
-                score,
-            )
-            .select_from(embedding_table)
-            .join(EbookChunk, EbookChunk.id == embedding_table.chunk_id)
-            .join(EbookSource, EbookSource.id == EbookChunk.source_id)
-            .outerjoin(EbookChapter, EbookChapter.id == EbookChunk.chapter_id)
-            .where(embedding_table.model_id == model.id)
-            .order_by(distance)
-            .limit(limit)
-        )
-        rows = session.execute(statement).mappings()
-        results = [search_result_from_row(row) for row in rows]
-        logger.info(
-            "ebook_vector_search_complete model=%s dimension=%s candidates=%s",
-            config.embedding_model,
-            model.dimension,
-            len(results),
-        )
-        return results
-
-
-def bm25_candidates(query: str, config: EbookSearchConfig) -> list[SearchResult]:
-    """Return BM25-ranked lexical candidates using the persisted corpus."""
-    try:
-        corpus = load_bm25_corpus(config)
-    except BM25CorpusUnavailableError as error:
-        logger.warning("ebook_bm25_index_unavailable_skipping error=%s", error)
-        return []
-
-    if not corpus.records:
-        logger.info("ebook_bm25_search_complete corpus=0 candidates=0")
-        return []
-
-    scored_records = score_bm25_corpus(query, corpus, limit=BM25_CANDIDATE_LIMIT)
-    results = [
-        replace(search_result_from_row(record), score=score, vector_score=None, bm25_score=score)
-        for record, score in scored_records
-    ]
-
-    max_score = results[0].bm25_score if results else 0.0
-    logger.info(
-        "ebook_bm25_search_complete corpus=%s candidates=%s max_score=%.6f",
-        len(corpus.records),
-        len(results),
-        max_score,
-    )
-    return results
-
-
-def reciprocal_rank_fusion(
-    vector_results: list[SearchResult],
-    lexical_results: list[SearchResult],
-    *,
-    rank_constant: int = 60,
-) -> list[SearchResult]:
-    """Fuse vector and lexical rankings with Reciprocal Rank Fusion."""
-    by_chunk: dict[int, SearchResult] = {}
-    scores: dict[int, float] = {}
-    vector_scores: dict[int, float] = {}
-    bm25_scores: dict[int, float] = {}
-
-    for rank, result in enumerate(vector_results, start=1):
-        by_chunk.setdefault(result.chunk_id, result)
-        vector_scores[result.chunk_id] = result.vector_score if result.vector_score is not None else result.score
-        scores[result.chunk_id] = scores.get(result.chunk_id, 0.0) + (1 / (rank_constant + rank))
-
-    for rank, result in enumerate(lexical_results, start=1):
-        by_chunk.setdefault(result.chunk_id, result)
-        bm25_scores[result.chunk_id] = result.bm25_score if result.bm25_score is not None else result.score
-        scores[result.chunk_id] = scores.get(result.chunk_id, 0.0) + (1 / (rank_constant + rank))
-
-    return sorted(
-        (
-            replace(
-                result,
-                score=scores[result.chunk_id],
-                vector_score=vector_scores.get(result.chunk_id),
-                bm25_score=bm25_scores.get(result.chunk_id),
-                fused_score=scores[result.chunk_id],
-                rank_source="Hybrid",
-            )
-            for result in by_chunk.values()
-        ),
-        key=lambda result: result.score,
-        reverse=True,
-    )
-
-
-def search_result_from_row(row: Mapping[str, object]) -> SearchResult:
-    """Convert a database row mapping into a search result."""
-    return SearchResult(
-        chunk_id=int(row["chunk_id"]),
-        text=str(row["text"]),
-        source_title=str(row["source_title"]),
-        source_author=optional_str(row["source_author"]),
-        chapter_title=optional_str(row["chapter_title"]),
-        page_label=optional_str(row["page_label"]),
-        score=float(row["score"]) if "score" in row else 0.0,
-        vector_score=float(row["score"]) if "score" in row else None,
-    )
-
-
-def optional_str(value: object) -> str | None:
-    """Convert nullable database values to optional strings."""
-    if value is None:
-        return None
-    return str(value)
-
-
-TOKEN_RE = re.compile(r"[A-Za-z0-9_]+")
-
-
-def tokens(text_value: str) -> list[str]:
-    """Extract tokens from a text value.
-
-    This is a simple approximation of the tokenization used by PostgreSQL's full-text search,
-    which is sufficient for BM25 candidate retrieval. It lowercases tokens and includes alphanumeric characters and
-    underscores.
-    """
-    return [match.group(0).lower() for match in TOKEN_RE.finditer(text_value)]
-
-
-QUERY_STOP_WORDS = {
-    "a",
-    "an",
-    "and",
-    "are",
-    "as",
-    "at",
-    "does",
-    "for",
-    "in",
-    "is",
-    "of",
-    "the",
-    "to",
-    "what",
-    "when",
-    "where",
-    "which",
-    "who",
-    "why",
-}
-
-
-def retrieval_query_from_text(query: str) -> str:
-    """Remove generic question words while preserving entity and series terms."""
-    keywords = [token for token in tokens(query) if token not in QUERY_STOP_WORDS]
-    if not keywords:
-        return query
-    return " ".join(keywords)

python/ebook_search/timing.py

@@ -1,36 +0,0 @@
-"""Runtime timing helpers for EPUB search."""
-
-from __future__ import annotations
-
-from dataclasses import dataclass
-from time import perf_counter
-from typing import TYPE_CHECKING
-
-if TYPE_CHECKING:
-    from collections.abc import Callable
-
-
-@dataclass(frozen=True)
-class RuntimeStep:
-    """Elapsed runtime for one named search step."""
-
-    name: str
-    duration_ms: float
-    counts_toward_total: bool = True
-
-
-def runtime_step_from_start(name: str, start_seconds: float) -> RuntimeStep:
-    """Create a runtime step from a prior perf_counter timestamp."""
-    return RuntimeStep(name=name, duration_ms=(perf_counter() - start_seconds) * 1000)
-
-
-def timed_result[T, **P](
-    name: str,
-    operation: Callable[P, T],
-    *args: P.args,
-    **kwargs: P.kwargs,
-) -> tuple[T, RuntimeStep]:
-    """Run an operation and return its result plus elapsed runtime."""
-    start_seconds = perf_counter()
-    result = operation(*args, **kwargs)
-    return result, runtime_step_from_start(name, start_seconds)

python/fastapi_tools/__init__.py

@@ -1,6 +0,0 @@
-"""Reusable FastAPI tools."""
-
-from python.fastapi_tools.db import DbSession, get_db
-from python.fastapi_tools.zstd_middleware import ZstdMiddleware
-
-__all__ = ["DbSession", "ZstdMiddleware", "get_db"]

python/gitea.py

@@ -1,347 +0,0 @@
-"""Small Gitea API client for repository automation."""
-
-from __future__ import annotations
-
-from dataclasses import dataclass
-from typing import Self
-from urllib.parse import quote
-
-import httpx
-
-DEFAULT_PAGE_SIZE = 100
-EXPECTED_NO_CONTENT = 204
-EXPECTED_CREATED = 201
-EXPECTED_OK = 200
-
-
-@dataclass(frozen=True)
-class CreatedIssue:
-    """Issue data returned by Gitea."""
-
-    number: int | None
-    html_url: str | None
-    title: str
-
-
-@dataclass(frozen=True)
-class PullRequest:
-    """Pull request data returned by Gitea."""
-
-    number: int
-    title: str
-    html_url: str | None
-    labels: tuple[str, ...]
-    head_branch: str | None
-    base_branch: str | None
-
-
-@dataclass(frozen=True)
-class WorkflowJob:
-    """Workflow job data returned by Gitea Actions."""
-
-    id: int
-    name: str
-    run_id: int | None
-    status: str | None
-    conclusion: str | None
-
-
-class GiteaError(RuntimeError):
-    """Raised when Gitea rejects an API request."""
-
-
-def split_repo_name(repo: str) -> tuple[str, str]:
-    """Split an owner/repo string into its parts."""
-    owner, separator, repo_name = repo.partition("/")
-    if not separator or not owner or not repo_name:
-        msg = f"Invalid repository name: {repo}"
-        raise ValueError(msg)
-    return owner, repo_name
-
-
-class GiteaClient:
-    """HTTP client for the subset of Gitea APIs used in this repository."""
-
-    def __init__(
-        self,
-        *,
-        base_url: str,
-        token: str,
-        timeout: int = 30,
-        transport: httpx.BaseTransport | None = None,
-    ) -> None:
-        """Initialize the Gitea client."""
-        self._client = httpx.Client(
-            base_url=base_url.rstrip("/"),
-            timeout=timeout,
-            headers={"Authorization": f"token {token}"},
-            transport=transport,
-        )
-
-    def create_issue(
-        self,
-        *,
-        owner: str,
-        repo: str,
-        title: str,
-        body: str,
-        labels: list[int] | None = None,
-    ) -> CreatedIssue:
-        """Create a Gitea issue."""
-        payload: dict[str, object] = {"title": title, "body": body, "labels": labels or []}
-        response = self._request(
-            "POST",
-            f"/api/v1/repos/{owner}/{repo}/issues",
-            expected_statuses={EXPECTED_CREATED},
-            json=payload,
-        )
-        data = response.json()
-        return CreatedIssue(
-            number=_optional_int(data.get("number")),
-            html_url=_optional_str(data.get("html_url")),
-            title=str(data.get("title", title)),
-        )
-
-    def resolve_label_ids(self, *, owner: str, repo: str, labels: list[str]) -> list[int]:
-        """Resolve label names to Gitea label IDs."""
-        if not labels:
-            return []
-
-        available_labels: dict[str, int] = {}
-        page = 1
-        while True:
-            response = self._request(
-                "GET",
-                f"/api/v1/repos/{owner}/{repo}/labels",
-                params={"page": page, "limit": DEFAULT_PAGE_SIZE},
-            )
-            batch = response.json()
-            if not batch:
-                break
-            for label in batch:
-                label_name = str(label.get("name", ""))
-                label_id = _optional_int(label.get("id"))
-                if label_name and label_id is not None:
-                    available_labels[label_name] = label_id
-            if len(batch) < DEFAULT_PAGE_SIZE:
-                break
-            page += 1
-
-        missing = [label for label in labels if label not in available_labels]
-        if missing:
-            missing_names = ", ".join(sorted(missing))
-            msg = f"Missing Gitea labels: {missing_names}"
-            raise GiteaError(msg)
-
-        return [available_labels[label] for label in labels]
-
-    def list_open_pull_requests(
-        self,
-        *,
-        owner: str,
-        repo: str,
-        labels: list[str] | None = None,
-        head: str | None = None,
-    ) -> list[PullRequest]:
-        """List open pull requests for a repository."""
-        expected_labels = set(labels or [])
-        pull_requests: list[PullRequest] = []
-        page = 1
-        while True:
-            response = self._request(
-                "GET",
-                f"/api/v1/repos/{owner}/{repo}/pulls",
-                params={"state": "open", "page": page, "limit": DEFAULT_PAGE_SIZE},
-            )
-            batch = response.json()
-            if not batch:
-                break
-
-            for item in batch:
-                pull_request = _pull_request_from_api(item)
-                if head and pull_request.head_branch != head:
-                    continue
-                if expected_labels and not expected_labels.issubset(set(pull_request.labels)):
-                    continue
-                pull_requests.append(pull_request)
-
-            if len(batch) < DEFAULT_PAGE_SIZE:
-                break
-            page += 1
-
-        return pull_requests
-
-    def create_pull_request(
-        self,
-        *,
-        owner: str,
-        repo: str,
-        title: str,
-        body: str,
-        head: str,
-        base: str,
-        labels: list[str] | None = None,
-    ) -> PullRequest:
-        """Create a pull request."""
-        payload: dict[str, object] = {
-            "title": title,
-            "body": body,
-            "head": head,
-            "base": base,
-        }
-        if labels:
-            payload["labels"] = self.resolve_label_ids(owner=owner, repo=repo, labels=labels)
-
-        response = self._request(
-            "POST",
-            f"/api/v1/repos/{owner}/{repo}/pulls",
-            expected_statuses={EXPECTED_CREATED},
-            json=payload,
-        )
-        return _pull_request_from_api(response.json())
-
-    def merge_pull_request(
-        self,
-        *,
-        owner: str,
-        repo: str,
-        number: int,
-        merge_method: str = "rebase",
-        head_commit_id: str | None = None,
-        delete_branch_after_merge: bool = False,
-    ) -> None:
-        """Merge a pull request."""
-        payload: dict[str, object] = {
-            "Do": merge_method,
-            "delete_branch_after_merge": delete_branch_after_merge,
-        }
-        if head_commit_id:
-            payload["head_commit_id"] = head_commit_id
-
-        self._request(
-            "POST",
-            f"/api/v1/repos/{owner}/{repo}/pulls/{number}/merge",
-            json=payload,
-        )
-
-    def dispatch_workflow(self, *, owner: str, repo: str, workflow_id: str, ref: str) -> None:
-        """Trigger a workflow_dispatch run."""
-        workflow_path = quote(workflow_id, safe="")
-        self._request(
-            "POST",
-            f"/api/v1/repos/{owner}/{repo}/actions/workflows/{workflow_path}/dispatches",
-            expected_statuses={EXPECTED_OK, EXPECTED_NO_CONTENT},
-            json={"ref": ref},
-        )
-
-    def list_run_jobs(self, *, owner: str, repo: str, run_id: str | int) -> list[WorkflowJob]:
-        """List workflow jobs for a specific run."""
-        jobs: list[WorkflowJob] = []
-        page = 1
-        while True:
-            response = self._request(
-                "GET",
-                f"/api/v1/repos/{owner}/{repo}/actions/jobs",
-                params={"page": page, "limit": DEFAULT_PAGE_SIZE},
-            )
-            payload = response.json()
-            batch = payload.get("jobs", [])
-            if not batch:
-                break
-
-            for item in batch:
-                if str(item.get("run_id")) != str(run_id):
-                    continue
-                jobs.append(_workflow_job_from_api(item))
-
-            if len(batch) < DEFAULT_PAGE_SIZE:
-                break
-            page += 1
-
-        return jobs
-
-    def download_job_logs(self, *, owner: str, repo: str, job_id: int) -> str:
-        """Download logs for a workflow job."""
-        response = self._request(
-            "GET",
-            f"/api/v1/repos/{owner}/{repo}/actions/jobs/{job_id}/logs",
-        )
-        return response.text
-
-    def close(self) -> None:
-        """Close the underlying HTTP client."""
-        self._client.close()
-
-    def __enter__(self) -> Self:
-        """Enter the context manager."""
-        return self
-
-    def __exit__(self, *args: object) -> None:
-        """Close the HTTP client."""
-        self.close()
-
-    def _request(
-        self,
-        method: str,
-        path: str,
-        *,
-        expected_statuses: set[int] | None = None,
-        **kwargs: object,
-    ) -> httpx.Response:
-        """Send an HTTP request and validate the response status."""
-        response = self._client.request(method, path, **kwargs)
-        statuses = expected_statuses or {EXPECTED_OK}
-        if response.status_code not in statuses:
-            msg = f"Gitea request failed ({response.status_code}): {response.text}"
-            raise GiteaError(msg)
-        return response
-
-
-def _pull_request_from_api(data: dict[str, object]) -> PullRequest:
-    """Convert Gitea API pull-request data into a dataclass."""
-    number = _optional_int(data.get("number")) or _optional_int(data.get("index"))
-    if number is None:
-        msg = "Gitea pull request payload is missing a number"
-        raise GiteaError(msg)
-
-    labels = tuple(str(label.get("name", "")) for label in data.get("labels", []))
-    head = data.get("head", {})
-    base = data.get("base", {})
-    return PullRequest(
-        number=number,
-        title=str(data.get("title", "")),
-        html_url=_optional_str(data.get("html_url")),
-        labels=tuple(label for label in labels if label),
-        head_branch=_optional_str(head.get("ref")) or _optional_str(data.get("head_branch")),
-        base_branch=_optional_str(base.get("ref")) or _optional_str(data.get("base_branch")),
-    )
-
-
-def _workflow_job_from_api(data: dict[str, object]) -> WorkflowJob:
-    """Convert Gitea API workflow-job data into a dataclass."""
-    job_id = _optional_int(data.get("id"))
-    if job_id is None:
-        msg = "Gitea workflow job payload is missing an ID"
-        raise GiteaError(msg)
-
-    return WorkflowJob(
-        id=job_id,
-        name=str(data.get("name", "")),
-        run_id=_optional_int(data.get("run_id")),
-        status=_optional_str(data.get("status")),
-        conclusion=_optional_str(data.get("conclusion")),
-    )
-
-
-def _optional_int(value: object) -> int | None:
-    """Convert an API value to an integer when present."""
-    if value is None:
-        return None
-    return int(value)
-
-
-def _optional_str(value: object) -> str | None:
-    """Convert an API value to a string when present."""
-    if value is None:
-        return None
-    return str(value)

python/gitea_flake_lock.py

@@ -1,148 +0,0 @@
-"""Automation helpers for flake.lock pull requests on Gitea."""
-
-from __future__ import annotations
-
-import subprocess
-from os import getenv
-from typing import Annotated
-
-import typer
-
-from python.gitea import GiteaClient, PullRequest, split_repo_name
-
-DEFAULT_BASE_BRANCH = "main"
-DEFAULT_BRANCH = "automation/update-flake-lock"
-DEFAULT_GITEA_URL = "https://gitea.tmmworkshop.com"
-PR_LABELS = ["dependencies", "automated", "flake_lock_update"]
-PR_CHECK_WORKFLOWS = ["build_systems.yml", "treefmt.yml", "pytest.yml"]
-PR_TITLE = "Update flake.lock"
-PR_BODY = "Automated flake.lock update."
-
-app = typer.Typer(add_completion=False)
-
-
-def run_cmd(cmd: list[str], *, check: bool = True) -> subprocess.CompletedProcess[str]:
-    """Run a subprocess command."""
-    return subprocess.run(cmd, capture_output=True, text=True, check=check)
-
-
-def ensure_flake_lock_pull_request(
-    client: GiteaClient,
-    *,
-    owner: str,
-    repo: str,
-    branch: str,
-    base: str,
-) -> PullRequest:
-    """Return an existing flake.lock PR for the branch or create one."""
-    pull_requests = client.list_open_pull_requests(owner=owner, repo=repo, head=branch)
-    if pull_requests:
-        return pull_requests[0]
-
-    return client.create_pull_request(
-        owner=owner,
-        repo=repo,
-        title=PR_TITLE,
-        body=PR_BODY,
-        head=branch,
-        base=base,
-        labels=PR_LABELS,
-    )
-
-
-def find_flake_lock_pull_request(client: GiteaClient, *, owner: str, repo: str) -> PullRequest | None:
-    """Find the first open flake.lock pull request."""
-    pull_requests = client.list_open_pull_requests(owner=owner, repo=repo, labels=["flake_lock_update"])
-    if not pull_requests:
-        return None
-    return pull_requests[0]
-
-
-def dispatch_pull_request_checks(client: GiteaClient, *, owner: str, repo: str, branch: str) -> None:
-    """Dispatch the workflows that normally run for pull requests."""
-    for workflow in PR_CHECK_WORKFLOWS:
-        client.dispatch_workflow(owner=owner, repo=repo, workflow_id=workflow, ref=branch)
-
-
-def has_worktree_changes() -> bool:
-    """Return whether `flake.lock` has worktree changes."""
-    result = run_cmd(["git", "diff", "--quiet", "--", "flake.lock"], check=False)
-    return result.returncode != 0
-
-
-def commit_flake_lock_update(*, branch: str) -> None:
-    """Commit the updated lock file to the automation branch."""
-    run_cmd(["git", "config", "user.name", "gitea-actions[bot]"])
-    run_cmd(["git", "config", "user.email", "gitea-actions@tmmworkshop.com"])
-    run_cmd(["git", "checkout", "-B", branch])
-    run_cmd(["git", "add", "flake.lock"])
-    run_cmd(["git", "commit", "-m", "chore: update flake.lock"])
-
-
-def push_branch(*, branch: str) -> None:
-    """Push the automation branch to origin."""
-    run_cmd(["git", "push", "origin", f"HEAD:{branch}", "--force"])
-
-
-def _required_gitea_token() -> str:
-    """Read the required Gitea token from the environment."""
-    token = getenv("GITEA_TOKEN")
-    if token:
-        return token
-
-    msg = "GITEA_TOKEN environment variable is required"
-    raise RuntimeError(msg)
-
-
-@app.command()
-def update(
-    repo: Annotated[str, typer.Option("--repo", help="Gitea repository in owner/repo form")],
-    base: Annotated[str, typer.Option("--base", help="Base branch")] = DEFAULT_BASE_BRANCH,
-    branch: Annotated[str, typer.Option("--branch", help="Automation branch")] = DEFAULT_BRANCH,
-) -> None:
-    """Commit flake.lock changes and ensure a pull request exists."""
-    if not has_worktree_changes():
-        typer.echo("No flake.lock changes detected")
-        return
-
-    commit_flake_lock_update(branch=branch)
-    push_branch(branch=branch)
-
-    owner, repo_name = split_repo_name(repo)
-    with GiteaClient(
-        base_url=getenv("GITEA_URL", DEFAULT_GITEA_URL),
-        token=_required_gitea_token(),
-    ) as client:
-        pull_request = ensure_flake_lock_pull_request(
-            client,
-            owner=owner,
-            repo=repo_name,
-            branch=branch,
-            base=base,
-        )
-        # We can remove this if Gitea fixes the following issue:
-        # https://github.com/go-gitea/gitea/issues/33963
-        dispatch_pull_request_checks(client, owner=owner, repo=repo_name, branch=branch)
-    typer.echo(pull_request.html_url or f"Pull request #{pull_request.number}")
-
-
-@app.command()
-def merge(
-    repo: Annotated[str, typer.Option("--repo", help="Gitea repository in owner/repo form")],
-) -> None:
-    """Merge the first open flake.lock pull request."""
-    owner, repo_name = split_repo_name(repo)
-    with GiteaClient(
-        base_url=getenv("GITEA_URL", DEFAULT_GITEA_URL),
-        token=_required_gitea_token(),
-    ) as client:
-        pull_request = find_flake_lock_pull_request(client, owner=owner, repo=repo_name)
-        if not pull_request:
-            typer.echo("No open PR found with label flake_lock_update")
-            return
-        client.merge_pull_request(owner=owner, repo=repo_name, number=pull_request.number, merge_method="rebase")
-    typer.echo(f"Merged PR #{pull_request.number}")
-
-
-if __name__ == "__main__":
-    app()

python/orm/__init__.py

@@ -1,9 +1,13 @@
 """ORM package exports."""
 
+from python.orm.data_science_dev.base import DataScienceDevBase
 from python.orm.richie.base import RichieBase
+from python.orm.signal_bot.base import SignalBotBase
 from python.orm.van_inventory.base import VanInventoryBase
 
 __all__ = [
+    "DataScienceDevBase",
     "RichieBase",
+    "SignalBotBase",
     "VanInventoryBase",
 ]

python/orm/common.py

@@ -31,24 +31,8 @@ def get_connection_info(name: str) -> tuple[str, str, str, str, str | None]:
     return cast("tuple[str, str, str, str, str | None]", (database, host, port, username, password))
 
 
-def get_postgres_engine(
+def get_postgres_engine(*, name: str = "POSTGRES", pool_pre_ping: bool = True) -> Engine:
-    *,
+    """Create a SQLAlchemy engine from environment variables."""
-    name: str = "POSTGRES",
-    pool_pre_ping: bool = True,
-    vector_engine: bool = False,
-) -> Engine:
-    """Create a SQLAlchemy engine from environment variables.
-
-    Args:
-        name (str, optional): The name of the environment variable prefix. Defaults to "POSTGRES".
-        pool_pre_ping (bool, optional): Whether to ping the database before each connection. Defaults to True.
-        This fixes the issue of trying to use a conection that has timed out on the database side.
-        vector_engine (bool, optional): Whether to use the vector search schema. Defaults to False.
-        This updates the search path the incldued the vecore types and operators.
-
-    Returns:
-        Engine: The SQLAlchemy engine.
-    """
     database, host, port, username, password = get_connection_info(name)
 
     url = URL.create(
@@ -60,14 +44,8 @@ def get_postgres_engine(
         database=database,
     )
 
-    connect_args = {}
-    # There more better way to do this is with separate PG account and a dedicated vector schema for the vector types
-    if vector_engine:
-        connect_args["options"] = "-csearch_path=main,public"
-
     return create_engine(
         url=url,
         pool_pre_ping=pool_pre_ping,
         pool_recycle=1800,
-        connect_args=connect_args,
     )

python/orm/data_science_dev/__init__.py

@@ -0,0 +1,11 @@
+"""Data science dev database ORM exports."""
+
+from __future__ import annotations
+
+from python.orm.data_science_dev.base import DataScienceDevBase, DataScienceDevTableBase, DataScienceDevTableBaseBig
+
+__all__ = [
+    "DataScienceDevBase",
+    "DataScienceDevTableBase",
+    "DataScienceDevTableBaseBig",
+]

python/orm/data_science_dev/base.py

@@ -0,0 +1,52 @@
+"""Data science dev database ORM base."""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import BigInteger, DateTime, MetaData, func
+from sqlalchemy.ext.declarative import AbstractConcreteBase
+from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
+
+from python.orm.common import NAMING_CONVENTION
+
+
+class DataScienceDevBase(DeclarativeBase):
+    """Base class for data_science_dev database ORM models."""
+
+    schema_name = "main"
+
+    metadata = MetaData(
+        schema=schema_name,
+        naming_convention=NAMING_CONVENTION,
+    )
+
+
+class _TableMixin:
+    """Shared timestamp columns for all table bases."""
+
+    created: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True),
+        server_default=func.now(),
+    )
+    updated: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True),
+        server_default=func.now(),
+        onupdate=func.now(),
+    )
+
+
+class DataScienceDevTableBase(_TableMixin, AbstractConcreteBase, DataScienceDevBase):
+    """Table with Integer primary key."""
+
+    __abstract__ = True
+
+    id: Mapped[int] = mapped_column(primary_key=True)
+
+
+class DataScienceDevTableBaseBig(_TableMixin, AbstractConcreteBase, DataScienceDevBase):
+    """Table with BigInteger primary key."""
+
+    __abstract__ = True
+
+    id: Mapped[int] = mapped_column(BigInteger, primary_key=True)

python/orm/data_science_dev/models.py

@@ -0,0 +1,10 @@
+"""Data science dev database ORM models."""
+
+from __future__ import annotations
+
+from python.orm.data_science_dev.posts import partitions  # noqa: F401 — registers partition classes in metadata
+from python.orm.data_science_dev.posts.tables import Posts
+
+__all__ = [
+    "Posts",
+]

python/orm/data_science_dev/posts/__init__.py

@@ -0,0 +1,11 @@
+"""Posts module — weekly-partitioned posts table and partition ORM models."""
+
+from __future__ import annotations
+
+from python.orm.data_science_dev.posts.failed_ingestion import FailedIngestion
+from python.orm.data_science_dev.posts.tables import Posts
+
+__all__ = [
+    "FailedIngestion",
+    "Posts",
+]

python/orm/data_science_dev/posts/columns.py

@@ -0,0 +1,33 @@
+"""Shared column definitions for the posts partitioned table family."""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import BigInteger, SmallInteger, Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+
+class PostsColumns:
+    """Mixin providing all posts columns. Used by both the parent table and partitions."""
+
+    post_id: Mapped[int] = mapped_column(BigInteger, primary_key=True)
+    user_id: Mapped[int] = mapped_column(BigInteger)
+    instance: Mapped[str]
+    date: Mapped[datetime] = mapped_column(primary_key=True)
+    text: Mapped[str] = mapped_column(Text)
+    langs: Mapped[str | None]
+    like_count: Mapped[int]
+    reply_count: Mapped[int]
+    repost_count: Mapped[int]
+    reply_to: Mapped[int | None] = mapped_column(BigInteger)
+    replied_author: Mapped[int | None] = mapped_column(BigInteger)
+    thread_root: Mapped[int | None] = mapped_column(BigInteger)
+    thread_root_author: Mapped[int | None] = mapped_column(BigInteger)
+    repost_from: Mapped[int | None] = mapped_column(BigInteger)
+    reposted_author: Mapped[int | None] = mapped_column(BigInteger)
+    quotes: Mapped[int | None] = mapped_column(BigInteger)
+    quoted_author: Mapped[int | None] = mapped_column(BigInteger)
+    labels: Mapped[str | None]
+    sent_label: Mapped[int | None] = mapped_column(SmallInteger)
+    sent_score: Mapped[float | None]

python/orm/data_science_dev/posts/failed_ingestion.py

@@ -0,0 +1,17 @@
+"""Table for storing JSONL lines that failed during post ingestion."""
+
+from __future__ import annotations
+
+from sqlalchemy import Text
+from sqlalchemy.orm import Mapped, mapped_column
+
+from python.orm.data_science_dev.base import DataScienceDevTableBase
+
+
+class FailedIngestion(DataScienceDevTableBase):
+    """Stores raw JSONL lines and their error messages when ingestion fails."""
+
+    __tablename__ = "failed_ingestion"
+
+    raw_line: Mapped[str] = mapped_column(Text)
+    error: Mapped[str] = mapped_column(Text)

python/orm/data_science_dev/posts/partitions.py

@@ -0,0 +1,71 @@
+"""Dynamically generated ORM classes for each weekly partition of the posts table.
+
+Each class maps to a PostgreSQL partition table (e.g. posts_2024_01).
+These are real ORM models tracked by Alembic autogenerate.
+
+Uses ISO week numbering (datetime.isocalendar().week). ISO years can have
+52 or 53 weeks, and week boundaries are always Monday to Monday.
+"""
+
+from __future__ import annotations
+
+import sys
+from datetime import UTC, datetime
+
+from python.orm.data_science_dev.base import DataScienceDevBase
+from python.orm.data_science_dev.posts.columns import PostsColumns
+
+PARTITION_START_YEAR = 2023
+PARTITION_END_YEAR = 2026
+
+_current_module = sys.modules[__name__]
+
+
+def iso_weeks_in_year(year: int) -> int:
+    """Return the number of ISO weeks in a given year (52 or 53)."""
+    dec_28 = datetime(year, 12, 28, tzinfo=UTC)
+    return dec_28.isocalendar().week
+
+
+def week_bounds(year: int, week: int) -> tuple[datetime, datetime]:
+    """Return (start, end) datetimes for an ISO week.
+
+    Start = Monday 00:00:00 UTC of the given ISO week.
+    End   = Monday 00:00:00 UTC of the following ISO week.
+    """
+    start = datetime.fromisocalendar(year, week, 1).replace(tzinfo=UTC)
+    if week < iso_weeks_in_year(year):
+        end = datetime.fromisocalendar(year, week + 1, 1).replace(tzinfo=UTC)
+    else:
+        end = datetime.fromisocalendar(year + 1, 1, 1).replace(tzinfo=UTC)
+    return start, end
+
+
+def _build_partition_classes() -> dict[str, type]:
+    """Generate one ORM class per ISO week partition."""
+    classes: dict[str, type] = {}
+
+    for year in range(PARTITION_START_YEAR, PARTITION_END_YEAR + 1):
+        for week in range(1, iso_weeks_in_year(year) + 1):
+            class_name = f"PostsWeek{year}W{week:02d}"
+            table_name = f"posts_{year}_{week:02d}"
+
+            partition_class = type(
+                class_name,
+                (PostsColumns, DataScienceDevBase),
+                {
+                    "__tablename__": table_name,
+                    "__table_args__": ({"implicit_returning": False},),
+                },
+            )
+
+            classes[class_name] = partition_class
+
+    return classes
+
+
+# Generate all partition classes and register them on this module
+_partition_classes = _build_partition_classes()
+for _name, _cls in _partition_classes.items():
+    setattr(_current_module, _name, _cls)
+__all__ = list(_partition_classes.keys())

python/orm/data_science_dev/posts/tables.py

@@ -0,0 +1,13 @@
+"""Posts parent table with PostgreSQL weekly range partitioning on date column."""
+
+from __future__ import annotations
+
+from python.orm.data_science_dev.base import DataScienceDevBase
+from python.orm.data_science_dev.posts.columns import PostsColumns
+
+
+class Posts(PostsColumns, DataScienceDevBase):
+    """Parent partitioned table for posts, partitioned by week on `date`."""
+
+    __tablename__ = "posts"
+    __table_args__ = ({"postgresql_partition_by": "RANGE (date)"},)

python/orm/richie/__init__.py

@@ -2,8 +2,8 @@
 
 from __future__ import annotations
 
-from python.orm.richie.audiobook import Audiobook, AudiobookAuthor, AudiobookSeries
 from python.orm.richie.base import RichieBase, TableBase, TableBaseBig, TableBaseSmall
+from python.orm.richie.congress import Bill, Legislator, Vote, VoteRecord
 from python.orm.richie.contact import (
     Contact,
     ContactNeed,
@@ -11,34 +11,19 @@ from python.orm.richie.contact import (
     Need,
     RelationshipType,
 )
-from python.orm.richie.ebook import (
-    EbookChapter,
-    EbookChunk,
-    EbookChunkEmbedding1024,
-    EbookChunkEmbedding2560,
-    EbookChunkEmbedding4096,
-    EbookEmbeddingModel,
-    EbookSource,
-)
 
 __all__ = [
-    "Audiobook",
+    "Bill",
-    "AudiobookAuthor",
-    "AudiobookSeries",
     "Contact",
     "ContactNeed",
     "ContactRelationship",
-    "EbookChapter",
+    "Legislator",
-    "EbookChunk",
-    "EbookChunkEmbedding1024",
-    "EbookChunkEmbedding2560",
-    "EbookChunkEmbedding4096",
-    "EbookEmbeddingModel",
-    "EbookSource",
     "Need",
     "RelationshipType",
     "RichieBase",
     "TableBase",
     "TableBaseBig",
     "TableBaseSmall",
+    "Vote",
+    "VoteRecord",
 ]

python/orm/richie/audiobook.py

@@ -1,55 +0,0 @@
-"""Audiobook catalog models."""
-
-from __future__ import annotations
-
-from sqlalchemy import ForeignKey, String, UniqueConstraint
-from sqlalchemy.orm import Mapped, mapped_column, relationship
-
-from python.orm.richie.base import TableBase
-
-
-class AudiobookAuthor(TableBase):
-    """Canonical audiobook author."""
-
-    __tablename__ = "audiobook_author"
-    __table_args__ = (UniqueConstraint("name"),)
-
-    name: Mapped[str] = mapped_column(String, unique=True)
-
-    books: Mapped[list[Audiobook]] = relationship("Audiobook", back_populates="author")
-    series: Mapped[list[AudiobookSeries]] = relationship("AudiobookSeries", back_populates="author")
-
-
-class AudiobookSeries(TableBase):
-    """Canonical audiobook series."""
-
-    __tablename__ = "audiobook_series"
-    __table_args__ = (UniqueConstraint("author_id", "name"),)
-
-    name: Mapped[str] = mapped_column(String)
-    author_id: Mapped[int] = mapped_column(ForeignKey("main.audiobook_author.id", ondelete="CASCADE"))
-
-    author: Mapped[AudiobookAuthor] = relationship("AudiobookAuthor", back_populates="series")
-    books: Mapped[list[Audiobook]] = relationship("Audiobook", back_populates="series")
-
-
-class Audiobook(TableBase):
-    """Canonical audiobook title."""
-
-    __tablename__ = "audiobook"
-    __table_args__ = (
-        UniqueConstraint(
-            "author_id",
-            "series_id",
-            "title",
-            postgresql_nulls_not_distinct=True,
-        ),
-    )
-
-    title: Mapped[str] = mapped_column(String)
-    author_id: Mapped[int] = mapped_column(ForeignKey("main.audiobook_author.id", ondelete="CASCADE"))
-    series_id: Mapped[int | None] = mapped_column(ForeignKey("main.audiobook_series.id", ondelete="SET NULL"))
-    series_index: Mapped[float] = mapped_column(default=0.0)
-
-    author: Mapped[AudiobookAuthor] = relationship("AudiobookAuthor", back_populates="books")
-    series: Mapped[AudiobookSeries | None] = relationship("AudiobookSeries", back_populates="books")

python/orm/richie/congress.py

@@ -0,0 +1,150 @@
+"""Congress Tracker database models."""
+
+from __future__ import annotations
+
+from datetime import date
+
+from sqlalchemy import ForeignKey, Index, Text, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+
+from python.orm.richie.base import RichieBase, TableBase
+
+
+class Legislator(TableBase):
+    """Legislator model - members of Congress."""
+
+    __tablename__ = "legislator"
+
+    # Natural key - bioguide ID is the authoritative identifier
+    bioguide_id: Mapped[str] = mapped_column(Text, unique=True, index=True)
+
+    # Other IDs for cross-referencing
+    thomas_id: Mapped[str | None]
+    lis_id: Mapped[str | None]
+    govtrack_id: Mapped[int | None]
+    opensecrets_id: Mapped[str | None]
+    fec_ids: Mapped[str | None]  # JSON array stored as string
+
+    # Name info
+    first_name: Mapped[str]
+    last_name: Mapped[str]
+    official_full_name: Mapped[str | None]
+    nickname: Mapped[str | None]
+
+    # Bio
+    birthday: Mapped[date | None]
+    gender: Mapped[str | None]  # M/F
+
+    # Current term info (denormalized for query efficiency)
+    current_party: Mapped[str | None]
+    current_state: Mapped[str | None]
+    current_district: Mapped[int | None]  # House only
+    current_chamber: Mapped[str | None]  # rep/sen
+
+    # Relationships
+    vote_records: Mapped[list[VoteRecord]] = relationship(
+        "VoteRecord",
+        back_populates="legislator",
+        cascade="all, delete-orphan",
+    )
+
+
+class Bill(TableBase):
+    """Bill model - legislation introduced in Congress."""
+
+    __tablename__ = "bill"
+
+    # Composite natural key: congress + bill_type + number
+    congress: Mapped[int]
+    bill_type: Mapped[str]  # hr, s, hres, sres, hjres, sjres
+    number: Mapped[int]
+
+    # Bill info
+    title: Mapped[str | None]
+    title_short: Mapped[str | None]
+    official_title: Mapped[str | None]
+
+    # Status
+    status: Mapped[str | None]
+    status_at: Mapped[date | None]
+
+    # Sponsor
+    sponsor_bioguide_id: Mapped[str | None]
+
+    # Subjects
+    subjects_top_term: Mapped[str | None]
+
+    # Relationships
+    votes: Mapped[list[Vote]] = relationship(
+        "Vote",
+        back_populates="bill",
+    )
+
+    __table_args__ = (
+        UniqueConstraint("congress", "bill_type", "number", name="uq_bill_congress_type_number"),
+        Index("ix_bill_congress", "congress"),
+    )
+
+
+class Vote(TableBase):
+    """Vote model - roll call votes in Congress."""
+
+    __tablename__ = "vote"
+
+    # Composite natural key: congress + chamber + session + number
+    congress: Mapped[int]
+    chamber: Mapped[str]  # house/senate
+    session: Mapped[int]
+    number: Mapped[int]
+
+    # Vote details
+    vote_type: Mapped[str | None]
+    question: Mapped[str | None]
+    result: Mapped[str | None]
+    result_text: Mapped[str | None]
+
+    # Timing
+    vote_date: Mapped[date]
+
+    # Vote counts (denormalized for efficiency)
+    yea_count: Mapped[int | None]
+    nay_count: Mapped[int | None]
+    not_voting_count: Mapped[int | None]
+    present_count: Mapped[int | None]
+
+    # Related bill (optional - not all votes are on bills)
+    bill_id: Mapped[int | None] = mapped_column(ForeignKey("main.bill.id"))
+
+    # Relationships
+    bill: Mapped[Bill | None] = relationship("Bill", back_populates="votes")
+    vote_records: Mapped[list[VoteRecord]] = relationship(
+        "VoteRecord",
+        back_populates="vote",
+        cascade="all, delete-orphan",
+    )
+
+    __table_args__ = (
+        UniqueConstraint("congress", "chamber", "session", "number", name="uq_vote_congress_chamber_session_number"),
+        Index("ix_vote_date", "vote_date"),
+        Index("ix_vote_congress_chamber", "congress", "chamber"),
+    )
+
+
+class VoteRecord(RichieBase):
+    """Association table: Vote <-> Legislator with position."""
+
+    __tablename__ = "vote_record"
+
+    vote_id: Mapped[int] = mapped_column(
+        ForeignKey("main.vote.id", ondelete="CASCADE"),
+        primary_key=True,
+    )
+    legislator_id: Mapped[int] = mapped_column(
+        ForeignKey("main.legislator.id", ondelete="CASCADE"),
+        primary_key=True,
+    )
+    position: Mapped[str]  # Yea, Nay, Not Voting, Present
+
+    # Relationships
+    vote: Mapped[Vote] = relationship("Vote", back_populates="vote_records")
+    legislator: Mapped[Legislator] = relationship("Legislator", back_populates="vote_records")

python/orm/richie/ebook.py

@@ -1,138 +0,0 @@
-"""EPUB search models."""
-
-from __future__ import annotations
-
-from datetime import datetime
-
-from pgvector.sqlalchemy import Vector
-from sqlalchemy import BigInteger, Boolean, DateTime, ForeignKey, Index, String, UniqueConstraint
-from sqlalchemy.orm import Mapped, mapped_column, relationship
-
-from python.orm.richie.base import TableBase, TableBaseBig
-
-
-class EbookSource(TableBase):
-    """One indexed EPUB file."""
-
-    __tablename__ = "ebook_source"
-    __table_args__ = (
-        UniqueConstraint("file_path"),
-        UniqueConstraint("file_sha256"),
-    )
-
-    title: Mapped[str]
-    author: Mapped[str | None]
-    language: Mapped[str | None]
-    publisher: Mapped[str | None]
-    identifier: Mapped[str | None]
-    file_path: Mapped[str]
-    file_sha256: Mapped[str] = mapped_column(String(64))
-    file_mtime: Mapped[datetime] = mapped_column(DateTime(timezone=True))
-    file_size: Mapped[int] = mapped_column(BigInteger)
-
-    chapters: Mapped[list[EbookChapter]] = relationship(
-        "EbookChapter",
-        back_populates="source",
-        cascade="all, delete-orphan",
-        passive_deletes=True,
-    )
-    chunks: Mapped[list[EbookChunk]] = relationship(
-        "EbookChunk",
-        back_populates="source",
-        cascade="all, delete-orphan",
-        passive_deletes=True,
-    )
-
-
-class EbookChapter(TableBase):
-    """A chapter or spine document inside an EPUB."""
-
-    __tablename__ = "ebook_chapter"
-    __table_args__ = (UniqueConstraint("source_id", "spine_index"),)
-
-    source_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_source.id", ondelete="CASCADE"))
-    spine_index: Mapped[int]
-    title: Mapped[str | None]
-    href: Mapped[str | None]
-
-    source: Mapped[EbookSource] = relationship("EbookSource", back_populates="chapters")
-    chunks: Mapped[list[EbookChunk]] = relationship(
-        "EbookChunk",
-        back_populates="chapter",
-        cascade="all, delete-orphan",
-        passive_deletes=True,
-    )
-
-
-class EbookChunk(TableBaseBig):
-    """A searchable text chunk."""
-
-    __tablename__ = "ebook_chunk"
-    __table_args__ = (
-        UniqueConstraint("source_id", "chunk_index", name="uq_ebook_chunk_source_id_chunk_index"),
-        UniqueConstraint("source_id", "content_sha256", name="uq_ebook_chunk_source_id_content_sha256"),
-    )
-
-    source_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_source.id", ondelete="CASCADE"))
-    chapter_id: Mapped[int | None] = mapped_column(ForeignKey("main.ebook_chapter.id", ondelete="SET NULL"))
-    chunk_index: Mapped[int]
-    text: Mapped[str]
-    token_start: Mapped[int]
-    token_count: Mapped[int]
-    page_label: Mapped[str | None]
-    content_sha256: Mapped[str] = mapped_column(String(64))
-    search_text: Mapped[str]
-
-    source: Mapped[EbookSource] = relationship("EbookSource", back_populates="chunks")
-    chapter: Mapped[EbookChapter | None] = relationship("EbookChapter", back_populates="chunks")
-
-
-class EbookEmbeddingModel(TableBase):
-    """A supported embedding model."""
-
-    __tablename__ = "ebook_embedding_model"
-
-    name: Mapped[str] = mapped_column(String, unique=True)
-    dimension: Mapped[int]
-    is_default: Mapped[bool] = mapped_column(Boolean, default=False)
-
-
-class EbookChunkEmbedding1024(TableBaseBig):
-    """1024-dimensional chunk embedding."""
-
-    __tablename__ = "ebook_chunk_embedding_1024"
-    __table_args__ = (
-        UniqueConstraint("chunk_id", "model_id"),
-        Index(
-            "ix_ebook_chunk_embedding_1024_embedding_cosine",
-            "embedding",
-            postgresql_using="hnsw",
-            postgresql_ops={"embedding": "vector_cosine_ops"},
-        ),
-    )
-
-    chunk_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_chunk.id", ondelete="CASCADE"))
-    model_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_embedding_model.id", ondelete="CASCADE"))
-    embedding: Mapped[list[float]] = mapped_column(Vector(1024))
-
-
-class EbookChunkEmbedding2560(TableBaseBig):
-    """2560-dimensional chunk embedding."""
-
-    __tablename__ = "ebook_chunk_embedding_2560"
-    __table_args__ = (UniqueConstraint("chunk_id", "model_id"),)
-
-    chunk_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_chunk.id", ondelete="CASCADE"))
-    model_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_embedding_model.id", ondelete="CASCADE"))
-    embedding: Mapped[list[float]] = mapped_column(Vector(2560))
-
-
-class EbookChunkEmbedding4096(TableBaseBig):
-    """4096-dimensional chunk embedding."""
-
-    __tablename__ = "ebook_chunk_embedding_4096"
-    __table_args__ = (UniqueConstraint("chunk_id", "model_id"),)
-
-    chunk_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_chunk.id", ondelete="CASCADE"))
-    model_id: Mapped[int] = mapped_column(ForeignKey("main.ebook_embedding_model.id", ondelete="CASCADE"))
-    embedding: Mapped[list[float]] = mapped_column(Vector(4096))

python/orm/signal_bot/__init__.py

@@ -0,0 +1,16 @@
+"""Signal bot database ORM exports."""
+
+from __future__ import annotations
+
+from python.orm.signal_bot.base import SignalBotBase, SignalBotTableBase, SignalBotTableBaseSmall
+from python.orm.signal_bot.models import DeadLetterMessage, DeviceRole, RoleRecord, SignalDevice
+
+__all__ = [
+    "DeadLetterMessage",
+    "DeviceRole",
+    "RoleRecord",
+    "SignalBotBase",
+    "SignalBotTableBase",
+    "SignalBotTableBaseSmall",
+    "SignalDevice",
+]

python/orm/signal_bot/base.py

@@ -0,0 +1,52 @@
+"""Signal bot database ORM base."""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import DateTime, MetaData, SmallInteger, func
+from sqlalchemy.ext.declarative import AbstractConcreteBase
+from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column
+
+from python.orm.common import NAMING_CONVENTION
+
+
+class SignalBotBase(DeclarativeBase):
+    """Base class for signal_bot database ORM models."""
+
+    schema_name = "main"
+
+    metadata = MetaData(
+        schema=schema_name,
+        naming_convention=NAMING_CONVENTION,
+    )
+
+
+class _TableMixin:
+    """Shared timestamp columns for all table bases."""
+
+    created: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True),
+        server_default=func.now(),
+    )
+    updated: Mapped[datetime] = mapped_column(
+        DateTime(timezone=True),
+        server_default=func.now(),
+        onupdate=func.now(),
+    )
+
+
+class SignalBotTableBaseSmall(_TableMixin, AbstractConcreteBase, SignalBotBase):
+    """Table with SmallInteger primary key."""
+
+    __abstract__ = True
+
+    id: Mapped[int] = mapped_column(SmallInteger, primary_key=True)
+
+
+class SignalBotTableBase(_TableMixin, AbstractConcreteBase, SignalBotBase):
+    """Table with Integer primary key."""
+
+    __abstract__ = True
+
+    id: Mapped[int] = mapped_column(primary_key=True)

python/orm/signal_bot/models.py

@@ -0,0 +1,62 @@
+"""Signal bot device, role, and dead letter ORM models."""
+
+from __future__ import annotations
+
+from datetime import datetime
+
+from sqlalchemy import DateTime, Enum, ForeignKey, SmallInteger, String, Text, UniqueConstraint
+from sqlalchemy.orm import Mapped, mapped_column, relationship
+
+from python.orm.signal_bot.base import SignalBotTableBase, SignalBotTableBaseSmall
+from python.signal_bot.models import MessageStatus, TrustLevel
+
+
+class RoleRecord(SignalBotTableBaseSmall):
+    """Lookup table for RBAC roles, keyed by smallint."""
+
+    __tablename__ = "role"
+
+    name: Mapped[str] = mapped_column(String(50), unique=True)
+
+
+class DeviceRole(SignalBotTableBase):
+    """Association between a device and a role."""
+
+    __tablename__ = "device_role"
+    __table_args__ = (
+        UniqueConstraint("device_id", "role_id", name="uq_device_role_device_role"),
+        {"schema": "main"},
+    )
+
+    device_id: Mapped[int] = mapped_column(ForeignKey("main.signal_device.id"))
+    role_id: Mapped[int] = mapped_column(SmallInteger, ForeignKey("main.role.id"))
+
+
+class SignalDevice(SignalBotTableBase):
+    """A Signal device tracked by phone number and safety number."""
+
+    __tablename__ = "signal_device"
+
+    phone_number: Mapped[str] = mapped_column(String(50), unique=True)
+    safety_number: Mapped[str | None]
+    trust_level: Mapped[TrustLevel] = mapped_column(
+        Enum(TrustLevel, name="trust_level", create_constraint=False, native_enum=False),
+        default=TrustLevel.UNVERIFIED,
+    )
+    last_seen: Mapped[datetime] = mapped_column(DateTime(timezone=True))
+
+    roles: Mapped[list[RoleRecord]] = relationship(secondary=DeviceRole.__table__)
+
+
+class DeadLetterMessage(SignalBotTableBase):
+    """A Signal message that failed processing and was sent to the dead letter queue."""
+
+    __tablename__ = "dead_letter_message"
+
+    source: Mapped[str]
+    message: Mapped[str] = mapped_column(Text)
+    received_at: Mapped[datetime] = mapped_column(DateTime(timezone=True))
+    status: Mapped[MessageStatus] = mapped_column(
+        Enum(MessageStatus, name="message_status", create_constraint=False, native_enum=False),
+        default=MessageStatus.UNPROCESSED,
+    )

python/signal_bot/__init__.py

@@ -0,0 +1 @@
+"""Signal command and control bot."""

python/signal_bot/commands/__init__.py

@@ -0,0 +1 @@
+"""Signal bot commands."""

python/signal_bot/commands/inventory.py

@@ -0,0 +1,137 @@
+"""Van inventory command — parse receipts and item lists via LLM, push to API."""
+
+from __future__ import annotations
+
+import json
+import logging
+from typing import TYPE_CHECKING, Any
+
+import httpx
+
+from python.signal_bot.models import InventoryItem, InventoryUpdate
+
+if TYPE_CHECKING:
+    from python.signal_bot.llm_client import LLMClient
+    from python.signal_bot.models import SignalMessage
+    from python.signal_bot.signal_client import SignalClient
+
+logger = logging.getLogger(__name__)
+
+SYSTEM_PROMPT = """\
+You are an inventory assistant. Extract items from the input and return ONLY
+a JSON array. Each element must have these fields:
+  - "name": item name (string)
+  - "quantity": numeric count or amount (default 1)
+  - "unit": unit of measure (e.g. "each", "lb", "oz", "gallon", "bag", "box")
+  - "category": category like "food", "tools", "supplies", etc.
+  - "notes": any extra detail (empty string if none)
+
+Example output:
+[{"name": "water bottles", "quantity": 6, "unit": "gallon", "category": "supplies", "notes": "1 gallon each"}]
+
+Return ONLY the JSON array, no other text.\
+"""
+
+IMAGE_PROMPT = "Extract all items from this receipt or inventory photo."
+TEXT_PROMPT = "Extract all items from this inventory list."
+
+
+def parse_llm_response(raw: str) -> list[InventoryItem]:
+    """Parse the LLM JSON response into InventoryItem list."""
+    text = raw.strip()
+    # Strip markdown code fences if present
+    if text.startswith("```"):
+        lines = text.split("\n")
+        lines = [line for line in lines if not line.startswith("```")]
+        text = "\n".join(lines)
+
+    items_data: list[dict[str, Any]] = json.loads(text)
+    return [InventoryItem.model_validate(item) for item in items_data]
+
+
+def _upsert_item(api_url: str, item: InventoryItem) -> None:
+    """Create or update an item via the van_inventory API.
+
+    Fetches existing items, and if one with the same name exists,
+    patches its quantity (summing). Otherwise creates a new item.
+    """
+    base = api_url.rstrip("/")
+    response = httpx.get(f"{base}/api/items", timeout=10)
+    response.raise_for_status()
+    existing: list[dict[str, Any]] = response.json()
+
+    match = next((e for e in existing if e["name"].lower() == item.name.lower()), None)
+
+    if match:
+        new_qty = match["quantity"] + item.quantity
+        patch = {"quantity": new_qty}
+        if item.category:
+            patch["category"] = item.category
+        response = httpx.patch(f"{base}/api/items/{match['id']}", json=patch, timeout=10)
+        response.raise_for_status()
+        return
+    payload = {
+        "name": item.name,
+        "quantity": item.quantity,
+        "unit": item.unit,
+        "category": item.category or None,
+    }
+    response = httpx.post(f"{base}/api/items", json=payload, timeout=10)
+    response.raise_for_status()
+
+
+def handle_inventory_update(
+    message: SignalMessage,
+    signal: SignalClient,
+    llm: LLMClient,
+    api_url: str,
+) -> InventoryUpdate:
+    """Process an inventory update from a Signal message.
+
+    Accepts either an image (receipt photo) or text list.
+    Uses the LLM to extract structured items, then pushes to the van_inventory API.
+    """
+    try:
+        logger.info(f"Processing inventory update from {message.source}")
+        if message.attachments:
+            image_data = signal.get_attachment(message.attachments[0])
+            raw_response = llm.chat(
+                IMAGE_PROMPT,
+                image_data=image_data,
+                system=SYSTEM_PROMPT,
+            )
+            source_type = "receipt_photo"
+        elif message.message.strip():
+            raw_response = llm.chat(
+                f"{TEXT_PROMPT}\n\n{message.message}",
+                system=SYSTEM_PROMPT,
+            )
+            source_type = "text_list"
+        else:
+            signal.reply(message, "Send a photo of a receipt or a text list of items to update inventory.")
+            return InventoryUpdate()
+
+        logger.info(f"{raw_response=}")
+
+        new_items = parse_llm_response(raw_response)
+
+        logger.info(f"{new_items=}")
+
+        for item in new_items:
+            _upsert_item(api_url, item)
+
+        summary = _format_summary(new_items)
+        signal.reply(message, f"Inventory updated with {len(new_items)} item(s):\n{summary}")
+
+        return InventoryUpdate(items=new_items, raw_response=raw_response, source_type=source_type)
+
+    except Exception:
+        logger.exception("Failed to process inventory update")
+        signal.reply(message, "Failed to process inventory update. Check logs for details.")
+        return InventoryUpdate()
+
+
+def _format_summary(items: list[InventoryItem]) -> str:
+    """Format items into a readable summary."""
+    lines = [f"  - {item.name} x{item.quantity} {item.unit} [{item.category}]" for item in items]
+    return "\n".join(lines)

python/signal_bot/commands/location.py

@@ -0,0 +1,64 @@
+"""Location command for the Signal bot."""
+
+from __future__ import annotations
+
+import logging
+from typing import TYPE_CHECKING, Any
+
+import httpx
+
+if TYPE_CHECKING:
+    from python.signal_bot.models import SignalMessage
+    from python.signal_bot.signal_client import SignalClient
+
+logger = logging.getLogger(__name__)
+
+
+def _get_entity_state(ha_url: str, ha_token: str, entity_id: str) -> dict[str, Any]:
+    """Fetch an entity's state from Home Assistant."""
+    entity_url = f"{ha_url}/api/states/{entity_id}"
+    logger.debug(f"Fetching {entity_url=}")
+    response = httpx.get(
+        entity_url,
+        headers={"Authorization": f"Bearer {ha_token}"},
+        timeout=30,
+    )
+    response.raise_for_status()
+    return response.json()
+
+
+def _format_location(latitude: str, longitude: str) -> str:
+    """Render a friendly location response."""
+    return f"Van location: {latitude}, {longitude}\nhttps://maps.google.com/?q={latitude},{longitude}"
+
+
+def handle_location_request(
+    message: SignalMessage,
+    signal: SignalClient,
+    ha_url: str | None,
+    ha_token: str | None,
+) -> None:
+    """Reply with van location from Home Assistant."""
+    if ha_url is None or ha_token is None:
+        signal.reply(message, "Location command is not configured (missing HA_URL or HA_TOKEN).")
+        return
+
+    lat_payload = None
+    lon_payload = None
+    try:
+        lat_payload = _get_entity_state(ha_url, ha_token, "sensor.van_last_known_latitude")
+        lon_payload = _get_entity_state(ha_url, ha_token, "sensor.van_last_known_longitude")
+    except httpx.HTTPError:
+        logger.exception("Couldn't fetch van location from Home Assistant right now.")
+        logger.debug(f"{ha_url=} {lat_payload=} {lon_payload=}")
+        signal.reply(message, "Couldn't fetch van location from Home Assistant right now.")
+        return
+
+    latitude = lat_payload.get("state", "")
+    longitude = lon_payload.get("state", "")
+
+    if not latitude or not longitude or latitude == "unavailable" or longitude == "unavailable":
+        signal.reply(message, "Van location is unavailable in Home Assistant right now.")
+        return
+
+    signal.reply(message, _format_location(latitude, longitude))

python/signal_bot/device_registry.py

@@ -0,0 +1,286 @@
+"""Device registry — tracks verified/unverified devices by safety number."""
+
+from __future__ import annotations
+
+import logging
+from datetime import datetime, timedelta
+from typing import TYPE_CHECKING, NamedTuple
+
+from sqlalchemy import delete, select
+from sqlalchemy.orm import Session
+
+from python.common import utcnow
+from python.orm.signal_bot.models import RoleRecord, SignalDevice
+from python.signal_bot.models import Role, TrustLevel
+
+if TYPE_CHECKING:
+    from sqlalchemy.engine import Engine
+
+    from python.signal_bot.signal_client import SignalClient
+
+logger = logging.getLogger(__name__)
+
+_BLOCKED_TTL = timedelta(minutes=60)
+_DEFAULT_TTL = timedelta(minutes=5)
+
+
+class _CacheEntry(NamedTuple):
+    expires: datetime
+    trust_level: TrustLevel
+    has_safety_number: bool
+    safety_number: str | None
+    roles: list[Role]
+
+
+class DeviceRegistry:
+    """Manage device trust based on Signal safety numbers.
+
+    Devices start as UNVERIFIED. An admin verifies them over SSH by calling
+    ``verify(phone_number)`` which marks the device VERIFIED and also tells
+    signal-cli to trust the identity.
+
+    Only VERIFIED devices may execute commands.
+    """
+
+    def __init__(self, signal_client: SignalClient, engine: Engine) -> None:
+        self.signal_client = signal_client
+        self.engine = engine
+        self._contact_cache: dict[str, _CacheEntry] = {}
+
+    def is_verified(self, phone_number: str) -> bool:
+        """Check if a phone number is verified."""
+        if entry := self._cached(phone_number):
+            return entry.trust_level == TrustLevel.VERIFIED
+        device = self._load_device(phone_number)
+        return device is not None and device.trust_level == TrustLevel.VERIFIED
+
+    def record_contact(self, phone_number: str, safety_number: str | None = None) -> None:
+        """Record seeing a device. Creates entry if new, updates last_seen."""
+        now = utcnow()
+
+        entry = self._cached(phone_number)
+        if entry and entry.safety_number == safety_number:
+            return
+
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if device:
+                if device.safety_number != safety_number and device.trust_level != TrustLevel.BLOCKED:
+                    logger.warning(f"Safety number changed for {phone_number}, resetting to UNVERIFIED")
+                    device.safety_number = safety_number
+                    device.trust_level = TrustLevel.UNVERIFIED
+                device.last_seen = now
+            else:
+                device = SignalDevice(
+                    phone_number=phone_number,
+                    safety_number=safety_number,
+                    trust_level=TrustLevel.UNVERIFIED,
+                    last_seen=now,
+                )
+                session.add(device)
+                logger.info(f"New device registered: {phone_number}")
+
+            session.commit()
+            self._update_cache(phone_number, device)
+
+    def has_safety_number(self, phone_number: str) -> bool:
+        """Check if a device has a safety number on file."""
+        if entry := self._cached(phone_number):
+            return entry.has_safety_number
+        device = self._load_device(phone_number)
+        return device is not None and device.safety_number is not None
+
+    def verify(self, phone_number: str) -> bool:
+        """Mark a device as verified. Called by admin over SSH.
+
+        Returns True if the device was found and verified.
+        """
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if not device:
+                logger.warning(f"Cannot verify unknown device: {phone_number}")
+                return False
+
+            device.trust_level = TrustLevel.VERIFIED
+            self.signal_client.trust_identity(phone_number, trust_all_known_keys=True)
+            session.commit()
+            self._update_cache(phone_number, device)
+            logger.info(f"Device verified: {phone_number}")
+            return True
+
+    def block(self, phone_number: str) -> bool:
+        """Block a device."""
+        return self._set_trust(phone_number, TrustLevel.BLOCKED, "Device blocked")
+
+    def unverify(self, phone_number: str) -> bool:
+        """Reset a device to unverified."""
+        return self._set_trust(phone_number, TrustLevel.UNVERIFIED)
+
+    # -- role management ------------------------------------------------------
+
+    def get_roles(self, phone_number: str) -> list[Role]:
+        """Return the roles for a device, defaulting to empty."""
+        if entry := self._cached(phone_number):
+            return entry.roles
+        device = self._load_device(phone_number)
+        return _extract_roles(device) if device else []
+
+    def has_role(self, phone_number: str, role: Role) -> bool:
+        """Check if a device has a specific role or is admin."""
+        roles = self.get_roles(phone_number)
+        return Role.ADMIN in roles or role in roles
+
+    def grant_role(self, phone_number: str, role: Role) -> bool:
+        """Add a role to a device. Called by admin over SSH."""
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if not device:
+                logger.warning(f"Cannot grant role for unknown device: {phone_number}")
+                return False
+
+            if any(record.name == role for record in device.roles):
+                return True
+
+            role_record = session.execute(select(RoleRecord).where(RoleRecord.name == role)).scalar_one_or_none()
+
+            if not role_record:
+                logger.warning(f"Unknown role: {role}")
+                return False
+
+            device.roles.append(role_record)
+            session.commit()
+            self._update_cache(phone_number, device)
+            logger.info(f"Device {phone_number} granted role {role}")
+            return True
+
+    def revoke_role(self, phone_number: str, role: Role) -> bool:
+        """Remove a role from a device. Called by admin over SSH."""
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if not device:
+                logger.warning(f"Cannot revoke role for unknown device: {phone_number}")
+                return False
+
+            device.roles = [record for record in device.roles if record.name != role]
+            session.commit()
+            self._update_cache(phone_number, device)
+            logger.info(f"Device {phone_number} revoked role {role}")
+            return True
+
+    def set_roles(self, phone_number: str, roles: list[Role]) -> bool:
+        """Replace all roles for a device. Called by admin over SSH."""
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if not device:
+                logger.warning(f"Cannot set roles for unknown device: {phone_number}")
+                return False
+
+            role_names = [str(role) for role in roles]
+            records = list(session.execute(select(RoleRecord).where(RoleRecord.name.in_(role_names))).scalars().all())
+            device.roles = records
+            session.commit()
+            self._update_cache(phone_number, device)
+            logger.info(f"Device {phone_number} roles set to {role_names}")
+            return True
+
+    # -- queries --------------------------------------------------------------
+
+    def list_devices(self) -> list[SignalDevice]:
+        """Return all known devices."""
+        with Session(self.engine) as session:
+            return list(session.execute(select(SignalDevice)).scalars().all())
+
+    def sync_identities(self) -> None:
+        """Pull identity list from signal-cli and record any new ones."""
+        identities = self.signal_client.get_identities()
+        for identity in identities:
+            number = identity.get("number", "")
+            safety = identity.get("safety_number", identity.get("fingerprint", ""))
+            if number:
+                self.record_contact(number, safety)
+
+    # -- internals ------------------------------------------------------------
+
+    def _cached(self, phone_number: str) -> _CacheEntry | None:
+        """Return the cache entry if it exists and hasn't expired."""
+        entry = self._contact_cache.get(phone_number)
+        if entry and utcnow() < entry.expires:
+            return entry
+        return None
+
+    def _load_device(self, phone_number: str) -> SignalDevice | None:
+        """Fetch a device by phone number (with joined roles)."""
+        with Session(self.engine) as session:
+            return session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+    def _update_cache(self, phone_number: str, device: SignalDevice) -> None:
+        """Refresh the cache entry for a device."""
+        ttl = _BLOCKED_TTL if device.trust_level == TrustLevel.BLOCKED else _DEFAULT_TTL
+        self._contact_cache[phone_number] = _CacheEntry(
+            expires=utcnow() + ttl,
+            trust_level=device.trust_level,
+            has_safety_number=device.safety_number is not None,
+            safety_number=device.safety_number,
+            roles=_extract_roles(device),
+        )
+
+    def _set_trust(self, phone_number: str, level: str, log_msg: str | None = None) -> bool:
+        """Update the trust level for a device."""
+        with Session(self.engine) as session:
+            device = session.execute(
+                select(SignalDevice).where(SignalDevice.phone_number == phone_number)
+            ).scalar_one_or_none()
+
+            if not device:
+                return False
+
+            device.trust_level = level
+            session.commit()
+            self._update_cache(phone_number, device)
+            if log_msg:
+                logger.info(f"{log_msg}: {phone_number}")
+            return True
+
+
+def _extract_roles(device: SignalDevice) -> list[Role]:
+    """Convert a device's RoleRecord objects to a list of Role enums."""
+    return [Role(record.name) for record in device.roles]
+
+
+def sync_roles(engine: Engine) -> None:
+    """Sync the Role enum to the role table, adding new and removing stale entries."""
+    expected = {role.value for role in Role}
+
+    with Session(engine) as session:
+        existing = {record.name for record in session.execute(select(RoleRecord)).scalars().all()}
+
+        to_add = expected - existing
+        to_remove = existing - expected
+
+        for name in to_add:
+            session.add(RoleRecord(name=name))
+            logger.info(f"Role added: {name}")
+
+        if to_remove:
+            session.execute(delete(RoleRecord).where(RoleRecord.name.in_(to_remove)))
+            for name in to_remove:
+                logger.info(f"Role removed: {name}")
+
+        session.commit()

python/signal_bot/llm_client.py

@@ -0,0 +1,80 @@
+"""Flexible LLM client for ollama backends."""
+
+from __future__ import annotations
+
+import base64
+import logging
+from typing import Any, Self
+
+import httpx
+
+logger = logging.getLogger(__name__)
+
+
+class LLMClient:
+    """Talk to an ollama instance.
+
+    Args:
+        model: Ollama model name.
+        host: Ollama host.
+        port: Ollama port.
+        temperature: Sampling temperature.
+    """
+
+    def __init__(
+        self,
+        *,
+        model: str,
+        host: str,
+        port: int = 11434,
+        temperature: float = 0.1,
+        timeout: int = 300,
+    ) -> None:
+        self.model = model
+        self.temperature = temperature
+        self._client = httpx.Client(base_url=f"http://{host}:{port}", timeout=timeout)
+
+    def chat(self, prompt: str, image_data: bytes | None = None, system: str | None = None) -> str:
+        """Send a text prompt and return the response."""
+        messages: list[dict[str, Any]] = []
+        if system:
+            messages.append({"role": "system", "content": system})
+
+        user_msg = {"role": "user", "content": prompt}
+        if image_data:
+            user_msg["images"] = [base64.b64encode(image_data).decode()]
+
+        messages.append(user_msg)
+        return self._generate(messages)
+
+    def _generate(self, messages: list[dict[str, Any]]) -> str:
+        """Call the ollama chat API."""
+        payload = {
+            "model": self.model,
+            "messages": messages,
+            "stream": False,
+            "options": {"temperature": self.temperature},
+        }
+        logger.info(f"LLM request to {self.model}")
+        response = self._client.post("/api/chat", json=payload)
+        response.raise_for_status()
+        data = response.json()
+        return data["message"]["content"]
+
+    def list_models(self) -> list[str]:
+        """List available models on the ollama instance."""
+        response = self._client.get("/api/tags")
+        response.raise_for_status()
+        return [m["name"] for m in response.json().get("models", [])]
+
+    def __enter__(self) -> Self:
+        """Enter the context manager."""
+        return self
+
+    def __exit__(self, *args: object) -> None:
+        """Close the HTTP client on exit."""
+        self.close()
+
+    def close(self) -> None:
+        """Close the HTTP client."""
+        self._client.close()

python/signal_bot/main.py

@@ -0,0 +1,239 @@
+"""Signal command and control bot — main entry point."""
+
+from __future__ import annotations
+
+import logging
+from dataclasses import dataclass
+from os import getenv
+from typing import TYPE_CHECKING, Annotated
+
+if TYPE_CHECKING:
+    from collections.abc import Callable
+
+import typer
+from alembic.command import upgrade
+from sqlalchemy.orm import Session
+from tenacity import before_sleep_log, retry, stop_after_attempt, wait_exponential
+
+from python.common import configure_logger, utcnow
+from python.database_cli import DATABASES
+from python.orm.common import get_postgres_engine
+from python.orm.signal_bot.models import DeadLetterMessage
+from python.signal_bot.commands.inventory import handle_inventory_update
+from python.signal_bot.commands.location import handle_location_request
+from python.signal_bot.device_registry import DeviceRegistry, sync_roles
+from python.signal_bot.llm_client import LLMClient
+from python.signal_bot.models import BotConfig, MessageStatus, Role, SignalMessage
+from python.signal_bot.signal_client import SignalClient
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass(frozen=True, slots=True)
+class Command:
+    """A registered bot command."""
+
+    action: Callable[[SignalMessage, str], None]
+    help_text: str
+    role: Role | None  # None = no role required (always allowed)
+
+
+class Bot:
+    """Holds shared resources and dispatches incoming messages to command handlers."""
+
+    def __init__(
+        self,
+        signal: SignalClient,
+        llm: LLMClient,
+        registry: DeviceRegistry,
+        config: BotConfig,
+    ) -> None:
+        self.signal = signal
+        self.llm = llm
+        self.registry = registry
+        self.config = config
+        self.commands: dict[str, Command] = {
+            "help": Command(action=self._help, help_text="show this help message", role=None),
+            "status": Command(action=self._status, help_text="show bot status", role=Role.STATUS),
+            "inventory": Command(
+                action=self._inventory,
+                help_text="update van inventory from a text list or receipt photo",
+                role=Role.INVENTORY,
+            ),
+            "location": Command(
+                action=self._location,
+                help_text="get current van location",
+                role=Role.LOCATION,
+            ),
+        }
+
+    # -- actions --------------------------------------------------------------
+
+    def _help(self, message: SignalMessage, _cmd: str) -> None:
+        """Return help text filtered to the sender's roles."""
+        self.signal.reply(message, self._build_help(self.registry.get_roles(message.source)))
+
+    def _status(self, message: SignalMessage, _cmd: str) -> None:
+        """Return the status of the bot."""
+        models = self.llm.list_models()
+        model_list = ", ".join(models[:10])
+        device_count = len(self.registry.list_devices())
+        self.signal.reply(
+            message,
+            f"Bot online.\nLLM: {self.llm.model}\nAvailable models: {model_list}\nKnown devices: {device_count}",
+        )
+
+    def _inventory(self, message: SignalMessage, _cmd: str) -> None:
+        """Process an inventory update."""
+        handle_inventory_update(message, self.signal, self.llm, self.config.inventory_api_url)
+
+    def _location(self, message: SignalMessage, _cmd: str) -> None:
+        """Reply with current van location."""
+        handle_location_request(message, self.signal, self.config.ha_url, self.config.ha_token)
+
+    # -- dispatch -------------------------------------------------------------
+
+    def _build_help(self, roles: list[Role]) -> str:
+        """Build help text showing only the commands the user can access."""
+        is_admin = Role.ADMIN in roles
+        lines = ["Available commands:"]
+        for name, cmd in self.commands.items():
+            if cmd.role is None or is_admin or cmd.role in roles:
+                lines.append(f"  {name:20s} — {cmd.help_text}")
+        return "\n".join(lines)
+
+    def dispatch(self, message: SignalMessage) -> None:
+        """Route an incoming message to the right command handler."""
+        source = message.source
+
+        if not self.registry.is_verified(source):
+            logger.info(f"Device {source} not verified, ignoring message")
+            return
+
+        if not self.registry.has_safety_number(source) and self.registry.has_role(source, Role.ADMIN):
+            logger.warning(f"Admin device {source} missing safety number, ignoring message")
+            return
+
+        text = message.message.strip()
+        parts = text.split()
+
+        if not parts and not message.attachments:
+            return
+
+        cmd = parts[0].lower() if parts else ""
+
+        logger.info(f"f{source=} running {cmd=} with {message=}")
+
+        command = self.commands.get(cmd)
+        if command is None:
+            if message.attachments:
+                command = self.commands["inventory"]
+                cmd = "inventory"
+            else:
+                return
+
+        if command.role is not None and not self.registry.has_role(source, command.role):
+            logger.warning(f"Device {source} denied access to {cmd!r}")
+            self.signal.reply(message, f"Permission denied: you do not have the '{command.role}' role.")
+            return
+
+        command.action(message, cmd)
+
+    def process_message(self, message: SignalMessage) -> None:
+        """Process a single message, sending it to the dead letter queue after repeated failures."""
+        max_attempts = self.config.max_message_attempts
+        for attempt in range(1, max_attempts + 1):
+            try:
+                safety_number = self.signal.get_safety_number(message.source)
+                self.registry.record_contact(message.source, safety_number)
+                self.dispatch(message)
+            except Exception:
+                logger.exception(f"Failed to process message (attempt {attempt}/{max_attempts})")
+            else:
+                return
+
+        logger.error(f"Message from {message.source} failed {max_attempts} times, sending to dead letter queue")
+        with Session(self.config.engine) as session:
+            session.add(
+                DeadLetterMessage(
+                    source=message.source,
+                    message=message.message,
+                    received_at=utcnow(),
+                    status=MessageStatus.UNPROCESSED,
+                )
+            )
+            session.commit()
+
+    def run(self) -> None:
+        """Listen for messages via WebSocket, reconnecting on failure."""
+        logger.info("Bot started — listening via WebSocket")
+
+        @retry(
+            stop=stop_after_attempt(self.config.max_retries),
+            wait=wait_exponential(multiplier=self.config.reconnect_delay, max=self.config.max_reconnect_delay),
+            before_sleep=before_sleep_log(logger, logging.WARNING),
+            reraise=True,
+        )
+        def _listen() -> None:
+            for message in self.signal.listen():
+                logger.info(f"Message from {message.source}: {message.message[:80]}")
+                self.process_message(message)
+
+        try:
+            _listen()
+        except Exception:
+            logger.critical("Max retries exceeded, shutting down")
+            raise
+
+
+def main(
+    log_level: Annotated[str, typer.Option()] = "DEBUG",
+    llm_timeout: Annotated[int, typer.Option()] = 600,
+) -> None:
+    """Run the Signal command and control bot."""
+    configure_logger(log_level)
+    signal_api_url = getenv("SIGNAL_API_URL")
+    phone_number = getenv("SIGNAL_PHONE_NUMBER")
+    inventory_api_url = getenv("INVENTORY_API_URL")
+
+    if signal_api_url is None:
+        error = "SIGNAL_API_URL environment variable not set"
+        raise ValueError(error)
+    if phone_number is None:
+        error = "SIGNAL_PHONE_NUMBER environment variable not set"
+        raise ValueError(error)
+    if inventory_api_url is None:
+        error = "INVENTORY_API_URL environment variable not set"
+        raise ValueError(error)
+
+    signal_bot_config = DATABASES["signal_bot"].alembic_config()
+    upgrade(signal_bot_config, "head")
+    engine = get_postgres_engine(name="SIGNALBOT")
+    sync_roles(engine)
+    config = BotConfig(
+        signal_api_url=signal_api_url,
+        phone_number=phone_number,
+        inventory_api_url=inventory_api_url,
+        ha_url=getenv("HA_URL"),
+        ha_token=getenv("HA_TOKEN"),
+        engine=engine,
+    )
+
+    llm_host = getenv("LLM_HOST")
+    llm_model = getenv("LLM_MODEL", "qwen3-vl:32b")
+    llm_port = int(getenv("LLM_PORT", "11434"))
+    if llm_host is None:
+        error = "LLM_HOST environment variable not set"
+        raise ValueError(error)
+
+    with (
+        SignalClient(config.signal_api_url, config.phone_number) as signal,
+        LLMClient(model=llm_model, host=llm_host, port=llm_port, timeout=llm_timeout) as llm,
+    ):
+        registry = DeviceRegistry(signal, engine)
+        bot = Bot(signal, llm, registry, config)
+        bot.run()
+
+
+if __name__ == "__main__":
+    typer.run(main)

python/signal_bot/models.py

@@ -0,0 +1,97 @@
+"""Models for the Signal command and control bot."""
+
+from __future__ import annotations
+
+from datetime import datetime  # noqa: TC003 - pydantic needs this at runtime
+from enum import StrEnum
+from typing import Any
+
+from pydantic import BaseModel, ConfigDict
+from sqlalchemy.engine import Engine  # noqa: TC002 - pydantic needs this at runtime
+
+
+class TrustLevel(StrEnum):
+    """Device trust level."""
+
+    VERIFIED = "verified"
+    UNVERIFIED = "unverified"
+    BLOCKED = "blocked"
+
+
+class Role(StrEnum):
+    """RBAC roles — one per command, plus admin which grants all."""
+
+    ADMIN = "admin"
+    STATUS = "status"
+    INVENTORY = "inventory"
+    LOCATION = "location"
+
+
+class MessageStatus(StrEnum):
+    """Dead letter queue message status."""
+
+    UNPROCESSED = "unprocessed"
+    PROCESSED = "processed"
+
+
+class Device(BaseModel):
+    """A registered device tracked by safety number."""
+
+    phone_number: str
+    safety_number: str
+    trust_level: TrustLevel = TrustLevel.UNVERIFIED
+    first_seen: datetime
+    last_seen: datetime
+
+
+class SignalMessage(BaseModel):
+    """An incoming Signal message."""
+
+    source: str
+    timestamp: int
+    message: str = ""
+    attachments: list[str] = []
+    group_id: str | None = None
+    is_receipt: bool = False
+
+
+class SignalEnvelope(BaseModel):
+    """Raw envelope from signal-cli-rest-api."""
+
+    envelope: dict[str, Any]
+    account: str | None = None
+
+
+class InventoryItem(BaseModel):
+    """An item in the van inventory."""
+
+    name: str
+    quantity: float = 1
+    unit: str = "each"
+    category: str = ""
+    notes: str = ""
+
+
+class InventoryUpdate(BaseModel):
+    """Result of processing an inventory update."""
+
+    items: list[InventoryItem] = []
+    raw_response: str = ""
+    source_type: str = ""  # "receipt_photo" or "text_list"
+
+
+class BotConfig(BaseModel):
+    """Top-level bot configuration."""
+
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    signal_api_url: str
+    phone_number: str
+    inventory_api_url: str
+    ha_url: str | None = None
+    ha_token: str | None = None
+    engine: Engine
+    reconnect_delay: int = 5
+    max_reconnect_delay: int = 300
+    max_retries: int = 10
+    max_message_attempts: int = 3

python/signal_bot/signal_client.py

@@ -0,0 +1,141 @@
+"""Client for the signal-cli-rest-api."""
+
+from __future__ import annotations
+
+import json
+import logging
+from typing import TYPE_CHECKING, Any, Self
+
+import httpx
+import websockets.sync.client
+
+if TYPE_CHECKING:
+    from collections.abc import Generator
+
+from python.signal_bot.models import SignalMessage
+
+logger = logging.getLogger(__name__)
+
+
+def _parse_envelope(envelope: dict[str, Any]) -> SignalMessage | None:
+    """Parse a signal-cli envelope into a SignalMessage, or None if not a data message."""
+    data_message = envelope.get("dataMessage")
+    if not data_message:
+        return None
+
+    attachment_ids = [att["id"] for att in data_message.get("attachments", []) if "id" in att]
+
+    group_info = data_message.get("groupInfo")
+    group_id = group_info.get("groupId") if group_info else None
+
+    return SignalMessage(
+        source=envelope.get("source", ""),
+        timestamp=envelope.get("timestamp", 0),
+        message=data_message.get("message", "") or "",
+        attachments=attachment_ids,
+        group_id=group_id,
+    )
+
+
+class SignalClient:
+    """Communicate with signal-cli-rest-api.
+
+    Args:
+        base_url: URL of the signal-cli-rest-api (e.g. http://localhost:8989).
+        phone_number: The registered phone number to send/receive as.
+    """
+
+    def __init__(self, base_url: str, phone_number: str) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.phone_number = phone_number
+        self._client = httpx.Client(base_url=self.base_url, timeout=30)
+
+    def _ws_url(self) -> str:
+        """Build the WebSocket URL from the base HTTP URL."""
+        url = self.base_url.replace("http://", "ws://").replace("https://", "wss://")
+        return f"{url}/v1/receive/{self.phone_number}"
+
+    def listen(self) -> Generator[SignalMessage]:
+        """Connect via WebSocket and yield messages as they arrive."""
+        ws_url = self._ws_url()
+        logger.info(f"Connecting to WebSocket: {ws_url}")
+
+        with websockets.sync.client.connect(ws_url) as ws:
+            for raw in ws:
+                try:
+                    data = json.loads(raw)
+                    envelope = data.get("envelope", {})
+                    message = _parse_envelope(envelope)
+                    if message:
+                        yield message
+                except json.JSONDecodeError:
+                    logger.warning(f"Non-JSON WebSocket frame: {raw[:200]}")
+
+    def send(self, recipient: str, message: str) -> None:
+        """Send a text message."""
+        payload = {
+            "message": message,
+            "number": self.phone_number,
+            "recipients": [recipient],
+        }
+        response = self._client.post("/v2/send", json=payload)
+        response.raise_for_status()
+
+    def send_to_group(self, group_id: str, message: str) -> None:
+        """Send a message to a group."""
+        payload = {
+            "message": message,
+            "number": self.phone_number,
+            "recipients": [group_id],
+        }
+        response = self._client.post("/v2/send", json=payload)
+        response.raise_for_status()
+
+    def get_attachment(self, attachment_id: str) -> bytes:
+        """Download an attachment by ID."""
+        response = self._client.get(f"/v1/attachments/{attachment_id}")
+        response.raise_for_status()
+        return response.content
+
+    def get_identities(self) -> list[dict[str, Any]]:
+        """List known identities and their trust levels."""
+        response = self._client.get(f"/v1/identities/{self.phone_number}")
+        response.raise_for_status()
+        return response.json()
+
+    def get_safety_number(self, phone_number: str) -> str | None:
+        """Look up the safety number for a contact from signal-cli's local store."""
+        for identity in self.get_identities():
+            if identity.get("number") == phone_number:
+                return identity.get("safety_number", identity.get("fingerprint", ""))
+        return None
+
+    def trust_identity(self, number_to_trust: str, *, trust_all_known_keys: bool = False) -> None:
+        """Trust an identity (verify safety number)."""
+        payload: dict[str, Any] = {}
+        if trust_all_known_keys:
+            payload["trust_all_known_keys"] = True
+        response = self._client.put(
+            f"/v1/identities/{self.phone_number}/trust/{number_to_trust}",
+            json=payload,
+        )
+        response.raise_for_status()
+
+    def reply(self, message: SignalMessage, text: str) -> None:
+        """Reply to a message, routing to group or individual."""
+        if message.group_id:
+            self.send_to_group(message.group_id, text)
+        else:
+            self.send(message.source, text)
+
+    def __enter__(self) -> Self:
+        """Enter the context manager."""
+        return self
+
+    def __exit__(self, *args: object) -> None:
+        """Close the HTTP client on exit."""
+        self.close()
+
+    def close(self) -> None:
+        """Close the HTTP client."""
+        self._client.close()