fixed fomat issue

this code was moved to https://gitea.tmmworkshop.com/Nornsight/weave

.github/workflows/build_systems.yml

@@ -23,6 +23,6 @@ jobs:
     steps:
       - uses: actions/checkout@v4
       - name: Build default package
-        run: "nixos-rebuild build --flake ./#${{ matrix.system }}"
+        run: "nixos-rebuild build --accept-flake-config --flake ./#${{ 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

@@ -1,30 +0,0 @@
-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

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

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

.gitignore

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

.vscode/settings.json

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

AGENTS.md

@@ -1,12 +0,0 @@
-## 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

@@ -23,7 +23,10 @@
   boot = {
     tmp.useTmpfs = true;
     kernelPackages = lib.mkDefault pkgs.linuxPackages_6_12;
-    zfs.package = lib.mkDefault pkgs.zfs_2_4;
+    zfs = {
+      package = lib.mkDefault pkgs.zfs_2_4;
+      forceImportRoot = lib.mkDefault false;
+    };
   };
 
   hardware.enableRedistributableFirmware = true;
@@ -37,10 +40,17 @@
 
   nixpkgs = {
     overlays = builtins.attrValues outputs.overlays;
-    config.allowUnfree = true;
+    config = {
+      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

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

common/optional/monitoring-agent.nix

@@ -0,0 +1,256 @@
+{
+  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 = "TBRULKD-7DZPGGZ-F6LLB7J-MSO54AY-7KLPBIN-QOFK6PX-W2HBEWI-PHM2CQI"; # cspell:disable-line
+      phone.id = "JPVQKQW-CFXOJXT-Q5G5F3H-QIDHDRE-GKHPTQB-GXZUQSP-U7FR7F7-INP3AAH"; # 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 = "github:RichieCahill/dotfiles";
+    flake = "git+https://gitea.tmmworkshop.com/richie/dotfiles?ref=main";
     allowReboot = true;
     dates = "Sat *-*-* 06:00:00";
   };

docs/zfs_failed_root_import_recovry.md

@@ -0,0 +1,76 @@
+# 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": 1773979456,
-        "narHash": "sha256-9kBMJ5IvxqNlkkj/swmE8uK1Sc7TL/LIRUI958m7uBM=",
+        "lastModified": 1781150628,
+        "narHash": "sha256-b4mp8l3qWuSCyYYo9HSngDtcB3PpecYiOXjULrjwwlw=",
         "owner": "rycee",
         "repo": "nur-expressions",
-        "rev": "81e28f47ac18d9e89513929c77e711e657b64851",
+        "rev": "753319310f4673a2dabbfab87482187b40bf9bac",
         "type": "gitlab"
       },
       "original": {
@@ -29,11 +29,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1774007980,
-        "narHash": "sha256-FOnZjElEI8pqqCvB6K/1JRHTE8o4rer8driivTpq2uo=",
+        "lastModified": 1781189114,
+        "narHash": "sha256-5inaamLgUMWy+MOBE9ChF9QAF1o/74LFuHkI0W/9rqc=",
         "owner": "nix-community",
         "repo": "home-manager",
-        "rev": "9670de2921812bc4e0452f6e3efd8c859696c183",
+        "rev": "486595d2cf49cfcd649b58a284fa11ac0e34da22",
         "type": "github"
       },
       "original": {
@@ -43,12 +43,15 @@
       }
     },
     "nixos-hardware": {
+      "inputs": {
+        "nixpkgs": "nixpkgs"
+      },
       "locked": {
-        "lastModified": 1774018263,
-        "narHash": "sha256-HHYEwK1A22aSaxv2ibhMMkKvrDGKGlA/qObG4smrSqc=",
+        "lastModified": 1781168557,
+        "narHash": "sha256-LOnLQ2tpYF9gqIDDr3+j3DbpJJr/QCH6zPRT2GzEUOE=",
         "owner": "nixos",
         "repo": "nixos-hardware",
-        "rev": "2d4b4717b2534fad5c715968c1cece04a172b365",
+        "rev": "6358ff76821101c178e3ab4919a62799bfe3652e",
         "type": "github"
       },
       "original": {
@@ -60,27 +63,24 @@
     },
     "nixpkgs": {
       "locked": {
-        "lastModified": 1773821835,
-        "narHash": "sha256-TJ3lSQtW0E2JrznGVm8hOQGVpXjJyXY2guAxku2O9A4=",
-        "owner": "nixos",
-        "repo": "nixpkgs",
-        "rev": "b40629efe5d6ec48dd1efba650c797ddbd39ace0",
-        "type": "github"
+        "lastModified": 1767892417,
+        "narHash": "sha256-8bW3q88CEg2u4hSP66Vf4lpbLonHz7hqDNBMcCY7E9U=",
+        "rev": "3497aa5c9457a9d88d71fa93a4a8368816fbeeba",
+        "type": "tarball",
+        "url": "https://releases.nixos.org/nixos/unstable/nixos-26.05pre924538.3497aa5c9457/nixexprs.tar.xz"
       },
       "original": {
-        "owner": "nixos",
-        "ref": "nixos-unstable",
-        "repo": "nixpkgs",
-        "type": "github"
+        "type": "tarball",
+        "url": "https://channels.nixos.org/nixos-unstable/nixexprs.tar.xz"
       }
     },
     "nixpkgs-master": {
       "locked": {
-        "lastModified": 1774051532,
-        "narHash": "sha256-d3CGMweyYIcPuTj5BKq+1Lx4zwlgL31nVtN647tOZKo=",
+        "lastModified": 1781229721,
+        "narHash": "sha256-ORvqDbb/LYxiJljGIejapjkc/kJbVote2N1WSb9W45I=",
         "owner": "nixos",
         "repo": "nixpkgs",
-        "rev": "8620c0b5cc8fbe76502442181be1d0514bc3a1b7",
+        "rev": "173d0ad7a974f8543a9ab01d2271b2e290341b33",
         "type": "github"
       },
       "original": {
@@ -106,12 +106,28 @@
         "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",
+        "nixpkgs": "nixpkgs_2",
         "nixpkgs-master": "nixpkgs-master",
         "nixpkgs-stable": "nixpkgs-stable",
         "sops-nix": "sops-nix",
@@ -125,11 +141,11 @@
         ]
       },
       "locked": {
-        "lastModified": 1773889674,
-        "narHash": "sha256-+ycaiVAk3MEshJTg35cBTUa0MizGiS+bgpYw/f8ohkg=",
+        "lastModified": 1780547341,
+        "narHash": "sha256-Gq8KNx5A7hBB3uGJaj6eQfLDIz5YdLu92gqBcvHvoUo=",
         "owner": "Mic92",
         "repo": "sops-nix",
-        "rev": "29b6519f3e0780452bca0ac0be4584f04ac16cc5",
+        "rev": "9ed65852b6257fbeae4355bc24ecfea307ca759a",
         "type": "github"
       },
       "original": {

frontend/.gitignore

@@ -1,24 +0,0 @@
-# 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

@@ -17,16 +17,41 @@
 
   python-env = final: _prev: {
     my_python = final.python314.withPackages (
-      ps: with ps; [
+      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
-        confluent-kafka
+        beautifulsoup4
+        ebooklib
         fastapi
         fastapi-cli
         httpx
         mypy
+        numpy
         orjson
+        pgvector
         polars
         psycopg
         pydantic
@@ -39,9 +64,10 @@
         ruff
         scalene
         sqlalchemy
-        sqlalchemy
+        bm25s
         tenacity
         textual
+        tiktoken
         tinytuya
         typer
         websockets

pyproject.toml

@@ -3,7 +3,7 @@ name = "system_tools"
 version = "0.1.0"
 description = ""
 authors = [{ name = "Richie Cahill", email = "richie@tmmworkshop.com" }]
-requires-python = "~=3.13.0"
+requires-python = "~=3.14.0"
 readme = "README.md"
 license = "MIT"
 # these dependencies are a best effort and aren't guaranteed to work
@@ -12,20 +12,23 @@ dependencies = [
     "alembic",
     "apprise",
     "apscheduler",
+    "fastapi",
+    "fastapi-cli",
     "httpx",
-    "python-multipart",
     "polars",
     "psycopg[binary]",
     "pydantic",
-    "pyyaml",
+    "python-multipart",
     "sqlalchemy",
+    "tenacity",
+    "tinytuya",
     "typer",
     "websockets",
 ]
 
 [project.scripts]
 database = "python.database_cli:app"
-van-inventory = "python.van_inventory.main:serve"
+whisper-transcribe = "python.tools.whisper.transcribe:main"
 
 [dependency-groups]
 dev = [
@@ -40,7 +43,7 @@ dev = [
 
 [tool.ruff]
 
-target-version = "py313"
+target-version = "py314"
 
 line-length = 120
 
@@ -50,6 +53,7 @@ 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]
@@ -78,15 +82,10 @@ 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

@@ -1,50 +0,0 @@
-"""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

@@ -1,80 +0,0 @@
-"""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

@@ -3,7 +3,6 @@
 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

@@ -0,0 +1,187 @@
+"""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

@@ -0,0 +1,93 @@
+"""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

@@ -0,0 +1,200 @@
+"""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

@@ -0,0 +1,63 @@
+"""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

@@ -0,0 +1,54 @@
+"""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

@@ -1,100 +0,0 @@
-"""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

@@ -1,72 +0,0 @@
-"""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

@@ -1,19 +1,23 @@
 """FastAPI interface for Contact database."""
 
+from __future__ import annotations
+
 import logging
-from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
-from typing import Annotated
+from typing import TYPE_CHECKING, Annotated
 
 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
 
+if TYPE_CHECKING:
+    from collections.abc import AsyncIterator
+
 logger = logging.getLogger(__name__)
 
 

python/api/routers/contact.py

@@ -9,7 +9,7 @@ from pydantic import BaseModel
 from sqlalchemy import select
 from sqlalchemy.orm import selectinload
 
-from python.api.dependencies import DbSession
+from python.fastapi_tools.db import DbSession  # noqa: TC001 this is a FastAPI needed at runtime
 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.api.dependencies import DbSession
+from python.fastapi_tools.db import DbSession  # noqa: TC001 this is a FastAPI needed at runtime
 from python.orm.richie.contact import Contact, ContactRelationship, Need, RelationshipType
 
 TEMPLATES_DIR = Path(__file__).parent.parent / "templates"

python/data_science/__init__.py

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

python/data_science/bluesky_ids.py

@@ -1,104 +0,0 @@
-"""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

@@ -1,143 +0,0 @@
-"""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

@@ -1,203 +0,0 @@
-"""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

@@ -1,230 +0,0 @@
-"""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

@@ -1,247 +0,0 @@
-"""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

@@ -4,12 +4,10 @@ Usage:
     database <db_name> <command> [args...]
 
 Examples:
-    database van_inventory upgrade head
-    database van_inventory downgrade head-1
-    database van_inventory revision --autogenerate -m "add meals table"
-    database van_inventory check
     database richie check
     database richie upgrade head
+    database richie downgrade head-1
+    database richie revision --autogenerate -m "add meals table"
 """
 
 from __future__ import annotations
@@ -48,10 +46,7 @@ class DatabaseConfig:
 
     def alembic_config(self) -> Config:
         """Build an alembic Config for this database."""
-        # Runtime import needed — Config is in TYPE_CHECKING for the return type annotation
-        from alembic.config import Config as AlembicConfig  # noqa: PLC0415
-
-        cfg = AlembicConfig()
+        cfg = Config()
         cfg.set_main_option("script_location", self.script_location)
         cfg.set_main_option("file_template", self.file_template)
         cfg.set_main_option("prepend_sys_path", ".")
@@ -76,27 +71,6 @@ DATABASES: dict[str, DatabaseConfig] = {
         base_class_name="RichieBase",
         models_module="python.orm.richie",
     ),
-    "van_inventory": DatabaseConfig(
-        env_prefix="VAN_INVENTORY",
-        version_location="python/alembic/van_inventory/versions",
-        base_module="python.orm.van_inventory.base",
-        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

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

python/ebook_search/answer.py

@@ -0,0 +1,57 @@
+"""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

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

python/ebook_search/api/bm25_tasks.py

@@ -0,0 +1,60 @@
+"""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

@@ -0,0 +1,79 @@
+"""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

@@ -0,0 +1,11 @@
+"""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

@@ -0,0 +1,107 @@
+"""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

@@ -0,0 +1,57 @@
+"""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

@@ -0,0 +1,58 @@
+"""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

@@ -0,0 +1,140 @@
+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

@@ -0,0 +1,57 @@
+<!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

@@ -0,0 +1,32 @@
+<!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

@@ -0,0 +1,31 @@
+<!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

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

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

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

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

@@ -0,0 +1,74 @@
+<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

@@ -0,0 +1,30 @@
+<!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

@@ -0,0 +1,13 @@
+"""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

@@ -0,0 +1,281 @@
+"""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

@@ -0,0 +1,117 @@
+"""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

@@ -0,0 +1,170 @@
+"""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

@@ -0,0 +1,95 @@
+"""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

@@ -0,0 +1,190 @@
+"""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

@@ -0,0 +1,143 @@
+"""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

@@ -0,0 +1,129 @@
+"""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

@@ -0,0 +1,383 @@
+"""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

@@ -0,0 +1,36 @@
+"""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

@@ -0,0 +1,6 @@
+"""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/fastapi_tools/db.py

@@ -1,11 +1,15 @@
 """FastAPI dependencies."""
 
-from collections.abc import Iterator
-from typing import Annotated
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Annotated
 
 from fastapi import Depends, Request
 from sqlalchemy.orm import Session
 
+if TYPE_CHECKING:
+    from collections.abc import Iterator
+
 
 def get_db(request: Request) -> Iterator[Session]:
     """Get database session from app state."""

python/fastapi_tools/zstd_middleware.py

@@ -1,10 +1,14 @@
-"""Middleware for the FastAPI application."""
+"""Zstd response compression middleware."""
 
 from compression import zstd
+from typing import TYPE_CHECKING
+
 from starlette.middleware.base import BaseHTTPMiddleware, RequestResponseEndpoint
-from starlette.requests import Request
 from starlette.responses import Response
 
+if TYPE_CHECKING:
+    from starlette.requests import Request
+
 MINIMUM_RESPONSE_SIZE = 500
 
 

python/gitea.py

@@ -0,0 +1,347 @@
+"""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

@@ -0,0 +1,148 @@
+"""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/heater/main.py

@@ -1,9 +1,10 @@
 """FastAPI heater control service."""
 
+from __future__ import annotations
+
 import logging
-from collections.abc import AsyncIterator
 from contextlib import asynccontextmanager
-from typing import Annotated
+from typing import TYPE_CHECKING, Annotated
 
 import typer
 import uvicorn
@@ -13,6 +14,9 @@ from python.common import configure_logger
 from python.heater.controller import HeaterController
 from python.heater.models import ActionResult, DeviceConfig, HeaterStatus
 
+if TYPE_CHECKING:
+    from collections.abc import AsyncIterator
+
 logger = logging.getLogger(__name__)
 
 

python/installer/__main__.py

@@ -262,6 +262,7 @@ def installer(
             ):
                 run(command, check=True, stdin=test.stdout)
 
+    # Fixed mount point for the new system; the installer runs as root on a fresh disk
     mnt_dir = "/tmp/nix_install"  # noqa: S108
 
     Path(mnt_dir).mkdir(parents=True, exist_ok=True)

python/installer/old_installer.py

@@ -16,9 +16,13 @@ from typing import TYPE_CHECKING
 if TYPE_CHECKING:
     from collections.abc import Sequence
 
+logger = logging.getLogger(__name__)
+ESCAPE_KEY = 27
+
 
 def configure_logger(level: str = "INFO") -> None:
     """Configure the logger.
+
     Args:
         level (str, optional): The logging level. Defaults to "INFO".
     """
@@ -32,15 +36,17 @@ def configure_logger(level: str = "INFO") -> None:
 
 def bash_wrapper(command: str) -> str:
     """Execute a bash command and capture the output.
+
     Args:
         command (str): The bash command to be executed.
+
     Returns:
         Tuple[str, int]: A tuple containing the output of the command (stdout) as a string,
         the error output (stderr) as a string (optional), and the return code as an integer.
     """
-    logging.debug(f"running {command=}")
+    logger.debug(f"running {command=}")
     # This is a acceptable risk
-    process = Popen(command.split(), stdout=PIPE, stderr=PIPE)  # noqa: S603
+    process = Popen(command.split(), stdout=PIPE, stderr=PIPE)
     output, _ = process.communicate()
     if process.returncode != 0:
         error = f"Failed to run command {command=} return code {process.returncode=}"
@@ -51,6 +57,7 @@ def bash_wrapper(command: str) -> str:
 
 def partition_disk(disk: str, swap_size: int, reserve: int = 0) -> None:
     """Partition a disk.
+
     Args:
         disk (str): The disk to partition.
         swap_size (int): The size of the swap partition in GB.
@@ -58,7 +65,7 @@ def partition_disk(disk: str, swap_size: int, reserve: int = 0) -> None:
         reserve (int, optional): The size of the reserve partition in GB. Defaults to 0.
             minimum value is 0.
     """
-    logging.info(f"partitioning {disk=}")
+    logger.info(f"partitioning {disk=}")
     swap_size = max(swap_size, 1)
     reserve = max(reserve, 0)
 
@@ -66,16 +73,16 @@ def partition_disk(disk: str, swap_size: int, reserve: int = 0) -> None:
 
     if reserve > 0:
         msg = f"Creating swap partition on {disk=} with size {swap_size=}GiB and reserve {reserve=}GiB"
-        logging.info(msg)
+        logger.info(msg)
 
         swap_start = swap_size + reserve
         swap_partition = f"mkpart swap -{swap_start}GiB -{reserve}GiB "
     else:
-        logging.info(f"Creating swap partition on {disk=} with size {swap_size=}GiB")
+        logger.info(f"Creating swap partition on {disk=} with size {swap_size=}GiB")
         swap_start = swap_size
         swap_partition = f"mkpart swap -{swap_start}GiB 100% "
 
-    logging.debug(f"{swap_partition=}")
+    logger.debug(f"{swap_partition=}")
 
     create_partitions = (
         f"parted --script --align=optimal {disk} -- "
@@ -87,13 +94,14 @@ def partition_disk(disk: str, swap_size: int, reserve: int = 0) -> None:
     )
     bash_wrapper(create_partitions)
 
-    logging.info(f"{disk=} successfully partitioned")
+    logger.info(f"{disk=} successfully partitioned")
 
 
 def create_zfs_pool(pool_disks: Sequence[str], mnt_dir: str) -> None:
     """Create a ZFS pool.
+
     Args:
-        disks (Sequence[str]): A tuple of disks to use for the pool.
+        pool_disks (Sequence[str]): A tuple of disks to use for the pool.
         mnt_dir (str): The mount directory.
     """
     if len(pool_disks) <= 0:
@@ -125,13 +133,12 @@ def create_zfs_pool(pool_disks: Sequence[str], mnt_dir: str) -> None:
     bash_wrapper(zpool_create)
     zpools = bash_wrapper("zpool list -o name")
     if "root_pool" not in zpools.splitlines():
-        logging.critical("Failed to create root_pool")
+        logger.critical("Failed to create root_pool")
         sys.exit(1)
 
 
 def create_zfs_datasets() -> None:
     """Create ZFS datasets."""
-
     bash_wrapper("zfs create -o canmount=noauto -o reservation=10G root_pool/root")
     bash_wrapper("zfs create root_pool/home")
     bash_wrapper("zfs create root_pool/var -o reservation=1G")
@@ -146,7 +153,7 @@ def create_zfs_datasets() -> None:
     }
     missing_datasets = expected_datasets.difference(datasets.splitlines())
     if missing_datasets:
-        logging.critical(f"Failed to create pools {missing_datasets}")
+        logger.critical(f"Failed to create pools {missing_datasets}")
         sys.exit(1)
 
 
@@ -159,6 +166,8 @@ def get_cpu_manufacturer() -> str:
     for line in output.splitlines():
         if "vendor_id" in line:
             return id_vendor[line.split(": ")[1].strip()]
+    error = "Failed to get CPU manufacturer"
+    raise RuntimeError(error)
 
 
 def get_boot_drive_id(disk: str) -> str:
@@ -167,9 +176,8 @@ def get_boot_drive_id(disk: str) -> str:
     return output.splitlines()[1]
 
 
-def create_nix_hardware_file(mnt_dir: str, disks: Sequence[str], encrypt: bool) -> None:
+def create_nix_hardware_file(mnt_dir: str, disks: Sequence[str], *, encrypt: bool) -> None:
     """Create a NixOS hardware file."""
-
     cpu_manufacturer = get_cpu_manufacturer()
 
     devices = ""
@@ -193,7 +201,15 @@ def create_nix_hardware_file(mnt_dir: str, disks: Sequence[str], encrypt: bool)
         '  imports = [ (modulesPath + "/installer/scan/not-detected.nix") ];\n\n'
         "  boot = {\n"
         "    initrd = {\n"
-        '      availableKernelModules = [ \n        "ahci"\n        "ehci_pci"\n        "nvme"\n        "sd_mod"\n        "usb_storage"\n        "usbhid"\n        "xhci_pci"\n      ];\n'
+        "      availableKernelModules = [ \n"
+        '        "ahci"\n'
+        '        "ehci_pci"\n'
+        '        "nvme"\n'
+        '        "sd_mod"\n'
+        '        "usb_storage"\n'
+        '        "usbhid"\n'
+        '        "xhci_pci"\n'
+        "      ];\n"
         "      kernelModules = [ ];\n"
         f" {devices}"
         "    };\n"
@@ -207,11 +223,18 @@ def create_nix_hardware_file(mnt_dir: str, disks: Sequence[str], encrypt: bool)
         '    "/nix" = {\n      device = "root_pool/nix";\n      fsType = "zfs";\n    };\n\n'
         '    "/boot" = {\n'
         f'      device = "/dev/disk/by-uuid/{get_boot_drive_id(disks[0])}";\n'
-        '      fsType = "vfat";\n      options = [\n        "fmask=0077"\n        "dmask=0077"\n      ];\n    };\n  };\n\n'
+        '      fsType = "vfat";\n'
+        "      options = [\n"
+        '        "fmask=0077"\n'
+        '        "dmask=0077"\n'
+        "      ];\n"
+        "    };\n"
+        "  };\n\n"
         "  swapDevices = [ ];\n\n"
         "  networking.useDHCP = lib.mkDefault true;\n\n"
         '  nixpkgs.hostPlatform = lib.mkDefault "x86_64-linux";\n'
-        f"  hardware.cpu.{cpu_manufacturer}.updateMicrocode = lib.mkDefault config.hardware.enableRedistributableFirmware;\n"
+        f"  hardware.cpu.{cpu_manufacturer}.updateMicrocode = lib.mkDefault "
+        "config.hardware.enableRedistributableFirmware;\n"
         f'  networking.hostId = "{host_id}";\n'
         "}\n"
     )
@@ -219,7 +242,7 @@ def create_nix_hardware_file(mnt_dir: str, disks: Sequence[str], encrypt: bool)
     Path(f"{mnt_dir}/etc/nixos/hardware-configuration.nix").write_text(nix_hardware)
 
 
-def install_nixos(mnt_dir: str, disks: Sequence[str], encrypt: bool) -> None:
+def install_nixos(mnt_dir: str, disks: Sequence[str], *, encrypt: bool) -> None:
     """Install NixOS."""
     bash_wrapper(f"mount -o X-mount.mkdir -t zfs root_pool/root {mnt_dir}")
     bash_wrapper(f"mount -o X-mount.mkdir -t zfs root_pool/home {mnt_dir}/home")
@@ -230,14 +253,16 @@ def install_nixos(mnt_dir: str, disks: Sequence[str], encrypt: bool) -> None:
         bash_wrapper(f"mkfs.vfat -n EFI {disk}-part1")
 
     # set up mirroring afterwards if more than one disk
-    boot_partition = f"mount -t vfat -o fmask=0077,dmask=0077,iocharset=iso8859-1,X-mount.mkdir {disks[0]}-part1 {mnt_dir}/boot"
+    boot_partition = (
+        f"mount -t vfat -o fmask=0077,dmask=0077,iocharset=iso8859-1,X-mount.mkdir {disks[0]}-part1 {mnt_dir}/boot"
+    )
     bash_wrapper(boot_partition)
 
     bash_wrapper(f"nixos-generate-config --root {mnt_dir}")
 
-    create_nix_hardware_file(mnt_dir, disks, encrypt)
+    create_nix_hardware_file(mnt_dir, disks, encrypt=encrypt)
 
-    run(("nixos-install", "--root", mnt_dir), check=True)  # noqa: S603
+    run(("nixos-install", "--root", mnt_dir), check=True)
 
 
 def installer(
@@ -247,27 +272,38 @@ def installer(
     encrypt_key: str | None,
 ) -> None:
     """Main."""
-    logging.info("Starting installation")
+    logger.info("Starting installation")
 
     for disk in disks:
         partition_disk(disk, swap_size, reserve)
 
         if encrypt_key:
             sleep(1)
-            for command in (
-                f'printf "{encrypt_key}" | cryptsetup luksFormat --type luks2 {disk}-part2 -',
-                f'printf "{encrypt_key}" | cryptsetup luksOpen {disk}-part2 luks-root-pool-{disk.split("/")[-1]}-part2 -',
-            ):
-                run(command, shell=True, check=True)
+            key_input = encrypt_key.encode()
+            run(
+                ("cryptsetup", "luksFormat", "--type", "luks2", f"{disk}-part2", "-"),
+                input=key_input,
+                check=True,
+            )
+            run(
+                (
+                    "cryptsetup",
+                    "luksOpen",
+                    f"{disk}-part2",
+                    f"luks-root-pool-{disk.split('/')[-1]}-part2",
+                    "-",
+                ),
+                input=key_input,
+                check=True,
+            )
 
+    # Fixed mount point for the new system; the installer runs as root on a fresh disk
     mnt_dir = "/tmp/nix_install"  # noqa: S108
 
     Path(mnt_dir).mkdir(parents=True, exist_ok=True)
 
     if encrypt_key:
-        pool_disks = [
-            f"/dev/mapper/luks-root-pool-{disk.split('/')[-1]}-part2" for disk in disks
-        ]
+        pool_disks = [f"/dev/mapper/luks-root-pool-{disk.split('/')[-1]}-part2" for disk in disks]
     else:
         pool_disks = [f"{disk}-part2" for disk in disks]
 
@@ -275,57 +311,73 @@ def installer(
 
     create_zfs_datasets()
 
-    install_nixos(mnt_dir, disks, encrypt_key)
+    install_nixos(mnt_dir, disks, encrypt=bool(encrypt_key))
 
-    logging.info("Installation complete")
+    logger.info("Installation complete")
 
 
 class Cursor:
-    def __init__(self):
+    """Track cursor position and constrain movement to screen bounds."""
+
+    def __init__(self) -> None:
+        """Initialize cursor position and screen dimensions."""
         self.x_position = 0
         self.y_position = 0
         self.height = 0
         self.width = 0
 
-    def set_height(self, height: int):
+    def set_height(self, height: int) -> None:
+        """Set the maximum screen height."""
         self.height = height
 
-    def set_width(self, width: int):
+    def set_width(self, width: int) -> None:
+        """Set the maximum screen width."""
         self.width = width
 
     def x_bounce_check(self, cursor: int) -> int:
+        """Clamp an x position to the screen width."""
         cursor = max(0, cursor)
         return min(self.width - 1, cursor)
 
     def y_bounce_check(self, cursor: int) -> int:
+        """Clamp a y position to the screen height."""
         cursor = max(0, cursor)
         return min(self.height - 1, cursor)
 
-    def set_x(self, x: int):
+    def set_x(self, x: int) -> None:
+        """Set the cursor x position."""
         self.x_position = self.x_bounce_check(x)
 
-    def set_y(self, y: int):
+    def set_y(self, y: int) -> None:
+        """Set the cursor y position."""
         self.y_position = self.y_bounce_check(y)
 
     def get_x(self) -> int:
+        """Get the cursor x position."""
         return self.x_position
 
     def get_y(self) -> int:
+        """Get the cursor y position."""
         return self.y_position
 
-    def move_up(self):
+    def move_up(self) -> None:
+        """Move the cursor up one row."""
         self.set_y(self.y_position - 1)
 
-    def move_down(self):
+    def move_down(self) -> None:
+        """Move the cursor down one row."""
         self.set_y(self.y_position + 1)
 
-    def move_left(self):
+    def move_left(self) -> None:
+        """Move the cursor left one column."""
         self.set_x(self.x_position - 1)
 
-    def move_right(self):
+    def move_right(self) -> None:
+        """Move the cursor right one column."""
         self.set_x(self.x_position + 1)
 
     def navigation(self, key: int) -> None:
+        """Move the cursor for a curses navigation key."""
         action = {
             curses.KEY_DOWN: self.move_down,
             curses.KEY_UP: self.move_up,
@@ -339,7 +391,8 @@ class Cursor:
 class State:
     """State class to store the state of the program."""
 
-    def __init__(self):
+    def __init__(self) -> None:
+        """Initialize installer menu state."""
         self.key = 0
         self.cursor = Cursor()
 
@@ -357,11 +410,9 @@ class State:
 
 
 def get_device(raw_device: str) -> dict[str, str]:
+    """Parse an lsblk key-value device row."""
     raw_device_components = raw_device.split(" ")
-    return {
-        thing.split("=")[0].lower(): thing.split("=")[1].strip('"')
-        for thing in raw_device_components
-    }
+    return {thing.split("=")[0].lower(): thing.split("=")[1].strip('"') for thing in raw_device_components}
 
 
 def get_devices() -> list[dict[str, str]]:
@@ -373,6 +424,7 @@ def get_devices() -> list[dict[str, str]]:
 
 def get_device_id_mapping() -> dict[str, set[str]]:
     """Get a list of device ids.
+
     Returns:
         list[str]: the list of device ids
     """
@@ -387,9 +439,8 @@ def get_device_id_mapping() -> dict[str, set[str]]:
     return device_id_mapping
 
 
-def calculate_device_menu_padding(
-    devices: list[dict[str, str]], column: str, padding: int = 0
-) -> int:
+def calculate_device_menu_padding(devices: list[dict[str, str]], column: str, padding: int = 0) -> int:
+    """Calculate the width needed for a device menu column."""
     return max(len(device[column]) for device in devices) + padding
 
 
@@ -401,6 +452,7 @@ def draw_device_ids(
     menu_width: list[int],
     device_ids: set[str],
 ) -> tuple[State, int]:
+    """Draw selectable device IDs for a device row."""
     for device_id in sorted(device_ids):
         row_number = row_number + 1
         if row_number == state.cursor.get_y() and state.cursor.get_x() in menu_width:
@@ -429,8 +481,9 @@ def draw_device_menu(
     state: State,
     menu_start_y: int = 0,
     menu_start_x: int = 0,
-) -> State:
-    """draw the device menu and handle user input
+) -> tuple[State, int]:
+    """Draw the device menu and handle user input.
+
     Args:
         std_screen (curses.window): the curses window to draw on
         devices (list[dict[str, str]]): the list of devices to draw
@@ -438,6 +491,7 @@ def draw_device_menu(
         state (State): the state object to update
         menu_start_y (int, optional): the y position to start drawing the menu. Defaults to 0.
         menu_start_x (int, optional): the x position to start drawing the menu. Defaults to 0.
+
     Returns:
         State: the updated state object
     """
@@ -448,7 +502,9 @@ def draw_device_menu(
     type_padding = calculate_device_menu_padding(devices, "type", padding)
     mountpoints_padding = calculate_device_menu_padding(devices, "mountpoints", padding)
 
-    device_header = f"{'Name':{name_padding}}{'Size':{size_padding}}{'Type':{type_padding}}{'Mountpoints':{mountpoints_padding}}"
+    device_header = (
+        f"{'Name':{name_padding}}{'Size':{size_padding}}{'Type':{type_padding}}{'Mountpoints':{mountpoints_padding}}"
+    )
 
     menu_width = range(menu_start_x, len(device_header) + menu_start_x)
 
@@ -481,8 +537,9 @@ def draw_device_menu(
 
 
 def debug_menu(std_screen: curses.window, key: int) -> None:
+    """Draw debug information for the current curses screen."""
     height, width = std_screen.getmaxyx()
-    width_height = "Width: {}, Height: {}".format(width, height)
+    width_height = f"Width: {width}, Height: {height}"
     std_screen.addstr(height - 4, 0, width_height, curses.color_pair(5))
 
     key_pressed = f"Last key pressed: {key}"[: width - 1]
@@ -490,7 +547,7 @@ def debug_menu(std_screen: curses.window, key: int) -> None:
         key_pressed = "No key press detected..."[: width - 1]
     std_screen.addstr(height - 3, 0, key_pressed)
 
-    for i in range(0, 8):
+    for i in range(8):
         std_screen.addstr(height - 2, i * 3, f"{i}██", curses.color_pair(i))
 
 
@@ -500,12 +557,11 @@ def status_bar(
     width: int,
     height: int,
 ) -> None:
+    """Draw the footer status bar."""
     std_screen.attron(curses.A_REVERSE)
     std_screen.attron(curses.color_pair(3))
 
-    status_bar = (
-        f"Press 'q' to exit | STATUS BAR | Pos: {cursor.get_x()}, {cursor.get_y()}"
-    )
+    status_bar = f"Press 'q' to exit | STATUS BAR | Pos: {cursor.get_x()}, {cursor.get_y()}"
     std_screen.addstr(height - 1, 0, status_bar)
     std_screen.addstr(height - 1, len(status_bar), " " * (width - len(status_bar) - 1))
 
@@ -514,13 +570,15 @@ def status_bar(
 
 
 def set_color() -> None:
+    """Initialize curses color pairs."""
     curses.start_color()
     curses.use_default_colors()
-    for i in range(0, curses.COLORS):
+    for i in range(curses.COLORS):
         curses.init_pair(i + 1, i, -1)
 
 
 def get_text_input(std_screen: curses.window, prompt: str, y: int, x: int) -> str:
+    """Read text input from a curses screen."""
     curses.echo()
     std_screen.addstr(y, x, prompt)
     input_str = ""
@@ -528,10 +586,10 @@ def get_text_input(std_screen: curses.window, prompt: str, y: int, x: int) -> st
         key = std_screen.getch()
         if key == ord("\n"):
             break
-        elif key == 27:  # ESC key
+        if key == ESCAPE_KEY:
             input_str = ""
             break
-        elif key in (curses.KEY_BACKSPACE, ord("\b"), 127):
+        if key in (curses.KEY_BACKSPACE, ord("\b"), 127):
             input_str = input_str[:-1]
             std_screen.addstr(y, x + len(prompt), input_str + " ")
         else:
@@ -546,6 +604,7 @@ def swap_size_input(
     state: State,
     swap_offset: int,
 ) -> State:
+    """Handle swap size input."""
     swap_size_text = "Swap size (GB): "
     std_screen.addstr(swap_offset, 0, f"{swap_size_text}{state.swap_size}")
     if state.key == ord("\n") and state.cursor.get_y() == swap_offset:
@@ -557,9 +616,7 @@ def swap_size_input(
             state.swap_size = int(swap_size_str)
             state.show_swap_input = False
         except ValueError:
-            std_screen.addstr(
-                swap_offset, 0, "Invalid input. Press any key to continue."
-            )
+            std_screen.addstr(swap_offset, 0, "Invalid input. Press any key to continue.")
             std_screen.getch()
             state.show_swap_input = False
 
@@ -571,22 +628,19 @@ def reserve_size_input(
     state: State,
     reserve_offset: int,
 ) -> State:
+    """Handle reserve size input."""
     reserve_size_text = "reserve size (GB): "
     std_screen.addstr(reserve_offset, 0, f"{reserve_size_text}{state.reserve_size}")
     if state.key == ord("\n") and state.cursor.get_y() == reserve_offset:
         state.show_reserve_input = True
 
     if state.show_reserve_input:
-        reserve_size_str = get_text_input(
-            std_screen, reserve_size_text, reserve_offset, 0
-        )
+        reserve_size_str = get_text_input(std_screen, reserve_size_text, reserve_offset, 0)
         try:
             state.reserve_size = int(reserve_size_str)
             state.show_reserve_input = False
         except ValueError:
-            std_screen.addstr(
-                reserve_offset, 0, "Invalid input. Press any key to continue."
-            )
+            std_screen.addstr(reserve_offset, 0, "Invalid input. Press any key to continue.")
             std_screen.getch()
             state.show_reserve_input = False
 
@@ -594,9 +648,11 @@ def reserve_size_input(
 
 
 def draw_menu(std_screen: curses.window) -> State:
-    """draw the menu and handle user input
+    """Draw the menu and handle user input.
+
     Args:
         std_screen (curses.window): the curses window to draw on
+
     Returns:
         State: the state object
     """
@@ -656,17 +712,18 @@ def draw_menu(std_screen: curses.window) -> State:
 
 
 def main() -> None:
+    """Run the installer menu and start installation."""
     configure_logger("DEBUG")
 
     state = curses.wrapper(draw_menu)
 
     encrypt_key = getenv("ENCRYPT_KEY")
 
-    logging.info("installing_nixos")
-    logging.info(f"disks: {state.selected_device_ids}")
-    logging.info(f"swap_size: {state.swap_size}")
-    logging.info(f"reserve: {state.reserve_size}")
-    logging.info(f"encrypted: {bool(encrypt_key)}")
+    logger.info("installing_nixos")
+    logger.info(f"disks: {state.selected_device_ids}")
+    logger.info(f"swap_size: {state.swap_size}")
+    logger.info(f"reserve: {state.reserve_size}")
+    logger.info(f"encrypted: {bool(encrypt_key)}")
 
     sleep(3)
 

python/orm/__init__.py

@@ -1,13 +1,7 @@
 """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

@@ -31,8 +31,24 @@ 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(*, name: str = "POSTGRES", pool_pre_ping: bool = True) -> Engine:
-    """Create a SQLAlchemy engine from environment variables."""
+def get_postgres_engine(
+    *,
+    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(
@@ -44,8 +60,14 @@ def get_postgres_engine(*, name: str = "POSTGRES", pool_pre_ping: bool = True) -
         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

@@ -1,11 +0,0 @@
-"""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

@@ -1,52 +0,0 @@
-"""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

@@ -1,10 +0,0 @@
-"""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

@@ -1,11 +0,0 @@
-"""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

@@ -1,33 +0,0 @@
-"""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

@@ -1,17 +0,0 @@
-"""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

@@ -1,71 +0,0 @@
-"""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

@@ -1,13 +0,0 @@
-"""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,
@@ -11,19 +11,34 @@ from python.orm.richie.contact import (
     Need,
     RelationshipType,
 )
+from python.orm.richie.ebook import (
+    EbookChapter,
+    EbookChunk,
+    EbookChunkEmbedding1024,
+    EbookChunkEmbedding2560,
+    EbookChunkEmbedding4096,
+    EbookEmbeddingModel,
+    EbookSource,
+)
 
 __all__ = [
-    "Bill",
+    "Audiobook",
+    "AudiobookAuthor",
+    "AudiobookSeries",
     "Contact",
     "ContactNeed",
     "ContactRelationship",
-    "Legislator",
+    "EbookChapter",
+    "EbookChunk",
+    "EbookChunkEmbedding1024",
+    "EbookChunkEmbedding2560",
+    "EbookChunkEmbedding4096",
+    "EbookEmbeddingModel",
+    "EbookSource",
     "Need",
     "RelationshipType",
     "RichieBase",
     "TableBase",
     "TableBaseBig",
     "TableBaseSmall",
-    "Vote",
-    "VoteRecord",
 ]

python/orm/richie/audiobook.py

@@ -0,0 +1,55 @@
+"""Audiobook catalog models."""
+
+from __future__ import annotations
+
+from sqlalchemy import ForeignKey, 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]
+
+    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]
+    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]
+    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

@@ -1,150 +0,0 @@
-"""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

@@ -0,0 +1,138 @@
+"""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

@@ -1,16 +0,0 @@
-"""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

@@ -1,52 +0,0 @@
-"""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

@@ -1,62 +0,0 @@
-"""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/orm/van_inventory/__init__.py

@@ -1 +0,0 @@
-"""Van inventory database ORM exports."""

python/orm/van_inventory/base.py

@@ -1,39 +0,0 @@
-"""Van inventory database ORM base."""
-
-from __future__ import annotations
-
-from datetime import datetime
-
-from sqlalchemy import 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 VanInventoryBase(DeclarativeBase):
-    """Base class for van_inventory database ORM models."""
-
-    schema_name = "main"
-
-    metadata = MetaData(
-        schema=schema_name,
-        naming_convention=NAMING_CONVENTION,
-    )
-
-
-class VanTableBase(AbstractConcreteBase, VanInventoryBase):
-    """Abstract concrete base for van_inventory tables with IDs and timestamps."""
-
-    __abstract__ = True
-
-    id: Mapped[int] = mapped_column(primary_key=True)
-    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(),
-    )

python/orm/van_inventory/models.py

@@ -1,46 +0,0 @@
-"""Van inventory ORM models."""
-
-from __future__ import annotations
-
-from sqlalchemy import ForeignKey, UniqueConstraint
-from sqlalchemy.orm import Mapped, mapped_column, relationship
-
-from python.orm.van_inventory.base import VanTableBase
-
-
-class Item(VanTableBase):
-    """A food item in the van."""
-
-    __tablename__ = "items"
-
-    name: Mapped[str] = mapped_column(unique=True)
-    quantity: Mapped[float] = mapped_column(default=0)
-    unit: Mapped[str]
-    category: Mapped[str | None]
-
-    meal_ingredients: Mapped[list[MealIngredient]] = relationship(back_populates="item")
-
-
-class Meal(VanTableBase):
-    """A meal that can be made from items in the van."""
-
-    __tablename__ = "meals"
-
-    name: Mapped[str] = mapped_column(unique=True)
-    instructions: Mapped[str | None]
-
-    ingredients: Mapped[list[MealIngredient]] = relationship(back_populates="meal")
-
-
-class MealIngredient(VanTableBase):
-    """Links a meal to the items it requires, with quantities."""
-
-    __tablename__ = "meal_ingredients"
-    __table_args__ = (UniqueConstraint("meal_id", "item_id"),)
-
-    meal_id: Mapped[int] = mapped_column(ForeignKey("meals.id"))
-    item_id: Mapped[int] = mapped_column(ForeignKey("items.id"))
-    quantity_needed: Mapped[float]
-
-    meal: Mapped[Meal] = relationship(back_populates="ingredients")
-    item: Mapped[Item] = relationship(back_populates="meal_ingredients")

python/signal_bot/__init__.py

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

python/signal_bot/commands/__init__.py

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

python/signal_bot/commands/inventory.py

@@ -1,137 +0,0 @@
-"""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)