Commit Graph
13 Commits
Author SHA1 Message Date
Cameron CordesandClaude Opus 5.5 431c3a7492 Every error response in the { error, code, details? } format (step 2)
Moves every remaining hand-built error response onto ApiError: ~300
sites across faces, image, video, files, memories, versions,
duplicates, favorites, libraries, auth, clip/unified search, prefs,
reels, tts, insight chat, persona chat, knowledge and personas.

- 500s: the body was the error's text (anyhow / diesel / {:?}); now
  ApiError::internal logs it and sends a generic message.
- Each 4xx/502/503 has a stable code and a message written for users;
  statuses are unchanged. Shared helpers per module (faces_unavailable,
  person_not_found, unknown_library, insight_not_found, ...).
- Pre-format top-level fields kept where clients read them: upload 409
  duplicate_of / content_hash / library_name.
- PersonaChatError converts into ApiError in one place.
- Multipart upload errors use the format (error::multipart_config).
- Guard test: no non-test code builds HttpResponse::<error>() by hand.

Closes #202

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-11-01 13:29:13 -05:00
Cameron CordesandClaude Opus 5.5 aa3536afee refactor(ai): read LLM settings from LlmConfig instead of env
Every LLM env reader now goes through ai::config::llm_config():
build_ollama / build_llamacpp / build_openrouter take config sections
(OPENROUTER_API_KEY is still read from env), and the backend switch,
embedding dim + prefixes, Ollama / llama.cpp / TTS timeouts, TTS voice and
ref length, agentic caps, chat turn timeout and the unified-search model
read their sections. LocalLlm::from_env -> from_config; the
test_daily_summary and populate_knowledge bins take Ollama defaults from
the config. env_max_iterations / env_default_num_ctx are renamed to
max_chat_iterations / default_num_ctx.

The picker still uses picker.include (= LLAMA_SWAP_ALLOWED_MODELS) until
discovery lands. Legacy env vars keep working through the config's
override layer; checked against the deployed .env, which resolves to the
same values. The LLM_BACKEND parsing tests move to ai::config.

llm.example.toml now leaves the embed prefixes empty: copying the
nomic prefixes onto a corpus embedded without them breaks search.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-26 17:30:24 -04:00
Cameron CordesandClaude Opus 5.5 e029c81274 fix(persona-chat): review fixes before merge
- Thread tools are bound server-side to the chat's own thread. The model
  used to pass contact_id, so practice mode could read any conversation it
  named; a model-supplied contact_id is now only checked, never trusted, and
  the prompts no longer hand it one.
- Practice chats need no persona. They're stored under PRACTICE_PERSONA_ID
  and run with an inert stand-in, so deleting or editing personas can't hide
  or break them. persona_id is optional on create for as_contact.
- The per-thread list filters in SQL (list_persona_chats_for_contact, served
  by idx_persona_chat_anchor_contact) instead of decoding every transcript.
- fetch_mms_image checks the content type and a 20 MB cap before reading
  the body, so a video attachment isn't downloaded in full.
- get_photos_near_time unions tags over every path sharing the content, per
  the multi-library model.
- look_at_photo only opens indexed photos, so an excluded folder can't be
  read by guessing a path.
- One date parser: get_photos_near_time uses date_info::parse_center.
- Practice prompt source rewrapped.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-20 19:38:08 -04:00
Cameron CordesandClaude Opus 5.5 7215c1bdfe fix(persona-chat): don't offer describe_photo in persona chats
describe_photo describes the file chat's photo. Persona chats have no photo,
so a vision-capable model was offered a tool that could only answer "No image
available". Persona chats now build their catalog with the vision gate off;
the thread tools still cover looking at images there.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-18 20:17:03 -04:00
Cameron CordesandClaude Opus 5.5 3f1bf42f1c feat(persona-chat): practice mode — play the contact
An anchored conversation now has a mode. 'about' is the existing behaviour (a
persona talks with the user about the thread). 'as_contact' has the model play
the contact so the user can rehearse the conversation: its own prompt (stay in
the contact's voice, don't invent facts, coach on 'out of character'), no
persona prompt, and only the thread tools — no memory, library, calendar or
other-thread access, and no knowledge writes.

The shared persona/file-chat loop now refuses tool calls that weren't in the
turn's catalog, so the gates hold even when a model names a tool it wasn't
offered.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 18:39:27 -04:00
Cameron CordesandClaude Opus 5.5 4ac574d4d2 feat(persona-chat): continue an SMS thread with a persona
Persona conversations can now be anchored on a message in an SMS thread.
Creating one snapshots the thread up to that message (via SMS-API) into the
row; every turn appends it to the persona prompt with guidance to talk like a
text thread rather than write an insight.

Anchored turns get four tools: get_thread_messages (page the thread),
look_at_message_image (local vision on an MMS photo), get_photos_near_time
(library photos with tags and people) and look_at_photo (local vision on a
library photo). The conversation list filters by contact_id.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-17 18:07:49 -04:00
Cameron CordesandClaude Opus 5.5 305eda5894 fix(chat): budget chat history against the model's served context window
Long insight/persona chats on llama-swap failed with "exceeds the
available context size" even after raising Context in the app:

- llama-server fixes its window at launch (-c) and ignores num_ctx, but
  the history budget trusted the requested num_ctx, so raising it kept
  MORE history than the server could hold. LlmClient::context_window()
  now reports the served window (llama-swap: /upstream/<model>/props,
  cached 10 min) and the budget uses min(requested, served).
- apply_context_budget could only drop tool-call pairs, so plain Q&A
  chats never shrank. It now also drops whole earlier exchanges (keeping
  user/assistant alternation) and, last, the current turn's tool results,
  never the in-progress question.
- The budget only ran once, before the tool loop. ContextFitter now
  fits every LLM call (on a copy; the stored transcript is untouched)
  and, on a context-overflow error, shrinks the budget from the server's
  reported token counts and retries once.

GET /insights/models reports each llama-swap model's context_window when
it's known without loading the model (cached, or currently running), for
the app's Context picker.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-10-15 19:21:04 -04:00
Cameron CordesandClaude Opus 5.5 b6deca2a52 Tracing: DAO layer + handler spans on tracing, drop all Context params (#141)
trace_db_call no longer takes an OpenTelemetry Context: it opens a
db.<query_type>.<operation> span (same name via otel.name, same
db.query_type / db.operation attrs) on the caller's ambient tracing span
and runs the DAO body inside it. The cx / ctx / context parameter is gone
from every DAO trait method, impl and call site, and from the helpers and
background drains that only threaded it.

The remaining request-handler spans (files, tags, faces, image, video,
favorites, duplicates, memories) move to #[instrument]; the
Context::current_with_span / with_remote_span_context plumbing is gone, as
is extract_context_from_request (the tracing-actix-web root span covers
it). otel::set_span_attributes replaces BoxedSpan::set_attributes.

Background-job raw spans (thumbnails, video actors) are left for #142.

tests/otel_db_spans.rs pins name, attributes, status and nesting (across
an instrumented spawn); otel_traceparent now uses an #[instrument]
handler. CLAUDE.md documents the tracing conventions.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-29 17:02:40 -04:00
Cameron CordesandClaude Opus 5.5 1c508cdabd Tracing: LLM clients + streaming spans on tracing, drop cx threading (#140)
LlmClient methods no longer take an OpenTelemetry Context. llm.request is
now a tracing span (otel.kind=client, llm.provider/operation/model) that
parents on the caller's ambient span; traceparent injection reads the
span's OTel context via OpenTelemetrySpanExt.

The src/ai feature spans (handlers, insight generation, chat, persona
chat, daily summaries, TTS) move to #[instrument] / info_span!, and every
LLM-bearing tokio::spawn carries its parent span with .instrument(): the
streaming chat turn (chat_turn_stream_inner), async chat / persona turns,
background insight jobs and TTS jobs. Sub-spans in the agentic loops
(ai.chat.loop, ai.agentic.loop) instrument each LLM / tool await.

DAO calls keep their explicit Context (derived from the tracing span)
until the DAO migration (#141).

tests/otel_llm_spans.rs pins nesting + traceparent for the blocking and
streaming paths across a spawn on a multi-thread runtime.

Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
2026-09-29 17:02:40 -04:00
Cameron Cordes 696d9fa8f3 Otel: llm.request client spans + traceparent on LLM calls (#130)
Add OpenTelemetry tracing to every LLM client call so an insight/chat
turn is a single trace from HTTP entry to each downstream inference.

- LlmClient trait: thread a &opentelemetry::Context through all 5
  methods (generate, chat_with_tools, chat_with_tools_stream,
  generate_embeddings, describe_image), matching the DAO convention of
  explicit context threading rather than ambient Context::current().
- otel::start_llm_request_span: single shared helper that every
  provider (openrouter / llamacpp / ollama) funnels through, so the
  span shape is identical: name llm.request, SpanKind::Client,
  llm.provider / llm.operation / llm.model.
- Per-method spans in all three clients with the spec's operation enum
  (chat | chat_stream | embeddings | describe_image | generate); stream
  spans are owned and moved into the async_stream generator so they end
  when the response drains, not when headers arrive.
- llm.tokens.input / llm.tokens.output recorded on non-stream and
  stream completion; llm.cost_usd from usage.cost (OpenRouter);
  http.status_code + error status on failure.
- W3C traceparent injected on outgoing LLM HTTP requests (llama-swap,
  Ollama, OpenRouter) gated on span_context.is_valid() so debug
  no-op-tracer builds don't send an all-zero parent.
- Turn-level spans (ai.chat.turn.execute, ai.persona_chat.turn.execute)
  now carry llm.backend + llm.model; with_entry streaming paths thread
  the turn context (turn_cx) to child describe_image / agentic-loop
  calls instead of the ambient context.

clippy clean; 690 lib + 775 integration + 4 doc tests green.
2026-09-28 01:21:46 -04:00
Cameron CordesandClaude Opus 5 65cceaa67c feat: multiple persona conversations with branching and generated titles
Persona chat stored a flat Vec<ChatMessage> keyed on (user_id, persona_id),
which meant one rolling transcript per persona and no way to revisit a turn.
This moves it onto the same ChatHistoryStore tree the file chat uses and
gives conversations their own identity.

Storage
- messages_json now holds a serialized ChatHistoryStore. Reads accept the
  old flat array and upgrade it in place, so existing transcripts survive
  without a data migration. The upgrade drops the v1 seed greeting, which
  the flat renderer hid but the tree renderer would surface as a bubble the
  user has never seen.
- New migration re-keys persona_chat_conversations on an opaque
  conversation_id and adds title + created_at, so one persona can hold any
  number of separate threads. Every DAO read and write is scoped by user_id
  as well: a conversation id is a bearer token for someone's transcript and
  must never grant access on its own.
- The per-conversation lock and in-flight turn slot key on conversation_id,
  so two threads with the same persona can run turns concurrently.

Endpoints
- POST/DELETE /persona_chat/conversations — start and remove a thread,
  replacing /persona_chat/reset.
- GET /persona_chat/conversations — the chat list, with snippet and counts
  derived from each tree's active branch.
- POST /persona_chat/rewind, POST /persona_chat/switch-branch,
  GET /persona_chat/branches — rewind and fork, mirroring the file chat.
  Index 0 is rewindable here (it is the user's own first question, not a
  synthetic prompt) and re-anchors on the seed node.
- history/turn/rewind/switch-branch/branches all key on conversation_id;
  history gained branch_id and now returns real fork_info, active_leaf_id
  and viewing_branch_id instead of placeholders.

The turn body no longer carries a persona at all — it is read from the
stored conversation, so a stale client cannot swap a thread's voice midway.

Titles
After the first turn persists, the conversation is named from its opening
exchange on the same backend the turn ran on. Small models wrap titles in
quotes, prefix them with "Title:" and append explanations, so sanitize_title
strips all of that and truncates on a character boundary. Any failure falls
back to the user's opening question. Generation runs after persistence: a
failed title must not cost the turn.

Fixes found along the way
- insight_chat: both file-chat turn paths captured path.len() before
  apply_context_budget drained messages out of the middle, then sliced
  messages[path_len..] for the new tree nodes. Once truncation fired that
  dropped the user turn from the tree or panicked on an out-of-range start
  index. Now read after the budget pass as history_len.
- Persona chat had no context budget at all and hardcoded truncated: false
  in the done frame, so a rolling transcript grew unbounded.
- A cancelled turn persisted a half-finished transcript and pushed a second
  terminal frame; it now returns early like the file chat.
- The seeded system prompt was frozen at conversation creation, so editing a
  persona never reached a thread already in flight. Re-resolved per turn.
- turn_count was overwritten each write with the per-turn message delta;
  it is now the cumulative assistant-turn count on the active branch.
- is_initial is always false: the file chat reserves it for its synthetic
  "describe this photo" prompt, and marking a persona chat's first question
  with it made the opening reply impossible to regenerate.

600 lib tests pass, clippy --all-targets clean.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
2026-08-25 18:23:10 -04:00
Cameron Cordes 883e2a0e1b fix: send persona_chat wire shapes in snake_case like file chat
The mobile client dispatches POST /persona_chat/turn with snake_case
keys (persona_id, user_message, num_ctx, ...) per the file-chat
convention, but the persona request/response structs carried camelCase
serde renames (personaId, userMessage, ...), so every dispatch 400'd
with 'missing field personaId'. Drop the renames from
PersonaChatTurnRequest, PersonaChatHistoryView, RenderedPersonaMessage,
and PersonaChatResetRequest — the persona wire shapes now match the
rest of the API (history query, 202 turn_id, SSE skip_before) — and
pin the contract with serialization round-trip tests.
2026-08-24 21:34:46 -04:00
Cameron Cordes 3b9d985025 feat: add /persona_chat endpoints for open chat with persona
- PersonaChatSession dispatches turns through the shared agent loop,
  persisting transcripts keyed on (user_id, persona_id) in the new
  persona_chat table (migration included).
- GET /persona_chat/history returns a rendered transcript (tool
  invocations folded, is_initial flag) matching the file-chat shape.
- POST /persona_chat/turn returns 202 with a turn_id; SSE replay and
  cancel reuse turn_replay_impl/cancel_turn_impl, extracted from the
  actix-attributed handlers so both route families share the logic.
- POST /persona_chat/reset clears the persona transcript.
- Concurrent dispatches for the same (user, persona) are rejected with
  409 via an in-flight gate (InFlightPersonaTurns) whose RAII guard
  drops with the spawned turn task, freeing the slot on completion,
  error, or abort.
2026-08-24 21:25:48 -04:00