- Few-shot injection on /insights/generate/agentic: compresses prior
training_messages into trajectory blocks (tool calls + result summaries)
and injects into the system prompt. Hardcoded default ids with optional
request override.
- New fewshot_source_ids column on photo_insights (+ migration) to track
which exemplars influenced a given row, for downstream training-set
filtering. Chat amend rows stamp None with a lineage note.
- Ollama client now remembers which server (primary/fallback) most
recently succeeded and tries it first on the next call, via a shared
Arc<AtomicBool>. Avoids re-404ing the primary on every agent iteration
when the chosen model only lives on the fallback.
- Demote noisy logs: daily_summary "Summary match" lines to debug;
inner chat_with_tools non-2xx body log from error to warn (outer
layer owns the terminal-error signal).
- Drift-guard tests for summarize_tool_result covering the success /
empty / error / unknown shape for every tool.
- Tidy: three pre-existing clippy warnings cleaned up.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add LlmClient::chat_with_tools_stream and SSE endpoint
POST /insights/chat/stream that emits text deltas, tool_call /
tool_result pairs, truncated notice, and a terminal done frame as the
agentic loop runs.
- Ollama: parses NDJSON from /api/chat stream, accumulates content
deltas, emits Done with tool_calls from the final chunk.
- OpenRouter: parses OpenAI-compatible SSE, reassembles tool_call
argument deltas by index, asks for stream_options.include_usage.
- InsightChatService spawns the loop on a tokio task, feeds events
through an mpsc channel, persists training_messages at the end.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
load_history now groups preceding tool_call + tool_result scaffolding
under each assistant reply as `tools: [{name, arguments, result}]`.
Result bodies over 2000 chars are truncated for payload size with a
`result_truncated` flag; the full value remains in training_messages.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Rewind: POST /insights/chat/rewind truncates training_messages at a
given rendered index, dropping the target message plus any preceding
tool-call scaffolding. The initial user prompt is protected.
Metrics: log prompt_eval_count/duration and eval_count/duration from
every Ollama chat response, rendered as tokens + ms + tok/s.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds POST /insights/chat and GET /insights/chat/history. Replays the
stored agentic conversation through the same backend the insight was
generated with (or a per-turn override), runs a short tool-calling
loop, and persists the extended history in append or amend mode.
Backend switching: same-backend or hybrid->local replay verbatim;
local->hybrid is rejected in v1 (would require on-the-fly vision
description rewrite).
Per-(library, file) async mutex serialises concurrent turns. Soft
context budget drops oldest tool_call+result pairs when the
serialized history exceeds num_ctx - 2048 tokens.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Add OPENROUTER_ALLOWED_MODELS env var and GET /insights/openrouter/models
endpoint returning the curated list verbatim. Drop the live capability
precheck in hybrid mode — trust the operator's allowlist; bad ids surface
as a chat-call error.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Adds a `backend` column to photo_insights (default 'local', migration
2026-04-20-000000) and a corresponding optional `backend` field on the
agentic request. When a request sets backend=hybrid:
- The local Ollama vision model is called once via describe_image to
produce a text description.
- The description is inlined into the first user message as text —
no base64 image is ever sent to the chat model.
- The agentic tool-calling loop and title generation route through an
OpenRouterClient (dispatched via &dyn LlmClient), letting the user
pick any tool-capable model from OpenRouter per request.
- describe_photo is removed from the offered tools since the description
is already present.
Embeddings and vision stay on local Ollama regardless of backend.
Hybrid mode requires OPENROUTER_API_KEY; handlers return a clear error
when hybrid is requested without it, and also when the selected
OpenRouter model lacks tool-calling support.
AppState gains an optional openrouter client built from
OPENROUTER_API_KEY / OPENROUTER_BASE_URL / OPENROUTER_DEFAULT_MODEL /
OPENROUTER_EMBEDDING_MODEL / attribution headers. Default model is
anthropic/claude-sonnet-4.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Silence forward-looking dead_code on unused DAO modules, annotate
individual placeholder items, rewrite tautological assert!(true/false)
in token tests as panic! arms, and pick up fmt drift.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Tags and insights now follow content across libraries via content_hash
lookups on the read path, so the same file indexed at different rel_paths
in multiple libraries shares its annotations. Recursive tag search scopes
hits to the selected library by checking each tagged rel_path against
the library's disk (with a content-hash sibling fallback so tags attached
under one library's rel_path still match a content-equivalent file in
another). The /image and /image/metadata handlers fall back across
libraries when the file isn't under the resolved one, so union-mode
search results (which carry no library attribution in the response)
still serve correctly.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Expose Ollama sampling params through the insight generation endpoints
so users can tune creativity/determinism per request. All four are
optional — omitted values fall through to the model's server-side
defaults.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Captures prompt_eval_count and eval_count from Ollama /api/chat responses
during the agentic loop and returns them in POST /insights/generate/agentic
so the frontend can display context window usage to the user.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Sanitise tool call arguments before re-sending in conversation history: non-object values (bool, string, null) that some models produce are normalised to {} to prevent Ollama 500s
- Map 'error parsing tool call' Ollama 500 to HTTP 400 with a descriptive message listing compatible models (llama3.1, llama3.2, qwen2.5, mistral-nemo)
- Add reverse_geocode tool backed by existing Nominatim helper; description hints model can chain it after get_location_history results
- Make get_sms_messages contact parameter optional (was required, forcing the model to guess); executor now passes None to fall back to all-contacts search
- Log tool result outcomes at warn level for errors/empty results, info for successes; log SMS API errors with full detail; log full request body on Ollama 500
- Strengthen system prompt to require 3-4 tool calls before final answer
- Try fallback server when checking model capabilities (primary-only check caused 500 for models only on fallback)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Register the agentic insight endpoint that validates tool-calling capability,
runs the agentic loop, and returns the stored PhotoInsightResponse. Returns 400
for unsupported models, 500 for other errors. Max iterations configurable via
AGENTIC_MAX_ITERATIONS env var (default 10).
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
