Code index (sol_code):
- SymbolDocument: file_path, repo_name, language, symbol_name, symbol_kind,
signature, docstring, branch, source, embedding (768-dim knn_vector)
- CodeIndexer: batch symbol indexer with idempotent upserts
- Branch-aware: symbols scoped to branch with mainline fallback
Breadcrumbs:
- build_breadcrumbs(): adaptive context injection for coding prompts
- Default: project outline via aggregation (modules, types, fns)
- Adaptive: hybrid search (_analyze → symbol matching → BM25 + neural)
- Token budget enforcement with priority (outline first, then relevance)
- format_symbol(): signature + first-line docstring + file:line
Query optimization: uses _analyze API to extract key terms from
free-form user text, matches against actual symbol names in the index
before running the hybrid search.
session_chat_via_orchestrator now:
- Spawns generation on a background task
- Reads in_stream for client tool results in foreground
- Forwards results to orchestrator.submit_tool_result()
- Uses tokio::select! to handle both concurrently
- Uses GenerateRequest + Metadata (no transport types in orchestrator)
- Calls grpc::bridge (not orchestrator::grpc_bridge)
Orchestrator engine:
- engine.rs: unified Mistral Conversations API tool loop that emits
OrchestratorEvent instead of calling Matrix/gRPC directly
- tool_dispatch.rs: ToolSide routing (client vs server tools)
- Memory loading stubbed (migrates in Phase 4)
Server-side tokenizer:
- tokenizer.rs: HuggingFace tokenizers-rs with Mistral's BPE tokenizer
- count_tokens() for accurate usage metrics
- Loads from local tokenizer.json or falls back to bundled vocab
- Config: mistral.tokenizer_path (optional)
No behavior change — engine is wired but not yet called from
sync.rs or session.rs (Phase 2 continuation).
Introduces the orchestrator module with:
- OrchestratorEvent enum: 11 event variants covering lifecycle, tools,
progress, and side effects
- RequestId (UUID per generation), ResponseMode (Chat/Code), ToolSide
- ChatRequest/CodeRequest structs for transport-agnostic request input
- Orchestrator struct with tokio::broadcast channel (capacity 256)
- subscribe() for transport bridges, emit() for the engine
- Client-side tool dispatch: pending_client_tools map with oneshot channels
- submit_tool_result() to unblock engine from gRPC client responses
Additive only — no behavior change. Existing responder + gRPC session
paths are untouched. Phase 2 will migrate the Conversations API path.
- gRPC dev_mode config: disables JWT auth, uses fixed dev identity
- Agent prefix (agents.agent_prefix): dev agents use "dev-sol-orchestrator"
to avoid colliding with production on shared Mistral accounts
- Coding sessions use instructions (system prompt + coding addendum)
with mistral-medium-latest for personality adherence
- Conversations API: don't send both model + agent_id (422 fix)
- GrpcState carries system_prompt + orchestrator_agent_id
- Session.end() keeps session active for reuse (not "ended")
- User messages posted as m.notice, assistant as m.text (role detection)
- History loaded from Matrix room on session resume
- Docker Compose local dev stack: OpenSearch 3 + Tuwunel + SearXNG
- Dev config: localhost URLs, dev_mode, opensearch-init.sh for ML setup
spawns gRPC server alongside Matrix sync loop when [grpc] config
is present. shares ToolRegistry, Store, MistralClient, and Matrix
client with the gRPC CodeSession handler.
research agents now have a 2-minute timeout via tokio::time::timeout.
a hung Mistral API call can no longer block Sol's entire sync loop.
timed-out agents return partial results instead of hanging forever.
on startup, Sol detects research sessions with status='running' from
previous crashes and marks them as failed. 6 new tests covering the
full research session lifecycle: create, append findings, complete,
fail, hung cleanup, and partial findings survival.
main.rs: create KratosClient, pass mistral+store to ToolRegistry,
build active_agents list for dynamic delegation.
conversations.rs: context_hint for new conversations, reset_all.
sdk/mod.rs: added kratos module.
conversations API path now injects per-message context headers with
live timestamps, room name, and memory notes. this replaces the
template variables in agent instructions which were frozen at
creation time.
memory notes (topical + recent backfill) loaded before each response
in the conversations path — was previously only in the legacy path.
context hint seeds new conversations with recent room history after
resets, so sol doesn't lose conversational continuity on sneeze.
tool call results now logged with preview + length for debugging.
reset_all() clears both in-memory and sqlite conversation state.
Mistral Agents + Conversations API integration:
- Orchestrator agent created on startup with Sol's personality + tools
- ConversationRegistry routes messages through persistent conversations
- Per-room conversation state (room_id → conversation_id + token counts)
- Function call handling within conversation responses
- Configurable via [agents] section in sol.toml (use_conversations_api flag)
Multimodal support:
- m.image detection and Matrix media download (mxc:// → base64 data URI)
- ContentPart-based messages sent to Mistral vision models
- Archive stores media_urls for image messages
System prompt rewrite:
- 687 → 150 lines — dense, few-shot examples, hard rules
- {room_context_rules} placeholder for group vs DM behavior
- Sender prefixing (<@user:server>) for multi-user turns in group rooms
SQLite persistence (/data/sol.db):
- Conversation mappings and agent IDs survive reboots
- WAL mode for concurrent reads
- Falls back to in-memory on failure (sneezes into all rooms to signal)
- PVC already mounted at /data alongside Matrix SDK state store
New modules:
- src/persistence.rs — SQLite state store
- src/conversations.rs — ConversationRegistry + message merging
- src/agents/{mod,definitions,registry}.rs — agent lifecycle
- src/agent_ux.rs — reaction + thread progress UX
- src/tools/bridge.rs — tool dispatch for domain agents
102 tests passing.
Three memory channels: hidden tool (sol.memory.set/get in scripts),
pre-response injection (relevant memories loaded into system prompt),
and post-response extraction (ministral-3b extracts facts after each
response). User isolation enforced at Rust level — user_id derived
from Matrix sender, never from script arguments.
New modules: context (ResponseContext), memory (schema, store, extractor).
ResponseContext threaded through responder → tools → script runtime.
OpenSearch index sol_user_memory created on startup alongside archive.
Matrix bot with E2EE (matrix-sdk 0.9) that passively archives all
messages to OpenSearch and responds to queries via Mistral AI with
function calling tools.
Core systems:
- Archive: bulk OpenSearch indexer with batch/flush, edit/redaction
handling, embedding pipeline passthrough
- Brain: rule-based engagement evaluator (mentions, DMs, name
invocations), LLM-powered spontaneous engagement, per-room
conversation context windows, response delay simulation
- Tools: search_archive, get_room_context, list_rooms, get_room_members
registered as Mistral function calling tools with iterative tool loop
- Personality: templated system prompt with Sol's librarian persona
47 unit tests covering config, evaluator, conversation windowing,
personality templates, schema serialization, and search query building.
