Backend.Upsert never received the fragment's Content, so ChromaDB (and any backend) stored the vector but silently dropped the actual text — saved memories had nothing to retrieve later. Backend.Search now also takes the raw query text, and a failed/missing embedding no longer hard-fails Add/Search: it degrades to a nil vector so a lexical-capable backend can still index/find the content (Chroma has no such fallback and now says so explicitly instead of misbehaving). Adds pkg/rag/backends/sqlitevec: a zero-dependency backend (pure-Go SQLite, no external service) that does cosine similarity when a real embedding vector is available and falls back to FTS5/BM25 full-text search otherwise. Adds pkg/rag/embeddings.OpenAICompatible, covering both a local llama.cpp server (`--embeddings` enabled) and real OpenAI (or any OpenAI-shaped /embeddings endpoint) through the same client. Also fixes token usage tracking for llama.cpp streaming: the client never requested `stream_options.include_usage` nor parsed a usage-only SSE event, and even when present, the agent loop's RunStream dropped any chunk with no Delta/ReasoningDelta — silently discarding the only chunk that carries usage. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> |
||
|---|---|---|
| .. | ||
| integration_test.go | ||
| loop.go | ||
| loop_test.go | ||
| README.es.md | ||
| README.md | ||
pkg/agent
The main loop that runs an LLM agent with guardrails.
Responsibility
Coordinate the iterative cycle between the LLM and tool execution:
while iteration < MaxIterations:
response = llm.Generate(messages, tools)
if no tool calls: return response
for tool_call in response.ToolCalls:
if needs_approval: ask_user()
result = execute(tool_call)
append tool result to messages
Public API
type Loop interface {
Run(ctx context.Context, input string, history ...llm.Message) (Response, error)
RunStream(ctx context.Context, input string, history ...llm.Message) iter.Seq2[Chunk, error]
}
type Config struct {
LLM llm.LLMClient
Persona persona.Persona
Tools tools.Registry
Sandbox Sandbox
MaxIters int
Approver Approver // nil = auto-approve all
OnIteration func(Iteration) // observability hook
}
type Response struct {
Content string
ToolCalls []tools.Call
Iterations int
Duration time.Duration
TokenUsage llm.TokenUsage
}
Guarantees
- Termination: Always terminates (max iterations, error, or final response)
- Idempotency: Re-running with the same input produces the same output (given the same LLM)
- Observability: Each iteration emits an OpenTelemetry span
- Approval: Destructive tools (
Askpermission) require confirmation
See also
- pkg/tools — Tool execution
- pkg/llm — LLMClient interface
- pkg/persona — Persona assembly