- Persistence layer (jsonl.go addMsg/SetHistory) normalizes CreatedAt
when missing so the invariant is guaranteed at the storage boundary
- API layer (session.go) exposes created_at on all transcript message
types with session.updated fallback for legacy messages
- Frontend uses per-message timestamps when available
- messagesContentEqual ignores CreatedAt for tail-matching after
JSONL roundtrip
Fixes#2787
* feat(chat,seahorse): persist and display model_name across history
* test(seahorse): fix lint regressions in repair coverage
* fix(pico): preserve model_name in live updates
* fix(pico): preserve model_name through live stream wrappers
* Support streaming
* fix: stream pico reasoning updates
Route Pico reasoning through the active streamer and hide empty thought placeholders.
* fix: harden configured streaming delivery
* fix ci
* fix split issue
* feat(web): download attachments in frontend
* fix: proxy pico media and force svg downloads
* feat(web): hide ephemeral media refs from persisted session history
- Add Media []string field to Message struct for image/media URLs
- Implement serializeMessages() to format messages with image_url content parts
- Enables OpenAI-compatible vision APIs to receive image attachments
Avoid rebuilding the entire system prompt on every BuildMessages() call
by caching the static portion (identity, bootstrap, skills summary,
memory) and only recomputing it when workspace source files change.
Key changes:
- ContextBuilder caches the static prompt behind an RWMutex with
double-checked locking. Source file changes are detected via cheap
os.Stat mtime checks so no explicit invalidation is needed.
- Track file existence at cache time (existedAtCache map) so that
newly created or deleted bootstrap/memory files also trigger a
rebuild — the old modifiedSince() silently returned false on
os.IsNotExist.
- Walk the skills directory recursively with filepath.WalkDir to
catch content-only edits at any nesting depth; directory mtime
alone misses in-place file modifications on most filesystems.
- ToolRegistry.sortedToolNames() sorts tool names before iteration,
ensuring deterministic tool definition order across calls — a
prerequisite for LLM-side prefix/KV cache reuse.
- Merge all context (static + dynamic + summary) into a single
system message for provider compatibility: the Anthropic adapter
extracts messages[0] as the top-level system parameter, and Codex
reads only the first system message as instructions.
- Fix a data race in BuildMessages() where cachedSystemPrompt was
read without holding the lock in a debug log statement.
- Add tests: single system message invariant, mtime auto-invalidation,
new-file creation detection, skill file content change, explicit
InvalidateCache, cache stability, concurrent access (20 goroutines
x 50 iterations, passes go test -race), and a benchmark.
Mistral's API strictly validates tool_calls in assistant messages and
rejects non-standard fields. The ToolCall struct had Name and Arguments
as top-level JSON fields, duplicating data already in Function.Name
and Function.Arguments. OpenAI silently ignored these extras but
Mistral returns 422.
Change json tags to "-" so these internal fields are no longer
serialized to API payloads while remaining available in Go code.
Models like Moonshot kimi-k2.5 and DeepSeek-R1 return a
reasoning_content field in assistant messages. When thinking is enabled,
the API requires this field to be echoed back in subsequent requests.
PicoClaw was silently dropping it, causing 400 errors on tool-call
round-trips.
- Add ReasoningContent to Message and LLMResponse types
- Parse reasoning_content in openai_compat parseResponse()
- Carry reasoning_content through assistant tool-call messages
- Add unit test for reasoning_content parsing
Fixes#588
Add support for persisting thought_signature metadata from Google/Gemini 3
models. This introduces ExtraContent and GoogleExtra types to handle
provider-specific metadata, and ensures thought signatures are properly
preserved through the tool call lifecycle.
- Move provider creation logic to factory_provider.go with protocol-based approach
- Add OpenAIProviderConfig with WebSearch support and embedded ProviderConfig
- Add maxTokensField to OpenAI-compatible provider for configurable token field
- Introduce new providers: Ollama, DeepSeek, GitHubCopilot, Antigravity, Qwen
- Remove redundant CreateProvider function from factory.go
- Add ThoughtSignature field to FunctionCall for tool response handling
- Remove duplicate Name field assignment in tool loop
- Update tests to reflect new provider configuration structure
Phase 1: centralize protocol message/tool/response types in protocoltypes and keep compatibility aliases in providers and protocol packages.
Phase 1: preserve HTTPProvider constructor compatibility and route Anthropic api_base through factory auth/provider constructors with base URL normalization.
Phase 2: expand provider routing/auth tests (deepseek/nvidia/shengsuanyun, codex/claude oauth/codex-cli) and add openai_compat + anthropic coverage for proxy transport, model normalization, numeric option coercion, token-source refresh, and base URL behavior.
Phase 3: apply gofmt and validate with Dockerized tests (go test ./pkg/providers/... ./pkg/migrate and go test ./...).
LiusCraft