* feat(provider): add Venice AI support and update related documentation
* revert(asr): restore asr files to previous commit
* feat(config): add Venice API base URL and local LM Studio configuration
* fix(config): update Venice API base URL to correct endpoint
* feat(provider): add lmstudio vendor and local no-key behavior
* refactor(provider): consolidate protocol metadata and local tests
* fix(provider): sync lmstudio probing and model normalization
* test(web): format lmstudio model status cases for golines
Allow configuring provider-specific fields like reasoning_split for minimax via
the model config's extra_body map. These fields are merged into the request
body last, giving them precedence over default values.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat(telegram): stream LLM responses in real-time via sendMessageDraft
Implements real-time token streaming to Telegram using the sendMessageDraft
API (telego v1.6.0). Instead of showing only a "Thinking..." placeholder
until the full response arrives, users now see partial LLM output appear
in the chat as it's generated.
The streaming pipeline threads through all layers:
- StreamingProvider interface (providers/types.go): opt-in ChatStream()
method that receives an onChunk callback with accumulated text
- OpenAI-compatible SSE streaming (openai_compat/provider.go): parses
SSE events with stream:true, handles text deltas and tool call assembly
- Anthropic native streaming (anthropic/provider.go): uses SDK's
NewStreaming() for direct Anthropic API connections
- HTTPProvider delegation (http_provider.go): delegates ChatStream to
the underlying openai_compat provider
- StreamingCapable + Streamer interfaces (channels/interfaces.go):
opt-in channel capability like TypingCapable/PlaceholderCapable
- Telegram streamer (telegram/telegram.go): BeginStream returns a
telegramStreamer that throttles sendMessageDraft calls (3s/200 chars)
with graceful degradation on API errors
- StreamDelegate bridge (bus/bus.go): decouples agent loop from channel
manager without tight imports
- Manager integration (manager.go): implements StreamDelegate, tracks
streamActive state, coordinates with placeholder editing
- Agent loop (loop.go): uses ChatStream when both provider and channel
support streaming, cancels stream on tool calls, skips PublishOutbound
when Finalize already delivered the message
Graceful degradation:
- Bots without forum/topics mode: first sendMessageDraft error sets
failed=true, subsequent Updates become no-ops, Finalize still delivers
via SendMessage. User sees normal non-streaming behavior.
- Non-streaming providers: type assertion fails, falls back to Chat()
- Config opt-out: streaming.enabled (default true) in telegram config
Closes#1098
* fix(telegram): delete placeholder message when streaming delivers response
When streaming was active, the "Thinking..." placeholder message stayed
in the chat because preSend only deleted the tracking entry without
removing the actual Telegram message. Now preSend deletes the placeholder
via the new MessageDeleter interface when streamActive is set.
* refactor(streaming): remove dead code and simplify streaming wiring
- Delete unused Anthropic ChatStream/parseStream (-131 lines) — factory
creates HTTPProvider for all OpenAI-compat providers including OpenRouter
- Simplify runLLMIteration from 4 to 3 return values (remove unused
streamed bool)
- Replace managerStreamer struct with finalizeHookStreamer using embedding
(Update/Cancel promoted, only Finalize overridden)
* fix(streaming): skip streamer acquisition when SendResponse is false
Heartbeat messages set SendResponse=false but the streaming path
was unconditionally acquiring a streamer, causing HEARTBEAT_OK to
leak to Telegram via streamer.Finalize().
* fix(streaming): guard streamer for non-sendable messages, add streaming config
Skip streamer acquisition for heartbeat (NoHistory=true), preventing
HEARTBEAT_OK from leaking to Telegram via streamer.Finalize().
Add streaming.enabled to Telegram defaults and example config.
* feat(telegram): stream LLM responses in real-time via sendMessageDraft
Implements real-time token streaming to Telegram using the sendMessageDraft
API (telego v1.6.0). Instead of showing only a "Thinking..." placeholder
until the full response arrives, users now see partial LLM output appear
in the chat as it's generated.
The streaming pipeline threads through all layers:
- StreamingProvider interface (providers/types.go): opt-in ChatStream()
method that receives an onChunk callback with accumulated text
- OpenAI-compatible SSE streaming (openai_compat/provider.go): parses
SSE events with stream:true, handles text deltas and tool call assembly
- Anthropic native streaming (anthropic/provider.go): uses SDK's
NewStreaming() for direct Anthropic API connections
- HTTPProvider delegation (http_provider.go): delegates ChatStream to
the underlying openai_compat provider
- StreamingCapable + Streamer interfaces (channels/interfaces.go):
opt-in channel capability like TypingCapable/PlaceholderCapable
- Telegram streamer (telegram/telegram.go): BeginStream returns a
telegramStreamer that throttles sendMessageDraft calls (3s/200 chars)
with graceful degradation on API errors
- StreamDelegate bridge (bus/bus.go): decouples agent loop from channel
manager without tight imports
- Manager integration (manager.go): implements StreamDelegate, tracks
streamActive state, coordinates with placeholder editing
- Agent loop (loop.go): uses ChatStream when both provider and channel
support streaming, cancels stream on tool calls, skips PublishOutbound
when Finalize already delivered the message
Graceful degradation:
- Bots without forum/topics mode: first sendMessageDraft error sets
failed=true, subsequent Updates become no-ops, Finalize still delivers
via SendMessage. User sees normal non-streaming behavior.
- Non-streaming providers: type assertion fails, falls back to Chat()
- Config opt-out: streaming.enabled (default true) in telegram config
Closes#1098
* fix(telegram): delete placeholder message when streaming delivers response
When streaming was active, the "Thinking..." placeholder message stayed
in the chat because preSend only deleted the tracking entry without
removing the actual Telegram message. Now preSend deletes the placeholder
via the new MessageDeleter interface when streamActive is set.
* refactor(streaming): remove dead code and simplify streaming wiring
- Delete unused Anthropic ChatStream/parseStream (-131 lines) — factory
creates HTTPProvider for all OpenAI-compat providers including OpenRouter
- Simplify runLLMIteration from 4 to 3 return values (remove unused
streamed bool)
- Replace managerStreamer struct with finalizeHookStreamer using embedding
(Update/Cancel promoted, only Finalize overridden)
* fix(streaming): skip streamer acquisition when SendResponse is false
Heartbeat messages set SendResponse=false but the streaming path
was unconditionally acquiring a streamer, causing HEARTBEAT_OK to
leak to Telegram via streamer.Finalize().
* fix(streaming): guard streamer for non-sendable messages, add streaming config
Skip streamer acquisition for heartbeat (NoHistory=true), preventing
HEARTBEAT_OK from leaking to Telegram via streamer.Finalize().
Add streaming.enabled to Telegram defaults and example config.
* fix(picoclaw): add missing closing brace for StreamingProvider interface
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: resolve golangci-lint formatting issues
Fix gci import ordering in telegram and anthropic provider, and break
long function signature in openai_compat provider to satisfy golines.
* fix: address code review feedback on streaming PR
- Deduplicate Streamer interface: alias channels.Streamer to bus.Streamer
to prevent type drift across packages
- Increase SSE scanner buffer to 10MB max to handle large single-line
responses that exceed bufio.Scanner's 64KB default
- Switch draftID generation from math/rand to crypto/rand for
collision-resistant random IDs
- Add context cancellation check in SSE parsing loop so cancelled
streams stop processing immediately
- Log Finalize failures with chat_id and content length for debugging
silent message delivery failures
* feat: make streaming throttle interval and min growth configurable
Move hardcoded streamThrottleInterval (3s) and streamMinGrowth (200)
into StreamingConfig so they can be tuned per deployment via config
or environment variables.
* fix(telegram): use parseTelegramChatID in DeleteMessage and BeginStream
These two functions called undefined parseChatID. Use
parseTelegramChatID with _ for the unused threadID instead of adding
a wrapper function. Fixes all three CI checks.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(streaming): set streamActive only after successful Finalize
Move onFinalize hook to run after Streamer.Finalize succeeds, so that
if Finalize fails the streamActive flag stays false and the regular
placeholder fallback path remains available.
Addresses review feedback from @alexhoshina.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* Add Novita provider support
- Add 'novita' prefix to normalizeModel switch in openai_compat provider
- Add Novita provider to all_supported_vendors table in README.md
- Add test cases for Novita model prefix stripping
Novita endpoint: https://api.novita.ai/openai
Default models: deepseek/deepseek-v3.2, zai-org/glm-5, minimax/minimax-m2.5
* feat: complete Novita provider integration
* chore: drop README changes from Novita PR
* fix: remove duplicate function declarations in openai_compat provider
The functions buildToolsList, SupportsNativeSearch, and isNativeSearchHost
were declared twice, causing compilation failures in all CI checks.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: break long line in novita test to satisfy golines linter
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* config: add prefer_native and NativeSearchCapable for model-native search
* providers: implement native web search for OpenAI and Codex
* agent: use provider-native search when prefer_native and supported
* tests: add coverage for model-native search
* fix: Golang lint errors
* fix: update the code based on the review
* fix: update codex_provider_test
* Add support for azure openai provider
* Add checks for deployment model name
* Apply suggestion from @Copilot
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
* Addressing @Copilot suggestion to remove the init() function which seemed redundant
* Fix readme
* Fix linting checks
---------
Co-authored-by: Copilot <175728472+Copilot@users.noreply.github.com>
Non-OpenAI providers (Mistral, DeepSeek, Groq, etc.) reject unknown
request fields with 422 errors. The previous blocklist only excluded
Google/Gemini, but the comment already noted this feature is
OpenAI-only. Flip to an allowlist so only api.openai.com receives
the field.
Fixes#1333
- Separate third-party imports from local module imports (gci)
- Fix byte slice literal formatting (gofumpt)
- Rename shadowed err variable to ftErr (govet)
- Remove trailing blank lines in test files
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
- serializeMessages: preserve ToolCallID/ToolCalls when Media is present
- resolveMediaRefs: add 20MB file size limit to prevent OOM
- mimeFromExtension: return empty string for unknown extensions
- Add 11 unit tests for serializeMessages, resolveMediaRefs, mimeFromExtension
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
The serializeMessages() function was not preserving the reasoning_content
field when serializing messages for vision API calls. This caused the
TestProviderChat_PreservesReasoningContentInHistory test to fail.
This fix ensures reasoning_content is included in both text-only messages
and vision messages with media attachments.
Co-authored-by: Zachary Guerrero <zack.grrr@gmail.com>
- 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
The openaiMessage struct and stripSystemParts() were not carrying over
the ReasoningContent field when serializing conversation history for
API requests. This caused thinking models (e.g. kimi-k2.5) to receive
incomplete assistant messages on subsequent turns, resulting in 400
errors from the Moonshot API.
Add the ReasoningContent field to openaiMessage and copy it in
stripSystemParts(). Also add a test to verify reasoning_content is
preserved when sending conversation history.
Fixes#588
Related: #876
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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.
Add Mistral as a first-class provider alongside the 17 existing ones.
Mistral uses the OpenAI-compatible API at https://api.mistral.ai/v1
with provider-specific model prefix stripping (mistral/model → model).
Changes:
- Add Mistral to ProvidersConfig, IsEmpty(), HasProvidersConfig()
- Add mistral entry in default model_list (defaults.go)
- Add mistral protocol in factory_provider.go and getDefaultAPIBase()
- Add mistral prefix stripping in openai_compat normalizeModel()
- Add mistral case in legacy factory.go resolveProviderSelection()
- Add mistral migration entry in ConvertProvidersToModelList()
- Add mistral to supported providers in migrate/config.go
- Add mistral section in config.example.json
- Update AllProviders test (17 → 18 providers)
Tested end-to-end with mistral-small-latest model.
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
lc6464