* 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
Migrate Azure OpenAI provider from legacy Chat Completions API to the OpenAI Responses API.
- Switch API endpoint from `/openai/deployments/{deployment}/chat/completions` to `/openai/v1/responses`
- Change auth header from `Api-Key` to `Authorization: Bearer`
- Use `responses.ResponseNewParams` SDK types for request construction
- Extract shared Responses API utilities into `openai_responses_common` package
- Deduplicate 178 lines from codex_provider.go by reusing shared package
- Add 593 lines of comprehensive test coverage for the shared package
Closes#2111
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* feat: add Xiaomi MiMo provider support
- Add 'mimo' protocol prefix support in factory_provider.go
- Add default API base URL for MiMo: https://api.xiaomimimo.com/v1
- Update provider-label.ts to include Xiaomi MiMo label
- Add MiMo to provider tables in both English and Chinese documentation
- Add comprehensive unit tests for MiMo provider
MiMo API is compatible with OpenAI API format, making it easy to integrate
with the existing HTTPProvider infrastructure.
Users can now use MiMo by configuring:
{
"model_name": "mimo",
"model": "mimo/mimo-v2-pro",
"api_key": "your-mimo-api-key"
}
* hassas dosyaları kaldırma
* Add .security.yml and onboard to .gitignore
Add support for AWS Bedrock as an LLM provider using the Converse API.
The implementation is behind a build tag (-tags bedrock) to keep the
default binary size small.
Features:
- AWS SDK v2 with automatic credential chain (env vars, profiles, IAM roles)
- Converse API for unified access to Claude, Llama, Mistral models
- Tool/function calling support with proper document handling
- Image support with base64 decoding and size limits
- Request timeout configuration
- Region validation and endpoint resolution for all AWS partitions
Usage:
go build -tags bedrock
model: bedrock/us.anthropic.claude-sonnet-4-20250514-v1:0
api_base: us-east-1 (or full endpoint URL)
Anthropic API returns 400 when multiple tool_result blocks share the same
tool_use_id, or when consecutive tool results are sent as separate user
messages. This fix:
1. Adds ToolCallID deduplication in sanitizeHistoryForProvider (context.go)
to drop duplicate tool results before sending to any provider.
2. Merges consecutive tool result messages into a single user message with
multiple tool_result content blocks in Anthropic's buildRequestBody,
for both "user" (with ToolCallID) and "tool" role messages.
3. Adds tests for both behaviors.
Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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>
- Add `AudioModelTranscriber` for model-based audio transcription via LLM providers
- Support selecting a transcription model with `voice.model_name` in config
- Keep Groq transcription as a fallback and move it into dedicated files with focused tests
- Serialize `data:audio/...` media as input_audio for OpenAI-compatible providers
- Improve transcription logging by rendering error fields as strings
- Add coverage for transcriber detection, audio-model behavior, provider audio serialization, and Groq transcription
Fixes#1890.
* 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>
* feat(config): support multiple API keys for failover
Add api_keys field to ModelConfig to support multiple API keys with
automatic failover. When multiple keys are configured, they are expanded
into separate model entries with fallbacks set up for key-level failover.
Example config:
{
"model_name": "glm-4.7",
"model": "zhipu/glm-4.7",
"api_keys": ["key1", "key2", "key3"]
}
Expands internally to:
- glm-4.7 (key1) -> fallbacks: [glm-4.7__key_1, glm-4.7__key_2]
- glm-4.7__key_1 (key2)
- glm-4.7__key_2 (key3)
Backward compatible: single api_key still works as before.
* fix(providers): change cooldown tracking from provider to ModelKey
This enables proper key-switching when multiple API keys share the same
provider. Previously, when one key failed, all keys were blocked because
cooldown was tracked per-provider.
Now each (provider, model) combination has independent cooldown, allowing
fallback to alternate keys when one is rate limited.
Includes TestMultiKeyWithModelFallback and related failover tests.
When building parameters for Anthropic API calls, tool calls with empty
names would cause 400 Bad Request errors with the message:
'tool_use.name: String should have at least 1 character'
This fix adds a check to skip tool calls that have empty names, preventing
the API error and allowing the conversation to continue normally.
Fixes#1658
* 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>
Problem:
During subturn context limit or truncation recoveries, the recovery loops repeatedly
called `runAgentLoop` with the same or modified `UserMessage`. Because `runAgentLoop`
unconditionally adds the `UserMessage` to the session history, this resulted in:
1. Duplicate User Messages polluting the history upon `context_length_exceeded` retries.
2. The possibility of injecting empty User Messages if `opts.UserMessage` was artificially blanked out to work around the duplication.
3. Messy or duplicate entries during `finish_reason="truncated"` recovery injections.
Solution:
- Introduce `SkipAddUserMessage` boolean to `processOptions` to explicitly control whether the agent loop should write the user prompt to history.
- Add an explicit `opts.UserMessage != ""` check in `runAgentLoop` to prevent polluting history with empty message content.
- In `subturn.go`'s recovery loop, set `SkipAddUserMessage: contextRetryCount > 0` to skip writing the user message on context
* 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 defensive nil check for tool call Arguments field
- replace nil input with empty object to comply with Anthropic spec
- prevent API errors when GLM models return null input in tool_use blocks
Zhipu AI's GLM series models may return tool_use blocks with null input field,
which causes their API to reject subsequent requests with error:
"ClaudeContentBlockToolResult object has no attribute id"
This fix ensures compatibility by converting nil inputs to empty objects {},
matching the Anthropic Messages API specification while maintaining backward
compatibility with other providers.
LC