- 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(pico): add pico_client outbound WebSocket channel
Add a client-mode counterpart to the existing pico server channel.
pico_client connects to a remote Pico Protocol WebSocket server,
enabling picoclaw to bridge messages with external Pico-compatible
services.
Includes config, factory registration, manager wiring, 8 unit tests,
and a minimal echo-server example for interactive testing.
* fix(pico): address PR #1198 review — goroutine leak, race, auth
- Add per-connection context cancel to picoConn to prevent pingLoop
goroutine leak on disconnect
- Re-acquire mutex in StartTyping stop closure to avoid stale conn race
- Remove query-param token auth from echo server (header-only)
- Move ListenAndServe to main goroutine where log.Fatal is safe
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix: replace ConsumeInbound with InboundChan select in client test
MessageBus does not expose a ConsumeInbound method. Use a select on
InboundChan() with context cancellation, matching the pattern used in
the bus package tests.
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* feat(feishu): add interactive card message parsing
Add support for parsing inbound Feishu interactive card messages.
When a user sends a card message, the text content is now extracted
and passed to the LLM for processing.
- Add extractCardText() to recursively extract text from card JSON
- Support both JSON 1.0 (legacy) and JSON 2.0 schema formats
- Handle nested elements: header, body, actions, columns
- Extract text from markdown, lark_md, and plain_text elements
- Add comprehensive unit tests for card parsing
Fixes #<issue_number>
💘 Generated with Crush
Assisted-by: GLM-5 via Crush <crush@charm.land>
* feat(feishu): extract and download images from interactive cards
When receiving interactive card messages, extract embedded images
(img_key, src, icon_key) and download them for LLM processing.
- Add extractCardImageKeys() to recursively extract image keys from card JSON
- Support img elements (img_key, src) and icon elements (icon_key)
- Update downloadInboundMedia() to handle MsgTypeInteractive
- Add comprehensive unit tests for image extraction
Images are downloaded and stored via MediaStore, then appended to
the message content as [image: photo] tags for LLM visibility.
💘 Generated with Crush
Assisted-by: GLM-5 via Crush <crush@charm.land>
* fix(feishu): simplify card parsing - pass raw JSON, only extract images
Address review feedback: text extraction cannot exhaustively handle all
card formats (i18n_elements, div.fields, etc.). Pass raw JSON to LLM
instead - same approach as MsgTypePost. Only image extraction remains
as images must be downloaded for LLM to process.
- Remove extractCardText() and helper functions
- extractContent() now returns raw JSON for MsgTypeInteractive
- Keep extractCardImageKeys() for downloading embedded images
- Update tests to expect raw JSON for interactive cards
* fix(feishu): don't append media tags to interactive card JSON
Appending media tags like "[attachment]" to raw JSON content produces
invalid JSON format. For interactive cards, the JSON already contains
image information and media refs are downloaded separately.
- Skip appendMediaTags for MsgTypeInteractive to preserve valid JSON
- Add test case for interactive card with images
* fix(feishu): filter out external URLs from card image extraction
Only Feishu-hosted image keys (img_xxx, icon_xxx) can be downloaded via
the Feishu API. External URLs in src field (https://...) should be
filtered out to avoid download failures.
- Add isFeishuImageKey() to detect Feishu-hosted keys vs external URLs
- Update extractImageKeysRecursive to skip external URLs in src field
- Add tests for external URL filtering and mixed scenarios
* feat(feishu): support downloading external images from interactive cards
Previously only Feishu-hosted images (img_key, icon_key) could be
downloaded. Now external URLs in src field are also downloaded via
HTTP and made available to the LLM.
- extractCardImageKeys now returns two slices: Feishu keys and external URLs
- Add downloadExternalImage to download images from HTTP URLs
- Update downloadInboundMedia to handle both Feishu API and HTTP downloads
- Update tests for new function signature
* fix(feishu): use HTTP client with timeout for external image downloads
Replaced http.DefaultClient with a client that has a 30-second timeout
to prevent hanging on unresponsive external URLs.
Generated with Crush
Assisted-by: GLM-5 via Crush <crush@charm.land>
* fix(feishu): resolve lint errors for shadow and formatting
- Rename err variables to avoid shadowing in downloadExternalImage
- Fix struct field alignment in TestExtractCardImageKeys
Generated with Crush
Assisted-by: GLM-5 via Crush <crush@charm.land>
* refactor(feishu): pass external image URLs to LLM instead of downloading
Instead of downloading external images from interactive cards, pass
the URLs directly to LLM. This reduces network overhead and lets
vision-capable models fetch images as needed.
- Remove downloadExternalImage function
- Append external URLs to card content for LLM processing
- Only download Feishu-hosted images via API
💘 Generated with Crush
Assisted-by: GLM-5 via Crush <crush@charm.land>
* fix(feishu): add blank line between functions for gci formatting
* fix(feishu): keep interactive card content as valid JSON
When both providers and model_list are configured, model_list entries
with empty api_key or api_base now automatically inherit from the
matching provider (matched by protocol prefix in the Model field).
Example: a model_list entry with model='deepseek/deepseek-chat' and
no api_key will inherit from providers.deepseek.api_key.
Explicit model_list values always take precedence.
Changes:
- Add InheritProviderCredentials() in migration.go
- Call it in LoadConfig() after provider-to-model-list conversion
- Add protocolProviderMapping for all 25 supported protocols
- 6 new tests covering inheritance, precedence, and edge cases
Closes#1635
* feat(wecom): add WebSocket long-connection support for WeCom AI Bot
- Introduced WeComAIBotWSChannel to handle WebSocket connections.
- Updated NewWeComAIBotChannel to prioritize WebSocket mode when BotID and Secret are provided.
- Enhanced WeComAIBotConfig to include BotID and Secret for WebSocket mode.
- Implemented message handling for text, image, voice, and mixed messages in WebSocket mode.
- Added tests for WebSocket mode functionality and ensured backward compatibility with webhook mode.
- Refactored existing code to improve clarity and maintainability.
* feat(wecom): implement periodic processing hints and enforce WeCom stream deadline
* feat(wecom): update WeCom AI Bot setup instructions and configuration parameters
* feat(wecom): enhance WeCom AI Bot with image handling and media support
* feat(wecom): refactor WeCom AI Bot task management to use req_id for concurrent message handling
* feat(wecom): refactor WeCom AI Bot to manage request states and late replies
* feat(wecom): add response timeout handling and improve WebSocket command acknowledgment
* fix(wecom): improve error handling for late reply proactive push delivery
* refactor(wecom): reorganize WeCom AI Bot configuration fields for improved readability
* fix(wecom): update error message for websocket delivery failure in late reply proactive push
* feat(wecom): implement shared HTTP clients for WeCom image handling and response URL posting
* refactor(wecom): simplify image download and storage process in storeWSImage
* fix(wecom): improve error logging for WebSocket message handling and proactive push delivery
* fix(wecom): enhance WebSocket connection stability and task cancellation handling
* fix(wecom): improve WS image message handling by ensuring proper error response and initializing mediaRefs
* feat(wecom): enhance WeCom AIBot WebSocket handling with message deduplication and support for file and video messages
* refactor(wecom): rename image handling functions to media handling and enhance media type support
* feat(wecom): implement byte-aware content splitting for WeCom AI Bot stream messages
* refactor(wecom): remove max message length constraint from WeCom AIBot WS channel
* 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.
* feat(feishu): add Lark (international) support via IsLark config field
Add IsLark field to FeishuConfig to switch between Feishu and Lark
domains. Also fix domain inconsistency where WS client defaulted to
LarkBaseUrl while HTTP client used FeishuBaseUrl.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* docs: update documentation and web UI for Lark support
Add is_lark field to config example, feishu docs, i18n translations,
and web frontend form.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
* fix(tools): propagate tool registry to subagents via Clone
SubagentManager was created with an empty ToolRegistry and SetTools()
was never called, causing all subagent tool invocations to fail with
"tool not found". This was a regression from the multi-agent refactor.
Fix: clone the parent agent's tool registry into the subagent manager
after creation but before spawn/spawn_status registration — giving
subagents access to file, exec, web, and other tools while preventing
recursive subagent spawning.
- Add ToolRegistry.Clone() for independent shallow copies
- Call subagentManager.SetTools(agent.Tools.Clone()) in registerSharedTools
- Add tests for Clone isolation, empty clone, and hidden tool state
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
* fix(tools): fix cron_test build error and add TTL clone test
- Fix cron_test.go:229 — replace non-existent SubscribeOutbound(ctx)
with select on OutboundChan(), matching the MessageBus channel API
- Add TestToolRegistry_Clone_PreservesTTLValue per reviewer feedback
- Add version reset note to Clone() doc comment
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
---------
Co-authored-by: Claude Opus 4.6 <noreply@anthropic.com>
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
The Lark SDK v3's built-in token retry loop does not clear stale tokens
from cache when the server returns error 99991663 (tenant_access_token
invalid), causing all API calls to fail until the token naturally
expires (~2 hours).
- Add tokenCache struct (implementing larkcore.Cache) with
Get/Set/InvalidateAll methods and proper expired-entry cleanup
- Wire custom cache into lark.NewClient via WithTokenCache()
- Add invalidateTokenOnAuthError helper called in all API methods
* 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>
* fix(telegram): improve HTML chunking and preserve word boundaries
* fix(telegram): address copilot feedback, filter empty chunks and add word-boundary regression test
* style(telegram): fix gofmt and gci lint errors in tests
* fix to feedback
* 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
RussellLuo