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6 Commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
 LiBr
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df8fbd8859 | feat(provider): add github copilot device flow provider (#364) | ||
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Acbox Liu
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8d5c38f0e5 |
refactor: unify providers and models tables (#338)
* refactor: unify providers and models tables
- Rename `llm_providers` → `providers`, `llm_provider_oauth_tokens` → `provider_oauth_tokens`
- Remove `tts_providers` and `tts_models` tables; speech models now live in the unified `models` table with `type = 'speech'`
- Replace top-level `api_key`/`base_url` columns with a JSONB `config` field on `providers`
- Rename `llm_provider_id` → `provider_id` across all references
- Add `edge-speech` client type and `conf/providers/edge.yaml` default provider
- Create new read-only speech endpoints (`/speech-providers`, `/speech-models`) backed by filtered views of the unified tables
- Remove old TTS CRUD handlers; simplify speech page to read-only + test
- Update registry loader to skip malformed YAML files instead of failing entirely
- Fix YAML quoting for model names containing colons in openrouter.yaml
- Regenerate sqlc, swagger, and TypeScript SDK
* fix: exclude speech providers from providers list endpoint
ListProviders now filters out client_type matching '%-speech' so Edge
and future speech providers no longer appear on the Providers page.
ListSpeechProviders uses the same pattern match instead of hard-coding
'edge-speech'.
* fix: use explicit client_type list instead of LIKE pattern
Replace '%-speech' pattern with explicit IN ('edge-speech') for both
ListProviders (exclusion) and ListSpeechProviders (inclusion). New
speech client types must be added to both queries.
* fix: use EXECUTE for dynamic SQL in migrations referencing old schema
PL/pgSQL pre-validates column/table references in static SQL statements
inside DO blocks before evaluating IF/RETURN guards. This caused
migrations 0010-0061 to fail on fresh databases where the canonical
schema uses `providers`/`provider_id` instead of `llm_providers`/
`llm_provider_id`.
Wrap all SQL that references potentially non-existent old schema objects
(llm_providers, llm_provider_id, tts_providers, tts_models, etc.) in
EXECUTE strings so they are only parsed at runtime when actually reached.
* fix: revert canonical schema to use llm_providers for migration compatibility
The CI migrations workflow (up → down → up) failed because 0061 down
renames `providers` back to `llm_providers`, but 0001 down only dropped
`providers` — leaving `llm_providers` as a remnant. On the second
migrate up, 0010 found the stale `llm_providers` and tried to reference
`models.llm_provider_id` which no longer existed.
Revert 0001 canonical schema to use original names (llm_providers,
tts_providers, tts_models) so incremental migrations work naturally and
0061 handles the final rename. Remove EXECUTE wrappers and unnecessary
guards from migrations that now always operate on llm_providers.
* fix: icons
* fix: sync canonical schema with 0061 migration to fix sqlc column mismatch
0001_init.up.sql still used old names (llm_providers, llm_provider_id)
and included dropped tts_providers/tts_models tables. sqlc could not
parse the PL/pgSQL EXECUTE in migration 0061, so generated code retained
stale columns (input_modalities, supports_reasoning) causing runtime
"column does not exist" errors when adding models.
- Update 0001_init.up.sql to current schema (providers, provider_id,
no tts tables, add provider_oauth_tokens)
- Use ALTER TABLE IF EXISTS in 0010/0041/0042 for backward compat
- Regenerate sqlc
* fix: guard all legacy migrations against fresh schema for CI compat
On fresh databases, 0001_init.up.sql creates providers/provider_id
(not llm_providers/llm_provider_id). Migrations 0013, 0041, 0046, 0047
referenced the old names without guards, causing CI migration failures.
- 0013: check llm_provider_id column exists before adding old constraint
- 0041: check llm_providers table exists before backfill/constraint DDL
- 0046: wrap CREATE TABLE in DO block with llm_providers existence check
- 0047: use ALTER TABLE IF EXISTS + DO block guard
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Yiming Qi
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64378d29ed |
feat: openai codex support (#292)
* feat(web): add provider oauth management ui * feat: add OAuth callback support on port 1455 * feat: enhance reasoning effort options and support for OpenAI Codex OAuth * feat: update twilight-ai dependency to v0.3.4 * refactor: promote openai-codex to first-class client_type, remove auth_type Replace the previous openai-responses + metadata auth_type=openai-codex-oauth combo with a dedicated openai-codex client_type. OAuth requirement is now determined solely by client_type, eliminating the auth_type concept from the LLM provider domain entirely. - Add openai-codex to DB CHECK constraint (migration 0047) with data migration - Add ClientTypeOpenAICodex constant and dedicated SDK/probe branches - Remove AuthType from SDKModelConfig, ModelCredentials, TriggerConfig, etc. - Simplify supportsOAuth to check client_type == openai-codex - Add conf/providers/codex.yaml preset with Codex catalog models - Frontend: replace auth_type selector with client_type-driven OAuth UI --------- Co-authored-by: Acbox <acbox0328@gmail.com> |
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Acbox
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65b2797626 |
refactor: unify SDK model factories into internal/models
Move CreateModel, BuildReasoningOptions, ReasoningBudgetTokens and related types from internal/agent to internal/models as NewSDKChatModel, SDKModelConfig, etc. This eliminates duplicate ClientType constants and centralises all Twilight AI SDK instance creation in a single package. NewSDKEmbeddingModel now accepts a clientType parameter and dispatches to the native Google embedding provider for google-generative-ai, instead of always using the OpenAI-compatible endpoint. |
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Acbox Liu
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b88ca96064 |
refactor: provider & models (#277)
* refactor: move client_type to provider, replace model fields with config JSONB - Move `client_type` from `models` to `llm_providers` table - Add `icon` field to `llm_providers` - Replace `dimensions`, `input_modalities`, `supports_reasoning` on `models` with a single `config` JSONB column containing `dimensions`, `compatibilities` (vision, tool-call, image-output, reasoning), and `context_window` - Auto-imported models default to vision + tool-call + reasoning - Update all backend consumers (agent, flow resolver, handlers, memory) - Regenerate sqlc, swagger, and TypeScript SDK - Update frontend forms, display, and i18n for new schema * ui: show provider icon avatar in sidebar and detail header, remove icon input * feat: add built-in provider registry with YAML definitions and enable toggle - Add `enable` column to llm_providers (default true, backward-compatible) - Create internal/registry package to load YAML provider/model definitions on startup and upsert into database (new providers disabled by default) - Add conf/providers/ with OpenAI, Anthropic, Google YAML definitions - Add RegistryConfig to TOML config (providers_dir, default conf/providers) - Model listing APIs and conversation flow now filter by enabled providers - Frontend: enable switch in provider form, green status dot in sidebar, enabled providers sorted to top * fix: make 0041 migration idempotent for fresh databases Guard data migration steps with column-existence checks so the migration succeeds on databases created from the updated init schema. |
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Acbox Liu
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7d7d0e4b51 |
refactor: introduce multi-session chat support (#session) (#267)
* refactor: introduce multi-session chat support (#session)
Replace the single-context-per-bot model with multiple chat sessions.
Database:
- Add bot_sessions table (route_id, channel_type, title, metadata, soft delete)
- Migrate bot_history_messages from (route_id, channel_type) to session_id
- Add active_session_id to bot_channel_routes
- Migration 0036 handles data migration from existing messages
Backend:
- New internal/session service for session CRUD
- Update message service/types to use session_id instead of route_id
- Update conversation flow (resolver, history, store) for session context
- Channel inbound auto-creates/retrieves active session via SessionEnsurer
- New REST endpoints: /bots/:bot_id/sessions (CRUD)
- WebSocket and message handlers accept optional session_id
- Wire session service into FX dependency graph (agent + memoh)
Frontend:
- Refactor chat store: sessions replaces chats, sessionId replaces chatId
- Session-aware message loading, sending, and pagination
- WebSocket sends include session_id
- New session sidebar component with select/delete
- Chat area header shows active session title + new session button
- API layer updated: fetchSessions, createSession, deleteSession
- i18n strings for session management (en + zh)
SDK:
- Regenerated TypeScript SDK and Swagger docs with session endpoints
* fix: update tests for session refactoring (RouteID → SessionID)
Remove references to removed RouteID and Platform fields from
PersistInput/Message in channel_test.go and service_integration_test.go.
* fix: restore accidentally deleted SDK files and guard migration 0032
- Restore packages/sdk/src/container-stream.ts and extra/index.ts that
were accidentally removed during SDK regeneration
- Wrap migration 0032 route_id index creation in a column existence check
to avoid failure on fresh databases where 0001_init.up.sql no longer
has route_id
* fix: guard migration 0036 data steps for fresh databases
Wrap steps 3-7 (which reference route_id/channel_type on
bot_history_messages) in a column existence check so the migration
is safe on fresh databases where 0001_init.up.sql already reflects
the final schema without those columns.
* feat: add title model setting and auto-generate session titles on user input
- Add title_model_id to bots table (migration 0037) and bot settings API
- Implement async title generation triggered at user message time (not after
assistant response) for faster title availability
- Publish session_title_updated events via SSE event hub for real-time
frontend updates without page refresh
- Fix SSE message event parsing: use direct JSON.parse instead of
normalizeStreamEvent which silently dropped non-chat-stream event types
- Add title model selector in bot settings UI with i18n support
* fix: session-scoped message filtering and URL-based chat routing
- Filter realtime SSE messages by session_id to prevent cross-session
message leakage after page refresh
- Add /chat/:sessionId? route with bidirectional URL ↔ store sync
- Visiting /chat shows a clean state with no bot or session pre-selected
- Visiting /chat/:sessionId loads the specific session directly
- Session switches from sidebar automatically update the URL
- Fix stale RouteID field in dedupe test (removed during session refactor)
* fix: skip cross-channel stream events to prevent session leakage
The bot-level web stream pushes events from all channels (Telegram,
Discord, etc.) without session_id context. Previously these were
rendered inline in the current chat view regardless of session.
Now cross-channel events are ignored in handleLocalStreamEvent;
persisted messages arrive via the SSE message events stream with
proper session_id filtering through appendRealtimeMessage.
* feat: show IM avatars and platform badges on session sidebar
- Add sender_avatar_url to route metadata from identity resolution
- Resolve group avatar and handle via directory adapter for group chats
- JOIN bot_channel_routes in ListSessionsByBot to return route metadata
- Display avatar with ChannelBadge on IM session items (group avatar
for groups, sender avatar for private chats)
- Show @groupname or @username as session sub-label
* fix: clean up RunConfig unused fields, fix skill system and copy bug
- Remove unused RunConfig fields: Tools, Channels, CurrentChannel,
ActiveContextTime
- Remove unused SessionContext fields: DisplayName, ConversationType
- Fix EnabledSkillNames copy bug: make([]string, 0, n) + copy copies
zero elements; changed to make([]string, n)
- Fix prepareRunConfig dead code: remove no-op loop over
CurrentPlatform runes; compute supportsImageInput from model's
InputModalities
- Fix EnabledSkills always nil in system prompt: resolve enabled skill
entries from EnabledSkillNames + Skills
- Fix use_skill tool returning empty response: now returns full skill
content (description + instructions) so LLM gets it in the same turn
- Skip use_skill tool registration when no skills are available
- Conditionally render Skills section in system prompt (hidden when
no skills exist)
* feat: add session type field and bind sessions to heartbeat/schedule executions
- Add `type` column to `bot_sessions` (chat | heartbeat | schedule)
- Add `session_id` to `bot_heartbeat_logs` for per-execution session tracking
- Create `schedule_logs` table binding schedule_id + session_id
- Heartbeat and schedule runs now create independent sessions and persist
agent messages via storeRound, enabling full conversation replay
- Add schedule logs API endpoints (list by bot, list by schedule, delete)
- Update Triggerer interfaces to return TriggerResult with status/usage/model
* refactor: modular system prompts per session type (chat/heartbeat/schedule)
Split the monolithic system.md into three type-specific system prompts
with shared fragments via {{include:_xxx}} syntax, so each session type
gets a focused prompt without irrelevant instructions.
* fix: prevent message duplication after task completion
message_created events from Persist() had an empty platform field because
toMessageFromCreate() didn't extract it from the session. This caused
appendRealtimeMessage to fail the platform === 'web' guard, and
hasMessageWithId to fail because local IDs differ from server UUIDs,
resulting in all messages being appended as duplicates.
- Extract platform from metadata in toMessageFromCreate so published events
carry the correct value
- Pass channel_type: 'web' when creating sessions from the web frontend so
List queries return the correct platform via the session JOIN
* fix: use per-message usage from SDK instead of misaligned step-level usages
Previously, token usage was stored via a separate per-step usages array
that didn't align with messages (off-by-one from prepending user message,
step count != message count). This caused:
- User messages incorrectly receiving usage data
- Usage values shifted across messages in multi-step rounds
- Last assistant message getting the accumulated total instead of its own step usage
- InputTokenDetails/OutputTokenDetails lost during manual accumulation
Now each sdk.Message carries its own per-step Usage (set by the SDK in
buildStepMessages), which is extracted in sdkMessagesToModelMessages and
stored directly via ModelMessage.Usage. The storeRound/storeMessages path
no longer needs external usage/usages parameters.
Also fixes the totalUsage accumulation in runStream to include all detail
fields (InputTokenDetails, OutputTokenDetails).
* feat: add /new slash command to create a new active session from IM channels
Users in Telegram/Discord/Feishu can now send /new to start a fresh
conversation, resetting the session context for the current chat thread.
The command resolves the channel route, creates a new session, sets it as
the active session on the route, and replies with a confirmation message.
* feat: distinguish heartbeat and schedule sessions with dedicated icons in sidebar
Heartbeat sessions show a heart-pulse icon (rose), schedule sessions
show a clock icon (amber), and both display a type label beneath the
session title.
* refactor: remove enabledSkills system prompt injection, keep sorted skill listing
use_skill now returns skill content directly as tool output, so there is
no need to inject enabled skill body text into the system prompt. Remove
the entire enabledSkills tracking chain (RunConfig.EnabledSkillNames,
StreamEvent.Skills, GenerateResult.Skills, ChatRequest/Response.Skills,
enableSkill closures in runStream/runGenerate, prepareRunConfig matching).
Keep a lightweight skills listing (name + description only) in the system
prompt so the model knows which skills are available. Sort entries by name
to guarantee deterministic ordering and maximize KV cache reuse.
* refactor: remove inbox system, persist passive messages directly to history
Replace the bot_inbox table and service with direct writes to
bot_history_messages for group conversations where the bot is not
@mentioned. Trigger-path messages continue to be persisted after the
agent responds (unchanged).
- Drop bot_inbox table and max_inbox_items column (migration 0039)
- Delete internal/inbox/, handlers/inbox.go, command/inbox.go,
agent/tools/inbox.go and the MCP message provider
- Add persistPassiveMessage() in channel inbound to write user
messages into the active session immediately
- Rewrite ListObservedConversationsByChannelIdentity to query
bot_history_messages + bot_sessions instead of bot_inbox
- Extract shared send/react logic into internal/messaging/executor.go;
agent/tools/message.go is now a thin SDK adapter
- Clean up all inbox references from agent prompts, flow resolver,
email trigger, settings, commands, DI wiring, and frontend
- Regenerate sqlc, swagger, and SDK
* feat: add list_sessions and search_messages agent tools
Provide agents with the ability to query session metadata and search
message history across all sessions. search_messages supports filtering
by time range, keyword (JSONB-aware ILIKE), session, contact, and role,
with a default 7-day lookback when no start_time is given.
* feat: inject last_heartbeat time and improve heartbeat search guidance
Query the previous heartbeat's started_at timestamp and pass it through
TriggerPayload into the heartbeat prompt template. Update system prompt
and HEARTBEAT.md checklist to guide agents to use search_messages with
start_time=last_heartbeat for efficient cross-session message review.
* fix: pass BridgeProvider to FSClient and store full heartbeat prompt
FSClient was always created with nil provider, causing all container
file reads (IDENTITY.md, SOUL.md, MEMORY.md, HEARTBEAT.md, etc.) to
silently return empty strings. Expose Agent.BridgeProvider() and wire
it into Resolver. Also fix heartbeat trigger to store the full prompt
template as the user message instead of the literal "heartbeat" string.
* feat: add line numbers to container file read output
Move line-number formatting from the bridge gRPC server to the agent
tool layer so that the raw content stored and transmitted via gRPC
remains clean, while the read_file tool output includes numbered lines
for easier reference by the agent.
* chore(deps): update twilight-ai to v0.3.2
* fix: lint, test
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