* fix(tts): config save + Edge provider registration + dark mode chat bubbles
- Wrap TTS config payload in `raw` field for config.patch RPC (#229)
- Always register Edge TTS provider (free, no API key) instead of gating on `enabled` flag
- Fix low-contrast user message bubbles in dark mode chat
* fix(tts): skip duplicate media dispatch when temp file already delivered
When both the agent loop and the message tool dispatch the same TTS
temp file, the first dispatch succeeds and cleanup deletes it. Filter
out missing temp media files before sending to prevent "file not found"
errors and spurious error notifications on Telegram/Slack/Discord.
* feat(tts): include edge-tts in Docker image when Python enabled
Edge TTS is free (no API key) and serves as a universal TTS fallback.
Install it alongside Python in both ENABLE_PYTHON and ENABLE_FULL_SKILLS builds.
* chore(docker): expose build args from .env for compose builds
Pass ENABLE_OTEL, ENABLE_PYTHON, ENABLE_FULL_SKILLS as env-driven
build args so .env can control Docker build features without editing
docker-compose.yml directly.
* fix(tts): hot-reload TTS config on settings change via pub/sub
TTS providers were only registered at startup, so changing provider/API
key via the Web UI had no effect until container restart. Add a
tts-config-reload bus subscriber that rebuilds the TTS manager on
config changes, matching the pattern used by quota, cron, and web_fetch.
Always create a TtsTool at startup (even without providers) so the
reload subscriber can populate it when settings are first configured.
* fix(tts): protect TtsTool.UpdateManager with RWMutex to prevent data race
UpdateManager() can be called from the config reload goroutine while
Execute() reads t.manager concurrently from agent goroutines. Add
sync.RWMutex following the same pattern as WebFetchTool.UpdatePolicy().
Also update setupTTS doc comment which incorrectly stated it could
return nil — Edge TTS is now always registered.
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Co-authored-by: viettranx <viettranx@gmail.com>
* fix(subagent): inherit parent agent's provider instead of alphabetical fallback
Subagents previously used a fixed provider (alphabetically first from the
registry, often "anthropic") regardless of which provider the parent agent
used. This caused invalid combos like anthropic/glm-5 when a zai-coding
agent spawned subagents.
- Pass provider registry to SubagentManager for runtime resolution
- Inject parent provider name into context (WithParentProvider)
- Resolve activeProvider from parent context before LLM call
- Fix trace spans to show actual resolved provider, not default
* fix(providers): api_base fallback from config/env for DB providers
DB providers with empty api_base now inherit from config/env vars
(e.g., GOCLAW_ANTHROPIC_BASE_URL). Prevents proxy API keys from being
sent to the real provider API endpoint.
- Add APIBaseForType() method on ProvidersConfig
- registerProvidersFromDB falls back to config when api_base is empty
- ProvidersHandler uses resolveAPIBase() for model listing
- Add api_base, display_name, settings to provider validation whitelist
* fix(tracing): pass resolved provider name to subagent span emitters
- emitSubagentSpanStart now accepts providerName param instead of
reading sm.provider.Name() — ensures root subagent span reflects
the inherited parent provider, not the fallback default
- registerInMemory now uses resolveAPIBase() so DB providers with
empty api_base inherit the config/env fallback (same as startup path)
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Co-authored-by: viettranx <viettranx@gmail.com>
The embedding provider resolution only matched 3 hardcoded names
(openai, openrouter, gemini), silently failing for DB-stored providers
like "openai-embedding". This caused memory chunks to be stored
without vectors even when a valid embedding provider was configured.
Changes:
- resolveEmbeddingProvider: fallback to provider registry for DB-stored
provider names when hardcoded match fails
- gateway startup: read per-agent memory config from DB (priority over
config file defaults) for embedding provider resolution
- memory IndexDocument: log embedding errors instead of swallowing them
- memory admin ListChunks: return full chunk text instead of truncating
to 200 chars, avoiding confusing partial content in the UI
Co-authored-by: Luvu182 <208665161+Luvu182@users.noreply.github.com>
Part A — Channel quota limiter (managed mode):
- DB-backed per-user/group request quotas with in-memory 60s TTL cache
- Config merge priority: Groups > Channels > Providers > Default
- Per-group quota override via channels.telegram.groups[chatID].quota
- Migration 000009: index on channel_requests for quota queries
- Hot-reload quota config via pub/sub (TopicConfigChanged)
Part B — Per-run tool call budget:
- Soft stop at configurable limit (default 25, per-agent override)
- MaxToolCalls field on AgentDefaults + AgentSpec + LoopConfig
- LLM gets one final call to summarize when budget exceeded
Part C — Web UI + config page refactor:
- QuotaSection with provider/channel dropdowns (useProviders, useChannelInstances)
- Config page refactored to vertical sidebar tabs layout
- Categories: General, Quota, Agents, Tools, Connections, Advanced, Raw Editor
- Fixed config.patch RPC to serialize raw JSON + baseHash correctly
- Config change pub/sub broadcast from handleApply/handlePatch
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Replaces List(ctx, "") + loop with a single-row query
(ORDER BY is_default DESC, created_at ASC LIMIT 1).
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
In managed mode, agents live in the database, not in config files.
ResolveDefaultAgentID() always returns "default" which doesn't exist
as a real agent, causing heartbeat to silently fail.
Add resolveDefaultAgentManaged() helper that checks the managed DB
for the agent marked is_default=true, falling back to the first
available agent. Apply it in setupHeartbeat().
- Replace deprecated text-embedding-004 with gemini-embedding-001
- Add WithDimensions() to OpenAIEmbeddingProvider for dimension truncation
- Pass dimensions=1536 for Gemini to match pgvector column size
- Allow config override of Gemini embedding model via embedding_model
Wire AgentToolPolicy from agent spec through loop creation and resolver, passing it to PolicyEngine.FilterTools for per-agent tool restrictions (nil = no restrictions). Set RestrictToWorkspace=true for default agent in managed mode seeding. Clean up thinking/placeholder messages in Discord and Telegram when agent suppresses empty/NO_REPLY responses by publishing empty outbound and deleting placeholders without sending messages.
Multi-agent AI gateway with WebSocket RPC, HTTP API, and messaging channel integrations.
Go port of OpenClaw with multi-tenant PostgreSQL, per-user isolation, security hardening,
and production observability.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
Duc Nguyen