Store per-session config in SQLite and route /model and /reset through command fast-paths so channel sessions keep independent model selection across reconnects and restarts.
Add runtime truthfulness modes and autonomy-level tool gating with audit metadata for overrides/denials.
Wire policy through prompt assembly, tool execution context, and daemon/gateway agent paths; update tests and planning state for Phase 3 PR #2 completion.
Replace manual process management with systemctl --user commands.
Uses ollama.service and llama-server.service units for proper lifecycle
management, VRAM cleanup, and integration with system services.
Track PIDs of backends started by /backend command and only kill those
specific PIDs. Previous implementation used pkill which would kill all
Ollama/llama-server processes including those started by the user or
systemd services. Now we only terminate processes we started.
- Add local_providers with ollama and llamacpp configurations
- /backend command now stops current daemon before starting new one
- Start backends as detached processes to avoid blocking TUI
- Wait 500ms for daemon to initialize before switching
- Add session_config SQLite table for per-session settings
- Update routing to support session override → agent config → global default resolution chain
- Upgrade WebChat SessionBridge from NativeAgent to AgentOrchestrator
- Add /model, /local, /cloud commands to Telegram adapter
- Add /model command to WebChat gateway handlers
- Clear session overrides on /reset command
- Pass memoryStore and config through to SessionBridge
- Add comprehensive tests for all new functionality
Fixes model persistence bug where TUI model changes didn't affect WebChat/Telegram sessions. Now:
- TUI /model sets global default (persists across restarts, affects all new sessions)
- WebChat/Telegram /model sets session override (only that conversation, cleared on /reset)
- WebChat sessions gain AgentOrchestrator features (delegation, compaction, memory)
- Send user feedback when voice/audio download fails instead of silent failure
- Send graceful message when audio transcription is not configured instead of empty text which crashes API
- Add capabilities.test.ts (18 tests) for supportsAudioInput()
- Add 15 audio tests to media.test.ts (hasAudio, stripAudioParts, attachmentToAudioSource)
- Add estimateAudioTokens() to tokens.ts (base64→bytes→duration→tokens)
- Update estimateMessageTokens() to include audio content parts
- Add 5 audio token tests to tokens.test.ts
- Add supports_audio config override to model schema
- Wire supports_audio from tier config through routing to capability check
Total tests: 1369 (was 1331, +38 audio-related)
- Create capabilities.ts with supportsAudioInput() detection
- Gemini, OpenAI, and GitHub Models get native audio passthrough
- Anthropic, Bedrock, Ollama, llama.cpp fall back to Whisper transcription
- routing.ts now checks model capability before deciding to transcribe
- Audio attachments are stripped for non-native models (only transcript text passed)
- Remove deprecated audioConfig from createMessageRouter deps (read from config.audio)
- Add AudioSource interface and 'audio' variant to MessageContentPart union
- Update buildUserMessage() to create audio content parts from attachments
- Add attachmentToAudioSource(), hasAudio(), stripAudioParts() helpers
- Gemini: native audio via inlineData (same format as images)
- OpenAI/GitHub: native audio via input_audio content parts
- Anthropic/Bedrock: graceful fallback to transcript text
- Update getMessageTextWithTools() to handle audio blocks for local models
- Add createAudioTranscribeTool with OpenAI/Groq/Ollama/llama.cpp provider support
- Refactor audio config schema to nested audio.enabled + audio.provider structure
- Move audio tool registration to initTools() for conditional enablement
- Fix duplication bug in audio-transcribe.ts URL download handler
- Support base64 data and URL-based audio input with format detection
- Add curly braces to all if/else/for/while statements
- Fix indentation and trailing spaces
- Auto-fixed 372 linting errors using eslint --fix
- Remaining issues are warnings only (non-null assertions, explicit any types)
OpenAI-compatible providers return 'stop' and 'tool_calls' as finish_reason
values, but Flynn's agent loop expects Anthropic-style 'end_turn' and
'tool_use'. This caused the agent to exit the tool loop prematurely when
falling back to GitHub Copilot (due to Anthropic API quota exhaustion).
- openai.ts: Map 'stop' → 'end_turn', 'length' → 'max_tokens', tool_calls
with actual tools → 'tool_use', tool_calls without tools → 'end_turn'
- github.ts: Handle edge case where finish_reason is 'tool_calls' but no
tools were parsed
- agent.ts: Accept both 'tool_use' and 'tool_calls' as valid stop reasons
(belt-and-suspenders), extract toolCalls to local variable for TS narrowing
- openai.test.ts: Update expectations to match new normalized values
- agent.ts: track consecutive calls to the same tool (ignoring args) and
inject a nudge after 4 repeats telling the model to summarize and respond,
preventing local models from endlessly retrying searches with slight
query variations
- agent.ts: wrap the entire tool loop iteration in try-catch so model/network
errors don't crash the daemon — returns a descriptive error message instead
- Tests for both: nudge triggers after 4 same-tool calls, error recovery
persists to history
William Valentin