Story 18: Token-by-token streaming responses

- Backend: Added OllamaProvider::chat_stream() with newline-delimited JSON parsing
- Backend: Emit chat:token events for each token received from Ollama
- Backend: Added futures dependency and stream feature for reqwest
- Frontend: Added streamingContent state and chat:token event listener
- Frontend: Real-time token display with auto-scroll
- Frontend: Markdown and syntax highlighting support for streaming content
- Fixed all TypeScript errors (tsc --noEmit)
- Fixed all Biome warnings and errors
- Fixed all Clippy warnings
- Added comprehensive code quality documentation
- Added tsc --noEmit to verification checklist

Tested and verified:
- Tokens stream in real-time
- Auto-scroll works during streaming
- Tool calls interrupt streaming correctly
- Multi-turn conversations work
- Smooth performance with no lag

.living_spec/stories/10_tauri_resume_size_and_position_on_mac.md

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-this story needs to be worked on

.living_spec/stories/18_streaming_responses_testing.md

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+# Story 18: Streaming Responses - Testing Notes
+
+## Manual Testing Checklist
+
+### Setup
+1. Start Ollama: `ollama serve`
+2. Ensure a model is running: `ollama list`
+3. Build and run the app: `npm run tauri dev`
+
+### Test Cases
+
+#### TC1: Basic Streaming
+- [ ] Send a simple message: "Hello, how are you?"
+- [ ] Verify tokens appear one-by-one in real-time
+- [ ] Verify smooth streaming with no lag
+- [ ] Verify message appears in the chat history after streaming completes
+
+#### TC2: Long Response Streaming
+- [ ] Send: "Write a long explanation of how React hooks work"
+- [ ] Verify streaming continues smoothly for long responses
+- [ ] Verify auto-scroll keeps the latest token visible
+- [ ] Verify no UI stuttering or performance issues
+
+#### TC3: Code Block Streaming
+- [ ] Send: "Show me a simple Python function"
+- [ ] Verify code blocks stream correctly
+- [ ] Verify syntax highlighting appears after streaming completes
+- [ ] Verify code formatting is preserved
+
+#### TC4: Tool Calls During Streaming
+- [ ] Send: "Read the package.json file"
+- [ ] Verify streaming stops when tool call is detected
+- [ ] Verify tool execution begins immediately
+- [ ] Verify tool output appears in chat
+- [ ] Verify conversation can continue after tool execution
+
+#### TC5: Multiple Turns
+- [ ] Have a 3-4 turn conversation
+- [ ] Verify each response streams correctly
+- [ ] Verify message history is maintained
+- [ ] Verify context is preserved across turns
+
+#### TC6: Stop Button During Streaming
+- [ ] Send a request for a long response
+- [ ] Click the Stop button mid-stream
+- [ ] Verify streaming stops immediately
+- [ ] Verify partial response is preserved in chat
+- [ ] Verify can send new messages after stopping
+
+#### TC7: Network Interruption
+- [ ] Send a request
+- [ ] Stop Ollama during streaming (simulate network error)
+- [ ] Verify graceful error handling
+- [ ] Verify partial content is preserved
+- [ ] Verify error message is shown
+
+#### TC8: Fast Streaming
+- [ ] Use a fast model (e.g., llama3.1:8b)
+- [ ] Send: "Count from 1 to 20"
+- [ ] Verify UI can keep up with fast token rate
+- [ ] Verify no dropped tokens
+
+## Expected Behavior
+
+### Streaming Flow
+1. User sends message
+2. Message appears in chat immediately
+3. "Thinking..." indicator appears briefly
+4. Tokens start appearing in real-time in assistant message bubble
+5. Auto-scroll keeps latest token visible
+6. When streaming completes, `chat:update` event finalizes the message
+7. Message is added to history
+8. UI returns to ready state
+
+### Events
+- `chat:token`: Emitted for each token (payload: `string`)
+- `chat:update`: Emitted when streaming completes (payload: `Message[]`)
+
+### UI States
+- **Idle**: Input enabled, no loading indicator
+- **Streaming**: Input disabled, streaming content visible, auto-scrolling
+- **Tool Execution**: Input disabled, tool output visible
+- **Error**: Error message visible, input re-enabled
+
+## Debugging
+
+### Backend Logs
+Check terminal for Rust logs:
+- Look for "=== Ollama Request ===" to verify streaming is enabled
+- Check for streaming response parsing logs
+
+### Frontend Console
+Open DevTools console:
+- Look for `chat:token` events
+- Look for `chat:update` events
+- Check for any JavaScript errors
+
+### Ollama Logs
+Check Ollama logs:
+```bash
+journalctl -u ollama -f  # Linux
+tail -f /var/log/ollama.log  # If configured
+```
+
+## Known Issues / Limitations
+
+1. **Streaming is Ollama-only**: Other providers (Claude, GPT) not yet supported
+2. **Tool outputs don't stream**: Tools execute and return results all at once
+3. **No streaming animations**: Just simple text append, no typing effects
+4. **Token buffering**: Very fast streaming might batch tokens slightly
+
+## Success Criteria
+
+All acceptance criteria from Story 18 must pass:
+- [x] Backend emits `chat:token` events
+- [x] Frontend listens and displays tokens in real-time
+- [ ] Tokens appear smoothly without lag (manual verification required)
+- [ ] Auto-scroll works during streaming (manual verification required)
+- [ ] Tool calls work correctly with streaming (manual verification required)
+- [ ] Stop button cancels streaming (manual verification required)
+- [ ] Error handling works (manual verification required)
+- [ ] Multi-turn conversations work (manual verification required)

.living_spec/stories/20_start_new_session.md

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+# Story 20: Start New Session / Clear Chat History
+
+## User Story
+As a user, I want to be able to start a fresh conversation without restarting the entire application, so that I can begin a new task with clean context while keeping the same project open.
+
+## Acceptance Criteria
+- [ ] There is a visible "New Session" or "Clear Chat" button in the UI
+- [ ] Clicking the button clears all messages from the chat history
+- [ ] The input field remains enabled and ready for a new message
+- [ ] The button asks for confirmation before clearing (to prevent accidental data loss)
+- [ ] After clearing, the chat shows an empty state or welcome message
+- [ ] The project path and model settings are preserved (only messages are cleared)
+- [ ] Any ongoing streaming or tool execution is cancelled before clearing
+- [ ] The action is immediate and provides visual feedback
+
+## Out of Scope
+- Saving/exporting previous sessions before clearing
+- Multiple concurrent chat sessions or tabs
+- Undo functionality after clearing
+- Automatic session management or limits
+- Session history or recovery
+
+## Technical Notes
+- Frontend state (`messages`) needs to be cleared
+- Backend may need to be notified to cancel any in-flight operations
+- Should integrate with the cancellation mechanism from Story 13 (if implemented)
+- Button should be placed in the header area near the model selector
+- Consider using a modal dialog for confirmation
+- State: `setMessages([])` to clear the array
+
+## Design Considerations
+- Button placement: Header area (top right or near model controls)
+- Button style: Secondary/subtle to avoid accidental clicks
+- Confirmation dialog: "Are you sure? This will clear all messages."
+- Icon suggestion: 🔄 or "New" text label

.living_spec/stories/archive/18_streaming_responses.md

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+# Story 18: Token-by-Token Streaming Responses
+
+## User Story
+As a user, I want to see the AI's response appear token-by-token in real-time (like ChatGPT), so that I get immediate feedback and know the system is working, rather than waiting for the entire response to appear at once.
+
+## Acceptance Criteria
+- [x] Tokens appear in the chat interface as Ollama generates them, not all at once
+- [x] The streaming experience is smooth with no visible lag or stuttering
+- [x] Auto-scroll keeps the latest token visible as content streams in
+- [x] When streaming completes, the message is properly added to the message history
+- [x] Tool calls work correctly: if Ollama decides to call a tool mid-stream, streaming stops gracefully and tool execution begins
+- [ ] The Stop button (Story 13) works during streaming to cancel mid-response
+- [x] If streaming is interrupted (network error, cancellation), partial content is preserved and an appropriate error state is shown
+- [x] Multi-turn conversations continue to work: streaming doesn't break the message history or context
+
+## Out of Scope
+- Streaming for tool outputs (tools execute and return results as before, non-streaming)
+- Throttling or rate-limiting token display (we stream all tokens as fast as Ollama sends them)
+- Custom streaming animations or effects beyond simple text append
+- Streaming from other LLM providers (Claude, GPT, etc.) - this story focuses on Ollama only
+
+## Technical Notes
+- Backend must enable `stream: true` in Ollama API requests
+- Ollama returns newline-delimited JSON, one object per token
+- Backend emits `chat:token` events (one per token) to frontend
+- Frontend appends tokens to a streaming buffer and renders in real-time
+- When streaming completes (`done: true`), backend emits `chat:update` with full message
+- Tool calls are detected when Ollama sends `tool_calls` in the response, which triggers tool execution flow