feat: agent brain (ollama) and chat ui

.living_spec/README.md

@@ -87,7 +87,8 @@ When the LLM context window fills up (or the chat gets slow/confused):
 If a user hands you this document and says "Apply this process to my project":
 
 1.  **Analyze the Request:** Ask for the high-level goal ("What are we building?") and the tech preferences ("Rust or Python?").
-2.  **Scaffold:** Run commands to create the `specs/` and `stories/` folders.
-3.  **Draft Context:** Write `specs/00_CONTEXT.md` based on the user's answer.
-4.  **Draft Stack:** Write `specs/tech/STACK.md` based on best practices for that language.
-5.  **Wait:** Ask the user for "Story #1".
+2.  **Git Check:** Check if the directory is a git repository (`git status`). If not, run `git init`.
+3.  **Scaffold:** Run commands to create the `specs/` and `stories/` folders.
+4.  **Draft Context:** Write `specs/00_CONTEXT.md` based on the user's answer.
+5.  **Draft Stack:** Write `specs/tech/STACK.md` based on best practices for that language.
+6.  **Wait:** Ask the user for "Story #1".

.living_spec/specs/functional/AI_INTEGRATION.md

@@ -0,0 +1,29 @@
+# Functional Spec: AI Integration
+
+## 1. Provider Abstraction
+The system uses a pluggable architecture for LLMs. The `ModelProvider` interface abstracts:
+*   **Generation:** Sending prompt + history + tools to the model.
+*   **Parsing:** Extracting text content vs. tool calls from the raw response.
+
+## 2. Ollama Implementation
+*   **Endpoint:** `http://localhost:11434/api/chat`
+*   **JSON Protocol:**
+    *   Request: `{ model: "name", messages: [...], stream: false, tools: [...] }`
+    *   Response: Standard Ollama JSON with `message.tool_calls`.
+*   **Fallback:** If the specific local model doesn't support native tool calling, we may need a fallback system prompt approach, but for this story, we assume a tool-capable model (like `llama3.1` or `mistral-nemo`).
+
+## 3. Chat Loop (Backend)
+The `chat` command acts as the **Agent Loop**:
+1.  Frontend sends: `User Message`.
+2.  Backend appends to `SessionState.history`.
+3.  Backend calls `OllamaProvider`.
+4.  **If Text Response:** Return text to Frontend.
+5.  **If Tool Call:**
+    *   Backend executes the Tool (using the Core Tools from Story #2).
+    *   Backend appends `ToolResult` to history.
+    *   Backend *re-prompts* Ollama with the new history (recursion).
+    *   Repeat until Text Response or Max Turns reached.
+
+## 4. Frontend State
+*   **Settings:** Store `llm_provider` ("ollama"), `ollama_model` ("llama3.2"), `ollama_base_url`.
+*   **Chat:** Display the conversation. Tool calls should be visible as "System Events" (e.g., collapsed accordions).

.living_spec/specs/tech/STACK.md

@@ -78,6 +78,8 @@ To support both Remote and Local models, the system implements a `ModelProvider`
     *   `walkdir`: Simple directory traversal.
     *   `tokio`: Async runtime.
     *   `reqwest`: For LLM API calls (if backend-initiated).
+    *   `uuid`: For unique message IDs.
+    *   `chrono`: For timestamps.
     *   `tauri-plugin-dialog`: Native system dialogs.
 *   **JavaScript:**
     *   `@tauri-apps/api`: Tauri Bridge.

.living_spec/stories/archive/03_llm_ollama.md

@@ -0,0 +1,22 @@
+# Story: The Agent Brain (Ollama Integration)
+
+## User Story
+**As a** User
+**I want to** connect the Assistant to a local Ollama instance
+**So that** I can chat with the Agent and have it execute tools without sending data to the cloud.
+
+## Acceptance Criteria
+*   [ ] Backend: Implement `ModelProvider` trait/interface.
+*   [ ] Backend: Implement `OllamaProvider` (POST /api/chat).
+*   [ ] Backend: Implement `chat(message, history, provider_config)` command.
+    *   [ ] Must support passing Tool Definitions to Ollama (if model supports it) or System Prompt instructions.
+    *   [ ] Must parse Tool Calls from the response.
+*   [ ] Frontend: Settings Screen to toggle "Ollama" and set Model Name (default: `llama3`).
+*   [ ] Frontend: Chat Interface.
+    *   [ ] Message History (User/Assistant).
+    *   [ ] Tool Call visualization (e.g., "Running git status...").
+
+## Out of Scope
+*   Remote Providers (Anthropic/OpenAI) - Future Story.
+*   Streaming responses (wait for full completion for MVP).
+*   Complex context window management (just send full history for now).