chore: updated plan

MISTRAL_PLAN.md

@@ -3,10 +3,23 @@
 ## Context
 bDS currently routes all AI chat through the OpenCode Zen gateway (`opencode.ai/zen/v1/...`) with two code paths: Anthropic Messages API and OpenAI-compatible. The user wants Mistral AI added as a direct alternative provider with frontier models that support chat completion, tool use, and vision. Mistral's API is OpenAI-compatible (`api.mistral.ai/v1/chat/completions`), making integration straightforward.
 
+**Important architecture facts:**
+- HTTP requests are currently **non-streaming** (full response body collected, text emitted after each complete call) — to be converted to SSE streaming as part of this work
+- Neither `sendAnthropicMessage()` nor `sendOpenAIMessage()` currently sets `tool_choice`
+- `sendOpenAIMessage()` does **not** convert `view_image` results to `image_url` format — they are JSON-stringified
+- `generateConversationTitle()` is hardcoded to `claude-haiku-4-5` via `ZEN_ANTHROPIC_URL`
+- `analyzeMediaImage()` is hardcoded to `claude-sonnet-4-5` via `ZEN_ANTHROPIC_URL`
+- `checkReady()` only checks the OpenCode key — blocks `sendMessage()` for keyless users
+
 ## Target Models
-- **Mistral Large 3** (`mistral-large-2512`) - frontier, vision, tools, 40k ctx
-- **Mistral Medium 3.1** (`mistral-medium-2508`) - frontier, vision, tools, 40k ctx
-- **Mistral Small 3.2** (`mistral-small-2506`) - vision, tools, 128k ctx
+
+| Model ID | Display Name | Vision | Tools | Context Window | Context Budget |
+|----------|-------------|--------|-------|----------------|----------------|
+| `mistral-large-2512` | Mistral Large 3 | yes | yes | 40k | 35,000 |
+| `mistral-medium-2508` | Mistral Medium 3.1 | yes | yes | 40k | 35,000 |
+| `mistral-small-2506` | Mistral Small 3.2 | yes | yes | 128k | 120,000 |
+| `devstral-small-2505` | Devstral Small | no | yes | 128k | 120,000 |
+| `devstral-large-2506` | Devstral 2 | no | yes | 256k | 240,000 |
 
 ## Files to Modify
 
@@ -21,37 +34,185 @@ bDS currently routes all AI chat through the OpenCode Zen gateway (`opencode.ai/
 'mistral-large-2512': 'Mistral Large 3'
 'mistral-medium-2508': 'Mistral Medium 3.1'
 'mistral-small-2506': 'Mistral Small 3.2'
+'devstral-small-2505': 'Devstral Small'
+'devstral-large-2506': 'Devstral 2'
 ```
 
 **C. Update `detectProvider()`** (lines 1839-1845)
-- Add: `if (id.startsWith('mistral') || id.startsWith('ministral')) return 'mistral';`
+- Add: `if (id.startsWith('mistral') || id.startsWith('ministral') || id.startsWith('devstral') || id.startsWith('codestral') || id.startsWith('pixtral')) return 'mistral';`
+- This covers all current and foreseeable Mistral model prefixes (Mistral, Ministral, Devstral, Codestral, Pixtral)
+
+**C2. Update `formatModelName()` and `UPPERCASE_PREFIXES`**
+- `formatModelName()` (L1869) first checks `MODEL_DISPLAY_NAMES`, then auto-formats via hyphen splitting + capitalization
+- All 5 Mistral models are in `MODEL_DISPLAY_NAMES`, so auto-format is a fallback for future unknown models — no changes needed
+- `UPPERCASE_PREFIXES` (L72) contains `['gpt', 'glm']` — no Mistral prefixes need uppercasing, so no changes needed
 
 **D. Add Mistral API key storage**
 - New field: `private mistralApiKey: string = ''`
 - New methods: `setMistralApiKey()`, `getMistralApiKey()`, `validateMistralApiKey()`
 - Load on init from settings key `'mistral_api_key'`
 
-**E. Add Mistral request path in `sendMessage()`**
+**E. Update `checkReady()`**
+- Return `ready: true` if **either** OpenCode key or Mistral key is set
+- Extend `ChatReadyStatus` to report per-provider availability, e.g. `providers: { opencode: boolean, mistral: boolean }`
+- Callers (`Sidebar.tsx`, `sendMessage()`) must gate on the relevant provider, not a single boolean
+
+**F. Add Mistral request path in `sendMessage()`**
 - Route `provider === 'mistral'` to new `sendMistralRequest()` method
 - Similar to OpenAI path but:
   - URL: `MISTRAL_API_URL` (direct, not through OpenCode gateway)
   - Auth: `Authorization: Bearer ${this.mistralApiKey}`
-  - No `tool_choice: "required"` — use `"any"` for Mistral's equivalent
-  - Context budget: 35,000 tokens (vs 150k for OpenCode) for 40k-ctx models, 120k for Small 3.2
+  - Context budget: per-model (see Target Models table above)
+  - `tool_choice: "auto"` — Mistral's default; do **not** set `"any"` (which forces a tool call every turn even when the model should respond with text). Omit `tool_choice` entirely, since `"auto"` is the default, matching existing OpenCode behavior
+  - `parallel_tool_calls: false` — set explicitly; our tool executor runs tools sequentially, so parallel tool calls would break the execution loop
 
-**F. Vision format for Mistral**
-- In `view_image` tool result handling: use `image_url` format with base64 data URI
-- Format: `{ type: 'image_url', image_url: { url: 'data:image/webp;base64,...' } }`
-- Same as OpenAI path (Mistral is compatible here)
+**F2. Add `MODEL_CONTEXT_BUDGETS` map**
+- New constant map `MODEL_CONTEXT_BUDGETS: Record<string, number>` with per-model token budgets
+- `truncateToTokenBudget()` (L1654) currently defaults to `maxContextTokens = 150000`
+- In `sendAnthropicMessage()` and `sendOpenAIMessage()`: pass the model's context budget from the map (defaulting to 150,000 for OpenCode models)
+- In `sendMistralRequest()`: look up `MODEL_CONTEXT_BUDGETS[modelId]` and pass to truncation
+- Values from Target Models table (35k, 120k, 240k)
 
-**G. Update `getAvailableModels()`**
+**G. Fix tool-call message history in OpenAI-compatible path**
+- `sendOpenAIMessage()` currently only keeps `user`/`assistant` messages in history, discarding `tool` role messages
+- Tool results must be persisted in conversation history so follow-up rounds have context
+- This affects all OpenAI-compatible providers (OpenCode OpenAI path + Mistral)
+
+**H. Fix vision in OpenAI-compatible path (affects Mistral too)**
+- `sendOpenAIMessage()` currently JSON-stringifies `view_image` results — no `image_url` conversion
+- Add `image_url` format conversion for `__isImageResult` objects in the OpenAI path:
+  `{ type: 'image_url', image_url: { url: 'data:image/webp;base64,...' } }`
+- This fixes vision for all OpenAI-compatible providers, not just Mistral
+
+**I. Update `getAvailableModels()`**
 - When Mistral key is set, include Mistral models in returned list
 - Add `provider` field to model entries so UI can group them
+- Invalidate `cachedModels`/`cachedModelsAt` when Mistral key is added or removed
 
-**H. Update `analyzeMediaImage()`** (lines 2066-2192)
-- Support Mistral models for image metadata analysis (title/alt/caption generation)
-- When a Mistral model is selected, use Mistral vision format (`image_url` with base64 data URI)
-- Route to `api.mistral.ai` with Mistral API key
+**J. Update `generateConversationTitle()` — make configurable in Preferences**
+- Currently hardcoded to `claude-haiku-4-5` via `ZEN_ANTHROPIC_URL` with OpenCode key
+- Add a **"Title generation model"** preference in Settings so users can pick the cheapest model for this task
+- Default: `claude-haiku-4-5` (OpenCode) or `mistral-small-2506` (Mistral) based on available keys
+- Route to the correct provider URL + API key based on the selected model's provider
+- Must work with any configured provider, not just OpenCode
+
+**K. Update `analyzeMediaImage()` — make configurable in Preferences** (lines 2066-2192)
+- Currently hardcoded to `claude-sonnet-4-5` via `ZEN_ANTHROPIC_URL`
+- Add an **"Image analysis model"** preference in Settings so users can select a dedicated vision model independent of their chat model (e.g. use Devstral for chat but Mistral Large 3 for images)
+- **Only vision-capable models may be offered** — filter model list by a `vision` capability flag (e.g. Devstral models have no vision and must be excluded)
+- Default: `claude-sonnet-4-5` (OpenCode) or first vision-capable Mistral model based on available keys
+- Route to the correct provider URL + API key based on the selected model's provider
+- When routed to Mistral: use `image_url` format with base64 data URI
+- When routed to OpenCode/Anthropic: keep current Anthropic-native `image` block format
+
+**L. Update `analyzeTaxonomy()`**
+- Currently uses `this.apiKey` (OpenCode) for both Anthropic and OpenAI paths
+- When a Mistral model is selected: use Mistral API key + `MISTRAL_API_URL`
+- Must branch on provider to select correct key and URL
+
+**M. Convert chat HTTP calls to SSE streaming**
+
+Currently `httpRequest()` buffers the entire response body before any text reaches the UI. Users wait 5–30s per API round with only a bouncing-dots indicator. All three providers (Anthropic, OpenAI, Mistral) support `stream: true` with SSE.
+
+**M1. Core streaming infrastructure — `httpRequestStream()`**
+- New method (~100 lines) — uses Node.js `https.request()` but reads `res` as a readable stream
+- Returns an async iterable of parsed SSE events (or accepts an `onEvent` callback)
+- SSE line protocol: lines separated by `\n\n`, each line prefixed with `event: ` or `data: `
+- Must handle:
+  - Buffering partial lines across `data` chunks (TCP may split mid-line)
+  - Empty `data:` lines (keep-alive pings)
+  - `data: [DONE]` sentinel — terminates the stream for OpenAI/Mistral (do NOT try to JSON.parse this)
+  - Multiple `data:` lines between double-newlines (concatenate per SSE spec)
+- Supports `AbortSignal` — calls `req.destroy()` to terminate immediately
+- 120-second timeout matching existing `httpRequest()`
+- On non-2xx status: collect the error body (not streamed) and throw with parsed error message
+
+**M2. SSE parser for OpenAI/Mistral format** (~50 lines)
+OpenAI and Mistral use identical SSE event structure:
+```
+data: {"id":"...","choices":[{"delta":{"content":"Hello"}}]}
+data: {"id":"...","choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_...","function":{"name":"search_posts","arguments":""}}]}}]}
+data: {"id":"...","choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\"query\""}}]}}]}
+...
+data: {"id":"...","usage":{"prompt_tokens":150,"completion_tokens":42,"total_tokens":192}}
+data: [DONE]
+```
+- **Text deltas**: `choices[0].delta.content` — emit via `onDelta(content)` immediately
+- **Tool call start**: `delta.tool_calls[i]` with `id` + `function.name` — begin accumulating arguments for tool call at index `i`
+- **Tool call argument fragments**: `delta.tool_calls[i].function.arguments` — append to argument accumulator string for index `i`
+- **Finish reason**: `choices[0].finish_reason === 'tool_calls'` or `'stop'` — signals end of this chunk
+- **Token usage**: arrives in the **final chunk before `[DONE]`** only if `stream_options: { include_usage: true }` is set in the request body — parse `usage.prompt_tokens`, `usage.completion_tokens`, `usage.total_tokens`
+- **`[DONE]` sentinel**: stop iteration, do NOT JSON.parse
+- After stream ends: if tool calls were accumulated, JSON.parse each tool's assembled arguments string and execute
+
+**M3. SSE parser for Anthropic format** (~60 lines)
+Anthropic uses named event types:
+```
+event: message_start
+data: {"type":"message_start","message":{"id":"...","model":"...","usage":{"input_tokens":150}}}
+
+event: content_block_start
+data: {"type":"content_block_start","index":0,"content_block":{"type":"text","text":""}}
+
+event: content_block_delta
+data: {"type":"content_block_delta","index":0,"delta":{"type":"text_delta","text":"Hello"}}
+
+event: content_block_start
+data: {"type":"content_block_start","index":1,"content_block":{"type":"tool_use","id":"toolu_...","name":"search_posts"}}
+
+event: content_block_delta
+data: {"type":"content_block_delta","index":1,"delta":{"type":"input_json_delta","partial_json":"{\"query\""}}
+
+event: content_block_stop
+data: {"type":"content_block_stop","index":1}
+
+event: message_delta
+data: {"type":"message_delta","delta":{"stop_reason":"tool_use"},"usage":{"output_tokens":42}}
+
+event: message_stop
+data: {"type":"message_stop"}
+```
+- **`message_start`**: extract `usage.input_tokens` (prompt tokens) + `usage.cache_read_input_tokens` + `usage.cache_creation_input_tokens`
+- **`content_block_start`** with `type: 'text'`: no-op (empty initial text)
+- **`content_block_start`** with `type: 'tool_use'`: record tool call `id` and `name` at block index
+- **`content_block_delta`** with `type: 'text_delta'`: emit via `onDelta(delta.text)` immediately
+- **`content_block_delta`** with `type: 'input_json_delta'`: append `delta.partial_json` to argument accumulator
+- **`content_block_stop`**: if tool block, JSON.parse the accumulated arguments for that block
+- **`message_delta`**: extract `usage.output_tokens` (completion tokens), `delta.stop_reason`
+- **`message_stop`**: stream complete
+- **`ping`**: ignore (keep-alive)
+- **`error`**: throw with `data.error.message` — handles mid-stream server errors (e.g. overloaded)
+
+**M4. Request body changes**
+- `sendAnthropicMessage()`: add `"stream": true` to request body
+- `sendOpenAIMessage()` / `sendMistralRequest()`: add `"stream": true` and `"stream_options": { "include_usage": true }` to request body — this is **required** to receive token usage in streaming mode (without it, usage is omitted from streamed responses)
+
+**M5. Tool call accumulation during streaming**
+- Tool call arguments arrive as partial JSON fragments across many SSE events
+- Maintain a per-stream accumulator: `Map<number, { id: string, name: string, arguments: string }>` keyed by tool call index
+- Append each `arguments` fragment to the accumulator string
+- On stream completion (finish_reason `tool_calls`/`tool_use`, or `content_block_stop` for Anthropic): JSON.parse the full accumulated arguments string and execute the tool
+- If JSON.parse fails on accumulated arguments, report a tool error to the model and continue
+
+**M6. Error handling during streaming**
+- **Non-2xx status on connection**: do NOT stream; collect the full error body and throw (same as current `httpRequest()` behavior)
+- **Mid-stream TCP disconnect / network error**: `res.on('error')` handler — emit whatever text was accumulated so far, then throw so the tool-call loop can surface the error to the user
+- **Mid-stream API error event**: Anthropic sends `event: error` with error details; OpenAI/Mistral return an error JSON in a `data:` line — detect and throw with parsed error message
+- **Abort during streaming**: `req.destroy()` triggers `res.on('error')` or `res.on('close')` — handle gracefully without surfacing as an error to the user (it's intentional cancellation)
+
+**What does NOT change:**
+- The renderer pipeline — `onDelta` → IPC `chat-stream-delta` → `appendStreamDelta` → React state → live Markdown rendering already works token-by-token; it just receives one big chunk today
+- `AbortController` abort support — `req.destroy()` stops the stream immediately instead of wasting a buffered response
+- The tool-call loop structure — still max 10 rounds, still sequential
+
+**What to keep non-streaming:**
+- `generateConversationTitle()` — small one-shot request, buffering is fine
+- `analyzeMediaImage()` — one-shot, no UI streaming needed
+- `analyzeTaxonomy()` — one-shot, no UI streaming needed
+- `validateApiKey()` / `validateMistralApiKey()` — small validation requests
+- Note: `validateMistralApiKey()` must call `GET https://api.mistral.ai/v1/models` with `Authorization: Bearer ${key}`. Mistral returns `{ data: [{ id, object, created, owned_by }] }` — check for HTTP 200 + non-empty `data` array. On 401, return invalid. On success, optionally cross-reference returned model IDs with `MODEL_DISPLAY_NAMES` to verify expected models are available
+
+**Estimated scope:** ~300 lines of new code in `OpenCodeManager.ts` (streaming adds ~100 lines vs original estimate)
 
 ### 2. `src/main/engine/ChatEngine.ts` - Settings persistence
 
@@ -60,10 +221,26 @@ bDS currently routes all AI chat through the OpenCode Zen gateway (`opencode.ai/
 - `setMistralApiKey(key)` - persist to settings table
 - Settings key: `'mistral_api_key'`
 
+**B. Default model is user-driven**
+- `getSelectedModel()` defaults to `'claude-sonnet-4-5'`
+- When user configures providers in Preferences, they explicitly select their default model — no automatic fallback logic needed
+- All surfaces (ChatPanel, AssistantSidebar, ImportAnalysisView) use this preference as default
+- If selected model's provider key is later removed:
+  - `sendMessage()` returns a clear error string: "The selected model requires a {provider} API key. Configure it in Settings."
+  - `checkReady()` still returns `ready: true` if any other provider is available
+  - ChatPanel shows an inline error banner (not a toast) with a link/button to open Settings
+  - i18n key: `chat.providerKeyMissing` — "The model '{model}' requires a {provider} API key. Go to Settings to configure it."
+  - Add this key to all 5 locale files
+
+**C. Add per-purpose model preferences**
+- `getTitleModel()` / `setTitleModel(modelId)` — settings key `'chat_title_model'`
+- `getImageAnalysisModel()` / `setImageAnalysisModel(modelId)` — settings key `'chat_image_analysis_model'`
+- Both default to `null` (= use hardcoded defaults per provider)
+
 ### 3. `src/main/ipc/chatHandlers.ts` - IPC bridge
 
 **A. Add Mistral-specific handlers**
-- `chat:setMistralApiKey` - validate + persist Mistral key
+- `chat:setMistralApiKey` - validate + persist Mistral key, invalidate model cache
 - `chat:getMistralApiKey` - return masked key
 - `chat:validateMistralApiKey` - test key against Mistral API
 
@@ -74,17 +251,33 @@ bDS currently routes all AI chat through the OpenCode Zen gateway (`opencode.ai/
 **C. Update `chat:checkReady`**
 - Report readiness for both providers independently
 
+**D. Update `getOpenCodeManager()` init**
+- Load `'mistral_api_key'` from settings on first call (alongside OpenCode key)
+- Call `manager.setMistralApiKey()` during init
+
+**E. Add per-purpose model preference handlers**
+- `chat:setTitleModel` / `chat:getTitleModel` — persist + load title generation model preference
+- `chat:setImageAnalysisModel` / `chat:getImageAnalysisModel` — persist + load image analysis model preference
+
 ### 4. `src/main/shared/electronApi.ts` - Type definitions
 
 **A. Extend `ChatModel` interface**
 - Add `provider: 'opencode' | 'mistral'` field (already optional, ensure populated)
+- Add `vision: boolean` field — indicates whether the model supports image inputs (used to filter the image analysis model dropdown)
 
-**B. Add Mistral IPC methods to `ElectronAPI.chat`**
+**B. Extend `ChatReadyStatus` interface**
+- Add `providers?: { opencode: boolean; mistral: boolean }` for per-provider status
+
+**C. Add Mistral IPC methods to `ElectronAPI.chat`**
 - `setMistralApiKey(key: string)`
 - `getMistralApiKey()`
 - `validateMistralApiKey(key: string)`
 
-### 5. `src/renderer/components/SettingsView.tsx` - UI settings
+**D. Add per-purpose model preference methods to `ElectronAPI.chat`**
+- `setTitleModel(modelId: string | null)` / `getTitleModel()`
+- `setImageAnalysisModel(modelId: string | null)` / `getImageAnalysisModel()`
+
+### 5. `src/renderer/components/SettingsView/SettingsView.tsx` - UI settings
 
 **A. Add Mistral API key section**
 - Separate input field for Mistral API key (below OpenCode key)
@@ -94,56 +287,176 @@ bDS currently routes all AI chat through the OpenCode Zen gateway (`opencode.ai/
 - Group models by provider in dropdown (optgroup: "OpenCode Zen", "Mistral AI")
 - Show provider badge next to selected model
 
+**C. Add per-purpose model preferences**
+- "Title generation model" dropdown — select cheapest/fastest model for auto-titling conversations
+- "Image analysis model" dropdown — select a dedicated vision model for media metadata (independent of chat model, e.g. use Devstral for chat but Mistral Large 3 for images); **only show vision-capable models** (filter out models without vision support like Devstral)
+- Both show available models from all configured providers, grouped by provider
+- Both allow a "Default" option that auto-selects per provider defaults
+
 ### 6. `src/renderer/components/ChatPanel/ChatPanel.tsx` - Chat UI
 
 **A. Update model selector in chat**
 - Group by provider in dropdown
 - Only show models for configured providers
 
-### 7. Preload/IPC registration
+### 7. `src/renderer/components/AssistantSidebar/` - Assistant UI
 
-**A. `src/main/ipc/handlers.ts` or preload**
-- Register new Mistral IPC channels
-- Expose in preload bridge
+**A. No model selector changes needed**
+- AssistantSidebar has no model selector and no `checkReady()` call of its own
+- It uses whatever default model is set in Preferences (via `getSelectedModel()`)
+- No code changes needed here — provider-awareness is handled at the Preferences and engine level
 
-### 8. MCP Server - `src/main/engine/MCPServer.ts`
+### 8. `src/renderer/components/Sidebar.tsx` - Navigation
+
+**A. Update readiness check**
+- Calls `chat.checkReady()` to show/hide chat features
+- Must handle multi-provider readiness (show chat if **any** provider is ready)
+- Note: Zustand store (`src/renderer/store/appStore.ts`) currently only tracks `chatTokenUsage` — no provider/readiness state is stored there. Provider readiness is ephemeral (fetched on mount via `checkReady()`), so no Zustand changes needed. If future features need reactive provider state, consider adding it then
+
+### 9. `src/renderer/components/ImportAnalysisView/ImportAnalysisView.tsx` - Taxonomy analysis UI
+
+**A. Update model selector**
+- Has its own model selector (`ChatModel[]` state + `getAvailableModels()` call) for taxonomy analysis
+- Currently renders a flat model list with no provider grouping
+- Apply same provider grouping as ChatPanel (optgroup by provider)
+- Default to whatever is set in Preferences as default model (via `getSelectedModel()`)
+- Use the shared `ModelSelector` component (see section 9b)
+
+### 9b. `src/renderer/components/shared/ModelSelector.tsx` - Shared model selector component (NEW)
+
+**Extract a reusable `ModelSelector` component** used by SettingsView, ChatPanel, and ImportAnalysisView:
+- Props: `models: ChatModel[]`, `selectedModelId: string`, `onChange: (modelId: string) => void`, `filterVisionOnly?: boolean`, `allowDefault?: boolean`, `disabled?: boolean`
+- Groups models into `<optgroup>` by `model.provider` (labels: "OpenCode Zen", "Mistral AI")
+- When `filterVisionOnly` is true, only shows models with `vision: true` (for image analysis model selector)
+- When `allowDefault` is true, adds a "Default" option at the top (for per-purpose model preferences)
+- All three surfaces currently duplicate this dropdown logic — extracting prevents drift
+
+### 10. Preload/IPC registration
+
+**A. `src/main/preload.ts`**
+- Register new Mistral IPC channels in preload bridge
+- All chat IPC channels are bridged 1:1; new methods need entries here
+
+### 11. i18n - All locale files
+
+**A. Add Mistral-specific i18n keys** in all 5 locale files:
+- `src/renderer/i18n/locales/en.json`
+- `src/renderer/i18n/locales/de.json`
+- `src/renderer/i18n/locales/fr.json`
+- `src/renderer/i18n/locales/es.json`
+- `src/renderer/i18n/locales/it.json`
+
+Keys needed:
+- `settings.ai.mistralApiKeyLabel` — "Mistral API Key"
+- `settings.ai.mistralApiKeyDescription` — description text
+- `settings.ai.mistralApiKeyPlaceholder` — placeholder text
+- `settings.ai.titleModelLabel` — "Title generation model"
+- `settings.ai.titleModelDescription` — description text
+- `settings.ai.imageAnalysisModelLabel` — "Image analysis model"
+- `settings.ai.imageAnalysisModelDescription` — description text
+- `settings.ai.defaultOption` — "Default" (for per-purpose model selectors)
+- `settings.ai.providerGroupOpenCode` — "OpenCode Zen" (optgroup label)
+- `settings.ai.providerGroupMistral` — "Mistral AI" (optgroup label)
+- `chat.providerKeyMissing` — "The model '{model}' requires a {provider} API key. Go to Settings to configure it."
+- `chat.apiKeyRequiredTitle` — make generic or multi-provider (currently hardcoded to "OpenCode Zen API Key Required")
+- `chat.apiKeyRequiredDescription` — make generic or multi-provider (currently hardcoded to OpenCode-specific text)
+
+### 12. MCP Server - `src/main/engine/MCPServer.ts`
 
 - No changes needed — MCP server exposes tools for external AI agents to call; no bDS-side AI runs during MCP requests
 
+### 13. Python API - `src/main/shared/pythonApiContractV1.ts`
+
+- No changes needed — AI/chat features are explicitly not exposed via Python API
+
+## Tests to Update
+
+### New tests
+- OpenCodeManager: Mistral key storage, `detectProvider('mistral-*')` + `detectProvider('devstral-*')` + `detectProvider('codestral-*')` + `detectProvider('pixtral-*')`, `sendMistralRequest()`, vision image conversion in OpenAI path, tool-call message persistence in OpenAI path, `generateConversationTitle()` Mistral routing, model cache invalidation, `MODEL_CONTEXT_BUDGETS` correctness, SSE line parsing (both OpenAI/Mistral and Anthropic formats), `[DONE]` sentinel handling, tool-call argument accumulation during streaming, mid-stream error handling, `stream_options` in request bodies
+- ChatEngine: `getMistralApiKey()`/`setMistralApiKey()`, `getTitleModel()`/`setTitleModel()`, `getImageAnalysisModel()`/`setImageAnalysisModel()`, default model fallback
+- chatHandlers: new Mistral IPC handlers, per-purpose model preference handlers
+
+### Existing tests to update
+- `tests/engine/OpenCodeManagerTools.test.ts` — if mocked manager gains new required fields
+- `tests/engine/ChatEngine.test.ts` — default model fallback logic
+- `tests/ipc/chatHandlers.test.ts` — new handler registration, init flow
+- `electronApiContract.test.ts` — `ElectronAPI.chat` shape now includes Mistral methods
+- 10 renderer test files that mock `window.electronAPI.chat` (12 mock blocks total) — add Mistral method stubs to mocks:
+  - `tests/renderer/components/SidebarChat.test.tsx`
+  - `tests/renderer/components/SettingsView.test.tsx` (2 mock blocks)
+  - `tests/renderer/components/SettingsView.i18n.test.tsx`
+  - `tests/renderer/components/TabBar.test.tsx`
+  - `tests/renderer/components/EditorDashboardTimeline.test.tsx`
+  - `tests/renderer/components/AssistantSidebar.wiring.test.tsx`
+  - `tests/renderer/navigation/chatSurfaceUsageGuards.test.ts`
+  - `tests/renderer/navigation/chatSurfaceModeUsageGuards.test.ts`
+  - `tests/renderer/navigation/assistantSidebarGuards.test.ts`
+  - `tests/renderer/a2ui/surfaceActionWiring.test.tsx`
+
 ## Implementation Order
 
 1. Tests first (per AGENTS.md)
-2. Types (`electronApi.ts`)
-3. Engine (`OpenCodeManager.ts` — constants, detection, key storage, request path)
-4. Persistence (`ChatEngine.ts` — settings helpers)
-5. IPC (`chatHandlers.ts` — new handlers)
-6. UI (`SettingsView.tsx`, `ChatPanel.tsx` — key input, model grouping)
-7. Build verification
+2. Types (`electronApi.ts` — `ChatModel`, `ChatReadyStatus`, `ElectronAPI.chat`)
+3. Engine (`OpenCodeManager.ts` — constants, `MODEL_CONTEXT_BUDGETS`, detection, key storage, `checkReady()`, request path, vision fix, title generation fallback)
+4. SSE streaming (`OpenCodeManager.ts` — `httpRequestStream()`, SSE parsers for Anthropic + OpenAI/Mistral formats, `stream: true` + `stream_options` in request bodies)
+5. Persistence (`ChatEngine.ts` — settings helpers, per-purpose model preferences, default model fallback)
+6. IPC (`chatHandlers.ts` — new handlers, init flow update)
+7. Preload (`preload.ts` — bridge new channels)
+8. i18n (all 5 locale files)
+9. Shared components (`ModelSelector.tsx` — extract reusable model selector with provider grouping)
+10. UI (`SettingsView/SettingsView.tsx`, `ChatPanel.tsx`, `ImportAnalysisView.tsx`, `Sidebar.tsx` — use shared `ModelSelector`)
+11. Update existing test mocks
+12. Build verification (`npm run build`)
 
 ## Key Differences to Handle
 
-| Aspect | OpenCode/OpenAI | Mistral |
-|--------|----------------|---------|
-| Base URL | `opencode.ai/zen/v1/...` | `api.mistral.ai/v1/...` |
-| Auth header | `Bearer ${openCodeKey}` | `Bearer ${mistralKey}` |
-| Tool choice forced | `"required"` | `"any"` |
-| Parallel tools | not set | `parallel_tool_calls: true` |
-| Context budget | 150k tokens | 35k (Large/Medium), 120k (Small) |
-| Vision format | `image_url` block | `image_url` block (same) |
-| Streaming | SSE deltas | SSE deltas (same) |
+| Aspect | OpenCode/Anthropic | OpenCode/OpenAI-compat | Mistral |
+|--------|-------------------|----------------------|---------|
+| Base URL | `opencode.ai/zen/v1/messages` | `opencode.ai/zen/v1/chat/completions` | `api.mistral.ai/v1/chat/completions` |
+| Auth header | `Bearer ${openCodeKey}` | `Bearer ${openCodeKey}` | `Bearer ${mistralKey}` |
+| Tool choice | not set | not set | not set (default `"auto"`) |
+| Parallel tools | not set | not set | `parallel_tool_calls: false` |
+| Context budget | 150k tokens | 150k tokens | per-model (see Target Models table) |
+| Stream options | `"stream": true` | `"stream": true, "stream_options": {"include_usage": true}` | `"stream": true, "stream_options": {"include_usage": true}` |
+| Vision in tool results | Anthropic `image` block (native) | **BUG: JSON-stringified** | `image_url` block (fix needed) |
+| HTTP mode | SSE streaming (`stream: true`) | SSE streaming (`stream: true`) | SSE streaming (`stream: true`) |
+| Title generation | `claude-haiku-4-5` default | N/A | `mistral-small-2506` default |
+| Image analysis | `claude-sonnet-4-5` default | N/A | user-selected vision model |
 
 ## Verification
 
 1. Run `npm test` — all existing + new tests pass
 2. Run `npm run build` — clean build
 3. Manual: set Mistral API key in Settings, verify validation
-4. Manual: select Mistral Large 3, send chat message, verify response streams
+4. Manual: select Mistral Large 3, send chat message, verify response completes
 5. Manual: use `view_image` tool in chat with Mistral model, verify vision works
 6. Manual: verify tool calling works (search_posts, list_posts, etc.)
 7. Manual: verify OpenCode models still work unchanged
+8. Manual: verify Mistral-only mode (no OpenCode key) — chat works, title generates, readiness shows correctly
+9. Manual: verify `analyzeMediaImage()` and `analyzeTaxonomy()` with Mistral model
+10. Manual: configure title generation model in Settings, verify titles use selected model
+11. Manual: configure image analysis model in Settings, verify media analysis uses selected model (independent of chat model)
+12. Manual: verify SSE streaming — text appears token-by-token (not as a single block after long wait)
+13. Manual: verify abort during streaming — text stops immediately, no wasted response
 
 ## Resolved Decisions
 
-1. **`analyzeMediaImage()`** — Mistral models will be usable for image metadata analysis
-2. **MCP server** — N/A; MCP server only exposes tools, no bDS-side AI runs during MCP requests
-3. **Model dropdown grouping** — Use `<optgroup>` labels ("OpenCode Zen", "Mistral AI")
+1. **`analyzeMediaImage()`** — Configurable via Settings preference; user selects a dedicated vision model independent of chat model; dropdown only shows vision-capable models
+2. **`generateConversationTitle()`** — Configurable via Settings preference; user selects cheapest/fastest model for auto-titling
+3. **`checkReady()`** — Returns true if any provider key is set; reports per-provider availability
+4. **Default model** — User-driven; set explicitly in Preferences when configuring provider + model; all surfaces (ChatPanel, AssistantSidebar, ImportAnalysisView) use this preference
+5. **Vision in OpenAI path** — Fix `image_url` conversion for all OpenAI-compatible providers (not just Mistral)
+6. **MCP server** — N/A; only exposes tools, no bDS-side AI runs
+7. **Python API** — N/A; AI/chat not exposed via Python API
+8. **Model dropdown grouping** — Use `<optgroup>` labels ("OpenCode Zen", "Mistral AI"); extract shared `ModelSelector` component to avoid duplication across 3 surfaces
+9. **SSE streaming** — Convert all chat HTTP calls to `stream: true` + SSE parsing; keep one-shot requests (title, image analysis, taxonomy, validation) non-streaming. Renderer needs zero changes — existing `onDelta` pipeline already supports incremental tokens. Token usage requires `stream_options: { include_usage: true }` for OpenAI/Mistral format; Anthropic provides usage in `message_start` + `message_delta` events
+10. **OpenAI tool-call history** — Fix `sendOpenAIMessage()` to persist `tool` role messages in conversation history (not just `user`/`assistant`), so follow-up tool rounds have context
+11. **ImportAnalysisView** — Has its own model selector; apply same provider grouping; default to Preferences model
+12. **AssistantSidebar** — No model selector of its own; uses Preferences default model; no code changes needed
+13. **`tool_choice`** — Do NOT set `tool_choice: "any"` for Mistral (this forces tool use every turn). Omit it entirely; Mistral defaults to `"auto"`, same as OpenCode. Set `parallel_tool_calls: false` explicitly since our tool executor is sequential
+14. **`detectProvider()` prefixes** — Cover all Mistral model families: `mistral`, `ministral`, `devstral`, `codestral`, `pixtral`
+15. **`formatModelName()` / `UPPERCASE_PREFIXES`** — No changes needed; all 5 Mistral models are in `MODEL_DISPLAY_NAMES`; auto-format fallback handles future unknown models correctly
+16. **Context budgets** — Stored in `MODEL_CONTEXT_BUDGETS` map; passed explicitly to `truncateToTokenBudget()` per provider path; OpenCode defaults to 150k, Mistral per-model (see Target Models table)
+17. **Error UX for removed provider key** — Inline error banner in ChatPanel (not a toast) with link to Settings; `sendMessage()` returns descriptive error string; `checkReady()` stays true if any provider available
+18. **Zustand store** — No changes needed; provider readiness is ephemeral (fetched on mount), token usage tracking is already in store and is provider-agnostic
+19. **`validateMistralApiKey()`** — Calls `GET https://api.mistral.ai/v1/models` with Bearer token; checks for HTTP 200 + non-empty `data` array; Mistral returns `{ data: [{ id, object, created, owned_by }] }` format