docs: comprehensive documentation update
Updates README with: - System prompts feature (model-specific, capability-based defaults) - Custom model creation with embedded prompts - Comprehensive Custom Tools Guide with examples - Updated API reference with all endpoints - Updated roadmap with completed features Adds detailed documentation for custom tools: - JavaScript, Python, and HTTP tool types - Parameter definitions and templates - Testing workflow and security notes - Complete weather tool example - Programmatic tool creation guide
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265
README.md
265
README.md
@@ -68,6 +68,12 @@ Vessel deliberately avoids becoming a platform. Its scope is narrow by design.
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- **Syntax highlighting** — Beautiful code blocks powered by Shiki with 100+ languages
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- **Dark/Light mode** — Seamless theme switching with system preference detection
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### System Prompts
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- **Prompt library** — Save and organize reusable system prompts
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- **Model-specific prompts** — Assign default prompts to specific models
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- **Capability-based defaults** — Auto-select prompts based on model capabilities (vision, tools, thinking, code)
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- **Quick selection** — Switch prompts mid-conversation with the prompt selector
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### Built-in Tools (Function Calling)
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Vessel includes five powerful tools that models can invoke automatically:
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@@ -79,11 +85,24 @@ Vessel includes five powerful tools that models can invoke automatically:
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| **Get Location** | Detect user location via GPS or IP for local queries |
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| **Get Time** | Current date/time with timezone support |
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### Custom Tools
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Create your own tools that models can invoke:
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- **JavaScript tools** — Run in-browser with full access to browser APIs
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- **Python tools** — Execute on the backend with any Python libraries
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- **HTTP tools** — Call external REST APIs (GET/POST)
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- **Built-in templates** — Start from 8 pre-built templates
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- **Test before saving** — Interactive testing panel validates your tools
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See the [Custom Tools Guide](#custom-tools-guide) for detailed documentation.
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### Model Management
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- **Model browser** — Browse, search, and pull models from Ollama registry
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- **Custom models** — Create models with embedded system prompts
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- **Edit custom models** — Update system prompts of existing custom models
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- **Live status** — See which models are currently loaded in memory
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- **Quick switch** — Change models mid-conversation
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- **Model metadata** — View parameters, quantization, and capabilities
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- **Update detection** — See which models have newer versions available
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### Developer Experience
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- **Beautiful code generation** — Syntax-highlighted output for any language
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@@ -369,13 +388,235 @@ docker compose -f docker-compose.dev.yml up
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| `POST` | `/api/v1/proxy/search` | Web search via DuckDuckGo |
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| `POST` | `/api/v1/proxy/fetch` | Fetch URL content |
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| `GET` | `/api/v1/location` | Get user location from IP |
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| `GET` | `/api/v1/models/registry` | Browse Ollama model registry |
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| `GET` | `/api/v1/models/search` | Search models |
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| `POST` | `/api/v1/chats/sync` | Sync conversations |
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| `POST` | `/api/v1/tools/execute` | Execute Python/JS tools |
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| `GET` | `/api/v1/models/local` | List local models with filtering |
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| `GET` | `/api/v1/models/local/updates` | Check for model updates |
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| `GET` | `/api/v1/models/remote` | Browse Ollama model registry |
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| `POST` | `/api/v1/models/remote/sync` | Sync registry from ollama.com |
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| `POST` | `/api/v1/chats` | Create new chat |
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| `GET` | `/api/v1/chats/grouped` | List chats grouped by date |
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| `POST` | `/api/v1/sync/push` | Push local changes to backend |
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| `GET` | `/api/v1/sync/pull` | Pull changes from backend |
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### Ollama Proxy
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### Ollama API Proxy
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All requests to `/ollama/*` are proxied to the Ollama API, enabling CORS.
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All Ollama API endpoints are proxied through `/api/v1/ollama/*`:
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| Method | Endpoint | Description |
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|--------|----------|-------------|
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| `GET` | `/api/v1/ollama/api/tags` | List installed models |
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| `POST` | `/api/v1/ollama/api/show` | Get model details |
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| `POST` | `/api/v1/ollama/api/pull` | Pull a model (streaming) |
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| `POST` | `/api/v1/ollama/api/create` | Create custom model (streaming) |
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| `DELETE` | `/api/v1/ollama/api/delete` | Delete a model |
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| `POST` | `/api/v1/ollama/api/chat` | Chat completion (streaming) |
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| `POST` | `/api/v1/ollama/api/embed` | Generate embeddings |
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---
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## Custom Tools Guide
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Vessel allows you to create custom tools that LLMs can invoke during conversations. Tools extend the model's capabilities beyond text generation.
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### Creating a Tool
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1. Navigate to **Tools** in the sidebar
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2. Click **Create Custom Tool**
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3. Fill in the tool details:
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- **Name** — Unique identifier (alphanumeric + underscores)
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- **Description** — Explains to the model when to use this tool
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- **Parameters** — Define inputs the model should provide
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- **Implementation** — Choose JavaScript, Python, or HTTP
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- **Code/Endpoint** — Your tool's logic
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### Tool Types
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#### JavaScript Tools
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JavaScript tools run directly in the browser. They have access to browser APIs and execute instantly.
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```javascript
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// Example: Format a date
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// Parameters: { date: string, format: string }
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const d = new Date(args.date);
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const formats = {
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'short': d.toLocaleDateString(),
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'long': d.toLocaleDateString('en-US', {
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weekday: 'long', year: 'numeric', month: 'long', day: 'numeric'
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}),
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'iso': d.toISOString()
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};
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return formats[args.format] || formats.short;
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```
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**Key points:**
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- Access parameters via the `args` object
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- Return any JSON-serializable value
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- Use `await` for async operations
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- Full access to browser APIs (fetch, localStorage, etc.)
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#### Python Tools
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Python tools execute on the backend server. They can use any Python libraries installed on the server.
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```python
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# Example: Calculate statistics
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# Parameters: { numbers: array }
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import json
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import sys
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import statistics
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# Read args from stdin
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args = json.loads(sys.stdin.read())
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numbers = args['numbers']
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result = {
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'mean': statistics.mean(numbers),
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'median': statistics.median(numbers),
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'stdev': statistics.stdev(numbers) if len(numbers) > 1 else 0
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}
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# Output JSON result
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print(json.dumps(result))
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```
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**Key points:**
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- Read arguments from `stdin` as JSON
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- Print JSON result to `stdout`
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- 30-second timeout (configurable up to 60s)
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- Use any installed Python packages
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- Stderr is captured for debugging
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#### HTTP Tools
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HTTP tools call external REST APIs. Configure the endpoint and Vessel handles the request.
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**Configuration:**
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- **Endpoint** — Full URL (e.g., `https://api.example.com/data`)
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- **Method** — GET or POST
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- **Parameters** — Sent as query params (GET) or JSON body (POST)
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The tool returns the JSON response from the API.
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### Defining Parameters
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Parameters tell the model what inputs your tool expects:
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| Field | Description |
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|-------|-------------|
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| **Name** | Parameter identifier (e.g., `query`, `count`) |
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| **Type** | `string`, `number`, `integer`, `boolean`, `array`, `object` |
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| **Description** | Explains what this parameter is for |
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| **Required** | Whether the model must provide this parameter |
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| **Enum** | Optional list of allowed values |
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### Built-in Templates
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Vessel provides 8 starter templates to help you get started:
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**JavaScript:**
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- API Request — Fetch data from REST APIs
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- JSON Transform — Filter and reshape JSON data
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- String Utilities — Text manipulation functions
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- Date Utilities — Date formatting and timezone conversion
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**Python:**
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- API Request — HTTP requests with urllib
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- Data Analysis — Statistical calculations
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- Text Analysis — Word frequency and sentiment
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- Hash & Encode — MD5, SHA256, Base64 operations
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### Testing Tools
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Before saving, use the **Test** panel:
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1. Enter sample parameter values
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2. Click **Run Test**
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3. View the result or error message
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4. Iterate until the tool works correctly
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### Enabling/Disabling Tools
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- **Global toggle** — Enable/disable all tools at once
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- **Per-tool toggle** — Enable/disable individual tools
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- Disabled tools won't be sent to the model
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### Security Considerations
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- **JavaScript** runs in the browser with your session's permissions
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- **Python** runs on the backend with server permissions
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- **HTTP** tools can call any URL — be careful with sensitive endpoints
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- Tools are stored locally in your browser (IndexedDB)
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### Programmatic Tool Creation
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Tools are stored in localStorage. You can manage them programmatically:
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```typescript
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// Tool definition structure
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interface CustomTool {
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id: string;
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name: string;
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description: string;
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parameters: {
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type: 'object';
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properties: Record<string, {
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type: 'string' | 'number' | 'boolean' | 'array' | 'object';
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description: string;
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enum?: string[];
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}>;
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required: string[];
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};
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implementation: 'javascript' | 'python' | 'http';
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code?: string; // For JS/Python
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endpoint?: string; // For HTTP
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httpMethod?: 'GET' | 'POST';
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enabled: boolean;
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createdAt: number;
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updatedAt: number;
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}
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// Access via localStorage
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const tools = JSON.parse(localStorage.getItem('customTools') || '[]');
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```
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### Example: Weather Tool
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Here's a complete example of a JavaScript tool that fetches weather:
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**Name:** `get_weather`
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**Description:** Get current weather for a city. Use this when the user asks about weather conditions.
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**Parameters:**
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| Name | Type | Required | Description |
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|------|------|----------|-------------|
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| city | string | Yes | City name (e.g., "London", "New York") |
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| units | string | No | Temperature units: "celsius" or "fahrenheit" |
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**Code (JavaScript):**
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```javascript
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const city = encodeURIComponent(args.city);
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const units = args.units === 'fahrenheit' ? 'imperial' : 'metric';
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const response = await fetch(
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`https://api.openweathermap.org/data/2.5/weather?q=${city}&units=${units}&appid=YOUR_API_KEY`
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);
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if (!response.ok) {
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throw new Error(`Weather API error: ${response.status}`);
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}
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const data = await response.json();
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return {
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city: data.name,
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temperature: data.main.temp,
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description: data.weather[0].description,
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humidity: data.main.humidity
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};
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```
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---
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@@ -388,9 +629,19 @@ The roadmap prioritizes **usability, clarity, and low friction** over feature br
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These improve the existing experience without expanding scope.
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- [ ] Improve model browser & search
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- better filtering (size, tags, quantization)
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- [x] Improve model browser & search
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- better filtering (size, tags, quantization, capabilities)
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- clearer metadata presentation
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- update detection for installed models
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- [x] Custom tools system
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- JavaScript, Python, and HTTP tool creation
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- built-in templates and testing panel
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- [x] System prompt management
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- prompt library with model-specific defaults
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- capability-based auto-selection
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- [x] Custom model creation
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- embed system prompts into Ollama models
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- edit existing custom models
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- [ ] Keyboard-first workflows
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- model switching
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- prompt navigation
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