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title: HF Agent
emoji: π€
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
hf_oauth: true
hf_oauth_scopes:
- read-repos
- write-repos
- contribute-repos
- manage-repos
- inference-api
- jobs
- write-discussions
---
# HF Agent
An MLE agent CLI with MCP (Model Context Protocol) integration and built-in tool support.
## Quick Start
### Installation
```bash
# Clone the repository
git clone git@github.com:huggingface/hf_agent.git
cd hf_agent
```
#### Install recommended dependencies
```bash
uv sync --extra agent # or uv sync --extra all
```
### Interactive CLI
```bash
uv run python -m agent.main
```
This starts an interactive chat session with the agent. Type your messages and the agent will respond, using tools as needed.
The agent will automatically discover and register all tools from configured MCP servers.
### Env Setup
```bash
ANTHROPIC_API_KEY=<one-key-to-rule-them-all>
HF_TOKEN=<hf-token-to-access-the-hub>
GITHUB_TOKEN=<gh-pat-key-for-not-reinventing-the-wheel>
HF_NAMESPACE=<hf-namespace-to-use>
```
## Architecture
### Component Overview
```
βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
β User/CLI β
ββββββββββββββ¬ββββββββββββββββββββββββββββββββββββββ¬ββββββββββββ
β User request β Events
β β
submission_queue event_queue
β β
β β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββ β
β submission_loop (agent_loop.py) β β
β ββββββββββββββββββββββββββββββββββββββββββββββββ β β
β β 1. Receive Operation from queue β β β
β β 2. Route to Handler (run_agent/compact/...) β β β
β ββββββββββββββββββββββββββββββββββββββββββββββββ β β
β β β β
β ββββββββββββββββββββββββββββββββββββββββββββββββ β β
β β Handlers.run_agent() β βββββββββββ€
β β β β Emit β
β β ββββββββββββββββββββββββββββββββββββββββββ β β Events β
β β β Agentic Loop (max 10 iterations) β β β β
β β β β β β β
β β β ββββββββββββββββββββββββββββββββββββ β β β β
β β β β Session β β β β β
β β β β ββββββββββββββββββββββββββββββ β β β β β
β β β β β ContextManager β β β β β β
β β β β β β’ Message history β β β β β β
β β β β β (litellm.Message[]) β β β β β β
β β β β β β’ Auto-compaction (180k) β β β β β β
β β β β ββββββββββββββββββββββββββββββ β β β β β
β β β β β β β β β
β β β β ββββββββββββββββββββββββββββββ β β β β β
β β β β β ToolRouter β β β β β β
β β β β β ββ explore_hf_docs β β β β β β
β β β β β ββ fetch_hf_docs β β β β β β
β β β β β ββ find_hf_api β β β β β β
β β β β β ββ plan_tool β β β β β β
β β β β β ββ hf_jobs* β β β β β β
β β β β β ββ hf_private_repos* β β β β β β
β β β β β ββ github_* (3 tools) β β β β β β
β β β β β ββ MCP tools (e.g., β β β β β β
β β β β β model_search, etc.) β β β β β β
β β β β ββββββββββββββββββββββββββββββ β β β β β
β β β ββββββββββββββββββββββββββββββββββββ β β β β
β β β β β β β
β β β Loop: β β β β
β β β 1. LLM call (litellm.acompletion) β β β β
β β β β β β β β
β β β 2. Parse tool_calls[] β β β β
β β β β β β β β
β β β 3. Execute via ToolRouter β β β β
β β β β β β β β
β β β 4. Add results to ContextManager β β β β
β β β β β β β β
β β β 5. Repeat if tool_calls exist β β β β
β β ββββββββββββββββββββββββββββββββββββββββββ β β β
β ββββββββββββββββββββββββββββββββββββββββββββββββ β β
ββββββββββββββββββββββββββββββββββββββββββββββββββββββ΄ββββββββββ
```
### Agentic Loop Flow
```
User Message
β
[Add to ContextManager]
β
βββββββββββββββββββββββββββββββββββββββββ
β Iteration Loop (max 10) β
β β
β Get messages + tool specs β
β β β
β litellm.acompletion() β
β β β
β Has tool_calls? ββNoββ> Done β
β β β
β Yes β
β β β
β Add assistant msg (with tool_calls) β
β β β
β For each tool_call: β
β β’ ToolRouter.execute_tool() β
β β’ Add result to ContextManager β
β β β
β Continue loop ββββββββββββββββββ β
β β β β
βββββββββββ§ββββββββββββββββββββββββ§ββββββ
```
## Project Structure
```
agent/
βββ config.py # Configuration models
βββ main.py # Interactive CLI entry point
βββ prompts/
β βββ system_prompt.yaml # Agent behavior and personality
βββ context_manager/
β βββ manager.py # Message history & auto-compaction
βββ core/
βββ agent_loop.py # Main agent loop and handlers
βββ session.py # Session management
βββ mcp_client.py # MCP SDK integration
βββ tools.py # ToolRouter and built-in tools
configs/
βββ main_agent_config.json # Model and MCP server configuration
tests/ # Integration and unit tests
eval/ # Evaluation suite (see eval/README.md)
```
## Events
The agent emits the following events via `event_queue`:
- `processing` - Starting to process user input
- `assistant_message` - LLM response text
- `tool_call` - Tool being called with arguments
- `tool_output` - Tool execution result
- `approval_request` - Requesting user approval for sensitive operations
- `turn_complete` - Agent finished processing
- `error` - Error occurred during processing
- `interrupted` - Agent was interrupted
- `compacted` - Context was compacted
- `undo_complete` - Undo operation completed
- `shutdown` - Agent shutting down
## Development
### Adding Built-in Tools
Edit `agent/core/tools.py`:
```python
def create_builtin_tools() -> list[ToolSpec]:
return [
ToolSpec(
name="your_tool",
description="What your tool does",
parameters={
"type": "object",
"properties": {
"param": {"type": "string", "description": "Parameter description"}
},
"required": ["param"]
},
handler=your_async_handler
),
# ... existing tools
]
```
### Adding MCP Servers
Edit `configs/main_agent_config.json`:
```json
{
"model_name": "anthropic/claude-sonnet-4-5-20250929",
"mcpServers": {
"your-server-name": {
"transport": "http",
"url": "https://example.com/mcp",
"headers": {
"Authorization": "Bearer ${YOUR_TOKEN}"
}
}
}
}
```
Note: Environment variables like `${YOUR_TOKEN}` are auto-substituted from `.env`.
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