> ## Documentation Index
> Fetch the complete documentation index at: https://reagent-ai.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Installation

> Install reagent-flow and choose the adapter path that fits your stack.

## Core package

Install the zero-dependency core first:

<CodeGroup>
  ```bash pip theme={null}
  pip install reagent-flow
  ```

  ```bash uv theme={null}
  uv add reagent-flow
  ```
</CodeGroup>

## Framework adapters

Install only the adapters you need:

<CodeGroup>
  ```bash pip theme={null}
  pip install reagent-flow-openai
  pip install reagent-flow-anthropic
  pip install reagent-flow-langchain
  pip install reagent-flow-langgraph
  pip install reagent-flow-crewai
  ```

  ```bash uv theme={null}
  uv add reagent-flow-openai
  uv add reagent-flow-anthropic
  uv add reagent-flow-langchain
  uv add reagent-flow-langgraph
  uv add reagent-flow-crewai
  ```
</CodeGroup>

## Which path should you use?

<CardGroup cols={3}>
  <Card title="Core Only" icon="box" href="/quickstart">
    Start with manual `session`, `log_llm_call`, and `log_tool_result` instrumentation.
  </Card>

  <Card title="Adapter Path" icon="plug" href="/adapters/overview">
    Auto-capture traces from OpenAI, Anthropic, LangChain, LangGraph, or CrewAI.
  </Card>

  <Card title="See the Demo" icon="shield-check" href="/examples/vendor-onboarding">
    Jump straight to the flagship multi-agent showcase.
  </Card>
</CardGroup>

## Verify the install

Create a quick smoke test:

```python theme={null}
import reagent_flow

with reagent_flow.session("smoke-test") as s:
    s.log_llm_call(tool_calls=[{"name": "ping", "arguments": {}}])
    s.log_tool_result("ping", result={"ok": True})

s.assert_called("ping")
```

Run it with pytest:

```bash theme={null}
uv run pytest test_smoke.py -v
```

If that passes, the core install is working. For CI setup, see [CI](/advanced/ci).