> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentguardian.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Scan a FastAPI chatbot

> Point AgentGuardian at any FastAPI agent endpoint with --endpoint — no framework required.

The smallest target AgentGuardian can scan is a FastAPI app with a single
`/chat` endpoint accepting `{"input": "..."}` and returning
`{"output": "..."}`. No agent framework, no in-process adapter — just the
HTTP transport.

## What this example tests

* All 10 ASI categories at the HTTP boundary.
* The `--endpoint` mode's pre-flight reachability check (an unreachable
  target fails fast with `EXIT_TARGET_UNREACHABLE` before any LLM budget
  is spent).
* The default `{"input": "<prompt>"}` request template (no contract
  required).

Source: [`src/agent_guardian/transports/http.py`](https://github.com/glacien-technologies/agent-guardian/blob/main/src/agent_guardian/transports/http.py).

## Prerequisites

* AgentGuardian installed — `pip install agent-guardian`.
* A FastAPI agent reachable at an HTTP URL. Use the bundled
  [`examples/fastapi_chatbot/`](https://github.com/glacien-technologies/agent-guardian/tree/main/examples/fastapi_chatbot)
  fixture or your own.
* A model spec — `--model stub` for an offline dry-run, or a real model
  spec for a graded assessment.

## Run target

The bundled fixture is a hermetic stub — no LLM calls, deterministic
responses:

```bash theme={null}
uv sync --extra examples
uv run uvicorn examples.fastapi_chatbot.serve:app --port 8000
```

Or write your own (the absolute minimum):

```python my_agent.py theme={null}
from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class ChatRequest(BaseModel):
    input: str


@app.post("/chat")
def chat(req: ChatRequest) -> dict:
    return {"output": f"You said: {req.input}"}
```

Run it: `uvicorn my_agent:app --port 8000`.

## Run AgentGuardian

```bash theme={null}
agent-guardian scan \
  --endpoint http://localhost:8000/chat \
  --model stub \
  --mode fast \
  --output md \
  --output-path scan.md
```

Flag-by-flag, every option below is verified against
`src/agent_guardian/cli.py`:

* `--endpoint URL` — hosted HTTP endpoint of the FastAPI agent.
* `--model stub` — offline default. Swap for a real model spec
  (`openai:gpt-4o`, `gemini:gemini-2.5-flash`, `ollama:llama3.1`) for a
  graded run.
* `--mode fast` — `fast` / `smart` / `full` (default).
* `--output md --output-path scan.md` — Markdown report. Other formats:
  `json`, `sarif`, `junit`, `pdf`.

## Expected output

`examples/fastapi_chatbot/sample-scan.json` ships a committed reference
scan for `--model stub`. A real-model run typically produces a populated
`severity_counts` block and a non-null `aivss_score`.

## Common errors

* **`EXIT_TARGET_UNREACHABLE` (exit code 6).** Two empty-body `POST`s
  with a 2 s timeout both failed. Pass `--no-preflight` if your endpoint
  refuses empty bodies but is actually up.
* **`422 Unprocessable Entity` on every request.** Your endpoint expects
  a different request shape than `{"input": "..."}`. Declare a target
  contract with the custom shape — see
  [Config file reference](/reference/config).

## Next step

* For a tool-bearing target with framework-adapter visibility, read
  [Scan a LangGraph agent](/try/scan-langgraph).
* For a retrieval-augmented target, read
  [Scan a RAG application](/try/scan-rag-app).