Backend API

Base URL: http://localhost:8000

Headers

x-model-id: required. Example: mistralai/Mistral-Small-24B-Instruct.

POST /

Sends conversation messages to the ReAct agent.

Request Body:

{
  "messages": [
    {"type": "human", "content": "What's the weather like today in Berlin?"}
  ]
}

Supported message types:

"human": User messages (requires content field)
"ai": Assistant messages (requires content field)
"tool": Tool messages (requires content field, optional name field)

Required Headers:

x-model-id: IONOS model identifier (e.g. mistralai/Mistral-Small-24B-Instruct)

Response: Returns the last message from the agent conversation as a LangChain message object.

Example Response:

{
    "content": "The weather in Berlin today is characterized by moderate rain with a temperature of 22.2°C (72.0°F). The humidity is 61%, and there is a slight breeze from the WSW at 17.3 km/h (10.7 mph). The sky is partly cloudy with 50% cloud cover. The wind chill feels like 20.0°C (68.0°F), and the heat index is also 20.0°C (68.0°F). The dew point is at 13.6°C (56.6°F), and visibility is good at 10 km (6 miles). The UV index is low at 1.1, and there are gusts of wind reaching up to 25.7 km/h (16.0 mph).",
    "additional_kwargs": {
        "refusal": null
    },
    "response_metadata": {
        "token_usage": {
            "completion_tokens": 181,
            "prompt_tokens": 1006,
            "total_tokens": 1187,
            "completion_tokens_details": null,
            "prompt_tokens_details": null
        },
        "model_name": "mistralai/Mistral-Small-24B-Instruct",
        "system_fingerprint": null,
        "id": "chatcmpl-762085b2228b42fb83a4cfd69aecf11e",
        "service_tier": null,
        "finish_reason": "stop",
        "logprobs": null
    },
    "type": "ai",
    "name": null,
    "id": "run--fa6dbcb0-2c5d-4f12-bd51-4cd6dfefc81f-0",
    "example": false,
    "tool_calls": [],
    "invalid_tool_calls": [],
    "usage_metadata": {
        "input_tokens": 1006,
        "output_tokens": 181,
        "total_tokens": 1187,
        "input_token_details": {},
        "output_token_details": {}
    }
}

Note: Frontend applications should extract the content field for the actual message text. The response includes comprehensive LangChain metadata including token usage, model information, and execution details.

Example Test in Postman

Postman API Test Example

The screenshot above shows a real test of the API endpoint using Postman, demonstrating the exact request payload and response format.

Agent Tools Troubleshooting