Mistral AI (gateway)

Route Mistral AI model calls through the Respan gateway to use Respan credentials, request logs, routing, fallbacks, and metadata. For direct Mistral AI SDK tracing, see Mistral AI tracing setup.

Setup

1

Install packages

$pip install openai python-dotenv
2

Set environment variables

$export RESPAN_API_KEY="YOUR_RESPAN_API_KEY"

No MISTRAL_API_KEY is required for gateway calls when your Mistral provider credentials are configured in Respan.

3

Point an OpenAI-compatible client to the Respan gateway

1import os
2
3from dotenv import load_dotenv
4from openai import OpenAI
5
6load_dotenv()
7
8client = OpenAI(
9 api_key=os.environ["RESPAN_API_KEY"],
10 base_url=os.getenv("RESPAN_BASE_URL", "https://api.respan.ai/api"),
11)
12
13response = client.chat.completions.create(
14 model="mistral/mistral-small",
15 messages=[{"role": "user", "content": "Say hello in three languages."}],
16)
17print(response.choices[0].message.content)

Switch models

Change the model parameter to use 250+ models from different providers through the same gateway.

1response = client.chat.completions.create(model="mistral/mistral-small", messages=messages)
2response = client.chat.completions.create(model="gpt-5.5", messages=messages)
3response = client.chat.completions.create(model="claude-sonnet-4-5-20250929", messages=messages)

See the full model list.

Respan parameters

Pass additional Respan parameters via extra_body for gateway features.

1response = client.chat.completions.create(
2 model="mistral/mistral-small",
3 messages=[{"role": "user", "content": "Hello"}],
4 extra_body={
5 "customer_identifier": "user_123",
6 "fallback_models": ["gpt-5.5"],
7 "metadata": {"session_id": "abc123"},
8 "thread_identifier": "conversation_456",
9 },
10)

See Respan params & metadata for the full list.