NekoPunch
f5dfb1413e
* feat(python): add Mistral chat client Implements native Mistral support (#7366) with streaming, tool calling, and structured output. Talks to the REST API directly over httpx: the mistralai SDK's pinned OpenTelemetry deps conflict with the workspace. * refactor(python): simplify Mistral client per review Drop the streamed tool-call accumulator and multi-choice parsing in favor of the framework's built-in fragment merging, mark n unsupported, omit unset strict from json_schema, and leave CI secret wiring to maintainers. * test(python): drop n forwarding assertion n is typed as unsupported on MistralChatOptions; the option-mapping test still passed n, failing pyrefly/ty/zuban/mypy in CI. * refactor(python): drop n from MistralChatOptions n is not part of the base ChatOptions, so removing the key rejects it without an explicit None override. * feat(python): mark Mistral feature usage Both clients flip the shared FeatureIndex.MISTRAL bit before each request, matching the feature-usage telemetry other providers emit. * fix(python): key streamed tool calls by index Mistral omits the tool call id on continuation fragments, and the framework only coalesces empty-id fragments into the immediately preceding call, so interleaved parallel calls merged into the wrong call with corrupted arguments. Accumulate fragments per (choice, index) and emit each call only once complete. * fix(python): restore Mistral SDK client injection Dropping the mistralai dependency turned the embedding client's client= parameter into a breaking change for injected SDK clients. Add http_client= for httpx.AsyncClient and keep client= working: httpx goes to the REST path, a duck-typed mistralai.Mistral goes through the legacy SDK path with a DeprecationWarning until the next major release. * chore(python): tidy Mistral sample header
Mistral AI Examples
This folder contains examples demonstrating how to use Mistral AI models with the Agent Framework.
Examples
| File | Description |
|---|---|
mistral_agent_basic.py |
Basic agent with tool usage using the Mistral AI chat client. |
mistral_embeddings.py |
Basic embedding generation with the Mistral AI embedding client. |
Environment Variables
MISTRAL_API_KEY: Your Mistral AI API keyMISTRAL_CHAT_MODEL: Chat model name (e.g.,mistral-small-latest)MISTRAL_EMBEDDING_MODEL: Embedding model name (e.g.,mistral-embed)MISTRAL_SERVER_URL(optional): Server URL override for custom deployments