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* Bump Python package versions for 1.13.0 release Bump all 37 Python package projects because the CHANGELOG-driven release includes cross-package feature-usage telemetry, with core and root advancing to 1.13.0, OpenAI to 1.12.0, patch bumps for other stable packages, and 260730 stamps for alpha and beta packages. No optional beta cohort bump was applied; every prerelease package changed. Raise core floors conservatively across co-released packages. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 * Align co-released Python package dependencies Update the four hosting adapter pins to the co-released agent-framework-hosting alpha and raise the Azure Functions Durable Task floor to the co-released beta. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 * Minimize Python release lockfile updates Regenerate uv.lock with the pre-commit hook pinned uv version so the release changes only workspace package versions while preserving platform markers and agentlightning 0.3.0. Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541 --------- Copilot-Session: e234a28b-c2fd-4ff4-a51d-3d8917936541
Get Started with Microsoft Agent Framework Mistral AI
Please install this package:
pip install agent-framework-mistral --pre
and see the README for more information.
See the Mistral embedding sample for a runnable example.
Embedding Client
The MistralEmbeddingClient provides embedding generation using Mistral AI models.
Quick Start
from agent_framework.mistral import MistralEmbeddingClient
# Using environment variables (MISTRAL_API_KEY, MISTRAL_EMBEDDING_MODEL)
client = MistralEmbeddingClient()
# Or passing parameters directly
client = MistralEmbeddingClient(
model="mistral-embed",
api_key="your-api-key",
)
# Generate embeddings
result = await client.get_embeddings(["Hello, world!", "How are you?"])
for embedding in result:
print(f"Dimensions: {embedding.dimensions}")
print(f"Vector: {embedding.vector[:5]}...")
Configuration
| Environment Variable | Description |
|---|---|
MISTRAL_API_KEY |
Your Mistral AI API key |
MISTRAL_EMBEDDING_MODEL |
Embedding model name (e.g., mistral-embed) |
MISTRAL_SERVER_URL |
Optional server URL override |