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Daria Korenieva
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* Python: Add Mistral AI embedding client package Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: fix dimensions check, sort embeddings by index, align docs Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Address review feedback: downgrade to alpha, remove integration tests - Change version to 1.0.0a260505 (alpha) - Update classifier to Development Status :: 3 - Alpha - Update PACKAGE_STATUS.md to alpha - Remove Mistral from integration test workflows (no API keys yet) Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Add samples directory for alpha package compliance Per python-package-management skill: alpha packages must include samples inside the package directory. Signed-off-by: Daria Korenieva <daric2612@gmail.com> * Fix ruff formatting in sample file Signed-off-by: Daria Korenieva <daric2612@gmail.com> --------- Signed-off-by: Daria Korenieva <daric2612@gmail.com>
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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.
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 |