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Merge branch 'main' into local-branch-fix-samples-and-sample-validation

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Tao Chen
2026-03-30 08:15:48 -07:00
Unverified
parent 6c44d04950 4527dee64b
commit c305017b4e
477 changed files with 22032 additions and 11430 deletions
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python/samples/02-agents/context_providers/azure_ai_search/search_context_semantic.py
+9 -8
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@@ -4,8 +4,9 @@ import asyncio
import os
from agent_framework import Agent
from agent_framework.azure import AzureAISearchContextProvider, AzureOpenAIEmbeddingClient
from agent_framework.azure import AzureAISearchContextProvider
from agent_framework.foundry import FoundryChatClient
from agent_framework.openai import OpenAIEmbeddingClient
from azure.identity.aio import AzureCliCredential
from dotenv import load_dotenv
@@ -31,8 +32,8 @@ Prerequisites:
- AZURE_SEARCH_INDEX_NAME: Your search index name
- FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
- AZURE_AI_MODEL_DEPLOYMENT_NAME: Your model deployment name (e.g., "gpt-4o")
- AZURE_OPENAI_EMBEDDING_MODEL_ID: (Optional) Your embedding model for hybrid search (e.g., "text-embedding-3-small")
- AZURE_OPENAI_ENDPOINT: (Optional) Your Azure OpenAI resource URL, required if using an OpenAI embedding model for hybrid search
- AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME: (Optional) Your Azure OpenAI embedding deployment for hybrid search
- AZURE_OPENAI_ENDPOINT: (Optional) Your Azure OpenAI resource URL, required if using Azure OpenAI embeddings
"""
# Sample queries to demonstrate RAG
@@ -55,13 +56,13 @@ async def main() -> None:
project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
model_deployment = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o")
openai_endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT")
embedding_model = os.environ.get("AZURE_OPENAI_EMBEDDING_MODEL_ID", "text-embedding-3-small")
embedding_deployment = os.environ.get("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME")
embedding_client = None
if openai_endpoint and embedding_model:
embedding_client = AzureOpenAIEmbeddingClient(
endpoint=openai_endpoint,
model=embedding_model,
if openai_endpoint and embedding_deployment:
embedding_client = OpenAIEmbeddingClient(
azure_endpoint=openai_endpoint,
model=embedding_deployment,
credential=credential,
)