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Python: [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces (#4990)

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* [BREAKING] Remove deprecated Python OpenAI/Azure AI surfaces

Also clean up follow-on docs, environment guidance, package metadata, and lab test stability.

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Fix deleted semantic-kernel sample links

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* Address PR review feedback

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

* improve foundry language

* Fix A2A Foundry sample regression

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
This commit is contained in:
Eduard van Valkenburg
2026-03-31 22:36:21 +02:00
committed by GitHub
Unverified
parent a5eacbbe65
commit 3a49b1d6dd
144 changed files with 669 additions and 18739 deletions
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python/samples/02-agents/context_providers/azure_ai_search/README.md
+12 -8
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@@ -49,14 +49,14 @@ Run `az login` if using Entra ID authentication.
**Common (both modes):**
- `AZURE_SEARCH_ENDPOINT`: Your Azure AI Search endpoint (e.g., `https://myservice.search.windows.net`)
- `AZURE_SEARCH_INDEX_NAME`: Name of your search index
- `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI Foundry project endpoint
- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: Model deployment name (e.g., `gpt-4o`, defaults to `gpt-4o`)
- `FOUNDRY_PROJECT_ENDPOINT`: Your Azure AI Foundry project endpoint
- `FOUNDRY_MODEL`: Model deployment name (e.g., `gpt-4o`, defaults to `gpt-4o`)
- `AZURE_SEARCH_API_KEY`: _(Optional)_ Your search API key - if not provided, uses DefaultAzureCredential
**Agentic mode only:**
- `AZURE_SEARCH_KNOWLEDGE_BASE_NAME`: Name of your Knowledge Base in Azure AI Search
- `AZURE_OPENAI_RESOURCE_URL`: Your Azure OpenAI resource URL (e.g., `https://myresource.openai.azure.com`)
- **Important**: This is different from `AZURE_AI_PROJECT_ENDPOINT` - Knowledge Base needs the OpenAI endpoint for model calls
- **Important**: This is different from `FOUNDRY_PROJECT_ENDPOINT` - Knowledge Base needs the OpenAI endpoint for model calls
### Example .env file
@@ -64,8 +64,8 @@ Run `az login` if using Entra ID authentication.
```env
AZURE_SEARCH_ENDPOINT=https://myservice.search.windows.net
AZURE_SEARCH_INDEX_NAME=my-index
AZURE_AI_PROJECT_ENDPOINT=https://<resource-name>.services.ai.azure.com/api/projects/<project-name>
AZURE_AI_MODEL_DEPLOYMENT_NAME=gpt-4o
FOUNDRY_PROJECT_ENDPOINT=https://<resource-name>.services.ai.azure.com/api/projects/<project-name>
FOUNDRY_MODEL=gpt-4o
# Optional - omit to use Entra ID
AZURE_SEARCH_API_KEY=your-search-key
```
@@ -127,7 +127,8 @@ AZURE_OPENAI_RESOURCE_URL=https://myresource.openai.azure.com
```python
from agent_framework import Agent
from agent_framework.azure import AzureAIAgentClient, AzureAISearchContextProvider
from agent_framework.azure import AzureAISearchContextProvider
from agent_framework.foundry import FoundryChatClient
from azure.identity.aio import DefaultAzureCredential
# Create search provider with semantic mode (default)
@@ -140,10 +141,13 @@ search_provider = AzureAISearchContextProvider(
)
# Create agent with search context
async with AzureAIAgentClient(credential=DefaultAzureCredential()) as client:
async with FoundryChatClient(
project_endpoint=project_endpoint,
model=model_deployment,
credential=DefaultAzureCredential(),
) as client:
async with Agent(
client=client,
model=model_deployment,
context_providers=[search_provider],
) as agent:
response = await agent.run("What information is in the knowledge base?")
python/samples/02-agents/context_providers/azure_ai_search/search_context_agentic.py
+2 -2
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@@ -34,7 +34,7 @@ Environment variables:
- AZURE_SEARCH_ENDPOINT: Your Azure AI Search endpoint
- AZURE_SEARCH_API_KEY: (Optional) API key - if not provided, uses AzureCliCredential
- FOUNDRY_PROJECT_ENDPOINT: Your Azure AI Foundry project endpoint
- AZURE_AI_MODEL_DEPLOYMENT_NAME: Your model deployment name (e.g., "gpt-4o")
- FOUNDRY_MODEL: Your model deployment name (e.g., "gpt-4o")
For using an existing Knowledge Base (recommended):
- AZURE_SEARCH_KNOWLEDGE_BASE_NAME: Your Knowledge Base name
@@ -59,7 +59,7 @@ async def main() -> None:
search_endpoint = os.environ["AZURE_SEARCH_ENDPOINT"]
search_key = os.environ.get("AZURE_SEARCH_API_KEY")
project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
model_deployment = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o")
model_deployment = os.environ.get("FOUNDRY_MODEL", "gpt-4o")
# Agentic mode requires exactly ONE of: knowledge_base_name OR index_name
# Option 1: Use existing Knowledge Base (recommended)
python/samples/02-agents/context_providers/azure_ai_search/search_context_semantic.py
+2 -2
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@@ -31,7 +31,7 @@ Prerequisites:
- AZURE_SEARCH_API_KEY: (Optional) Your search API key - if not provided, uses AzureCliCredential for Entra ID
- 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")
- FOUNDRY_MODEL: Your model deployment name (e.g., "gpt-4o")
- 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
"""
@@ -54,7 +54,7 @@ async def main() -> None:
search_key = os.environ.get("AZURE_SEARCH_API_KEY")
index_name = os.environ["AZURE_SEARCH_INDEX_NAME"]
project_endpoint = os.environ["FOUNDRY_PROJECT_ENDPOINT"]
model_deployment = os.environ.get("AZURE_AI_MODEL_DEPLOYMENT_NAME", "gpt-4o")
model_deployment = os.environ.get("FOUNDRY_MODEL", "gpt-4o")
openai_endpoint = os.environ.get("AZURE_OPENAI_ENDPOINT")
embedding_deployment = os.environ.get("AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME")
python/samples/02-agents/context_providers/mem0/README.md
+2 -2
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@@ -33,8 +33,8 @@ Set the following environment variables:
- `OPENAI_API_KEY`: Your OpenAI API key (used by Mem0 OSS for embedding generation and automatic memory extraction)
**For Azure AI:**
- `AZURE_AI_PROJECT_ENDPOINT`: Your Azure AI project endpoint
- `AZURE_AI_MODEL_DEPLOYMENT_NAME`: The name of your model deployment
- `FOUNDRY_PROJECT_ENDPOINT`: Your Azure AI project endpoint
- `FOUNDRY_MODEL`: The name of your model deployment
## Key Concepts
python/samples/02-agents/context_providers/redis/README.md
+6 -6
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@@ -51,8 +51,8 @@ See quickstart: `https://learn.microsoft.com/azure/redis/quickstart-create-manag
### Environment variables
- `AZURE_AI_PROJECT_ENDPOINT` (required): Azure AI Foundry project endpoint for `AzureOpenAIResponsesClient`
- `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME` (required): Azure OpenAI Responses deployment name
- `FOUNDRY_PROJECT_ENDPOINT` (required): Azure AI Foundry project endpoint for `FoundryChatClient`
- `FOUNDRY_MODEL` (required): Foundry model deployment name
- `OPENAI_API_KEY` (optional): Required only if you set `vectorizer_choice="openai"` to enable hybrid search.
### Provider configuration highlights
@@ -73,7 +73,7 @@ The provider supports both full‑text only and hybrid vector search:
2. Agent integration: teaches the agent a preference and verifies it is remembered across turns.
3. Agent + tool: calls a sample tool (flight search) and then asks the agent to recall details remembered from the tool output.
It uses `AzureOpenAIResponsesClient` (Foundry project endpoint setup) for chat and, in some steps, optional OpenAI embeddings for hybrid search.
It uses `FoundryChatClient` for chat and, in some steps, optional OpenAI embeddings for hybrid search.
## How to run
@@ -82,8 +82,8 @@ It uses `AzureOpenAIResponsesClient` (Foundry project endpoint setup) for chat a
2) Set Azure Foundry/OpenAI responses environment variables:
```bash
export AZURE_AI_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
export AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME="<deployment-name>"
export FOUNDRY_PROJECT_ENDPOINT="https://<resource>.services.ai.azure.com/api/projects/<project>"
export FOUNDRY_MODEL="<deployment-name>"
```
3) (Optional) Set your OpenAI key if using embeddings:
@@ -119,6 +119,6 @@ You should see the agent responses and, when using embeddings, context retrieved
## Troubleshooting
- Ensure at least one of `application_id`, `agent_id`, `user_id`, or `thread_id` is set; the provider requires a scope.
- Verify `AZURE_AI_PROJECT_ENDPOINT` and `AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME` are set for the chat client.
- Verify `FOUNDRY_PROJECT_ENDPOINT` and `FOUNDRY_MODEL` are set for the chat client.
- If using embeddings, verify `OPENAI_API_KEY` is set and reachable.
- Make sure Redis exposes RediSearch (Redis Stack image or managed service with search enabled).