* Python: Support prompt cache breakpoints for GPT-5.6 models in OpenAI clients Add request-level prompt_cache_options to OpenAIChatOptions and OpenAIChatCompletionOptions, and forward a per-part prompt_cache_breakpoint from Content.additional_properties onto the content blocks each API supports. Text parts that carry a breakpoint keep typed list content, since the plain-string form cannot hold one; without a breakpoint the existing string forms are unchanged. * Clarify system-message content-shape comment * Address review: SDK prompt cache types, private helper, add sample Replace the custom PromptCacheOptions TypedDict with the openai SDK's own types for each API, which raises the openai floor to 2.45.0 where those types were introduced. Make the breakpoint helper private to the two chat clients. Add a prompt caching sample with a README entry, and unquote the helper's Content annotation so the pyupgrade hook passes. * Guard the prompt cache options import for older openai versions The SDK's PromptCacheOptions types only exist in openai 2.45.0 and later, so each client falls back to a local mirror when the import fails and the dependency floor stays at 2.25.0. A TYPE_CHECKING-only import is not enough because the options classes are introspected with get_type_hints() at runtime. Verified against openai 2.25.0: the package imports, the fallback resolves, and part-level breakpoints still work; sending the option itself requires 2.45.0, which the field docstrings now note. * Make the old-openai fallback for PromptCacheOptions deliberately empty Assigning None instead, as suggested in review, trips pyright's reportInvalidTypeForm on the field annotation (the symbol becomes type | None after the try/except). An empty TypedDict gives the same effect for users on older openai versions: any content they put in prompt_cache_options is flagged by their type checker, since the option cannot be sent on those versions anyway, while get_type_hints() on the options classes keeps working at runtime. * Guard prompt_cache_options at runtime instead of via an empty fallback type The empty-TypedDict fallback flagged valid `prompt_cache_options` usage under pyright on every openai version — including this PR's own `client_prompt_caching.py` sample (`poe check -S`) — because pyright resolves the try/except symbol to the fallback shape regardless of the installed openai, while mypy/ty resolve the failed import to `Any` and never warn. So a type-only "warn on old openai" signal is not achievable cleanly across type checkers. Restore the faithful fallback (mirrors the SDK's `mode`/`ttl` shape) so the option type-checks identically on every supported openai version, and add a runtime guard: setting `prompt_cache_options` on openai < 2.45 now raises a clear ChatClientInvalidRequestException instead of forwarding an unusable option to the SDK. This keeps the option non-silent for all users regardless of type checker, without forcing an openai upgrade. Adds tests covering the guard for both clients. * Gate system/developer breakpoint shape on a real mapping value The system/developer branch switched to list-form content whenever prompt_cache_breakpoint was set to any non-None value, but the option is only attached when the value is a mapping. A malformed value (e.g. a string) therefore changed the message shape without adding a breakpoint. Decide the shape from the built part instead, matching the user-role path.
Python Samples
This directory contains samples demonstrating the capabilities of Microsoft Agent Framework for Python.
Structure
| Folder | Description |
|---|---|
01-get-started/ |
Progressive tutorial: hello agent → hosting |
02-agents/ |
Deep-dive by concept: tools, middleware, providers, orchestrations |
03-workflows/ |
Workflow patterns: sequential, concurrent, state, declarative, explicit output designation |
04-hosting/ |
Deployment: Azure Functions, Durable Tasks, A2A |
05-end-to-end/ |
Full applications, evaluation, demos |
Getting Started
Start with 01-get-started/ and work through the numbered files:
- 01_hello_agent.py — Create and run your first agent
- 02_add_tools.py — Add function tools with
@tool - 03_multi_turn.py — Multi-turn conversations with
AgentSession - 04_memory.py — Agent memory with
ContextProvider - 05_functional_workflow_with_agents.py — Call agents inside a functional workflow
- 06_functional_workflow_basics.py — Write a workflow as a plain async function
- 07_first_graph_workflow.py — Build a workflow with executors and edges
- 08_host_your_agent.py — Host your agent via Azure Functions
Prerequisites
pip install agent-framework-foundry
Install only the specific Agent Framework distributions required by the sample you want to run. Individual sample READMEs and PEP 723 metadata list any additional packages.
Environment Variables
Samples call load_dotenv() to automatically load environment variables from a .env file in the python/ directory. This is a convenience for local development and testing.
For local development, set up your environment using any of these methods:
Option 1: Using a .env file (recommended for local development):
- Copy
.env.exampleto.envin thepython/directory:cp .env.example .env - Edit
.envand set your values (API keys, endpoints, etc.)
Option 2: Export environment variables directly:
export FOUNDRY_PROJECT_ENDPOINT="your-foundry-project-endpoint"
export FOUNDRY_MODEL="gpt-4o"
Option 3: Using env_file_path parameter (for per-client configuration):
All client classes (e.g., OpenAIChatClient, OpenAIChatCompletionClient) support an env_file_path parameter to load environment variables from a specific file:
from agent_framework.openai import OpenAIChatClient
# Load from a custom .env file
client = OpenAIChatClient(env_file_path="path/to/custom.env")
This allows different clients to use different configuration files if needed.
For the generic OpenAI clients (OpenAIChatClient and OpenAIChatCompletionClient), routing
precedence is:
- Explicit Azure inputs such as
credential,azure_endpoint, orapi_version OPENAI_API_KEY/ explicit OpenAI API-key parameters- Azure environment fallback such as
AZURE_OPENAI_ENDPOINTandAZURE_OPENAI_API_KEY
If you keep both OpenAI and Azure variables in your shell, the generic clients stay on OpenAI until you pass an explicit Azure input.
For the getting-started samples, you'll need at minimum:
FOUNDRY_PROJECT_ENDPOINT="your-foundry-project-endpoint"
FOUNDRY_MODEL="gpt-4o"
Consolidated sample env inventory
This is the single source of truth for package-level environment variables read by packages included by
agent-framework-core[all]. It intentionally excludes variables that are only read by standalone samples,
package sample folders, or tests. When package code adds, removes, or renames an environment variable,
update this table in the same change.
Example values below are illustrative. For entries not backed by a single public class, the class
column names the closest public surface, helper, or package-level initialization point that reads the
variable.
| package | class/module | env var | example value |
|---|---|---|---|
agent-framework-anthropic |
AnthropicClient |
ANTHROPIC_API_KEY |
sk-ant-api03-... |
agent-framework-anthropic |
AnthropicClient |
ANTHROPIC_CHAT_MODEL |
claude-sonnet-4-5-20250929 |
agent-framework-foundry |
FoundryEmbeddingClient |
FOUNDRY_MODELS_ENDPOINT |
https://my-endpoint.inference.ai.azure.com |
agent-framework-foundry |
FoundryEmbeddingClient |
FOUNDRY_MODELS_API_KEY |
env-key |
agent-framework-foundry |
FoundryEmbeddingClient |
FOUNDRY_EMBEDDING_MODEL |
text-embedding-3-small |
agent-framework-foundry |
FoundryEmbeddingClient |
FOUNDRY_IMAGE_EMBEDDING_MODEL |
Cohere-embed-v3-english |
agent-framework-azure-ai-search |
AzureAISearchContextProvider |
AZURE_SEARCH_ENDPOINT |
https://my-search.search.windows.net |
agent-framework-azure-ai-search |
AzureAISearchContextProvider |
AZURE_SEARCH_API_KEY |
search-key |
agent-framework-azure-ai-search |
AzureAISearchContextProvider |
AZURE_SEARCH_INDEX_NAME |
hotels-index |
agent-framework-azure-ai-search |
AzureAISearchContextProvider |
AZURE_SEARCH_KNOWLEDGE_BASE_NAME |
hotels-kb |
agent-framework-azure-cosmos |
CosmosHistoryProvider |
AZURE_COSMOS_ENDPOINT |
https://my-cosmos.documents.azure.com:443/ |
agent-framework-azure-cosmos |
CosmosHistoryProvider |
AZURE_COSMOS_DATABASE_NAME |
agent-history |
agent-framework-azure-cosmos |
CosmosHistoryProvider |
AZURE_COSMOS_CONTAINER_NAME |
messages |
agent-framework-azure-cosmos |
CosmosHistoryProvider |
AZURE_COSMOS_KEY |
C2F...== |
agent-framework-bedrock |
BedrockChatClient |
BEDROCK_REGION |
us-east-1 |
agent-framework-bedrock |
BedrockChatClient |
BEDROCK_CHAT_MODEL |
anthropic.claude-3-5-sonnet-20241022-v2:0 |
agent-framework-bedrock |
BedrockEmbeddingClient |
BEDROCK_REGION |
us-east-1 |
agent-framework-bedrock |
BedrockEmbeddingClient |
BEDROCK_EMBEDDING_MODEL |
amazon.titan-embed-text-v2:0 |
agent-framework-bedrock |
BedrockChatClient / BedrockEmbeddingClient |
AWS_ACCESS_KEY_ID |
AKIAIOSFODNN7EXAMPLE |
agent-framework-bedrock |
BedrockChatClient / BedrockEmbeddingClient |
AWS_SECRET_ACCESS_KEY |
wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY |
agent-framework-bedrock |
BedrockChatClient / BedrockEmbeddingClient |
AWS_SESSION_TOKEN |
IQoJb3JpZ2luX2VjEO7//////////wEaCXVzLXdlc3QtMiJHMEUCIQD... |
agent-framework-copilotstudio |
CopilotStudioAgent |
COPILOTSTUDIOAGENT__ENVIRONMENTID |
00000000-0000-0000-0000-000000000000 |
agent-framework-copilotstudio |
CopilotStudioAgent |
COPILOTSTUDIOAGENT__SCHEMANAME |
cr123_agentname |
agent-framework-copilotstudio |
CopilotStudioAgent |
COPILOTSTUDIOAGENT__TENANTID |
11111111-1111-1111-1111-111111111111 |
agent-framework-copilotstudio |
CopilotStudioAgent |
COPILOTSTUDIOAGENT__AGENTAPPID |
22222222-2222-2222-2222-222222222222 |
agent-framework-core |
observability |
ENABLE_INSTRUMENTATION |
true |
agent-framework-core |
observability |
ENABLE_SENSITIVE_DATA |
false |
agent-framework-core |
observability |
ENABLE_CONSOLE_EXPORTERS |
true |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_ENDPOINT |
http://localhost:4317 |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_TRACES_ENDPOINT |
http://localhost:4318/v1/traces |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_METRICS_ENDPOINT |
http://localhost:4318/v1/metrics |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_LOGS_ENDPOINT |
http://localhost:4318/v1/logs |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_PROTOCOL |
grpc |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_HEADERS |
api-key=demo |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_TRACES_HEADERS |
api-key=trace-demo |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_METRICS_HEADERS |
api-key=metric-demo |
agent-framework-core |
observability |
OTEL_EXPORTER_OTLP_LOGS_HEADERS |
api-key=log-demo |
agent-framework-core |
observability |
OTEL_SERVICE_NAME |
sample-agent |
agent-framework-core |
observability |
OTEL_SERVICE_VERSION |
1.0.0 |
agent-framework-core |
observability |
OTEL_RESOURCE_ATTRIBUTES |
deployment.environment=dev,service.namespace=agent-framework |
agent-framework-devui |
DevUI server |
DEVUI_AUTH_TOKEN |
my-devui-token |
agent-framework-foundry |
FoundryChatClient |
FOUNDRY_PROJECT_ENDPOINT |
https://my-project.services.ai.azure.com/api/projects/my-project |
agent-framework-foundry |
FoundryChatClient |
FOUNDRY_MODEL |
gpt-4o |
agent-framework-foundry |
FoundryAgent |
FOUNDRY_AGENT_NAME |
travel-planner |
agent-framework-foundry |
FoundryAgent |
FOUNDRY_AGENT_VERSION |
v1 |
agent-framework-github-copilot |
GitHubCopilotAgent |
GITHUB_COPILOT_CLI_PATH |
copilot |
agent-framework-github-copilot |
GitHubCopilotAgent |
GITHUB_COPILOT_MODEL |
gpt-5 |
agent-framework-github-copilot |
GitHubCopilotAgent |
GITHUB_COPILOT_TIMEOUT |
60 |
agent-framework-github-copilot |
GitHubCopilotAgent |
GITHUB_COPILOT_LOG_LEVEL |
info |
agent-framework-mem0 |
agent_framework_mem0 package import |
MEM0_TELEMETRY |
false |
agent-framework-ollama |
OllamaChatClient |
OLLAMA_HOST |
http://localhost:11434 |
agent-framework-ollama |
OllamaChatClient |
OLLAMA_MODEL |
llama3.1:8b |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
OPENAI_API_KEY |
sk-proj-... |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
OPENAI_MODEL |
gpt-4o-mini |
agent-framework-openai |
OpenAIChatClient |
OPENAI_CHAT_MODEL |
gpt-4.1-mini |
agent-framework-openai |
OpenAIChatCompletionClient |
OPENAI_CHAT_COMPLETION_MODEL |
gpt-4o |
agent-framework-openai |
OpenAIEmbeddingClient |
OPENAI_EMBEDDING_MODEL |
text-embedding-3-small |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
OPENAI_BASE_URL |
https://api.openai.com/v1/ |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
OPENAI_ORG_ID |
org_123456789 |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_ENDPOINT |
https://my-resource.openai.azure.com/ |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_API_KEY |
sk-azure-... |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_API_VERSION |
2024-10-21 |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_BASE_URL |
https://my-resource.openai.azure.com/openai/v1/ |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_MODEL |
gpt-4o |
agent-framework-openai |
OpenAIChatClient |
AZURE_OPENAI_CHAT_MODEL |
gpt-4.1 |
agent-framework-openai |
OpenAIChatCompletionClient |
AZURE_OPENAI_CHAT_COMPLETION_MODEL |
gpt-4o-mini |
agent-framework-openai |
OpenAIEmbeddingClient |
AZURE_OPENAI_EMBEDDING_MODEL |
text-embedding-3-large |
agent-framework-openai |
OpenAIChatClient / OpenAIChatCompletionClient / OpenAIEmbeddingClient |
AZURE_OPENAI_RESOURCE_URL |
https://cognitiveservices.azure.com/ |
agent-framework-openai supports the Azure OpenAI client-specific deployment aliases listed above; keep
packages/openai/README.md as the authoritative reference for the exact fallback order and package-specific
behavior.
Note for production: In production environments, set environment variables through your deployment platform (e.g., Azure App Settings, Kubernetes ConfigMaps/Secrets) rather than using .env files. The load_dotenv() call in samples will have no effect when a .env file is not present, allowing environment variables to be loaded from the system.
For Azure authentication, run az login before running samples.
Note on XML tags
Some sample files include XML-style snippet tags (for example <snippet_name> and </snippet_name>). These are used by our documentation tooling and can be ignored or removed when you use the samples outside this repository.
Additional Resources
- Agent Framework Documentation
- AGENTS.md — Structure documentation for maintainers
- SAMPLE_GUIDELINES.md — Coding conventions for samples