Files
microsoft--agent-framework/python/samples
Ahmed Muhsin 5ab8877ba5 Python: HITL respond-URL addressing from inside workflows (#7001)
* feat(durabletask): surface HITL respond-URL addressing to workflow executors

Let a workflow notify a human reviewer (e.g. email an approval link) from inside the
graph, without the caller threading the instanceId/requestId by hand.

- durabletask: the orchestrator injects host_context {instance_id, workflow_name,
  request_path_prefix} into each activity input; CapturingRunnerContext surfaces it as
  host_metadata. No new core API.
- azurefunctions: WorkflowHitlContext.from_context(ctx) builds the canonical
  respond/status URLs (returns None in-process so callers degrade gracefully).
  Re-exported through the agent_framework.azure lazy namespace.
- Nested sub-workflows: the address context (root instance + workflow name +
  accumulated {executor}~{ordinal}~ prefix) propagates down call_sub_orchestrator via a
  new SUBWORKFLOW_ADDRESS_KEY marker, so an executor at any depth builds a URL that
  targets the addressable top-level instance with a qualified request id. The per-child
  ordinal matches the read-side enumerate() index used by the status/respond endpoints.
  The marker is stripped from untrusted input alongside SUBWORKFLOW_INPUT_KEY
  (confused-deputy / info-leak guard).
- Samples 12 and 13 reworked into the retry-safe two-step notify pattern: the emitter
  generates an explicit request id and a downstream NotifyExecutor builds the URL and
  notifies, so failed upstream retries never produce a dead link.

Tests: unit coverage for the metadata round-trip, address/ordinal agreement (fan-out at
depth and nested prefix accumulation), marker stripping, and URL building; integration
tests assert the helper-built URL equals the server respondUrl and resumes the run, for
both the flat (12) and nested (13) samples.

* refactor(durabletask): read back request_info id instead of generating one in samples

Add WorkflowHitlContext.pending_request_id(ctx), an async helper that returns the
id request_info just generated (read from the runner context's pending request-info
events). This works on any host via the core RunnerContext protocol method, so it
needs no core change.

Samples 12 and 13 now call request_info() and read the id back to forward to the
NotifyExecutor, instead of minting a uuid by hand and passing request_id=. The
read-back happens in the same activity execution that generated the id, so the
pending request event and the notify message still commit together with the same id
(retry-safe; failed upstream retries notify no one).

* docs(azurefunctions): document request_info id read-back and notify safety

Tighten pending_request_id docstring to require calling it immediately after request_info, and explain why that is safe on the durable host (each executor runs in its own activity with its own runner context, so the pending set only holds this executor's requests and the newest is the one just emitted). Document the two-step notify pattern in the 12 and 13 sample READMEs, including the downstream-notifier retry safety and the nested address-prefix propagation.

* fix(python): resolve ty typing error and address PR review comments

- test_subworkflow_orchestration: replace the mypy-only type:ignore[arg-type] with a cast so the ty checker passes too (the other four checkers already honored the ignore).

- samples 12/13 README: guard the notify snippet against None before build_respond_url to match the documented graceful-degradation behavior.

- integration tests 12/13: reword comments that implied request_info now generates an explicit uuid4; it generates the id internally by default.

* fix(python): honor configurable Functions route prefix and address HITL PR review

- Resolve the route prefix from host.json (extensions.http.routePrefix, default api) in a new azurefunctions _routes module, used by both the server endpoints and WorkflowHitlContext, so a custom or empty routePrefix no longer 404s respond/status URLs (was hardcoded /api/ in four places).

- Extract respond/status URL construction into one shared builder called from _app.py and _hitl_context.py, removing the sync-by-test duplication.

- Broaden loopback detection (localhost, 127.0.0.0/8, 0.0.0.0, ::1, [::1]) via a _is_loopback helper so local links use http.

- Pin the host_context key names as shared constants in durabletask so producer and azurefunctions consumer cannot drift.

- Reword a stale base_url comment to reference WEBSITE_HOSTNAME.

- Add unit tests for the route module and loopback handling.

* refactor(azurefunctions): derive server-side HITL URLs from the request URL

The run and status endpoints now derive the base URL and route prefix from the incoming request URL (the value the host actually routed) via split_request_url, so the caller-visible respond/status URLs no longer depend on reading host.json on the server. The in-workflow helper keeps reading host.json since it has no request context. Replaces strip_route_prefix and updates its tests.

* test(durabletask): enforce sub-workflow ordinal and read-index agreement

Extract the read-side subworkflows grouping into a shared _index_subworkflows helper (used by the orchestrator) and add test_readside_index_matches_dispatch_ordinal, which round-trips a fan-out through that helper and asserts subworkflows[executor][ordinal] resolves to the child the dispatch stamped that ordinal onto. Turns the previously comment-only write-ordinal / read-index invariant into a shared, CI-enforced one.

* fix(azurefunctions): suppress bandit B104 on loopback host set
2026-07-16 22:06:25 +00:00
..
2025-07-28 07:33:42 +00:00

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:

  1. 01_hello_agent.py — Create and run your first agent
  2. 02_add_tools.py — Add function tools with @tool
  3. 03_multi_turn.py — Multi-turn conversations with AgentSession
  4. 04_memory.py — Agent memory with ContextProvider
  5. 05_functional_workflow_with_agents.py — Call agents inside a functional workflow
  6. 06_functional_workflow_basics.py — Write a workflow as a plain async function
  7. 07_first_graph_workflow.py — Build a workflow with executors and edges
  8. 08_host_your_agent.py — Host your agent via Azure Functions

Prerequisites

pip install agent-framework

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):

  1. Copy .env.example to .env in the python/ directory:
    cp .env.example .env
    
  2. Edit .env and 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:

  1. Explicit Azure inputs such as credential, azure_endpoint, or api_version
  2. OPENAI_API_KEY / explicit OpenAI API-key parameters
  3. Azure environment fallback such as AZURE_OPENAI_ENDPOINT and AZURE_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