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Eduard van Valkenburg d5c07f2623 Python: feat(foundry): add to_prompt_agent / deploy_as_prompt_agent (experimental) (#5959) 
* feat(foundry): add experimental to_prompt_agent converter

Adds `to_prompt_agent(agent)`, an experimental converter
(`ExperimentalFeature.TO_PROMPT_AGENT`) that turns an Agent Framework
`Agent` into a Foundry `PromptAgentDefinition` ready to publish via
`AIProjectClient.agents.create_version(...)`.

Behaviour:

* `agent.client` must be a `FoundryChatClient` (or subclass); otherwise
  `TypeError` is raised. The model deployment name is lifted from the
  bound client so the same Agent definition used for local runs can be
  published as a hosted prompt agent without restating the model.
* Foundry SDK tool instances (from `FoundryChatClient.get_*_tool()`) are
  passed through unchanged. AF `FunctionTool`s (and `@tool`-decorated
  callables) are emitted as Foundry `FunctionTool` declarations.
* Local AF MCP tools cannot be expressed in a `PromptAgentDefinition`;
  the converter raises `ValueError` and points at
  `FoundryChatClient.get_mcp_tool()` for hosted MCP servers.
* The converter walks both `agent.default_options["tools"]` and
  `agent.mcp_tools` because `normalize_tools()` splits local MCP off
  into its own list.

Re-exported through the `agent_framework.foundry` lazy-loading namespace
(updates both `__init__.py` and the `__init__.pyi` type stub).

Adds a portable-agent sample showing the same `Agent` driven through
both `agent.run(...)` and `to_prompt_agent(agent)`, and a README section
covering the new converter.

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

* chore(samples): remove snippet tags from portable agent sample

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

* chore(samples): inline FoundryChatClient and enable prompt-agent publish

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

* chore(samples): drop async credential context manager

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

* docs(foundry): trim README to_prompt_agent example to publish-only flow

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

* docs(foundry): note FoundryAgent runs @tool callables for deployed prompt agents

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

* fix(foundry): address review comments on to_prompt_agent converter

* Construct `PromptAgentDefinition` `Tool` from a dict via `**tool_item`
  unpacking rather than the positional Mapping constructor \u2014 cleaner and
  matches the typical Pydantic / Azure SDK pattern.
* Drop the redundant `isinstance(mcp_tool, MCPTool)` guard in
  `_convert_tools`; the parameter is already typed `Iterable[MCPTool]` so
  the second `raise` was unreachable. The remaining single `raise`
  fires for every entry as intended.

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

* fix(foundry): match Agent.__init__ model resolution in to_prompt_agent

* Read the model from `agent.default_options.get("model")` first,
  falling back to `agent.client.model`. This mirrors the order
  `Agent.__init__` uses (`_agents.py:740`) when assembling
  default_options, so the model the agent runs with is the same model
  the converter publishes \u2014 e.g. when the caller passes
  `default_options={"model": "..."}` to override the bound client.
* Updated the missing-model error message to point at both the client
  and the default_options paths.
* Added tests:
  * tool-only agent with no `instructions` produces a definition
    where `instructions` is `None` and is omitted from the dict
    payload (`Agent.__init__` strips None values from default_options
    before storing them).
  * `default_options['model']` wins over the bound client's model.
  * Fallback to client.model when default_options has no model.

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

* feat(foundry): add deploy_as_prompt_agent helper + samples

Adds `deploy_as_prompt_agent(agent)`, a convenience wrapper around
`to_prompt_agent` that reuses the bound FoundryChatClient's project
client to call `project_client.agents.create_version(...)`. Defaults
`agent_name` / `description` from `agent.name` / `agent.description`
so the Agent stays the single source of truth.

* Exposed from `agent_framework_foundry` and the lazy-loading
  `agent_framework.foundry` namespace (including the .pyi stub).
* Marked experimental with the existing
  `ExperimentalFeature.TO_PROMPT_AGENT` tag.
* Tests cover the happy path, name/description defaulting, explicit
  override, no-name error, metadata + description forwarding, extra
  kwargs passthrough, and the experimental metadata.

Samples:
* Renamed the existing sample to `creating_prompt_agents.py`, drops
  'portable' wording, presents `deploy_as_prompt_agent` first as the
  recommended path and `to_prompt_agent` + `AIProjectClient` as the
  two-step alternative, and adds a cleanup step that deletes the
  published agent so re-runs stay idempotent.
* New `using_prompt_agents.py` shows the end-to-end loop: deploy the
  agent, connect to it with `FoundryAgent` passing the same local
  `@tool` callable, run a query against the deployed prompt agent,
  then clean up.

README updated to introduce `deploy_as_prompt_agent` as the
recommended path and link to both runnable samples.

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

* fix(foundry): restore missing-model ValueError in to_prompt_agent

The check was accidentally dropped while reworking docstrings in the
previous commit. Test `test_to_prompt_agent_rejects_missing_model`
exercises this path and was failing on CI as a result.

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

* refactor(foundry): rename deploy_as_prompt_agent -> create_prompt_agent

Renames the helper across the foundry package, core lazy-loader stubs,
tests, README and samples. The new name better matches the action
performed (a prompt-agent definition is created in Foundry) and is
consistent with the surrounding ''create_*'' API surface.

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

* refactor(foundry): drop create_prompt_agent, enrich to_prompt_agent params

Remove the create_prompt_agent helper and consolidate on to_prompt_agent.
Expose every PromptAgentDefinition parameter that has either an Agent
Framework equivalent (sourced from default_options) or no equivalent
(accepted as a keyword argument).

* default_options-sourced (with kwarg overrides):
  temperature, top_p, string tool_choice
* kwarg-only Foundry knobs:
  reasoning, text, structured_inputs, rai_config, ToolChoiceParam tool_choice

Precedence is always: explicit keyword > default_options entry > unset.

Tests cover every path (defaults, default_options, kwargs, kwarg override).
Samples and README rewritten around the enriched to_prompt_agent.

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

* refactor(foundry): single source of truth for prompt-agent options

Stop duplicating the generation-parameter surface between FoundryChatOptions
and to_prompt_agent. Translate every field with an Agent Framework equivalent
(temperature, top_p, tool_choice, reasoning, response_format/text/verbosity)
from agent.default_options via a new RawFoundryChatClient helper
_prepare_prompt_agent_options. Only Foundry-specific fields with no AF
equivalent — structured_inputs and rai_config — remain as keyword arguments
on to_prompt_agent.

- tool_choice is dropped when there are no tools (mirrors _prepare_options
  semantics and avoids polluting tool-less prompt agents with Agent.__init__'s
  'auto' default).
- response_format Pydantic models route through
  openai.lib._parsing._responses.type_to_text_format_param; dict shapes go
  through the existing _prepare_response_and_text_format helper.
- default_options is not mutated; text dict is defensively copied.

Tests, README, and creating_prompt_agents.py sample updated to reflect the
new single-source model.

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

* docs(foundry): consolidate prompt-agent sample

Drop creating_prompt_agents.py (the publish-only variant) and rename
using_prompt_agents.py to foundry_prompt_agents.py so the single sample
covers the full convert -> publish -> connect -> run loop. Update the
README link list accordingly.

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

* docs(foundry): run local Agent + deployed agent in same sample

Add an agent.run() call against the local Agent before publishing, then run
the deployed prompt agent on the same query. Expand the docstring with a
compare-and-contrast covering runtime/latency, configurability, and
persistence/sharing differences between the two execution paths.

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

* test(foundry): cover conflicting response_format + text.format in to_prompt_agent

Exercises the ValueError path when a Pydantic response_format would overwrite
an explicit text.format mapping with a different shape. Lifts _chat_client.py
coverage from 89% to 90%.

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

* refactor(foundry): move _prepare_prompt_agent_options into _to_prompt_agent

Lift the translation helper off RawFoundryChatClient and into the
_to_prompt_agent module as a module-private function that takes the client
as its first argument. The chat client no longer needs to carry a method
whose only consumer is the prompt-agent converter, while still serving as
the source of the request-path helper (_prepare_response_and_text_format)
that the converter reuses for dict-shaped response_format values.

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

* docs(python): codify GA terminology + post-run docs review

Add two pieces of guidance to python/AGENTS.md:

* Terminology - reserve 'GA' for hosted services; use 'released' or 'stable'
  for Agent Framework code/features to match the feature-lifecycle stages.
* Maintaining Documentation - review AGENTS.md and skills at the end of every
  run and update any guidance the conversation made stale; before adding a
  new principle, ask the user to confirm it should be captured.

Also pulls in a docstring fix in foundry_prompt_agents.py that swaps the
stray 'GA' for 'released', applying the new terminology rule.

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

* address PR review: strict=True default, Tool._deserialize dispatch, sample cleanup safety

- FunctionTool published as strict=True so the server-side schema validation
  matches what the local FoundryAgent(tools=[same_callable]) dispatcher
  enforces. AF FunctionTool has no 'strict' attribute, so the safer default
  is used uniformly instead of silently downgrading to a permissive contract.
- _validate_mapping_tool now dispatches through ProjectsTool._deserialize so
  dict-shaped tools rehydrate to the concrete subclass (FunctionTool,
  WebSearchTool, ...) via the 'type' discriminator instead of returning a
  generic Tool. Added a test that asserts isinstance(WebSearchTool) and a
  new test for the function-typed dict path.
- foundry_prompt_agents.py sample now wraps credential + project client in
  async with and the create_version / run flow in try/finally so a failure
  on connect or run still deletes the published prompt agent rather than
  leaving an orphaned, billable resource in the user's Foundry project.

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

* fix(ci): correct linkspector ignorePattern typo (./pulls -> ./pull)

GitHub PR URLs use the singular segment /pull/N (compare to /issues/N
for issues). The existing './pulls' ignore pattern never matched
anything as a result, so legitimately stale PR links (e.g. PRs deleted
from forks) surface as linkspector failures on unrelated PRs.

This is the same convention the './issues' rule above already follows.
Fixes the markdown-link-check failure on a dangling link in
dotnet/src/Microsoft.Agents.AI.DurableTask/CHANGELOG.md.

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

---------

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
d5c07f2623 · 2026-05-27 13:31:21 +00:00
History
..
01-get-started
Python: Add requirements.txt and .env.example to the a2a/ sample for pip-based setup (#5510)
2026-04-27 22:22:07 +00:00
02-agents
Python: feat(foundry): add to_prompt_agent / deploy_as_prompt_agent (experimental) (#5959)
2026-05-27 13:31:21 +00:00
03-workflows
Python: Add Python parity sample for invoking Foundry Toolbox tools from declarative workflows (#5933)
2026-05-26 15:36:33 +00:00
04-hosting
Python: Show more authentication methods in Foundry Toolbox MCP (#5719)
2026-05-20 12:00:38 +00:00
05-end-to-end
Python: Update package dependencies (#5555)
2026-04-29 06:18:03 +00:00
autogen-migration
Fix handoff workflow context management and improve AG-UI demo (#5136)
2026-04-08 04:08:24 +00:00
semantic-kernel-migration
Python: Improve the handling of intermediate outputs for workflows and orchestrations (#5623)
2026-05-19 00:15:25 +00:00
shared
Python: Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference (#4207)
2026-02-25 17:45:08 +00:00
__init__.py
Python telemetry (#223)
2025-07-28 07:33:42 +00:00
AGENTS.md
Python: [BREAKING] update to v1.0.0 (#5062)
2026-04-02 15:26:30 +00:00
README.md
[BREAKING] Python: Enable instrumentation by default (#5865)
2026-05-20 11:52:08 +00:00
SAMPLE_GUIDELINES.md
Python: [BREAKING] Python: Provider-leading client design & OpenAI package extraction (#4818)
2026-03-25 09:56:29 +00:00

README.md

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

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