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agent-framework/python/AGENTS.md
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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>
2026-05-27 13:31:21 +00:00

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AGENTS.md

Instructions for AI coding agents working in the Python codebase.

Key Documentation:

Agent Skills (.github/skills/) — detailed, task-specific instructions loaded on demand:

  • python-development — coding standards, type annotations, docstrings, logging, performance
  • python-testing — test structure, fixtures, async mode, running tests
  • python-code-quality — linting, formatting, type checking, prek hooks, CI workflow
  • python-feature-lifecycle — package vs feature lifecycle stages, decorators, enums, and promotion guidance
  • python-package-management — monorepo structure, lazy loading, versioning, new packages
  • python-samples — sample file structure, PEP 723, documentation guidelines

Maintaining Documentation

When making changes to a package, check if the following need updates:

  • The package's AGENTS.md file (adding/removing/renaming public APIs, architecture changes, import path changes)
  • The agent skills in .github/skills/ if conventions, commands, or workflows change

At the end of every run, re-read AGENTS.md and the relevant skill files and update any guidance that the conversation revealed to be out of date, incomplete, or misleading (renamed files, changed commands, new conventions the user confirmed, etc.). Before adding a new principle or rule, ask the user whether they want it captured as a durable principle — do not invent team norms from a single conversation without explicit confirmation.

Terminology

  • Avoid "GA" for Agent Framework code. Reserve GA for hosted services (e.g. "the Foundry service is GA"). For Agent Framework packages, features, and APIs use "released" or "stable" depending on context — these match the feature-lifecycle stages documented in the python-feature-lifecycle skill.

Pull Request Description Guidance

When preparing a PR description:

  • Follow the repository PR template at .github/pull_request_template.md and keep its structure/headings.
  • Describe the net change relative to main (this is implied; do not call it out explicitly as "vs main").
  • Do not add ad-hoc validation sections (for example, "Validation" or "Tests run"); CI/CD and the template checklist cover validation status.

Quick Reference

Run uv run poe from the python/ directory to see available commands. See DEV_SETUP.md for detailed usage.

Project Structure

python/
├── packages/
│   ├── core/                 # agent-framework-core (main package)
│   │   ├── agent_framework/  # Public API exports
│   │   └── tests/
│   ├── foundry/              # agent-framework-foundry
│   ├── anthropic/            # agent-framework-anthropic
│   ├── ollama/               # agent-framework-ollama
│   └── ...                   # Other provider packages
├── samples/                  # Sample code and examples
├── .github/skills/           # Agent skills for Copilot
└── tests/                    # Integration tests

Package Relationships

  • agent-framework-core contains core abstractions and OpenAI/Azure OpenAI built-in
  • Provider packages (foundry, anthropic, etc.) extend core with specific integrations
  • Core uses lazy loading via __getattr__ in provider folders (e.g., agent_framework/azure/)

Package Documentation

Core

  • core - Core abstractions, types, and built-in OpenAI/Azure OpenAI support

LLM Providers

Azure Integrations

Protocols & UI

  • a2a - Agent-to-Agent protocol
  • ag-ui - AG-UI protocol
  • chatkit - OpenAI ChatKit integration
  • devui - Developer UI for testing

Storage & Memory

  • mem0 - Mem0 memory integration
  • redis - Redis storage

Infrastructure

Experimental

  • lab - Experimental features
  • monty - Monty-backed CodeAct integrations (alpha)
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