* Python: Add header_provider to MCPStreamableHTTPTool (#4808)
Add a header_provider callback parameter to MCPStreamableHTTPTool that
enables injecting dynamic per-request HTTP headers from runtime kwargs
(originating from FunctionInvocationContext.kwargs set in agent middleware).
The implementation uses contextvars and httpx event hooks to ensure headers
are task-local and safe for concurrent tool calls:
- header_provider receives the runtime kwargs dict and returns headers
- call_tool sets a ContextVar before delegating to MCPTool.call_tool
- An httpx request event hook reads from the ContextVar and injects headers
Example usage:
mcp_tool = MCPStreamableHTTPTool(
name="web-api",
url="https://api.example.com/mcp",
header_provider=lambda kwargs: {
"X-Auth-Token": kwargs.get("auth_token", ""),
},
)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4808: Python: [Bug]: Unable to pass AgentContext to MCPStreamableHTTPTool
* Add test for header_provider via FunctionTool.invoke with FunctionInvocationContext
Addresses PR review comment: exercises the full pipeline from
FunctionInvocationContext.kwargs through FunctionTool.invoke to
MCPStreamableHTTPTool.call_tool and header_provider, rather than
testing call_tool in isolation.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4808: review comment fixes
* Fix streamable MCP transport defaults
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Azure AI test client mocks
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP runtime kwarg regressions
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Stabilize MCP tool runtime kwargs
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Use context kwargs in MCP wrappers
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated mcp samples
* fix link
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Support MCP sampling tools capability (#4625)
Forward systemPrompt, tools, and toolChoice from MCP sampling requests
to the chat client's get_response() call. Also advertise the
sampling.tools capability to MCP servers when a client is configured.
- Pass SamplingCapability with tools support to ClientSession
- Convert systemPrompt to instructions in options
- Convert MCP Tool objects to FunctionTool instances for options
- Map MCP ToolChoice.mode to tool_choice in options
- Add tests for all new behaviors and update existing sampling tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#4625: Support MCP sampling tool with proper typing and structured content
- Fix mypy error by typing sampling callback options as ChatOptions[None]
instead of dict[str, Any], and importing ChatOptions from _types
- Handle structuredContent from CallToolResult in _parse_tool_result_from_mcp,
serializing it as JSON text Content when present
- Add tests for structuredContent parsing (with and without regular content)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix lint: add author to TODO comment
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: remove default=str, add edge-case tests
- Remove default=str from json.dumps for structuredContent to fail fast
on non-JSON-serializable values instead of silently converting
- Add test for non-JSON-serializable structuredContent (TypeError)
- Add tests for empty systemPrompt ('') and empty tools list ([]) edge
cases in sampling callback
- Expand TODO comment noting list[Content] return type constraint for
future result_type support
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Sanitize sampling callback error to avoid leaking internals (#4625)
Log exception details at DEBUG level instead of including them in the
ErrorData message returned to the MCP server, which may be untrusted.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: move params to options, restore error info
- Remove stale TODO comment about response_format (ChatOptions already has it)
- Restore {ex} in sampling callback error message for useful debugging info
- Set structuredContent as additional_property on Content for structured access
- Move temperature, max_tokens, stop into options dict (not top-level kwargs)
- Only set temperature when provided (not all models support it)
- Add tests for generation params in options and temperature omission
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix MCP sampling callback and structured content error handling (#4625)
- Guard max_tokens like temperature: only set when not None, so options
can properly evaluate to None when all params are absent
- Wrap json.dumps of structuredContent in try/except to fall back to
str() for non-serializable values instead of propagating TypeError
- Extract test_connect_sampling_capabilities_with_client into its own
test function so pytest can discover it independently
- Add test for max_tokens=None omission from options
- Update structured content non-serializable test to expect fallback
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #4625: review comment fixes
* Fix MCP and Azure validation regressions
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: avoid duplicate agent response telemetry
* Python: conditionally suppress duplicate agent telemetry
* Simplify telemetry ownership tracking
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Aggregate token usage from inner chat spans on invoke_agent span
The invoke_agent span now carries the aggregated input/output token
counts from all inner chat completion spans that occur during an agent
run. Previously, when inner ChatTelemetryLayer spans captured usage,
the outer AgentTelemetryLayer skipped setting usage entirely to avoid
duplication. Now a new INNER_ACCUMULATED_USAGE context variable tracks
cumulative usage across all inner completions, and the agent span
always reports the total.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* [BREAKING] Refactor middleware layering and raw clients
Reorder chat client layers so function invocation wraps chat middleware, and chat middleware stays outside telemetry while still running for each inner model call. Add middleware pipeline caching, refresh docs and samples, and split Anthropic into raw and public clients to match the standard layering model.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Tighten typing ignores in ancillary modules
Add targeted typing ignores in workflow visualization and lab modules so pyright stays clean alongside the middleware refactor work.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix categorize_middleware to unpack tuple/Sequence and use relative MRO assertions
- Broaden isinstance check in categorize_middleware from list to Sequence
so tuples and other Sequence types are properly unpacked instead of
being appended as a single item.
- Replace fragile hardcoded MRO index assertions in anthropic test with
relative ordering via mro.index().
- Add regression tests for categorize_middleware with tuple, list, and
None inputs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix middleware string decomposition, add middleware param to FunctionInvocationLayer, and add tests (#4710)
- Guard categorize_middleware Sequence check against str/bytes to prevent
character-by-character decomposition of accidentally passed strings
- Add explicit middleware parameter to FunctionInvocationLayer.get_response
and merge it into client_kwargs before categorization, fixing the
inconsistency where only OpenAIChatClient supported this parameter
- Add assertions that RawAnthropicClient does not inherit convenience layers
- Add chat middleware cache test with non-empty base middleware
- Add tests for single unwrapped middleware item and string input
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Apply pre-commit auto-fixes
* Address review feedback for #4710: review comment fixes
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Copilot <copilot@github.com>
* Fix A2AAgent to invoke context providers before and after run
A2AAgent.run() bypassed the context provider lifecycle (before_run/after_run)
that BaseAgent defines as a contract for all agents. This caused A2AAgent to
violate the semantic definition of BaseAgent, resulting in inconsistency with
other agent implementations.
The fix follows the same pattern used by WorkflowAgent:
- Create SessionContext and run before_run on all context providers before
processing the A2A stream
- Collect response updates and run after_run on all context providers after
the stream is fully consumed
- Auto-create a session when context providers are configured but no session
is explicitly passed
Fixes#4754
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report from repository
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback for #4754
- Validate messages when no continuation_token: raise ValueError if
normalized_messages is empty, preventing IndexError on messages[-1]
- Import BaseContextProvider/SessionContext from public agent_framework
package instead of internal agent_framework._sessions module
- Add test for ValueError on run(None) without continuation_token
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Improve test coverage for empty-messages guard in A2AAgent.run (#4754)
- Parameterize test to cover both messages=None and messages=[] inputs
- Add test verifying run(None, continuation_token=...) does not raise
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix invoke_agent span to aggregate token usage across LLM calls (#4062)
The FunctionInvocationLayer._get_response() loop was overwriting the
response on each iteration, so usage_details only reflected the last
chat completion call. Now tracks aggregated_usage across all iterations
using add_usage_details() and sets it on the returned response.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Remove reproduction report artifact
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Apply pre-commit auto-fixes
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated automation tasks and commands, with alias for the time being
* Restore aggregate test exclusions
Preserve the legacy all-tests scope for test --all by excluding lab and devui from the default aggregate sweep, while still allowing explicit package selection. Also ignore hidden/generated test directories such as .mypy_cache during aggregate discovery.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated versions in pre-commit
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Re-read env vars in configure_otel_providers and enable_instrumentation (#4119)
Fix ENABLE_SENSITIVE_DATA and VS_CODE_EXTENSION_PORT env vars being ignored
when load_dotenv() runs after module import. The module-level
OBSERVABILITY_SETTINGS singleton cached env state at import time, and
configure_otel_providers() / enable_instrumentation() never re-read from
os.environ when parameters were None.
Both functions now construct a fresh ObservabilitySettings() to pick up
current env vars when explicit parameters are not provided, matching the
existing behavior of the env_file_path branch.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review feedback for #4119: avoid throwaway ObservabilitySettings
- Add _read_bool_env/_read_int_env helpers to read env vars without
constructing a full ObservabilitySettings (which calls create_resource())
- Replace ObservabilitySettings() in enable_instrumentation() and
configure_otel_providers() else-branch with direct env reads
- Add enable_console_exporters parameter to configure_otel_providers()
for override parity with enable_sensitive_data and vs_code_extension_port
- Propagate _resource and _executed_setup in the non-env_file_path branch
- Make existing tests hermetic (clear VS_CODE_EXTENSION_PORT and
ENABLE_CONSOLE_EXPORTERS env vars)
- Add tests: enable_console_exporters env refresh, explicit param overrides
for both enable_instrumentation() and configure_otel_providers()
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address remaining review feedback for #4119
- Refresh enable_console_exporters in enable_instrumentation() for
consistency with configure_otel_providers(), so env var changes
after import are picked up by both public API functions
- Make test_configure_otel_providers_reads_env_vs_code_port hermetic
by clearing ENABLE_CONSOLE_EXPORTERS from the environment
- Add test_enable_instrumentation_reads_env_console_exporters to
cover the new refresh behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Remove unconditional enable_console_exporters overwrite from enable_instrumentation() (#4119)
enable_instrumentation() is documented as not configuring exporters, so
managing enable_console_exporters there was a leaky abstraction. The
unconditional _read_bool_env call silently reset the value to False when
ENABLE_CONSOLE_EXPORTERS was absent from env, clobbering any value
previously set by configure_otel_providers(enable_console_exporters=True).
- Remove the unconditional overwrite line from enable_instrumentation()
- Replace test_enable_instrumentation_reads_env_console_exporters with
test_enable_instrumentation_does_not_touch_console_exporters
- Add regression test: enable_instrumentation() does not clobber a
previously configured enable_console_exporters value
- Add test: explicit enable_sensitive_data param still leaves
enable_console_exporters untouched
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Content serialization in DurableAgentStateUnknownContent (#4719)
DurableAgentStateUnknownContent.from_unknown_content() stored raw Content
objects without converting them to dicts, causing json.dumps to fail in
Azure Durable Functions' entity state serialization. This affected content
types not explicitly handled (e.g., mcp_server_tool_call/result).
The fix converts Content objects to dicts via to_dict() when storing in
DurableAgentStateUnknownContent, and restores them via Content.from_dict()
in to_ai_content().
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add to_json and from_json methods to Content class (#4719)
Add to_json() and from_json() methods to the Content class to match the
serialization interface provided by SerializationMixin on other model classes.
Also fix pre-existing pyright type errors in durabletask's
DurableAgentStateUnknownContent.to_ai_content().
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review: add type guard, remove to_json, add fallback, and tests
- Remove Content.to_json() per reviewer request (comment 3)
- Add type guard in Content.from_json() for non-dict JSON (comments 1, 4)
- Wrap json.JSONDecodeError as ValueError for consistent exception contract
- Add try/except fallback in to_ai_content() for invalid Content dicts (comment 5)
- Add test_content_to_dict_exclude_none and test_content_to_dict_exclude_fields (comment 2)
- Add test_unknown_content_to_ai_content_fallback_on_invalid_type_dict (comment 5)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Apply pre-commit auto-fixes
* Address review feedback for #4719: review comment fixes
* Remove Content.from_json, move logic to consuming code (#4719)
Remove the from_json convenience method from Content class per review
feedback. This is the same trivial json.loads + from_dict wrapper as
to_json which was already removed. Consumers should call json.loads
and Content.from_dict directly.
Update tests to use Content.from_dict(json.loads(...)) pattern and
remove from_json-specific error handling tests (those errors are
already covered by json.loads and Content.from_dict).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: clean up kwargs across agents, chat clients, tools, and sessions (#3642)
Audit and refactor public **kwargs usage across core agents, chat clients,
tools, sessions, and provider packages per the migration strategy codified
in CODING_STANDARD.md.
Key changes:
- Add explicit runtime buckets: function_invocation_kwargs and client_kwargs
on RawAgent.run() and chat client get_response() layers.
- Refactor FunctionTool to prefer explicit ctx: FunctionInvocationContext
injection; legacy **kwargs tools still work via _forward_runtime_kwargs.
- Refactor Agent.as_tool() to use direct JSON schema, always-streaming
wrapper, approval_mode parameter, and UserInputRequiredException
propagation (integrates PR #4568 behavior).
- Remove implicit session bleeding into FunctionInvocationContext; tools
that need a session must receive it via function_invocation_kwargs.
- Lower chat-client layers after FunctionInvocationLayer accept only
compatibility **kwargs (client_kwargs flattened, function_invocation_kwargs
ignored).
- Add layered docstring composition from Raw... implementations via
_docstrings.py helper.
- Clean up provider constructors to use explicit additional_properties.
- Deprecation warnings on legacy direct kwargs paths.
- Update samples, tests, and typing across all 23 packages.
Resolves#3642
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* clarified docstring
* feedback fixes
* Add unit tests for _docstrings.py build/apply helpers
Tests cover: no docstring source, no extra kwargs, appending to existing
Keyword Args section, inserting after Args, inserting in plain docstrings,
multiline descriptions, ordering, and apply_layered_docstring.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add test for propagate_session TypeError on non-AgentSession values
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add tests for multi-content and empty UserInputRequiredException propagation
Cover the branching logic in _try_execute_function_calls for:
- Multiple user_input_request items in a single exception (extra_user_input_contents path)
- Empty contents list (fallback function_result path)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add tests for DurableAIAgent.get_session forwarding service_session_id
Verifies get_session correctly forwards service_session_id and session_id
to the executor's get_new_session, replacing the removed kwargs test.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Simplify ag-ui test stub to read session from client_kwargs only
Remove dual-mode detection (client_kwargs vs raw kwargs fallback) from
the test mock. Session is now read exclusively from client_kwargs,
matching the settled public calling convention.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated create and get sessions in durable
* fixed docstrings
* fix test
* updated session handling
* updated from main
* updated tests
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Implement annotation-based context compaction
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Handle missing compaction attributes in BaseChatClient
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix CI typing and bandit issues
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Optimize incremental compaction annotation pass
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refinement
* Python: add ToolResultCompactionStrategy and CompactionProvider
Add ToolResultCompactionStrategy that collapses older tool-call groups
into short summary messages (e.g. [Tool calls: get_weather]) while
keeping the most recent groups verbatim. This mirrors the .NET
ToolResultCompactionStrategy from PR #4533.
Add CompactionProvider as a context-provider that auto-applies compaction
before each agent turn and stores compacted history in session state
after each turn.
Includes tests and samples for both features.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refinement and alignment with dotnet PR
* updated tool result compaction
* updated tool result compaction
* Python: add ToolResultCompactionStrategy, CompactionProvider, and skip_excluded
- ToolResultCompactionStrategy collapses older tool-call groups into
[Tool results: func_name: result] summaries with bidirectional tracing
(same pattern as SummarizationStrategy).
- CompactionProvider as BaseContextProvider with separate before_strategy
and after_strategy parameters. before_strategy compacts loaded context;
after_strategy compacts stored history via history_source_id.
- InMemoryHistoryProvider gains skip_excluded flag to filter out messages
marked as excluded by compaction strategies.
- Tests, samples, and exports updated.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixed checks
* fix mypy
* Fix: ensure summary messages from both strategies get full compaction annotations
SummarizationStrategy was not calling annotate_message_groups after
inserting its summary message, so the summary lacked core group
annotations (id, kind, index, has_reasoning, _excluded). Added the
missing call. ToolResultCompactionStrategy already had it.
Added tests verifying both strategies produce fully annotated summaries.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated propagation
* fix mypy
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Prepare azure-ai-projects 2.0 GA compatibility
Add allow_preview support for internal AIProjectClient creation, keep backward compatibility for renamed SDK model classes, and align Azure AI/core paths and tests for GA validation workflows.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* upgrade to ai-project==2.0.0
* Python: remove azure-ai-projects keyword-guard paths
Assume azure-ai-projects 2.0+ in Azure AI client/provider/responses code paths by removing _supports_keyword_argument gating and related fallback branching.
Also fix pyright typing in FoundryMemoryProvider memory store calls by using ResponseInputItemParam-typed items.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* check fixes
* Python: remove unsupported foundry_features option
Drop foundry_features from Azure AI client and provider surfaces because azure-ai-projects 2.0.0 does not expose that create_version parameter.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: add allow_preview to Foundry memory provider
Propagate allow_preview when FoundryMemoryProvider constructs an AIProjectClient and update tests accordingly.
Also finish wiring allow_preview through AzureAIClient-facing surfaces and related docs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* aligning docstrings
* udpated lock
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix Python pyright package scoping and typing remediation
Implements issue #4407 by removing the root pyright include, adding package-level pyright includes, and resolving pyright/mypy typing issues across Python packages. Also cleans unnecessary casts and applies line-level, rule-specific ignores where external libraries are too dynamic.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Reduce pyright cost in handoff cloning
Simplify cloned_options construction in HandoffAgentExecutor to avoid expensive TypedDict narrowing/inference in _handoff.py, which was causing pyright to spend a long time in orchestrations.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix types
* Fix lint and type-check regressions
Resolve current Python package check failures across lint, pyright, and mypy after recent code changes, including purview/declarative pyright issues and multiple ruff simplification findings.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixed hooks
* Stabilize package tests and test tasks
Resolve cross-package non-integration test failures, simplify streaming type flow, harden locale/culture handling, and standardize package test poe tasks to exclude integration tests where applicable.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* lots of small fixes
* Fix current Python test regressions
Address current failing unit tests in azure-ai, bedrock, and azure-cosmos while keeping Bedrock parsing logic inline (no new static helper methods).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* small fixes
* small fixes
* removed pydantic from json
* final updates
* fix core
* fix tests
* fix obser
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Phase 2: Embedding clients for Ollama, Bedrock, and Azure AI Inference
Add embedding client implementations to existing provider packages:
- OllamaEmbeddingClient: Text embeddings via Ollama's embed API
- BedrockEmbeddingClient: Text embeddings via Amazon Titan on Bedrock
- AzureAIInferenceEmbeddingClient: Text and image embeddings via Azure AI
Inference, supporting Content | str input with separate model IDs for
text (AZURE_AI_INFERENCE_EMBEDDING_MODEL_ID) and image
(AZURE_AI_INFERENCE_IMAGE_EMBEDDING_MODEL_ID) endpoints
Additional changes:
- Rename EmbeddingCoT -> EmbeddingT, EmbeddingOptionsCoT -> EmbeddingOptionsT
- Add otel_provider_name passthrough to all embedding clients
- Register integration pytest marker in all packages
- Add lazy-loading namespace exports for Ollama and Bedrock embeddings
- Add image embedding sample using Cohere-embed-v3-english
- Add azure-ai-inference dependency to azure-ai package
Part of #1188
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy duplicate name and ruff lint issues
- Rename second 'vector' variable to 'img_vector' in image embedding loop
- Combine nested with statements in tests
- Remove unused result assignments in tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updates from feedback
* Fix CI failures in embedding usage handling
- Fix Azure AI embedding mypy issues by normalizing vectors to list[float],
safely accumulating optional usage token fields, and filtering None entries
before constructing GeneratedEmbeddings
- Avoid Bandit false positive by initializing usage details as an empty dict
- Update OpenAI embedding tests to assert canonical usage keys
(input_token_count/total_token_count)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* small updates and improvements in the azure AISearch provider
* Fix mypy errors and embedding function test
- Use separate variable for embeddings result to avoid mypy type reassignment error
- Fix test_vectorized_query_with_embedding_function: use real async function
instead of AsyncMock which falsely matches SupportsGetEmbeddings protocol
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixes from feedback
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* updated integration tests and guidance
* fixed merge test
* updated integration tests
* fix: remove duplicate --dist loadfile flag from pytest-xdist config
Only one --dist mode can be active at a time; the second value silently
overrides the first. Keep --dist worksteal (dynamic load balancing) and
remove the redundant --dist loadfile from all workflow files and
pyproject.toml configs.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* docs: add keep-in-sync notes for merge and integration test workflows
Both python-merge-tests.yml and python-integration-tests.yml share the
same parallel job structure. Added sync reminders in workflow file
comments, the python-testing SKILL.md, and CODING_STANDARD.md.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* refactor: remove RUN_INTEGRATION_TESTS flag
Integration test gating now uses two mechanisms:
- `@pytest.mark.integration` for test selection via `-m` filtering
- `skip_if_*_disabled` for credential/service availability checks
The RUN_INTEGRATION_TESTS env var was redundant since the marker handles
selection and the skip decorators already check for actual credentials.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: sync missing env vars from merge-tests to integration-tests
Add OPENAI_EMBEDDINGS_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME
to python-integration-tests.yml to match python-merge-tests.yml.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: remove remaining RUN_INTEGRATION_TESTS from embedding tests and docs
Missed test_openai_embedding_client.py and vector-stores README in the
earlier cleanup.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* set functions tests to 3.10
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* feat(python): Add embedding abstractions and OpenAI implementation (Phase 1)
This PR contains two parts:
1. **Overall migration plan** for porting vector stores and embeddings from
Semantic Kernel to Agent Framework (docs/features/vector-stores-and-embeddings/README.md)
covering all 10 phases from core abstractions through connectors and TextSearch.
2. **Phase 1 implementation** — core embedding abstractions and OpenAI/Azure OpenAI
embedding clients:
Core types (_types.py):
- EmbeddingGenerationOptions TypedDict (total=False)
- Embedding[EmbeddingT] generic class with model_id, dimensions, created_at
- GeneratedEmbeddings[EmbeddingT, EmbeddingOptionsT] list container with options, usage
- EmbeddingInputT (default str) and EmbeddingT (default list[float]) TypeVars
Protocol + base class (_clients.py):
- SupportsGetEmbeddings protocol — Generic[EmbeddingInputT, EmbeddingT, OptionsContraT]
- BaseEmbeddingClient ABC — Generic[EmbeddingInputT, EmbeddingT, OptionsCoT]
Telemetry (observability.py):
- EmbeddingTelemetryLayer with gen_ai.operation.name = "embeddings"
OpenAI implementation (openai/_embedding_client.py):
- RawOpenAIEmbeddingClient, OpenAIEmbeddingClient, OpenAIEmbeddingOptions
- Uses _ensure_client() factory pattern
Azure OpenAI implementation (azure/_embedding_client.py):
- AzureOpenAIEmbeddingClient following AzureOpenAIChatClient pattern
- Supports API key, Entra ID credentials, env var configuration
Tests:
- 47 unit tests for types, protocol, base class, OpenAI, and Azure clients
- 6 integration tests (gated behind RUN_INTEGRATION_TESTS + credentials)
Samples:
- samples/02-agents/embeddings/openai_embeddings.py
- samples/02-agents/embeddings/azure_openai_embeddings.py
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Add AzureOpenAIEmbeddingClient to azure __init__.pyi stub
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* ci: Add embedding env vars to Python integration tests
Map OPENAI_EMBEDDING_MODEL_ID and AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME
from GitHub vars to the integration test environment.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Handle base64 encoding_format in OpenAI embedding client
When encoding_format='base64' is used, the OpenAI API returns base64-encoded
floats instead of a JSON array. Decode these automatically to list[float]
so the return type stays consistent regardless of encoding format.
Also adds a unit test for base64 decoding and fixes minor docstring/import issues.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Only record INPUT_TOKENS for embedding telemetry
Embeddings have no output/completion tokens. Remove OUTPUT_TOKENS recording
which was double-counting prompt_tokens via the total_tokens fallback.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Resolve mypy variance error and lint warning
Use contravariant/covariant TypeVars for SupportsGetEmbeddings Protocol.
Combine nested if into single statement in telemetry layer.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Make EmbeddingCoT invariant for mypy compatibility
GeneratedEmbeddings is invariant in its type param, so the Protocol
TypeVar cannot be covariant.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Address PR review - empty values guard, service_url for telemetry
- Add early return for empty values in get_embeddings to avoid unnecessary API calls
- Add service_url() method to RawOpenAIEmbeddingClient for proper telemetry endpoint reporting
- Add test for empty values behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix OpenAI chat client compatibility with third-party endpoints and OTel 0.4.14 (#4161)
* Fix system message content sent as list instead of string
Some OpenAI-compatible endpoints (e.g. NVIDIA NIM) reject system messages
when content is a list of content parts. This change flattens system and
developer message content to a plain string in the Chat Completions client.
Fixes https://github.com/microsoft/agent-framework/issues/1407
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix compatibility with opentelemetry-semantic-conventions-ai 0.4.14
Version 0.4.14 removed several LLM_* attributes from SpanAttributes
(LLM_SYSTEM, LLM_REQUEST_MODEL, LLM_RESPONSE_MODEL, LLM_REQUEST_MAX_TOKENS,
LLM_REQUEST_TEMPERATURE, LLM_REQUEST_TOP_P, LLM_TOKEN_TYPE).
Move these to the OtelAttr enum with their well-known gen_ai.* string values
and update all references in observability.py and tests.
Fixes https://github.com/microsoft/agent-framework/issues/4160
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Flatten text-only message content to string for all roles
Extend the system/developer fix to all message roles. Text-only content
lists are now post-processed into plain strings, while multimodal content
(text + images/audio) remains as a list. This fixes compatibility with
OpenAI-like endpoints that cannot deserialize list content (e.g. Foundry
Local's Neutron backend).
Partially fixes https://github.com/microsoft/agent-framework/issues/4084
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix streaming text lost when usage data in same chunk
Some providers (e.g. Gemini) include both usage data and text content
in the same streaming chunk. The early return on chunk.usage caused
text and tool call parsing to be skipped entirely. Remove the early
return and process usage alongside text/tool calls.
Fixes https://github.com/microsoft/agent-framework/issues/3434
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy errors in _chat_client.py
Rename shadowed variable 'args' in system/developer branch to 'sys_args'
and rename loop variable 'content' to 'msg_content' to avoid type conflict.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* reorder imports
* fix: Use OtelAttr.REQUEST_MODEL instead of removed SpanAttributes.LLM_REQUEST_MODEL
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* docs: Add score_threshold to vector store plan
Reference SK .NET PR #13501 for score threshold filtering semantics.
Include score_threshold in SearchOptions from Phase 3.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* docs: Add reference to roji's SK .NET MEVD work for SQL connectors
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: Clear env vars in construction tests to avoid CI leakage
Tests for missing API key / model ID now use monkeypatch.delenv to ensure
env vars from the integration test environment don't prevent the expected
ValueError from being raised.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add max_function_calls to FunctionInvocationConfiguration (#2329)
Add a new per-request max_function_calls setting to FunctionInvocationConfiguration
that limits the total number of individual function invocations across all iterations
within a single get_response call. This complements max_iterations (which limits LLM
roundtrips) by providing a hard cap on actual tool executions regardless of parallelism.
- Add max_function_calls field to FunctionInvocationConfiguration (default: None/unlimited)
- Track cumulative function call count in both streaming and non-streaming tool loops
- Force tool_choice='none' when the limit is reached
- Add validation in normalize_function_invocation_configuration
- Improve docstrings for FunctionInvocationConfiguration, FunctionTool, and @tool
to clarify semantics of max_iterations vs max_function_calls vs max_invocations
- Add tests for parallel calls, single calls, unlimited mode, and config validation
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add sample for controlling total tool executions
Showcases all three mechanisms for limiting tool executions:
1. max_iterations — caps LLM roundtrips
2. max_function_calls — caps total individual function invocations per request
3. max_invocations — lifetime cap on a specific tool instance
Plus a combined scenario demonstrating defense in depth.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Suppress ruff E305/fmt in hosting sample to preserve XML doc tags
The XML snippet tags (# <create_agent> / # </create_agent>) are used for
docs extraction and must stay adjacent to the code they wrap. Both ruff
check (E305) and ruff format add blank lines after the function definition,
pushing the closing tag away. Suppress with ruff: noqa: E305 and fmt: off.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add per-agent tool wrapping scenario to control_total_tool_executions sample
Show that wrapping the same callable with @tool multiple times creates
independent FunctionTool instances with separate invocation counters,
enabling per-agent max_invocations budgets for shared functions.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Clarify max_function_calls is a best-effort limit
The limit is checked after each batch of parallel calls completes, so the
current batch always runs to completion even if it overshoots the limit.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR review: fix docstring reference, clarify best-effort in sample
- Fix malformed Sphinx :attr: role in FunctionTool docstring — use plain
backtick reference instead
- Update sample to say 'best-effort cap' instead of 'hard cap' for
max_function_calls, noting it's checked between iterations
- Parametrize pattern is correct (fixture override, matching existing tests)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* clarify max_invocations limits
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix system message content sent as list instead of string
Some OpenAI-compatible endpoints (e.g. NVIDIA NIM) reject system messages
when content is a list of content parts. This change flattens system and
developer message content to a plain string in the Chat Completions client.
Fixes https://github.com/microsoft/agent-framework/issues/1407
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix compatibility with opentelemetry-semantic-conventions-ai 0.4.14
Version 0.4.14 removed several LLM_* attributes from SpanAttributes
(LLM_SYSTEM, LLM_REQUEST_MODEL, LLM_RESPONSE_MODEL, LLM_REQUEST_MAX_TOKENS,
LLM_REQUEST_TEMPERATURE, LLM_REQUEST_TOP_P, LLM_TOKEN_TYPE).
Move these to the OtelAttr enum with their well-known gen_ai.* string values
and update all references in observability.py and tests.
Fixes https://github.com/microsoft/agent-framework/issues/4160
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Flatten text-only message content to string for all roles
Extend the system/developer fix to all message roles. Text-only content
lists are now post-processed into plain strings, while multimodal content
(text + images/audio) remains as a list. This fixes compatibility with
OpenAI-like endpoints that cannot deserialize list content (e.g. Foundry
Local's Neutron backend).
Partially fixes https://github.com/microsoft/agent-framework/issues/4084
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix streaming text lost when usage data in same chunk
Some providers (e.g. Gemini) include both usage data and text content
in the same streaming chunk. The early return on chunk.usage caused
text and tool call parsing to be skipped entirely. Remove the early
return and process usage alongside text/tool calls.
Fixes https://github.com/microsoft/agent-framework/issues/3434
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix mypy errors in _chat_client.py
Rename shadowed variable 'args' in system/developer branch to 'sys_args'
and rename loop variable 'content' to 'msg_content' to avoid type conflict.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: strip function_call and text_reasoning from cross-agent workflow handoff
When a reasoning model (e.g. gpt-5-mini) runs as Agent 1 in a workflow, its
response includes text_reasoning items (with server-scoped IDs like rs_XXXX)
and function_call items. Forwarding these to Agent 2 in a fresh conversation
caused API errors because the reasoning/call IDs are scoped to the original
stored response context.
Changes:
- Strip 'function_call', 'text_reasoning', 'function_approval_request', and
'function_approval_response' from handoff messages in _agent_executor.py
- Keep 'function_result' so the actual tool output content is preserved for
the next agent's context
- Update unit tests to reflect that function_result messages survive handoff
(messages grow from 2→3: user, tool(result), assistant(summary))
- Fix incorrect test assertions in test_function_invocation_stop_clears_*
that assumed the client layer updates session.service_session_id
- Also fixed _extract_function_calls to search all messages with call_id
deduplication, and the error-limit stop path to submit function_call_output
items before halting (via tool_choice=none cleanup call)
Relates to: https://github.com/microsoft/agent-framework/issues/4047
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: reasoning model workflow handoff and history serialization
Fixes multiple related issues when using reasoning models (gpt-5-mini,
gpt-5.2) in multi-agent workflows that chain agents via from_response
or replay full conversation history via AgentExecutorRequest.
## Reasoning items always emitted on output_item.added
When a reasoning model produces encrypted or hidden reasoning (no
visible text), the Responses API still fires a reasoning output item
without any reasoning_text.delta events. Previously no text_reasoning
Content was emitted in that case, making it invisible to downstream
logic. Both the non-streaming (_parse_response_from_openai) and
streaming (output_item.added) paths now always emit at least one
text_reasoning Content — with empty text if no content is available —
so co-occurrence detection and serialization guards work reliably.
## Reasoning items only serialized when paired with a function_call
The Responses API only accepts reasoning items in input when they
directly preceded a function_call in the original response. Sending a
reasoning item that preceded a text response (no tool call) causes:
"reasoning was provided without its required following item"
_prepare_message_for_openai now checks has_function_call per message
and skips text_reasoning serialization when there is no accompanying
function_call.
## summary field is an array, not an object
The reasoning item summary field sent to the Responses API must be an
array of objects ([{"type": "summary_text", "text": ...}]), not a
single object. Fixed _prepare_content_for_openai accordingly.
## service_session_id cleared when explicit history is provided
When a workflow coordinator replays a full conversation (including
function calls from a previous agent run) back to an executor via
AgentExecutorRequest or from_response, the executor's session still
held a service_session_id (previous_response_id) from the prior run.
The API then received the same function-call items twice — once from
previous_response_id (server-stored) and once from the explicit input —
causing: "Duplicate item found with id fc_...".
AgentExecutor.run (when should_respond=True) and from_response now
reset self._session.service_session_id = None before running so that
explicit input is the sole source of conversation context.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* small improvements in text reasoning
* refactor: add reset_service_session to AgentExecutorRequest for explicit history replay
Replace the implicit 'always clear service_session_id when should_respond=True'
with an explicit opt-in field on AgentExecutorRequest.
The old approach used should_respond=True as a proxy for 'full history replay',
but that conflates two distinct intents:
- Orchestrations group chat sends should_respond=True with an empty/single-message
list (not a full replay) — unnecessarily clearing service_session_id.
- HITL / feedback coordinators send the full prior conversation and truly need
a fresh service session ID to avoid duplicate-item API errors.
Changes:
- Add AgentExecutorRequest.reset_service_session: bool = False
- AgentExecutor.run only clears service_session_id when this flag is True
- AgentExecutor.from_response unchanged (always clears; always full conversation)
- Set reset_service_session=True in all full-history-replay call sites:
agents_with_HITL.py, azure_chat_agents_tool_calls_with_feedback.py,
autogen-migration round-robin coordinator, tau2 runner
- Update _FullHistoryReplayCoordinator test helper to pass the flag
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* comment update
* fixes from feedback
* fix test
* reverted changes to agent executor
* fix: remove reset_service_session from tau2 runner
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* two other reverts
* fix sample
---------
Co-authored-by: Giles Odigwe <79032838+giles17@users.noreply.github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
- Rename UserNameProvider → UserMemoryProvider
- Use session state (state dict) instead of instance variables
- Use context.extend_instructions() instead of context.instructions.append()
- Use DEFAULT_SOURCE_ID class attribute
- Fix imports to use public agent_framework API
- Add session state inspection at end of sample
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: improve .env precedence and observability samples
- Switch load_settings to explicit precedence: overrides -> explicit .env -> environment -> defaults\n- Raise when env_file_path is provided but missing\n- Update settings docs and tests for new behavior\n- Refresh observability samples and README guidance for env loading options\n\nCloses #3864\n\nCo-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fixed some imports
* Fix load_settings CI regressions
Allow explicit env_file_path values that exist but are not regular files (for example /dev/null) by checking path existence before dotenv parsing, and restore a dict accumulator with typed return cast to satisfy mypy.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Avoid implicit dotenv in observability
Only load dotenv in observability helpers when env_file_path is explicitly provided, and remove test os.devnull workarounds that are no longer necessary.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix#3600: Pass JSON schemas through without Pydantic conversion
This change optimizes FunctionTool and MCP flows by passing JSON schemas
directly to providers without converting them to Pydantic models first.
Key changes:
- Store JSON schema as-is when supplied to FunctionTool
- Skip Pydantic model_validate for schema-supplied tools in invoke()
- Return MCP tool schemas directly without conversion
- Add comprehensive tests for schema passthrough behavior
Performance benefits:
- Eliminates expensive Pydantic model creation for supplied schemas
- Preserves exact schema structure (additionalProperties, custom fields, etc.)
- Reduces memory overhead and initialization time
Maintains backward compatibility:
- Function signature inference still uses Pydantic models
- Explicit Pydantic models passed as input_model work as before
- All existing tests pass
* Fix schema passthrough validation and remove helper
* Simplify FunctionTool without generic model dependency
* Fix FunctionTool typing fallout in 3600
* Remove FunctionTool[Any] compatibility shim
* Use serializable kwargs in OTEL tool args
* Python: Replace wildcard imports with explicit imports
- Replace all 'from ... import *' with explicit symbol imports
- Add __all__ declarations to namespace packages for re-exports
- Update CODING_STANDARD.md to prohibit wildcard imports
- Maintain exported API and preserve all functionality
fixes#3605
* Refine wildcard guidance example text
* Simplify explicit exports without self-aliases
* fix: prevent repeating instructions in continued Responses API conversations
- Instructions are now only prepended to messages on the first turn
- When conversation_id/response_id exists (continuation), instructions are skipped
- Covers OpenAI and Azure Responses API paths
- Adds regression tests for all continuation scenarios
Fixes#3498
* Apply lint fixes to continuation tests
* Consolidate responses continuation tests
* PR2: Wire context provider pipeline and update all internal consumers
- Replace AgentThread with AgentSession across all packages
- Replace ContextProvider with BaseContextProvider across all packages
- Replace context_provider param with context_providers (Sequence)
- Replace thread= with session= in run() signatures
- Replace get_new_thread() with create_session()
- Add get_session(service_session_id) to agent interface
- DurableAgentThread -> DurableAgentSession
- Remove _notify_thread_of_new_messages from WorkflowAgent
- Wire before_run/after_run context provider pipeline in RawAgent
- Auto-inject InMemoryHistoryProvider when no providers configured
* fix: update all tests for context provider pipeline, fix lazy-loaders, remove old test files
* refactor: update all sample files for context provider pipeline (AgentThread→AgentSession, ContextProvider→BaseContextProvider)
* fix: update remaining ag-ui references (client docstring, getting_started sample)
* fix: make get_session service_session_id keyword-only to avoid confusion with session_id
* refactor: rename _RunContext.thread_messages to session_messages
* refactor: remove _threads.py, _memory.py, and old provider files; migrate devui to use plain message lists
* rename: remove _new_ prefix from test files
* refactor: rewrite SlidingWindowChatMessageStore as SlidingWindowHistoryProvider(InMemoryHistoryProvider)
* fix: read full history from session state directly instead of reaching into provider internals
* fix: update stale .pyi stubs, sample imports, and README references for new provider types
* fix: remove stale message_store, _notify_thread_of_new_messages, and session_id.key references in samples
* refactor: merge context_providers and sessions sample folders into sessions, remove aggregate_context_provider
* refactor: UserInfoMemory stores state in session.state instead of instance attributes
* feat: add Pydantic BaseModel support to session state serialization
Pydantic models stored in session.state are now automatically serialized
via model_dump() and restored via model_validate() during to_dict()/from_dict()
round-trips. Models are auto-registered on first serialization; use
register_state_type() for cold-start deserialization.
Also export register_state_type as a public API.
* fix mem0
* Update sample README links and descriptions for session terminology
- Replace 'thread' with 'session' in sample descriptions across all READMEs
- Update file links for renamed samples (mem0_sessions, redis_sessions, etc.)
- Fix Threads section → Sessions section in main samples/README.md
- Update tools, middleware, workflows, durabletask, azure_functions READMEs
- Update architecture diagrams in concepts/tools/README.md
- Update migration guides (autogen, semantic-kernel)
* Fix broken Redis README link to renamed sample
* Fix Mem0 OSS client search: pass scoping params as direct kwargs
AsyncMemory (OSS) expects user_id/agent_id/run_id as direct kwargs,
while AsyncMemoryClient (Platform) expects them in a filters dict.
Adds tests for both client types.
Port of fix from #3844 to new Mem0ContextProvider.
* Fix rebase issues: restore missing _conversation_state.py and checkpoint decode logic
- Add back _conversation_state.py (encode/decode_chat_messages) lost in rebase
- Fix on_checkpoint_restore to decode cache/conversation with decode_chat_messages
- Fix on_checkpoint_restore to use decode_checkpoint_value for pending requests
- Add tests/workflow/__init__.py for relative import support
- Fix test_agent_executor checkpoint selection (checkpoints[1] not superstep)
* Add STORES_BY_DEFAULT ClassVar to skip redundant InMemoryHistoryProvider injection
Chat clients that store history server-side by default (OpenAI Responses API,
Azure AI Agent) now declare STORES_BY_DEFAULT = True. The agent checks this
during auto-injection and skips InMemoryHistoryProvider unless the user
explicitly sets store=False.
* Fix broken markdown links in azure_ai and redis READMEs
* Fix getting-started samples to use session API instead of removed thread/ContextProvider API
* updates to workflow as agent
* fix group chat import
* Rename Thread→Session throughout, fix service_session_id propagation, remove stale AGUIThread
- Fix: Propagate conversation_id from ChatResponse back to session.service_session_id
in both streaming and non-streaming paths in _agents.py
- Rename AgentThreadException → AgentSessionException
- Remove stale AGUIThread from ag_ui lazy-loader
- Rename use_service_thread → use_service_session in ag-ui package
- Rename test functions from *_thread_* to *_session_*
- Rename sample files from *_thread* to *_session*
- Update docstrings and comments: thread → session
- Update _mcp.py kwargs filter: add 'session' alongside 'thread'
- Fix ContinuationToken docstring example: thread=thread → session=session
- Fix _clients.py docstring: 'Agent threads' → 'Agent sessions'
* Fix broken markdown links after thread→session file renames
* fix azure ai test
* restructure: Python samples into progressive 01-05 layout
- 01-get-started/: 6 numbered steps (hello agent → hosting)
- 02-agents/: all agent concept samples (tools, middleware, providers, etc.)
- 03-workflows/: ALL existing workflow samples preserved as-is
- 04-hosting/: azure-functions, durabletask, a2a
- 05-end-to-end/: demos, evaluation, hosted agents
- Old files moved to _to_delete/ for review
- Added AGENTS.md with structure documentation
- autogen-migration/ and semantic-kernel-migration/ preserved at root
* fix: switch to AzureOpenAI Foundry, fix CI failures
- Switch all 01-get-started samples to AzureOpenAIResponsesClient with
Azure AI Foundry project endpoint (AZURE_AI_PROJECT_ENDPOINT +
AZURE_OPENAI_RESPONSES_DEPLOYMENT_NAME + AzureCliCredential)
- Add _to_delete/ and 05-end-to-end/ to pyrightconfig.samples.json excludes
- Fix test paths in packages/ that referenced old getting_started/ dirs:
durabletask conftest + streaming test, azurefunctions conftest,
devui conftest + capture_messages + openai_sdk_integration
- Fix workflow_as_agent_human_in_the_loop.py import (sibling import)
- Update hosting READMEs and tool comment paths
- Replace root README.md with new structure overview
- Update AGENTS.md to document Azure OpenAI Foundry as default provider
* cleanup: remove _to_delete folder, copy resource files to active dirs
All files in _to_delete/ were either:
- Exact duplicates of files in the new structure (240 files)
- Same file with only comment path updates (100 files)
- One import-fix diff (workflow_as_agent_human_in_the_loop.py)
- One superseded minimal_sample.py
Resource files (sample.pdf, countries.json, employees.pdf, weather.json)
copied to 02-agents/sample_assets/ and 02-agents/resources/ since active
samples reference them.
* fix: address PR review comments, centralize resources, remove root duplicates
- Fix type annotation in 04_memory.py (string union -> proper types)
- Fix old sample paths in observability files
- Fix grammar/spelling in observability samples
- Move sample_assets/ and resources/ to shared/ folder
- Remove 8 duplicate observability files from 02-agents root
- Update resource path references in multimodal_input and provider samples
* fix: update broken links from old getting_started paths to new structure
- Update relative paths in READMEs: getting_started/ → 01-get-started/,
02-agents/, 03-workflows/, 04-hosting/, 05-end-to-end/
- Fix absolute GitHub URLs in package READMEs
- Fix broken link in ollama package README
* fix: convert absolute GitHub URLs to relative paths for link checker
Absolute URLs to python/samples/ on main branch 404 until PR merges.
Converted to relative paths that linkspector can verify locally.
* fix: update link for handoff sample moved to orchestrations/
* fix: update chatkit-integration README path from demos/ to 05-end-to-end/
* fix: update broken links in orchestrations README to match flat directory structure
* Centralize tool result parsing in FunctionTool.invoke()
- Add parse_result static method to FunctionTool that converts raw
function return values to strings at invocation time
- Add result_parser parameter to FunctionTool and @tool decorator
for custom parsing
- Remove prepare_function_call_results from all 9 consumer files
and from the public API
- Update MCPTool to parse MCP types directly to strings via
_parse_tool_result_from_mcp and _parse_prompt_result_from_mcp
- Change MCPTool parse_tool_results/parse_prompt_results type from
Literal[True] | Callable | None to Callable | None
- Remove ReturnT type parameter from FunctionTool (now single
generic ArgsT since invoke() always returns str)
- Update all subclass signatures and docstrings
Fixes#1147
* Fix test_mcp_tool_call_tool_with_meta_integration for string results
The test was still accessing result[0].additional_properties but
invoke() now returns a string, not a list of Content objects.
* Fix SIM108 lint: use binary operator for output assignment
* Fix bedrock: use FunctionTool.parse_result instead of str() fallback
str(result) turns None into literal 'None' and dicts into Python reprs
with single quotes, breaking JSON parsing. Use the shared parse_result
which handles None as '' and serializes via json.dumps.
* updated lock
* updates from feedback
* Replace Pydantic Settings with TypedDict + load_settings()
- Remove pydantic-settings dependency, add python-dotenv
- Delete _pydantic.py (AFBaseSettings, HTTPsUrl)
- Add _settings.py with generic load_settings() function, SecretString,
type coercion, and Required field validation (SettingNotFoundError)
- Convert all 13 settings classes from AFBaseSettings subclasses to
TypedDict definitions with load_settings() calls
- Update all consumers from attribute access to dict access
- Add 20 unit tests for load_settings() covering basic loading, dotenv,
SecretString, type coercion, and required field validation
- Update all existing tests for new settings patterns
* Fix mypy type errors from settings conversion
- Fix str | None attribute access in responses_client (walrus operator)
- Fix SecretString | None narrowing in bedrock (type: ignore after guard)
- Convert _context_provider.py attribute access to dict access (missed file)
- Fix endpoint type narrowing in search_provider and context_provider
- Fix purview: str | None .rstrip(), int | None defaults, urlparse bytes
* Address PR review: required_fields param, type validation, fixes
- Move required field validation from TypedDict annotations (Required)
to a required_fields parameter on load_settings(), enabling runtime
decisions about which fields are required
- Remove Required imports and restore from __future__ import annotations
in ollama and foundry_local
- Add _check_override_type() for deterministic ServiceInitializationError
on invalid override types (e.g. dict passed for str field)
- Fix all multi-exception test catches back to single exception type
- Fix Ollama host=None: use .get() so None is passed through to SDK default
- Fix Purview processor: use explicit is-None checks instead of or operator
- Remove unused BaseModel import from openai/_shared.py
- Add 4 new tests (24 total): required_fields param, type validation
* Fix type validation: allow int for float fields
_check_override_type now permits int values for float-typed fields,
matching Python's standard numeric promotion behavior.
* fix: wrap urlparse arg with str() to fix mypy bytes endswith error
* PR1: Add core context provider types and tests
New types in _sessions.py (no changes to existing code):
- SessionContext: per-invocation state with extend_messages/get_messages/
extend_instructions/extend_tools and read-only response property
- _ContextProviderBase: base class with before_run/after_run hooks
- _HistoryProviderBase: storage base with load/store flags, abstract
get_messages/save_messages, default before_run/after_run
- AgentSession: lightweight session with state dict, to_dict/from_dict
- InMemoryHistoryProvider: built-in provider storing in session.state
35 unit tests covering all classes and configuration flags.
* feat: keyword-only params, stateless InMemoryHistoryProvider, deep serialization
- Make before_run/after_run parameters keyword-only
- InMemoryHistoryProvider stores ChatMessage objects directly (no per-cycle serialization)
- Deep serialization via to_dict/from_dict only at session boundary
- State type registry for automatic deserialization of registered types
- Updated tests for new serialization approach
* feat: add new-pattern provider implementations for external packages
- _RedisContextProvider(BaseContextProvider) - Redis search/vector context
- _RedisHistoryProvider(BaseHistoryProvider) - Redis-backed message storage
- _Mem0ContextProvider(BaseContextProvider) - Mem0 semantic memory
- _AzureAISearchContextProvider(BaseContextProvider) - Azure AI Search (semantic + agentic)
All use temporary _ prefix names for side-by-side coexistence with existing providers.
Will be renamed in PR2 when old ContextProvider/ChatMessageStore are removed.
* test: add tests for new-pattern provider implementations
- 32 tests for _RedisContextProvider and _RedisHistoryProvider
- 29 tests for _Mem0ContextProvider
- 17 tests for _AzureAISearchContextProvider
* fix: address PR review comments and CI failures
- Move module docstring before imports in _sessions.py (review comment)
- Import TYPE_CHECKING unconditionally in Redis _context_provider.py (NameError on Python <3.12)
- Fix Mem0 test_init_auto_creates_client_when_none to patch at class level
* feat: add source attribution to extend_messages
Set attribution marker in additional_properties for each message
added via extend_messages(), matching the tool attribution pattern.
Uses setdefault to preserve any existing attribution.
* refactor: make attribution value a dict with source_id key
* add attribution and use sets for filters
* Add source_type to message attribution and copy messages in extend_messages
- SessionContext.extend_messages now accepts source as str or object with
source_id attribute; when an object is passed, its class name is recorded
as source_type in the attribution dict
- Messages are shallow-copied before attribution is added so callers'
original objects are never mutated
- Filter framework-internal keys (attribution) from A2A wire metadata
to prevent leaking internal state over the wire
* fix: correct mypy type: ignore comment from union-attr to attr-defined
* set attribution to _attribution
* adjusted naming of bools
* Python: Add long-running agents and background responses support
- Add ContinuationToken TypedDict to core types
- Add continuation_token field to ChatResponse, ChatResponseUpdate,
AgentResponse, and AgentResponseUpdate
- Add background and continuation_token options to OpenAIResponsesOptions
- Implement polling via responses.retrieve() and streaming resumption
in RawOpenAIResponsesClient
- Propagate continuation tokens through agent run() and
map_chat_to_agent_update
- Fix streaming telemetry 'Failed to detach context' error in both
ChatTelemetryLayer and AgentTelemetryLayer by avoiding
trace.use_span() context attachment for async-managed spans
- Add 14 unit tests for continuation token types and background flows
- Add background_responses sample showing polling and stream resumption
Fixes#2478
* Python: Add A2A long-running task support via ContinuationToken
- Make ContinuationToken provider-agnostic (total=False, optional task_id/context_id fields)
- Add background param to A2AAgent.run() controlling token emission
- Add poll_task() for single-request task state retrieval
- Add resubscribe support via continuation_token param on run()
- Extract _updates_from_task() and _map_a2a_stream() for cleaner code
- Streamline run()/streaming by removing intermediate _stream_updates wrapper
- Update A2A sample to show background=False (default) with link to background_responses sample
- Remove stale BareAgent from __all__
- Add 12 new A2A continuation token tests
* fix logic for overriding continuation token when done
* refactored ContinuationToken setup
* Python: fix prek runner running fmt/lint in all packages on core change
When a core package file changed, run_tasks_in_changed_packages.py ran
fmt, lint, and pyright in ALL 22 packages (66 tasks). Only type-checking
tasks (pyright, mypy) need to propagate to all packages since type
changes in core affect downstream packages. File-local tasks (fmt, lint)
only need to run in packages with actual file changes.
This reduces a core-only change from 66 tasks to 24 tasks (2 local +
22 pyright).
Also adds no-commit-to-branch builtin hook to protect the main branch
from direct commits.
* Python: add agent skills extracted from AGENTS.md and coding standards
Add 5 skills to python/.github/skills/ following the Agent Skills format:
- python-development: coding standards, type annotations, docstrings, logging
- python-testing: test structure, fixtures, running tests, async mode
- python-code-quality: linting, formatting, type checking, prek hooks, CI
- python-package-management: monorepo structure, lazy loading, versioning
- python-samples: sample structure, PEP 723, documentation guidelines
* Python: deduplicate AGENTS.md and instructions with agent skills
* updated skills
* fixes from review
* Python: increase timeout for web search integration test
* Add ADR for Python ContextMiddleware unification
* Add session serialization/deserialization design to ADR
* Add Related Issues section mapping to ADR
* Update session management: create_session, get_session_by_id, agent.serialize_session
* ADR: Add hooks alternative, context compaction discussion, and PR feedback
- Add Option 3: ContextHooks with before_run/after_run pattern
- Add detailed pros/cons for both wrapper and hooks approaches
- Add Open Discussion section on context compaction strategies
- Clarify response_messages is read-only (use AgentMiddleware for modifications)
- Add SimpleRAG examples showing input-only filtering
- Clarify default storage only added when NO middleware configured
- Add RAGWithBuffer examples for self-managed history
- Rename hook methods to before_run/after_run
* ADR: Restructure and add .NET comparison
- Add class hierarchy clarification for both options
- Merge detailed design sections (side-by-side comparison)
- Move detailed design before decision outcome
- Move compaction discussion after decision
- Add .NET implementation comparison (feature equivalence)
- Update .NET method names to match actual implementation
- Rename hook methods to before_run/after_run
- Fix storage context table for injected context
* tweaks
* fix smart load
* ADR: Add naming discussion note for ContextHooks
- Note that class and method names are open for discussion
- Add alternative method naming options table
- Include invoking/invoked as option matching current Python and .NET
* Update context middleware design: remove smart mode, add attribution filtering
- Remove smart mode for load_messages (now explicit bool, default True)
- Add attribution marker in additional_properties for message filtering
- Update validation to warn on multiple or zero storage loaders
- Add note about ChatReducer naming from .NET
- Note that attribution should not be propagated to storage
* Add Decision 2: Instance Ownership (instances in session vs agent)
- Option A: Instances in Session (current proposal)
- Option B: Instances in Agent, State in Session
- B1: Simple dict state with optional return
- B2: SessionState object with mutable wrapper
- Updated examples to use Hooks pattern (before_run/after_run)
- Added open discussion on hook factories in Option B model
* Update ADR: Choose ContextPlugin with before_run/after_run and Option B1
Decision outcomes:
- Option 3 (Hooks pattern) with ContextPlugin class name
- Methods: before_run/after_run
- Option B1: Instances in Agent, State in Session (simple dict)
- Whole state dict passed to plugins (mutable, no return needed)
- Added trust note: plugins reason over messages, so they're trusted by default
Status changed from proposed to accepted.
* Add agent and session params to before_run/after_run methods
Signature now: before_run(agent, session, context, state)
* Remove ContextPluginRunner, store plugins directly on agent
Simpler design: agent stores Sequence[ContextPlugin] and calls
before_run/after_run directly in the run method.
* Update workplan to 2 PRs for simpler review
* updated doc
* Refine ADR: serialization, ownership, decorators, session methods, exports
- Add to_dict()/from_dict() on AgentSession with 'type' discriminator
- Present serialization as Option A (direct) vs Option B (through agent)
- Rewrite ownership section as 2x2 matrix (orthogonal decision)
- Move Instance Ownership Options before Decision Outcome
- Fix get_session to use service_session_id, split from create_session
- Add decorator-based provider convenience API (@before_run/@after_run)
- Add _ prefix naming strategy for all PR1 types (core + external)
- Constructor compatibility table for existing providers
- Add load_messages=False skip logic to all agent run loops
- Clarify abstract vs non-abstract in execution pattern samples
- Update auto-provision: trigger on conversation_id or store=True
- Document root package exports (ContextProvider, HistoryProvider, etc.)
- Rename section heading to 'Key Design Considerations'
* Rename ADR to 0016-python-context-middleware.md
* Fix broken link: #3-unified-storage-middleware → #3-unified-storage
* python: replace pre-commit with prek, add PEP 723 script deps, clean up dev dependencies
- Replace pre-commit with prek (Rust-native, faster pre-commit alternative)
- Move supported hooks to repo: builtin for zero-clone speed
- Add new builtin hooks: trailing-whitespace, check-merge-conflict, detect-private-key, check-added-large-files
- Update all hook versions to latest (pre-commit-hooks v6, pyupgrade v3.21.2, bandit 1.9.3, uv-pre-commit 0.10.0)
- Add PEP 723 inline script metadata to 34 samples with external deps
- Remove autogen-agentchat/autogen-ext from dev deps (now declared per-sample)
- Remove unused dev deps: pytest-env, tomli-w
- Add agent-framework-core>=1.0.0b260130 lower bound to all 21 packages
- Update CI workflow to use j178/prek-action
- Update docs: DEV_SETUP.md, AGENTS.md, CODING_STANDARD.md, SAMPLE_GUIDELINES.md
* updated lock
* python: fix prek config paths for local execution and CI workflow
Remove global 'files: ^python/' filter and strip python/ prefix from all path patterns in .pre-commit-config.yaml so prek finds files when run from the python/ directory. Update CI workflow to use --cd python instead of --config path. Include trailing whitespace fixes and dev dependency cleanup.
* python: move helper scripts to scripts/ folder and exclude from checks
* python: exclude AGENTS.md from prek markdown code lint
* python: exclude AGENTS.md and azure_ai_search sample from markdown lint
* fix m365 sample
* python: ignore CPY rule for samples with PEP 723 headers
* fix in dev_setup
* python: replace aiofiles with regular open in samples
* python: suppress reportUnusedImport in markdown code block checker
* python: use samples pyright config for markdown code block checker
Write a temp pyrightconfig.json matching pyrightconfig.samples.json rules (typeCheckingMode=off, only reportMissingImports and reportAttributeAccessIssue). Filter output to only fail on these rules since syntax-level errors (top-level await, undefined vars) are expected in README documentation snippets.
* python: use markdown-code-lint with fixed globs instead of prek file list
The prek-markdown-code-lint task received all changed files including non-README markdown and files with pre-existing broken imports. Replace with the standard markdown-code-lint task which uses the correct glob patterns (README.md, packages/**/README.md, samples/**/*.md).
* python: exclude READMEs with pre-existing broken imports from markdown lint
* python: fix broken README code snippets instead of excluding them
- ag-ui: replace TextContent (removed) with content.type == 'text'
- durabletask: fix import path to durabletask.worker.TaskHubGrpcWorker
- orchestrations: use constructor params instead of .participants() method
- observability: mark deprecated code blocks as plain text, filter
reportMissingImports to agent_framework modules only
- remove README excludes from markdown-code-lint task
* add revision to gaia download
* feat(python): parallelize checks across packages
Run (package Ă— task) cross-product in parallel using ThreadPoolExecutor
and subprocesses. Key changes:
- Add scripts/task_runner.py with shared parallel execution engine
- Update run_tasks_in_packages_if_exists.py to accept multiple tasks
- Update run_tasks_in_changed_packages.py with --files flag and parallel support
- Add check-packages poe task (fmt+lint+pyright+mypy in parallel)
- Add prek-markdown-code-lint and prek-samples-check with change detection
- Split CI code quality workflow into parallel prek and mypy jobs
- Update DEV_SETUP.md to document new parallel behavior
Core package changes still trigger checks on all packages.
* feat(ci): split code quality into 4 parallel jobs
Split the single prek job into parallel jobs:
- pre-commit-hooks: lightweight hooks (SKIP=poe-check)
- package-checks: fmt/lint/pyright/mypy via check-packages
- samples-markdown: samples-lint, samples-syntax, markdown-code-lint
- mypy: change-detected mypy checks
All 4 jobs run concurrently (Ă—2 Python versions = 8 runners).
* feat(ci): use only Python 3.10 for code quality checks
* refactor(python): add future annotations and remove quoted types
Add `from __future__ import annotations` to 93 package files that
used quoted string annotations, then run pyupgrade --py310-plus to
remove the now-unnecessary quotes.
Fixes https://github.com/microsoft/agent-framework/issues/3578
* Add samples syntax checking with pyright
- Add pyrightconfig.samples.json with relaxed type checking but import validation
- Add samples-syntax poe task to check samples for syntax and import errors
- Add samples-syntax to check and pre-commit-check tasks
- Fix 78 sample errors:
- Update workflow builder imports to use agent_framework_orchestrations
- Change content type isinstance checks to content.type comparisons
- Use Content factory methods instead of removed content type classes
- Fix TypedDict access patterns for Annotation
- Fix various API mismatches (normalize_messages, ChatMessage.text, role)
* fixed a bunch of samples and tweaks to pre-commit
* updated lock
* updated lock
* fixes
* added lint to samples
* WIP
* big update to new ResponseStream model
* fixed tests and typing
* fixed tests and typing
* fixed tools typevar import
* fix
* mypy fix
* mypy fixes and some cleanup
* fix missing quoted names
* and client
* fix imports agui
* fix anthropic override
* fix agui
* fix ag ui
* fix import
* fix anthropic types
* fix mypy
* refactoring
* updated typing
* fix 3.11
* fixes
* redid layering of chat clients and agents
* redid layering of chat clients and agents
* Fix lint, type, and test issues after rebase
- Add @overload decorators to AgentProtocol.run() for type compatibility
- Add missing docstring params (middleware, function_invocation_configuration)
- Fix TODO format (TD002) by adding author tags
- Fix broken observability tests from upstream:
- Replace non-existent use_instrumentation with direct instantiation
- Replace non-existent use_agent_instrumentation with AgentTelemetryLayer mixin
- Fix get_streaming_response to use get_response(stream=True)
- Add AgentInitializationError import
- Update streaming exception tests to match actual behavior
* Fix AgentExecutionException import error in test_agents.py
- Replace non-existent AgentExecutionException with AgentRunException
* Fix test import and asyncio deprecation issues
- Add 'tests' to pythonpath in ag-ui pyproject.toml for utils_test_ag_ui import
- Replace deprecated asyncio.get_event_loop().run_until_complete with asyncio.run
* Fix azure-ai test failures
- Update _prepare_options patching to use correct class path
- Fix test_to_azure_ai_agent_tools_web_search_missing_connection to clear env vars
* Convert ag-ui utils_test_ag_ui.py to conftest.py
- Move test utilities to conftest.py for proper pytest discovery
- Update all test imports to use conftest instead of utils_test_ag_ui
- Remove old utils_test_ag_ui.py file
- Revert pythonpath change in pyproject.toml
* fix: use relative imports for ag-ui test utilities
* fix agui
* Rename Bare*Client to Raw*Client and BaseChatClient
- Renamed BareChatClient to BaseChatClient (abstract base class)
- Renamed BareOpenAIChatClient to RawOpenAIChatClient
- Renamed BareOpenAIResponsesClient to RawOpenAIResponsesClient
- Renamed BareAzureAIClient to RawAzureAIClient
- Added warning docstrings to Raw* classes about layer ordering
- Updated README in samples/getting_started/agents/custom with layer docs
- Added test for span ordering with function calling
* Fix layer ordering: FunctionInvocationLayer before ChatTelemetryLayer
This ensures each inner LLM call gets its own telemetry span, resulting in
the correct span sequence: chat -> execute_tool -> chat
Updated all production clients and test mocks to use correct ordering:
- ChatMiddlewareLayer (first)
- FunctionInvocationLayer (second)
- ChatTelemetryLayer (third)
- BaseChatClient/Raw...Client (fourth)
* Remove run_stream usage
* Fix conversation_id propagation
* Python: Add BaseAgent implementation for Claude Agent SDK (#3509)
* Added ClaudeAgent implementation
* Updated streaming logic
* Small updates
* Small update
* Fixes
* Small fix
* Naming improvements
* Updated imports
* Addressed comments
* Updated package versions
* Update Claude agent connector layering
* fix test and plugin
* Store function middleware in invocation layer
* Fix telemetry streaming and ag-ui tests
* Remove legacy ag-ui tests folder
* updates
* Remove terminate flag from FunctionInvocationContext, use MiddlewareTermination instead
- Remove terminate attribute from FunctionInvocationContext
- Add result attribute to MiddlewareTermination to carry function results
- FunctionMiddlewarePipeline.execute() now lets MiddlewareTermination propagate
- _auto_invoke_function captures context.result in exception before re-raising
- _try_execute_function_calls catches MiddlewareTermination and sets should_terminate
- Fix handoff middleware to append to chat_client.function_middleware directly
- Update tests to use raise MiddlewareTermination instead of context.terminate
- Add middleware flow documentation in samples/concepts/tools/README.md
- Fix ag-ui to use FunctionMiddlewarePipeline instead of removed create_function_middleware_pipeline
* fix: remove references to removed terminate flag in purview tests, add type ignore
* fix: move _test_utils.py from package to test folder
* fix: call get_final_response() to trigger context provider notification in streaming test
* fix: correct broken links in tools README
* docs: clarify default middleware behavior in summary table
* fix: ensure inner stream result hooks are called when using map()/from_awaitable()
* Fix mypy type errors
* Address PR review comments on observability.py
- Remove TODO comment about unconsumed streams, add explanatory note instead
- Remove redundant _close_span cleanup hook (already called in _finalize_stream)
- Clarify behavior: cleanup hooks run after stream iteration, if stream is not
consumed the span remains open until garbage collected
* Remove gen_ai.client.operation.duration from span attributes
Duration is a metrics-only attribute per OpenTelemetry semantic conventions.
It should be recorded to the histogram but not set as a span attribute.
* Remove duration from _get_response_attributes, pass directly to _capture_response
Duration is a metrics-only attribute. It's now passed directly to _capture_response
instead of being included in the attributes dict that gets set on the span.
* Remove redundant _close_span cleanup hook in AgentTelemetryLayer
_finalize_stream already calls _close_span() in its finally block,
so adding it as a separate cleanup hook is redundant.
* Use weakref.finalize to close span when stream is garbage collected
If a user creates a streaming response but never consumes it, the cleanup
hooks won't run. Now we register a weak reference finalizer that will close
the span when the stream object is garbage collected, ensuring spans don't
leak in this scenario.
* Fix _get_finalizers_from_stream to use _result_hooks attribute
Renamed function to _get_result_hooks_from_stream and fixed it to
look for the _result_hooks attribute which is the correct name in
ResponseStream class.
* Add missing asyncio import in test_request_info_mixin.py
* Fix leftover merge conflict marker in image_generation sample
* Update integration tests
* Fix integration tests: increase max_iterations from 1 to 2
Tests with tool_choice options require at least 2 iterations:
1. First iteration to get function call and execute the tool
2. Second iteration to get the final text response
With max_iterations=1, streaming tests would return early with only
the function call/result but no final text content.
* Fix duplicate function call error in conversation-based APIs
When using conversation_id (for Responses/Assistants APIs), the server
already has the function call message from the previous response. We
should only send the new function result message, not all messages
including the function call which would cause a duplicate ID error.
Fix: When conversation_id is set, only send the last message (the tool
result) instead of all response.messages.
* Add regression test for conversation_id propagation between tool iterations
Port test from PR #3664 with updates for new streaming API pattern.
Tests that conversation_id is properly updated in options dict during
function invocation loop iterations.
* Fix tool_choice=required to return after tool execution
When tool_choice is 'required', the user's intent is to force exactly one
tool call. After the tool executes, return immediately with the function
call and result - don't continue to call the model again.
This fixes integration tests that were failing with empty text responses
because with tool_choice=required, the model would keep returning function
calls instead of text.
Also adds regression tests for:
- conversation_id propagation between tool iterations (from PR #3664)
- tool_choice=required returns after tool execution
* Document tool_choice behavior in tools README
- Add table explaining tool_choice values (auto, none, required)
- Explain why tool_choice=required returns immediately after tool execution
- Add code example showing the difference between required and auto
- Update flow diagram to show the early return path for tool_choice=required
* Fix tool_choice=None behavior - don't default to 'auto'
Remove the hardcoded default of 'auto' for tool_choice in ChatAgent init.
When tool_choice is not specified (None), it will now not be sent to the
API, allowing the API's default behavior to be used.
Users who want tool_choice='auto' can still explicitly set it either in
default_options or at runtime.
Fixes#3585
* Fix tool_choice=none should not remove tools
In OpenAI Assistants client, tools were not being sent when
tool_choice='none'. This was incorrect - tool_choice='none' means
the model won't call tools, but tools should still be available
in the request (they may be used later in the conversation).
Fixes#3585
* Add test for tool_choice=none preserving tools
Adds a regression test to ensure that when tool_choice='none' is set but
tools are provided, the tools are still sent to the API. This verifies
the fix for #3585.
* Fix tool_choice=none should not remove tools in all clients
Apply the same fix to OpenAI Responses client and Azure AI client:
- OpenAI Responses: Remove else block that popped tool_choice/parallel_tool_calls
- Azure AI: Remove tool_choice != 'none' check when adding tools
When tool_choice='none', the model won't call tools, but tools should
still be sent to the API so they're available for future turns.
Also update README to clarify tool_choice=required supports multiple tools.
Fixes#3585
* Keep tool_choice even when tools is None
Move tool_choice processing outside of the 'if tools' block in OpenAI
Responses client so tool_choice is sent to the API even when no tools
are provided.
* Update test to match new parallel_tool_calls behavior
Changed test_prepare_options_removes_parallel_tool_calls_when_no_tools to
test_prepare_options_preserves_parallel_tool_calls_when_no_tools to reflect
that parallel_tool_calls is now preserved even when no tools are present,
consistent with the tool_choice behavior.
* Fix ChatMessage API and Role enum usage after rebase
- Update ChatMessage instantiation to use keyword args (role=, text=, contents=)
- Fix Role enum comparisons to use .value for string comparison
- Add created_at to AgentResponse in error handling
- Fix AgentResponse.from_updates -> from_agent_run_response_updates
- Fix DurableAgentStateMessage.from_chat_message to convert Role enum to string
- Add Role import where needed
* Fix additional ChatMessage API and method name changes
- Fix ChatMessage usage in workflow files (use text= instead of contents= for strings)
- Fix AgentResponse.from_updates -> from_agent_run_response_updates in workflow files
- Fix test files for ChatMessage and Role enum usage
* Fix remaining ChatMessage API usage in test files
* Fix more ChatMessage and Role API changes in source and test files
- Fix ChatMessage in _magentic.py replan method
- Fix Role enum comparison in test assertions
- Fix remaining test files with old ChatMessage syntax
* Fix ChatMessage and Role API changes across packages
- Add Role import where missing
- Fix ChatMessage signature: positional args to keyword args (role=, text=, contents=)
- Fix Role enum comparisons: .role.value instead of .role string
- Fix FinishReason enum usage in ag-ui event converters
- Rename AgentResponse.from_updates to from_agent_run_response_updates in ag-ui
Fixes API compatibility after Types API Review improvements merge
* Fix ChatMessage and Role API changes in github_copilot tests
* Fix ChatMessage and Role API changes in redis and github_copilot packages
- Fix redis provider: Role enum comparison using .value
- Fix redis tests: ChatMessage signature and Role comparisons
- Fix github_copilot tests: ChatMessage signature and Role comparisons
- Update docstring examples in redis chat message store
* Fix ChatMessage and Role API changes in devui package
- Fix executor: ChatMessage signature change
- Fix conversations: Role enum to string conversion in two places
- Fix tests: ChatMessage signatures and Role comparisons
* Fix ChatMessage and Role API changes in a2a and lab packages
- Fix a2a tests: Role comparisons and ChatMessage signatures
- Fix lab tau2 source: Role enum comparison in flip_messages, log_messages, sliding_window
- Fix lab tau2 tests: ChatMessage signatures and Role comparisons
* Remove duplicate test files from ag-ui/tests (tests are in ag_ui_tests)
* Fix ChatMessage and Role API changes across packages
After rebasing on upstream/main which merged PR #3647 (Types API Review
improvements), fix all packages to use the new API:
- ChatMessage: Use keyword args (role=, text=, contents=) instead of
positional args
- Role: Compare using .value attribute since it's now an enum
Packages fixed:
- ag-ui: Fixed Role value extraction bugs in _message_adapters.py
- anthropic: Fixed ChatMessage and Role comparisons in tests
- azure-ai: Fixed Role comparison in _client.py
- azure-ai-search: Fixed ChatMessage and Role in source/tests
- bedrock: Fixed ChatMessage signatures in tests
- chatkit: Fixed ChatMessage and Role in source/tests
- copilotstudio: Fixed ChatMessage and Role in tests
- declarative: Fixed ChatMessage in _executors_agents.py
- mem0: Fixed ChatMessage and Role in source/tests
- purview: Fixed ChatMessage in source/tests
* Fix mypy errors for ChatMessage and Role API changes
- durabletask: Use str() fallback in role value extraction
- core: Fix ChatMessage in _orchestrator_helpers.py to use keyword args
- core: Add type ignore for _conversation_state.py contents deserialization
- ag-ui: Fix type ignore comments (call-overload instead of arg-type)
- azure-ai-search: Fix get_role_value type hint to accept Any
- lab: Move get_role_value to module level with Any type hint
* Improve CI test timeout configuration
- Increase job timeout from 10 to 15 minutes
- Reduce per-test timeout to 60s (was 900s/300s)
- Add --timeout_method thread for better timeout handling
- Add --timeout-verbose to see which tests are slow
- Reduce retries from 3 to 2 and delay from 10s to 5s
This ensures individual test timeouts are shorter than the job
timeout, providing better visibility when tests hang.
With 60s timeout and 2 retries, worst case per test is ~180s.
* Fix ChatMessage API usage in docstrings and source
- Fix ChatMessage positional args in docstrings: _serialization.py, _threads.py, _middleware.py
- Fix ChatMessage in tau2 runner.py
- Fix role comparison in _orchestrator_helpers.py to use .value
- Fix role comparison in _group_chat.py docstring example
- Fix role assertions in test_durable_entities.py to use .value
* Revert tool_choice/parallel_tool_calls changes - must be removed when no tools
OpenAI API requires tool_choice and parallel_tool_calls to only be
present when tools are specified. Restored the logic that removes
these options when there are no tools.
- Restored check in _chat_client.py to remove tool_choice and
parallel_tool_calls when no tools present
- Restored same logic in _responses_client.py
- Reverted test to expect the correct behavior
* fixed issue in tests
* fix: resolve merge conflict markers in ag-ui tests
* fix: restructure ag-ui tests and fix Role/FinishReason to use string types
* fix: streaming function invocation and middleware termination
- Refactor streaming function invocation to use get_final_response() on inner streams
- Fix MiddlewareTermination to accept result parameter for passing results
- Fix _AutoHandoffMiddleware to use MiddlewareTermination instead of context.terminate
- Fix AgentMiddlewareLayer.run() to properly forward function/chat middleware
- Remove duplicate middleware registration in AgentMiddlewareLayer.__init__
- Fix exception handling in _auto_invoke_function to properly capture termination
- Fix mypy errors in core package
- Update tests to use stream=True parameter for unified run API
* fix all tests command
* Refactor integration tests to use pytest fixtures
- Merge testutils.py into conftest.py for azurefunctions integration tests
- Merge dt_testutils.py into conftest.py for durabletask integration tests
- Convert all integration tests to use fixtures instead of direct imports
(fixes ModuleNotFoundError with --import-mode=importlib)
- Add sample_helper fixture for azurefunctions tests
- Add agent_client_factory and orchestration_helper fixtures for durabletask
- Integration tests now skip with descriptive messages when services unavailable
- Restructure devui tests into tests/devui/ with proper conftest.py
- Add test organization guidelines to CODING_STANDARD.md
- Remove __init__.py from test directories per pytest best practices
* Fix pytest_collection_modifyitems to only skip integration tests
The hook was skipping all tests in the test session, not just
integration tests. Now it only skips items in the integration_tests
directory.
* Fix mem0 tests failing on Python 3.13
Use patch.object on the imported module instead of @patch with string
path to ensure the mock takes effect regardless of import timing.
* fix mem0
* another attempt for mem0
* fix for mem0
* fix mem0
* Increase worker initialization wait time in durabletask tests
Increase from 2 to 8 seconds to allow time for:
- Python startup and module imports
- Azure OpenAI client creation
- Agent registration with DTS worker
- Worker connection to DTS
This helps prevent test failures in CI where the first tests may run
before the worker is fully ready to process requests.
* Fix streaming test to use ResponseStream with finalizer
The _consume_stream method now expects a ResponseStream that can provide
a final AgentResponse via get_final_response(). Update the test to use
ResponseStream with AgentResponse.from_updates as the finalizer.
* Fix MockToolCallingAgent to use new ResponseStream API and update samples
* small updates to run_stream to run
* fix sub workflow
* temp fix for az func test
---------
Co-authored-by: Dmytro Struk <13853051+dmytrostruk@users.noreply.github.com>
* Replace Role and FinishReason classes with NewType + Literal
- Remove EnumLike metaclass from _types.py
- Replace Role class with NewType('Role', str) + RoleLiteral
- Replace FinishReason class with NewType('FinishReason', str) + FinishReasonLiteral
- Update all usages across codebase to use string literals
- Remove .value access patterns (direct string comparison now works)
- Add backward compatibility for legacy dict serialization format
- Update tests to reflect new string-based types
Addresses #3591, #3615
* Simplify ChatResponse and AgentResponse type hints (#3592)
- Remove overloads from ChatResponse.__init__
- Remove text parameter from ChatResponse.__init__
- Remove | dict[str, Any] from finish_reason and usage_details params
- Remove **kwargs from AgentResponse.__init__
- Both now accept ChatMessage | Sequence[ChatMessage] | None for messages
- Update docstrings and examples to reflect changes
- Fix tests that were using removed kwargs
- Fix Role type hint usage in ag-ui utils
* Remove text parameter from ChatResponseUpdate and AgentResponseUpdate (#3597)
- Remove text parameter from ChatResponseUpdate.__init__
- Remove text parameter from AgentResponseUpdate.__init__
- Remove **kwargs from both update classes
- Simplify contents parameter type to Sequence[Content] | None
- Update all usages to use contents=[Content.from_text(...)] pattern
- Fix imports in test files
- Update docstrings and examples
* Rename from_chat_response_updates to from_updates (#3593)
- ChatResponse.from_chat_response_updates → ChatResponse.from_updates
- ChatResponse.from_chat_response_generator → ChatResponse.from_update_generator
- AgentResponse.from_agent_run_response_updates → AgentResponse.from_updates
* Remove try_parse_value method from ChatResponse and AgentResponse (#3595)
- Remove try_parse_value method from ChatResponse
- Remove try_parse_value method from AgentResponse
- Remove try_parse_value calls from from_updates and from_update_generator methods
- Update samples to use try/except with response.value instead
- Update tests to use response.value pattern
- Users should now use response.value with try/except for safe parsing
* Add agent_id to AgentResponse and clarify author_name documentation (#3596)
- Add agent_id parameter to AgentResponse class
- Document that author_name is on ChatMessage objects, not responses
- Update ChatResponse docstring with author_name note
- Update AgentResponse docstring with author_name note
* Simplify ChatMessage.__init__ signature (#3618)
- Make contents a positional argument accepting Sequence[Content | str]
- Auto-convert strings in contents to TextContent
- Remove overloads, keep text kwarg for backward compatibility with serialization
- Update _parse_content_list to handle string items
- Update all usages across codebase to use new format: ChatMessage("role", ["text"])
* Allow Content as input on run and get_response
- Update prepare_messages and normalize_messages to accept Content
- Update type signatures in _agents.py and _clients.py
- Add tests for Content input handling
* Fix ChatMessage usage across packages and samples
Update all remaining ChatMessage(role=..., text=...) to use new
ChatMessage('role', ['text']) signature.
* Fix Role string usage and response format parsing
- Fix redis provider: remove .value access on string literals
- Fix durabletask ensure_response_format: set _response_format before accessing .value
* Fix ollama .value and ai_model_id issues, handle None in content list
- Fix ollama _chat_client: remove .value on string literals
- Fix ollama _chat_client: rename ai_model_id to model_id
- Fix _parse_content_list: skip None values gracefully
* Fix A2AAgent type signature to include Content
* Fix Role/FinishReason NewType dict annotations and improve test coverage to 95%
* Fix mypy errors for Role/FinishReason NewType usage
* Fix Role.TOOL and Role.ASSISTANT usage in _orchestrator_helpers.py
* Fix Role NewType usage in durabletask _models.py
* changed AIFunction to FunctionTool and @ai_function to @tool
* test and mypy fixes
* mypy fix
* switch function tool to always_require
* fix noop
* fix github copilot imports
* test fixes
* fix ollama test
* fixes for tests
* fix tests
* reverted change to always_require and extended timeout
* fix test
* ADR for simplified get response
* updated some language, added agent option and code comparison
* small update in sample
* added workflows and expanded some points
* changed decision and number
* updated with stream=False default
* removed display_name, renamed context_providers, middleware and AggregateContextProvider
* fixes
* fixed test
* testfix
* removed mistakenly put back test
* updated new test
* rename middlewares to middleware
* middleware fixes
* fix Python: kwargs are not passed to _prepare_thread_and_messages in ChatAgent.run
Fixes#3118
* fix Python: [Bug]: model_id versus model_deployment_name is confusing in Azure AI Agents
Fixes#3147
* add types
* fixed type and docstring
* refactoring and unifying naming schemes of internal methods of chat clients
* set tool_choice to auto
* fix for mypy
* added note on naming and fix#2951
* fix responses
* fixes in azure ai agents client
* added more complete parsing for mcp tool arguments
* fixed mypy
* added nonlocal model counter, and some fixes
* fixes in naming logic
* extracted json parsing function, added parametrized test and checked coverage
* first work on declarative
* initial version of the declarative support
* fix tests and mypy
* fix parameters of functiontool
* slight logic improvement
* remove path until merge
* updates from comments
* create dispatcher and spec type, json_schema method
* fix mypy, skipping model
* updated lock
* fixed declarative tests and renamed some other test files
* refined loader
* updated lock
* fix mypy
* added readme to samples folder
* fixes from review
* undid test file rename
* Fixes Python: @ai_function doesn't properly handle 'self' param
Fixes#1343
* fix for declaration only funcs
* fix mypy
2025-11-19 15:49:50 +00:00
Eduard van ValkenburgGitHubCopilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>eavanvalkenburgcopilot-swe-agent[bot] <198982749+Copilot@users.noreply.github.com>Copilot Autofix powered by AI <62310815+github-advanced-security[bot]@users.noreply.github.com>CopilotVictor Dibia
