* Foundry Evals integration for .NET
- Core evaluation framework: EvalItem, LocalEvaluator, FunctionEvaluator, EvalChecks
- IAgentEvaluator interface with MeaiEvaluatorAdapter bridge
- AgentEvaluationExtensions for agent.EvaluateAsync() overloads
- FoundryEvals wrapping MEAI quality/safety evaluators
- ConversationSplitters (LastTurn, Full) and IConversationSplitter
- EvalItem.PerTurnItems() for multi-turn decomposition
- HasImageContent for multimodal content detection
- WorkflowEvaluationExtensions for per-agent workflow evaluation
- 7 eval samples mirroring Python parity:
02-agents/Evaluation: SimpleEval, ExpectedOutputs, Multimodal
03-workflows/Evaluation: WorkflowEval
05-end-to-end/Evaluation: FoundryQuality, MixedProviders, ConversationSplits
- Comprehensive unit tests (1958 passing)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Rewrite FoundryEvals to use real Foundry Evals API
Replace MEAI evaluator shim with actual OpenAI EvaluationClient protocol
methods. FoundryEvals now creates eval definitions, submits runs, polls
for completion, and fetches per-item results server-side.
- New constructor: FoundryEvals(AIProjectClient, model, evaluators)
- Add FoundryEvalConverter for MEAI ChatMessage -> Foundry JSON format
- Add EvalId, RunId, ReportUrl to AgentEvaluationResults
- All 20 built-in evaluator constants now work (agent, tool, quality, safety)
- Remove Microsoft.Extensions.AI.Evaluation.Quality/Safety dependencies
- Update all samples for new constructor (no more ChatConfiguration)
- Replace BuildEvaluators tests with ResolveEvaluator tests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add response output to CustomEvals and ExpectedOutputs samples
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review: pagination, validation, error handling, tests
FoundryEvals fixes:
- Add pagination for output items (has_more/after cursor)
- Add guard clauses for pollIntervalSeconds/timeoutSeconds <= 0
- Fix double TryGetProperty for passed field parsing
- Throw on all-tool-evaluators with no tool definitions
- Fix XML doc (default 300s, not 180s)
New tests (30 added, 1989 total):
- EvalChecks: NonEmpty, ContainsExpected (pass/fail/skip/case),
HasImageContent, ToolCallsPresent
- FoundryEvalConverter: ConvertMessage (text, image, function call,
function results fan-out, empty fallback, mixed content),
ConvertEvalItem, BuildTestingCriteria (quality/agent/tool/groundedness
data mappings), BuildItemSchema
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix review: null-refs, Data.ToString() bug, ContainsExpected, add tests
- Fix NullReferenceException in sample Response display (pattern matching)
- Fix WorkflowEvaluationExtensions Data?.ToString() producing type names
instead of message text (pattern-match ChatMessage/AgentResponse/list)
- Change EvalChecks.ContainsExpected to return Passed=false when no
ExpectedOutput (was silently passing, masking misconfiguration)
- Add EvalItem constructor tests with LastTurn/Full/null splitters
- Add FoundryEvalConverter.ConvertMessage DataContent (base64 image) test
- Add ExtractAgentData tests with ChatMessage, list, and AgentResponse data
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Fix review: conversation fidelity, eval caching, fallback tests
- WorkflowEvaluationExtensions: preserve full response messages (tool calls,
intermediate) instead of synthetic 2-message conversation. Cast completed
Data to AgentResponse and use Messages when available, fallback to text.
- FoundryEvals: cache evalId per schema shape (hasContext, hasTools) so
subsequent EvaluateAsync calls create runs under the same eval definition.
- MeaiEvaluatorAdapter: code already correctly passes queryMessages (not full
conversation) to IEvaluator — no change needed, verified by inspection.
- Add tests: AgentResponse full messages preservation, unknown object
ToString() fallback for ExtractAgentData.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Rename AzureAI→Foundry: move eval files, update references
- Move FoundryEvals.cs and FoundryEvalConverter.cs from
Microsoft.Agents.AI.AzureAI to Microsoft.Agents.AI.Foundry
- Update namespace from AzureAI to Foundry in both files
- Add explicit usings required by Foundry project (no implicit usings)
- Move FoundryEvalConverter tests to Foundry.UnitTests project
(avoids ReplacingRedactor type conflict from dual project refs)
- Update all sample csproj references and using statements
- Remove Foundry project reference from AI UnitTests
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* PR review round 4: wire up tool extraction, remove eval cache, fix null safety
- BuildEvalItem: extract tools from agent via GetService<ChatOptions>() into EvalItem.Tools (Python parity)
- FoundryEvals: remove eval ID cache - each call creates fresh definition (matches Python behavior)
- FoundryEvals: replace null-forgiving operators with descriptive InvalidOperationException
- MixedProviders sample: remove unnecessary explicit PackageReferences (transitively provided)
- FoundryEvalConverter: document that tool results take precedence over text content
- Add LocalEvaluator zero-checks test documenting 0 metrics = failed behavior
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python-dotnet parity: 9 feature gaps filled
New checks:
- ToolCallArgsMatch() — verify tool call names + argument subset match
- ToolCalledCheck(ToolCalledMode.Any, ...) — match any of the specified tools
- ToolCalledMode enum (All/Any)
FoundryEvals enhancements:
- Default evaluators now [Relevance, Coherence, TaskAdherence] (was Relevance, Coherence)
- Auto-add ToolCallAccuracy when items have tool definitions
- EvaluateTracesAsync — evaluate by response_ids, trace_ids, or agent_id
- EvaluateFoundryTargetAsync — evaluate deployed Foundry targets
Result type enrichment:
- AgentEvaluationResults: added Status, Error, PerEvaluator, DetailedItems
- New EvalItemResult/EvalScoreResult/PerEvaluatorResult types
- FoundryEvals populates all new fields from API responses
Workflow fix:
- Skip internal executors (_*, input-conversation, end-conversation, end)
Tests: 8 new tests covering ToolCallArgsMatch, ToolCalledMode.Any, internal executor filtering
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add MeaiEvaluatorAdapter and PerTurnItems edge case tests
- 3 tests for MeaiEvaluatorAdapter: query message forwarding, synthetic
response fallback, multiple items aggregation
- 3 tests for EvalItem.PerTurnItems: empty conversation, no user messages,
system+assistant only
- StubEvaluator and StubChatClient test helpers
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Blocking link check for outdated package in DevUI.
* Replace Dictionary<string, object> payloads with typed wire models
Introduce internal FoundryEvalWireModels.cs with compile-time-safe types
for the OpenAI Evals API wire format. The OpenAI .NET SDK (2.9.1) only
provides protocol-level methods with BinaryContent/ClientResult — no
typed request models. These internal models replace scattered dictionary
literals with [JsonPropertyName]-annotated classes, giving:
- Compile-time safety (typos become build errors)
- Single point of change when the API evolves
- IntelliSense discoverability
- Cleaner serialization via JsonPolymorphic for content items
Models: WireContentItem hierarchy (text, image, tool_call, tool_result),
WireMessage, WireEvalItemPayload, WireTestingCriterion, WireItemSchema,
WireCreateEvalRequest, WireCreateRunRequest, and data source variants.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Skip metric when Foundry returns neither score nor passed
When an evaluator returns no score and no passed value, the previous
code created BooleanMetric(name, false), which falsely failed items
via ItemPassed. Now we skip the MEAI metric entirely for indeterminate
results — the raw data remains available in DetailedItems for diagnostics.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address PR #4914 review comments: fix tool evaluator bug and add tests
- Fix duplicate ToolCallAccuracy: resolve evaluator names before checking
against ToolEvaluators set (Comment 2)
- Make FilterToolEvaluators internal for testability; add tests for the
ArgumentException edge case when all evaluators are tool-type (Comment 3)
- Add CancellationToken test for LocalEvaluator (Comment 4)
- Add EvaluateAsync integration test on Run with sequential workflow and
per-agent SubResults verification (Comment 5)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address Peter's review comments on PR #4914
- Add trailing newline to Evaluation_FoundryQuality.csproj (Comment 6)
- Make evaluator name lookups case-insensitive: switch BuiltinEvaluators,
ToolEvaluators, AgentEvaluators, and ResolveEvaluator's StartsWith check
from Ordinal to OrdinalIgnoreCase (Comment 7)
- Add Trace.TraceWarning when Foundry returns fewer results than submitted
items, indicating expected vs actual count before padding (Comment 8)
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Add Microsoft.Extensions.AI.Evaluation packages to Directory.Packages.props
These were removed in #5269 as unused, but are needed by the Foundry
and core evaluation integration added in this PR.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: alliscode <bentho@microsoft.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* feat: add finish_reason support to AgentResponse and AgentResponseUpdate
Add finish_reason field to AgentResponse and AgentResponseUpdate classes,
propagate it through _process_update() and map_chat_to_agent_update(),
and add comprehensive unit tests.
Fixes#4622
* feat: add finish_reason to AgentResponse and AgentResponseUpdate
* style: add copyright header to test_finish_reason.py
* docs: add finish_reason to AgentResponse and AgentResponseUpdate docstrings
* refactor: move finish_reason tests into test_types.py per review feedback
Move all finish_reason test cases from the separate test_finish_reason.py
file into test_types.py as requested by eavanvalkenburg. Tests are placed
in a new '# region finish_reason' section at the end of the file.
* fix: use model instead of model_id in _process_update
Address PR review feedback from @eavanvalkenburg — ChatResponse and
ChatResponseUpdate both use 'model', not 'model_id'.
* fix: resolve SIM102 lint error in _process_update
Combine nested if statements for AgentResponse finish_reason check
to satisfy ruff SIM102 rule, with line wrapping to stay under 120 chars.
* fix: resolve pyright reportArgumentType in map_chat_to_agent_update
Add type: ignore[arg-type] for FinishReason NewType widening when
passing ChatResponseUpdate.finish_reason to AgentResponseUpdate.
Matches existing patterns in the codebase (40+ similar ignores).
* Fix url_citation annotations dropped in streaming (#5029)
Add url_citation branch to the streaming annotation handler in
_parse_chunk_from_openai, mirroring the existing non-streaming path.
The handler creates an Annotation with type='citation', title, url,
and annotated_regions (TextSpanRegion), wrapped in Content.from_text.
Update test_streaming_annotation_added_with_unknown_type to use a
truly unknown type, and add new tests for url_citation (with and
without url).
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5029: Python: [Bug]: url_citation annotations silently dropped in Foundry streaming (SharePoint grounding citations lost)
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
- Update Anthropic from 12.11.0 to 12.13.0
- Update Anthropic.Foundry from 0.4.2 to 0.5.0
- Change Anthropic project from release candidate to preview
- Add new IBetaService members (Agents, Environments, Sessions, Vaults) to test mock
Fixes#5246
When a custom @executor transforms agent output and sends a plain str,
the downstream AgentExecutor.from_str handler loses the full conversation
context. This adds a with_text() helper that creates a new
AgentExecutorResponse with replaced text while preserving the prior
conversation chain, so AgentExecutor.from_response is invoked instead.
- Add with_text(text) method to AgentExecutorResponse dataclass
- Add 3 regression tests in test_full_conversation.py
Co-authored-by: Evan Mattson <35585003+moonbox3@users.noreply.github.com>
* Improve workflow unit tests
* Update test name prefix for clarity.
* Update tests to surface any errors.
* fix check-point restore-time race in off-thread workflow event stream
* Fixes an intermittent checkpoint-restore race in in-process workflow runs.
The local MCP server can't be used for hosted tools tests because
Anthropic's backend needs to reach the MCP URL from their infrastructure
(not localhost on the CI runner). Revert to learn.microsoft.com/api/mcp
but catch BadRequestError, InternalServerError, APIConnectionError, and
APITimeoutError and pytest.skip so upstream outages don't block the
merge queue.
* Python: use local MCP server for hosted tools test and broaden image assertion
The hosted tools integration test was hitting rate limits on the external
learn.microsoft.com MCP server, causing persistent failures that retries
couldn't recover from. Switch to the local MCP server already spun up in
CI via LOCAL_MCP_URL, skipping when the env var isn't set.
Also broaden the image description assertion to accept common synonyms
(cottage, mansion, villa, etc.) instead of just "house", since the model
legitimately uses varied vocabulary for the same image.
* Address review feedback: validate LOCAL_MCP_URL scheme and use word boundaries
- Skip hosted tools test when LOCAL_MCP_URL lacks http/https scheme,
matching the pattern used in test_mcp.py.
- Use regex word boundaries for image assertion to avoid false matches
like "villain" matching "villa".
The misc-integration job (Anthropic, Ollama, MCP) frequently fails on merge to main when the upstream MCP server (e.g. learn.microsoft.com/api/mcp) returns a transient rate-limit error. The previous 5s retry delay is too short to ride out the upstream backoff window, so all retries fail and the merge queue is blocked. Bumping to 30s gives the upstream a chance to recover before pytest-retry re-runs the test.
* Add agent-framework-gemini package
* Add AGENTS.md documentation
* Add LICENSE file
* Add README.md for agent-framework-gemini package
* Add Google Gemini API keys to .env.example
* Add Google Gemini chat client implementation
* Add tests for GeminiChatClient
* Add Google Gemini agent examples
* Fix client inheritence order
* Update Gemini agent examples
* Update documentation
* Update AGENTS.md
* Add tests for JSON string handling in GeminiChatClient
* Add final response assembly test in GeminiChatClient
* Add tests for handling empty candidates in GeminiChatClient
* Improve Pydantic response handling in GeminiChatClient
* Add tests for function result resolution and callable tool normalization
* Add test for function result resolution when call_id is generated
* Refactor GeminiChatClient to correct inheritance order
Also updates constructor parameter order for environment file handling
* Enhance documentation and clarify Gemini-specific fields
* Update ThinkingConfig with new attributes and type
* Add tests for GoogleSearch and GoogleMaps configs
* Suppress valid-type mypy error on GeminiChatOptionsT
* Move service_url method near overrides
* Order _prepare_config kwargs by base then Gemini-specific
* Use FunctionCallingConfigMode for clarity and type safety
* Fix code_execution doc
* Add agent-framework-gemini to project dependencies
* Remove package from core dependencies
Initial release will be done without agent-framework-gemini in
core[all].
* Move integration tests into one file
* Remove __init__.py file from gemini tests directory
* Introduce RawGeminiChatClient as lightweight chat client
Updated GeminiChatClient to inherit from RawGeminiChatClient, maintaining full functionality with added features.
* Updated variable names from `model_id` to `model`
Across the codebase, including environment variables and client initialization. Adjusted related tests and sample scripts to reflect this change, ensuring consistency in the usage of the Gemini model identifier.
* Update AGENTS.md
* Update Gemini package to alpha status
* Fix docstrings in Gemini tests
* Change 'model_id' to 'model' in response handling
* Fix model property change in response handling
* Add built-in tool factory methods to Gemini client
Replaces boolean tool options (code_execution, google_search_grounding,
google_maps_grounding) with static factory methods that return types.Tool
objects: get_code_interpreter_tool, get_web_search_tool, get_mcp_tool,
get_file_search_tool, and get_maps_grounding_tool.
Simplifies _prepare_tools to a single translation boundary between
FunctionTool (framework) and FunctionDeclaration (Gemini API), with
types.Tool objects passed through unchanged.
* Surface code execution parts
_parse_parts now maps executable_code and code_execution_result
parts to text Content objects so callers can see the code run
and its output. Unknown part types log at debug level rather than
being silently dropped.
* Update Gemini client documentation
* Unify Gemini model name
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Update Agent Framework core version
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Add Python 3.14 in classifiers
* Replace kwargs with parameters in tool factories
* Refactor chat options handling in Gemini client
* Add tests for handling unknown and consumed keys
* Update Gemini documentation
Now reflects new options and built-in tool factory methods
* Change build system to flit
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Fix build system in pyproject.toml
* Fix type checking for generate_content_stream
---------
Co-authored-by: Eduard van Valkenburg <eavanvalkenburg@users.noreply.github.com>
* Python: Skip get_final_response in OTel _finalize_stream when stream errored
When a streaming error occurs, _finalize_stream (a cleanup hook registered by
AgentTelemetryLayer) was unconditionally calling get_final_response(), which
triggers all registered result hooks including after_run context providers.
This caused providers to fire incorrectly on error paths.
Guard against this by checking result_stream._consumed: True only after
StopAsyncIteration (normal completion), False when an exception was raised.
The fix applies to both the chat client and agent telemetry layers.
Closes#5231
* Python: Expose consumed/stream_error on ResponseStream and capture error in OTel span
Address Copilot review feedback on #5232:
- Add `_stream_error: Exception | None` to ResponseStream, set in __anext__'s
except branch so cleanup hooks can inspect the failure.
- Expose public `consumed` and `stream_error` properties to avoid coupling
observability.py to private stream internals.
- Update both _finalize_stream closures (chat and agent layers) to use the
public properties and call capture_exception() with the stream error before
returning early, ensuring the OTel span records the failure rather than
closing silently.
* Python: Address Copilot review feedback on stream error handling
- Use stream_error is not None as the guard in _finalize_stream instead of
not consumed, so the early-return path is keyed precisely to actual errors
rather than any non-normal completion state.
- Clear _stream_error after _run_cleanup_hooks() completes to avoid retaining
the exception traceback (and any large object graphs it references) on the
stream instance beyond the cleanup phase.
* Python: Remove consumed/stream_error properties, use private attrs directly
Per review feedback: since observability.py and _types.py are in the same
package, accessing _stream_error directly is fine and the public properties
are unnecessary.
* Python: Fix Pyright reportPrivateUsage via inline ignore comments
Keep _stream_error private (consistent with rest of ResponseStream), and
suppress reportPrivateUsage at the call sites in observability.py with
inline pyright: ignore comments — access is intentional within the package.
* AG-UI deterministic state updates from tool results
* fix(ag-ui): address PR #5201 review comments
1. Add missing AGUIEventConverter, AGUIHttpService, __version__ to
_IMPORTS in core ag_ui lazy-export list to match the .pyi stub.
2. Coalesce predictive and deterministic state snapshots into a single
StateSnapshotEvent when both mechanisms are active on the same tool
result, reducing redundant snapshot traffic.
3. Update state_update() docstring to clarify that a predictive snapshot
may be emitted before the deterministic one when predict_state_config
is active.
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 HandoffBuilder dropping function-level middleware when cloning agents (#5173)
_clone_chat_agent() was using agent.agent_middleware (agent-level only)
instead of agent.middleware (all types), which silently dropped any
function middleware registered on the original agent.
Changed to use agent.middleware to preserve all middleware types
(agent, function, and chat) during cloning.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Fix HandoffBuilder dropping function-level middleware when cloning agents
Fixes#5173
* Fix false-positive middleware regression test (#5173)
The test used isinstance(m, FunctionMiddleware) which matched
_AutoHandoffMiddleware (always appended during build) instead of the
user's @function_middleware decorator. Assert directly that
tracking_middleware is present in the cloned agent's middleware list.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Address review feedback for #5173: Python: [Bug]: HandoffBuilder drops function-level middleware when cloning agents
---------
Co-authored-by: Copilot <copilot@github.com>
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add allowed_checkpoint_types support to CosmosCheckpointStorage (#5200)
Add allowed_checkpoint_types parameter to CosmosCheckpointStorage for
parity with FileCheckpointStorage. This ensures both providers use the
same restricted pickle deserialization by default.
Changes:
- Accept allowed_checkpoint_types kwarg in __init__, stored as frozenset
- Convert _document_to_checkpoint from @staticmethod to instance method
- Forward allowed_types to decode_checkpoint_value on all load paths
- Update class docstring to describe the new parameter
- Add tests covering built-in safe types, app type opt-in/blocking,
and all load paths (load, list_checkpoints, get_latest)
- Add changelog entry noting the breaking behavior change
BREAKING CHANGE: CosmosCheckpointStorage now uses restricted pickle
deserialization by default. Checkpoints containing application-defined
types will require passing those types via allowed_checkpoint_types.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* Python: Add `allowed_checkpoint_types` support to `CosmosCheckpointStorage` for parity with `FileCheckpointStorage`
Fixes#5200
* Address PR review: add pickle security warning and fix docstring examples
- Reintroduce explicit security warning about pickle deserialization risks
- Convert Example:: block to .. code-block:: python with imports for
consistency with other docstring examples
- Note: PR title should be updated to include [BREAKING] prefix per
changelog convention (comment #3, requires GitHub UI change)
Fixes#5200
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 python-feature-lifecycle skill YAML frontmatter
Remove copyright comment that preceded the YAML frontmatter delimiter,
which prevented the skill from loading. The --- block must be the very
first line of SKILL.md.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* fix: update broken eslint-react plugin links in devui README
The upstream eslint-react repo moved plugins from packages/plugins/
to the top-level plugins/ directory, causing 404 errors detected by
linkspector CI.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* feat: Refactor Handoff Orchestration and add HITL support
* Change HandoffAgentExecutor to use factory-based instantiation
* Extract shared request collection logic in AIAgentUnservicedRequestsCollector
* Refactor HandoffAgentExecutor to use the "ContinueTurn" pattern as in AIAgentHostExecutor
* fix: Remove '$' from exception strings
Rename authored identifiers, XML docs, log messages, and comments
from 'folder' to 'directory' across the file skills codebase for
consistency with the agentskills.io specification and .NET conventions.
Public API changes (experimental):
- ScriptFolders → ScriptDirectories
- ResourceFolders → ResourceDirectories
.NET BCL API calls (Directory.Exists, Path.GetDirectoryName, etc.)
were already using 'directory' and are unchanged.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* support reflection for discovery of resources and scripts in class-based skills
* fix format issues
* refactor samples to use reflection
* Validate resource member signatures during discovery
Add discovery-time validation in AgentClassSkill.DiscoverResources() to
fail fast when [AgentSkillResource] is applied to members with incompatible
signatures:
- Reject indexer properties (getter has parameters)
- Reject methods with parameters other than IServiceProvider or
CancellationToken
Throws InvalidOperationException with actionable error messages instead of
allowing silent runtime failures when ReadAsync invokes the AIFunction with
no named arguments.
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
* prevent duplicates
---------
Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>
Tao Chen
L. Elaine DazzioandGitHub
Kartik MadanandGitHub
Roger BarretoandGitHub
Peter IbekweandGitHub
Dineshsuriya DandGitHub
