From 7e48cc48bc13a5670ac0b15ab5ad69582736d81a Mon Sep 17 00:00:00 2001 From: Aakanksha Duggal Date: Thu, 2 Oct 2025 06:50:32 -0400 Subject: [PATCH] refactor(agents): migrate to OpenAI chat completions API (#3323) --- .../agents/meta_reference/agent_instance.py | 106 +- .../recordings/responses/0002a233aedd.json | 609 ++++ .../recordings/responses/0468a3e1be9f.json | 415 +++ .../recordings/responses/0a8ca6adf364.json | 415 +++ .../recordings/responses/0ac2d8c6c619.json | 592 ++++ .../recordings/responses/1beaba7ed76e.json | 3128 +++++++++++++++++ .../recordings/responses/234cd70ccae2.json | 415 +++ .../recordings/responses/3387f56ccac9.json | 57 + .../recordings/responses/4c651211b0e0.json | 57 + .../recordings/responses/51398b60b155.json | 551 +++ .../recordings/responses/5fe3783b188e.json | 57 + .../recordings/responses/669968ea617e.json | 415 +++ .../recordings/responses/679d1f560e7b.json | 389 ++ .../recordings/responses/72d82d62bca2.json | 237 ++ .../recordings/responses/7d28e973eff5.json | 1513 ++++++++ .../recordings/responses/8e5912c90491.json | 120 + .../recordings/responses/8f000a878ccd.json | 57 + .../recordings/responses/955ac3680d99.json | 389 ++ .../recordings/responses/9cbcd12e26d4.json | 415 +++ .../recordings/responses/9d3896237c12.json | 415 +++ .../recordings/responses/afaacb433b7c.json | 120 + .../recordings/responses/b367f68a8355.json | 120 + .../recordings/responses/b58e35a624b0.json | 57 + .../recordings/responses/ba2761dcee2d.json | 136 + .../recordings/responses/c02a8dfb5458.json | 420 +++ .../recordings/responses/c8cbe86c6dae.json | 57 + .../recordings/responses/ca5e40a262f5.json | 57 + .../recordings/responses/ce7f0b89454f.json | 168 + .../recordings/responses/d68f6c1abf34.json | 389 ++ .../recordings/responses/dd6cc3f2e6ce.json | 125 + .../recordings/responses/ec4853ce509b.json | 120 + .../recordings/responses/f55d47f584e9.json | 120 + 32 files changed, 12226 insertions(+), 15 deletions(-) create mode 100644 tests/integration/recordings/responses/0002a233aedd.json create mode 100644 tests/integration/recordings/responses/0468a3e1be9f.json create mode 100644 tests/integration/recordings/responses/0a8ca6adf364.json create mode 100644 tests/integration/recordings/responses/0ac2d8c6c619.json create mode 100644 tests/integration/recordings/responses/1beaba7ed76e.json create mode 100644 tests/integration/recordings/responses/234cd70ccae2.json create mode 100644 tests/integration/recordings/responses/3387f56ccac9.json create mode 100644 tests/integration/recordings/responses/4c651211b0e0.json create mode 100644 tests/integration/recordings/responses/51398b60b155.json create mode 100644 tests/integration/recordings/responses/5fe3783b188e.json create mode 100644 tests/integration/recordings/responses/669968ea617e.json create mode 100644 tests/integration/recordings/responses/679d1f560e7b.json create mode 100644 tests/integration/recordings/responses/72d82d62bca2.json create mode 100644 tests/integration/recordings/responses/7d28e973eff5.json create mode 100644 tests/integration/recordings/responses/8e5912c90491.json create mode 100644 tests/integration/recordings/responses/8f000a878ccd.json create mode 100644 tests/integration/recordings/responses/955ac3680d99.json create mode 100644 tests/integration/recordings/responses/9cbcd12e26d4.json create mode 100644 tests/integration/recordings/responses/9d3896237c12.json create mode 100644 tests/integration/recordings/responses/afaacb433b7c.json create mode 100644 tests/integration/recordings/responses/b367f68a8355.json create mode 100644 tests/integration/recordings/responses/b58e35a624b0.json create mode 100644 tests/integration/recordings/responses/ba2761dcee2d.json create mode 100644 tests/integration/recordings/responses/c02a8dfb5458.json create mode 100644 tests/integration/recordings/responses/c8cbe86c6dae.json create mode 100644 tests/integration/recordings/responses/ca5e40a262f5.json create mode 100644 tests/integration/recordings/responses/ce7f0b89454f.json create mode 100644 tests/integration/recordings/responses/d68f6c1abf34.json create mode 100644 tests/integration/recordings/responses/dd6cc3f2e6ce.json create mode 100644 tests/integration/recordings/responses/ec4853ce509b.json create mode 100644 tests/integration/recordings/responses/f55d47f584e9.json diff --git a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py index 467777b72..32c59ba2c 100644 --- a/llama_stack/providers/inline/agents/meta_reference/agent_instance.py +++ b/llama_stack/providers/inline/agents/meta_reference/agent_instance.py @@ -50,6 +50,12 @@ from llama_stack.apis.inference import ( CompletionMessage, Inference, Message, + OpenAIAssistantMessageParam, + OpenAIDeveloperMessageParam, + OpenAIMessageParam, + OpenAISystemMessageParam, + OpenAIToolMessageParam, + OpenAIUserMessageParam, SamplingParams, StopReason, SystemMessage, @@ -68,6 +74,11 @@ from llama_stack.models.llama.datatypes import ( BuiltinTool, ToolCall, ) +from llama_stack.providers.utils.inference.openai_compat import ( + convert_message_to_openai_dict_new, + convert_openai_chat_completion_stream, + convert_tooldef_to_openai_tool, +) from llama_stack.providers.utils.kvstore import KVStore from llama_stack.providers.utils.telemetry import tracing @@ -177,12 +188,12 @@ class ChatAgent(ShieldRunnerMixin): return messages async def create_and_execute_turn(self, request: AgentTurnCreateRequest) -> AsyncGenerator: + turn_id = str(uuid.uuid4()) span = tracing.get_current_span() if span: span.set_attribute("session_id", request.session_id) span.set_attribute("agent_id", self.agent_id) span.set_attribute("request", request.model_dump_json()) - turn_id = str(uuid.uuid4()) span.set_attribute("turn_id", turn_id) if self.agent_config.name: span.set_attribute("agent_name", self.agent_config.name) @@ -505,26 +516,93 @@ class ChatAgent(ShieldRunnerMixin): tool_calls = [] content = "" - stop_reason = None + stop_reason: StopReason | None = None async with tracing.span("inference") as span: if self.agent_config.name: span.set_attribute("agent_name", self.agent_config.name) - async for chunk in await self.inference_api.chat_completion( - self.agent_config.model, - input_messages, - tools=self.tool_defs, - tool_prompt_format=self.agent_config.tool_config.tool_prompt_format, + + def _serialize_nested(value): + """Recursively serialize nested Pydantic models to dicts.""" + from pydantic import BaseModel + + if isinstance(value, BaseModel): + return value.model_dump(mode="json") + elif isinstance(value, dict): + return {k: _serialize_nested(v) for k, v in value.items()} + elif isinstance(value, list): + return [_serialize_nested(item) for item in value] + else: + return value + + def _add_type(openai_msg: dict) -> OpenAIMessageParam: + # Serialize any nested Pydantic models to plain dicts + openai_msg = _serialize_nested(openai_msg) + + role = openai_msg.get("role") + if role == "user": + return OpenAIUserMessageParam(**openai_msg) + elif role == "system": + return OpenAISystemMessageParam(**openai_msg) + elif role == "assistant": + return OpenAIAssistantMessageParam(**openai_msg) + elif role == "tool": + return OpenAIToolMessageParam(**openai_msg) + elif role == "developer": + return OpenAIDeveloperMessageParam(**openai_msg) + else: + raise ValueError(f"Unknown message role: {role}") + + # Convert messages to OpenAI format + openai_messages: list[OpenAIMessageParam] = [ + _add_type(await convert_message_to_openai_dict_new(message)) for message in input_messages + ] + + # Convert tool definitions to OpenAI format + openai_tools = [convert_tooldef_to_openai_tool(x) for x in (self.tool_defs or [])] + + # Extract tool_choice from tool_config for OpenAI compatibility + # Note: tool_choice can only be provided when tools are also provided + tool_choice = None + if openai_tools and self.agent_config.tool_config and self.agent_config.tool_config.tool_choice: + tc = self.agent_config.tool_config.tool_choice + tool_choice_str = tc.value if hasattr(tc, "value") else str(tc) + # Convert tool_choice to OpenAI format + if tool_choice_str in ("auto", "none", "required"): + tool_choice = tool_choice_str + else: + # It's a specific tool name, wrap it in the proper format + tool_choice = {"type": "function", "function": {"name": tool_choice_str}} + + # Convert sampling params to OpenAI format (temperature, top_p, max_tokens) + temperature = getattr(getattr(sampling_params, "strategy", None), "temperature", None) + top_p = getattr(getattr(sampling_params, "strategy", None), "top_p", None) + max_tokens = getattr(sampling_params, "max_tokens", None) + + # Use OpenAI chat completion + openai_stream = await self.inference_api.openai_chat_completion( + model=self.agent_config.model, + messages=openai_messages, + tools=openai_tools if openai_tools else None, + tool_choice=tool_choice, response_format=self.agent_config.response_format, + temperature=temperature, + top_p=top_p, + max_tokens=max_tokens, stream=True, - sampling_params=sampling_params, - tool_config=self.agent_config.tool_config, - ): + ) + + # Convert OpenAI stream back to Llama Stack format + response_stream = convert_openai_chat_completion_stream( + openai_stream, enable_incremental_tool_calls=True + ) + + async for chunk in response_stream: event = chunk.event if event.event_type == ChatCompletionResponseEventType.start: continue elif event.event_type == ChatCompletionResponseEventType.complete: - stop_reason = StopReason.end_of_turn + stop_reason = event.stop_reason or StopReason.end_of_turn continue delta = event.delta @@ -533,7 +611,7 @@ class ChatAgent(ShieldRunnerMixin): tool_calls.append(delta.tool_call) elif delta.parse_status == ToolCallParseStatus.failed: # If we cannot parse the tools, set the content to the unparsed raw text - content = delta.tool_call + content = 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