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feat: add Prompts API to Responses API

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r3v5 2025-09-21 13:52:55 +01:00
parent 9f6c658f2a
commit bdc16ea392
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15 changed files with 526 additions and 4 deletions
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4
llama_stack/apis/agents/agents.py
View file

@ -38,6 +38,7 @@ from .openai_responses import (
OpenAIResponseInputTool,
OpenAIResponseObject,
OpenAIResponseObjectStream,
OpenAIResponsePromptParam,
OpenAIResponseText,
)
@ -796,6 +797,7 @@ class Agents(Protocol):
self,
input: str | list[OpenAIResponseInput],
model: str,
prompt: OpenAIResponsePromptParam | None = None,
instructions: str | None = None,
previous_response_id: str | None = None,
store: bool | None = True,
@ -807,9 +809,9 @@ class Agents(Protocol):
max_infer_iters: int | None = 10, # this is an extension to the OpenAI API
) -> OpenAIResponseObject | AsyncIterator[OpenAIResponseObjectStream]:
"""Create a new OpenAI response.
:param input: Input message(s) to create the response.
:param model: The underlying LLM used for completions.
:param prompt: Prompt object with ID, version, and variables.
:param previous_response_id: (Optional) if specified, the new response will be a continuation of the previous response. This can be used to easily fork-off new responses from existing responses.
:param include: (Optional) Additional fields to include in the response.
:returns: An OpenAIResponseObject.

17
llama_stack/apis/agents/openai_responses.py
View file

@ -9,6 +9,7 @@ from typing import Annotated, Any, Literal
from pydantic import BaseModel, Field
from typing_extensions import TypedDict
from llama_stack.apis.prompts.prompts import Prompt
from llama_stack.apis.vector_io import SearchRankingOptions as FileSearchRankingOptions
from llama_stack.schema_utils import json_schema_type, register_schema
@ -336,6 +337,20 @@ class OpenAIResponseTextFormat(TypedDict, total=False):
strict: bool | None
@json_schema_type
class OpenAIResponsePromptParam(BaseModel):
"""Prompt object that is used for OpenAI responses.
:param id: Unique identifier of the prompt template
:param variables: Dictionary of variable names to values for template substitution
:param version: Version number of the prompt to use (defaults to latest if not specified)
"""
id: str
variables: dict[str, Any] | None = None
version: str | None = None
@json_schema_type
class OpenAIResponseText(BaseModel):
"""Text response configuration for OpenAI responses.
@ -357,6 +372,7 @@ class OpenAIResponseObject(BaseModel):
:param object: Object type identifier, always "response"
:param output: List of generated output items (messages, tool calls, etc.)
:param parallel_tool_calls: Whether tool calls can be executed in parallel
:param prompt: (Optional) Prompt object with ID, version, and variables
:param previous_response_id: (Optional) ID of the previous response in a conversation
:param status: Current status of the response generation
:param temperature: (Optional) Sampling temperature used for generation
@ -373,6 +389,7 @@ class OpenAIResponseObject(BaseModel):
output: list[OpenAIResponseOutput]
parallel_tool_calls: bool = False
previous_response_id: str | None = None
prompt: Prompt | None = None
status: str
temperature: float | None = None
# Default to text format to avoid breaking the loading of old responses

4
llama_stack/core/stack.py
View file

@ -321,6 +321,10 @@ def add_internal_implementations(impls: dict[Api, Any], run_config: StackRunConf
)
impls[Api.conversations] = conversations_impl
# Set prompts API on agents provider if it exists
if Api.agents in impls and hasattr(impls[Api.agents], "set_prompts_api"):
impls[Api.agents].set_prompts_api(prompts_impl)
class Stack:
def __init__(self, run_config: StackRunConfig, provider_registry: ProviderRegistry | None = None):

1
llama_stack/providers/inline/agents/meta_reference/__init__.py
View file

@ -21,6 +21,7 @@ async def get_provider_impl(config: MetaReferenceAgentsImplConfig, deps: dict[Ap
deps[Api.safety],
deps[Api.tool_runtime],
deps[Api.tool_groups],
None, # prompts_api will be set later when available
policy,
)
await impl.initialize()

13
llama_stack/providers/inline/agents/meta_reference/agents.py
View file

@ -28,7 +28,7 @@ from llama_stack.apis.agents import (
Session,
Turn,
)
from llama_stack.apis.agents.openai_responses import OpenAIResponseText
from llama_stack.apis.agents.openai_responses import OpenAIResponsePromptParam, OpenAIResponseText
from llama_stack.apis.common.responses import PaginatedResponse
from llama_stack.apis.inference import (
Inference,
@ -37,6 +37,7 @@ from llama_stack.apis.inference import (
ToolResponseMessage,
UserMessage,
)
from llama_stack.apis.prompts import Prompts
from llama_stack.apis.safety import Safety
from llama_stack.apis.tools import ToolGroups, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
@ -63,6 +64,7 @@ class MetaReferenceAgentsImpl(Agents):
safety_api: Safety,
tool_runtime_api: ToolRuntime,
tool_groups_api: ToolGroups,
prompts_api: Prompts | None,
policy: list[AccessRule],
):
self.config = config
@ -71,6 +73,7 @@ class MetaReferenceAgentsImpl(Agents):
self.safety_api = safety_api
self.tool_runtime_api = tool_runtime_api
self.tool_groups_api = tool_groups_api
self.prompts_api = prompts_api
self.in_memory_store = InmemoryKVStoreImpl()
self.openai_responses_impl: OpenAIResponsesImpl | None = None
@ -86,8 +89,14 @@ class MetaReferenceAgentsImpl(Agents):
tool_runtime_api=self.tool_runtime_api,
responses_store=self.responses_store,
vector_io_api=self.vector_io_api,
prompts_api=self.prompts_api,
)
def set_prompts_api(self, prompts_api: Prompts) -> None:
self.prompts_api = prompts_api
if hasattr(self, "openai_responses_impl") and self.openai_responses_impl:
self.openai_responses_impl.prompts_api = prompts_api
async def create_agent(
self,
agent_config: AgentConfig,
@ -320,6 +329,7 @@ class MetaReferenceAgentsImpl(Agents):
self,
input: str | list[OpenAIResponseInput],
model: str,
prompt: OpenAIResponsePromptParam | None = None,
instructions: str | None = None,
previous_response_id: str | None = None,
store: bool | None = True,
@ -333,6 +343,7 @@ class MetaReferenceAgentsImpl(Agents):
return await self.openai_responses_impl.create_openai_response(
input,
model,
prompt,
instructions,
previous_response_id,
store,

48
llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py
View file

@ -21,6 +21,7 @@ from llama_stack.apis.agents.openai_responses import (
OpenAIResponseMessage,
OpenAIResponseObject,
OpenAIResponseObjectStream,
OpenAIResponsePromptParam,
OpenAIResponseText,
OpenAIResponseTextFormat,
)
@ -29,6 +30,8 @@ from llama_stack.apis.inference import (
OpenAIMessageParam,
OpenAISystemMessageParam,
)
from llama_stack.apis.prompts import Prompts
from llama_stack.apis.prompts.prompts import Prompt
from llama_stack.apis.tools import ToolGroups, ToolRuntime
from llama_stack.apis.vector_io import VectorIO
from llama_stack.log import get_logger
@ -61,12 +64,14 @@ class OpenAIResponsesImpl:
tool_runtime_api: ToolRuntime,
responses_store: ResponsesStore,
vector_io_api: VectorIO, # VectorIO
prompts_api: Prompts,
):
self.inference_api = inference_api
self.tool_groups_api = tool_groups_api
self.tool_runtime_api = tool_runtime_api
self.responses_store = responses_store
self.vector_io_api = vector_io_api
self.prompts_api = prompts_api
self.tool_executor = ToolExecutor(
tool_groups_api=tool_groups_api,
tool_runtime_api=tool_runtime_api,
@ -123,6 +128,41 @@ class OpenAIResponsesImpl:
if instructions:
messages.insert(0, OpenAISystemMessageParam(content=instructions))
async def _prepend_prompt(
self, messages: list[OpenAIMessageParam], prompt_params: OpenAIResponsePromptParam
) -> Prompt:
if not prompt_params or not prompt_params.id:
return None
try:
# Check if prompt exists in Llama Stack and retrieve it
prompt_version = int(prompt_params.version) if prompt_params.version else None
cur_prompt = await self.prompts_api.get_prompt(prompt_params.id, prompt_version)
if cur_prompt and cur_prompt.prompt:
cur_prompt_text = cur_prompt.prompt
cur_prompt_variables = cur_prompt.variables
final_prompt_text = cur_prompt_text
if prompt_params.variables:
# check if the variables are valid
for name in prompt_params.variables.keys():
if name not in cur_prompt_variables:
raise ValueError(f"Variable {name} not found in prompt {prompt_params.id}")
# replace the variables in the prompt text
for name, value in prompt_params.variables.items():
final_prompt_text = final_prompt_text.replace(f"{{{{ {name} }}}}", str(value))
messages.insert(0, OpenAISystemMessageParam(content=final_prompt_text))
logger.info(f"Prompt {prompt_params.id} found and applied\nFinal prompt text: {final_prompt_text}")
return cur_prompt
except ValueError:
logger.warning(
f"Prompt {prompt_params.id} with version {prompt_params.version} not found, skipping prompt prepending"
)
return None
async def get_openai_response(
self,
response_id: str,
@ -199,6 +239,7 @@ class OpenAIResponsesImpl:
self,
input: str | list[OpenAIResponseInput],
model: str,
prompt: OpenAIResponsePromptParam | None = None,
instructions: str | None = None,
previous_response_id: str | None = None,
store: bool | None = True,
@ -215,6 +256,7 @@ class OpenAIResponsesImpl:
stream_gen = self._create_streaming_response(
input=input,
model=model,
prompt=prompt,
instructions=instructions,
previous_response_id=previous_response_id,
store=store,
@ -243,6 +285,7 @@ class OpenAIResponsesImpl:
self,
input: str | list[OpenAIResponseInput],
model: str,
prompt: OpenAIResponsePromptParam | None = None,
instructions: str | None = None,
previous_response_id: str | None = None,
store: bool | None = True,
@ -253,6 +296,10 @@ class OpenAIResponsesImpl:
) -> AsyncIterator[OpenAIResponseObjectStream]:
# Input preprocessing
all_input, messages = await self._process_input_with_previous_response(input, previous_response_id)
# Prepend reusable prompt (if provided)
prompt_obj = await self._prepend_prompt(messages, prompt)
await self._prepend_instructions(messages, instructions)
# Structured outputs
@ -276,6 +323,7 @@ class OpenAIResponsesImpl:
ctx=ctx,
response_id=response_id,
created_at=created_at,
prompt=prompt_obj,
text=text,
max_infer_iters=max_infer_iters,
tool_executor=self.tool_executor,

5
llama_stack/providers/inline/agents/meta_reference/responses/streaming.py
View file

@ -45,6 +45,7 @@ from llama_stack.apis.inference import (
OpenAIChoice,
OpenAIMessageParam,
)
from llama_stack.apis.prompts.prompts import Prompt
from llama_stack.log import get_logger
from .types import ChatCompletionContext, ChatCompletionResult
@ -81,6 +82,7 @@ class StreamingResponseOrchestrator:
ctx: ChatCompletionContext,
response_id: str,
created_at: int,
prompt: Prompt | None,
text: OpenAIResponseText,
max_infer_iters: int,
tool_executor, # Will be the tool execution logic from the main class
@ -89,6 +91,7 @@ class StreamingResponseOrchestrator:
self.ctx = ctx
self.response_id = response_id
self.created_at = created_at
self.prompt = prompt
self.text = text
self.max_infer_iters = max_infer_iters
self.tool_executor = tool_executor
@ -109,6 +112,7 @@ class StreamingResponseOrchestrator:
object="response",
status="in_progress",
output=output_messages.copy(),
prompt=self.prompt,
text=self.text,
)
@ -195,6 +199,7 @@ class StreamingResponseOrchestrator:
model=self.ctx.model,
object="response",
status="completed",
prompt=self.prompt,
text=self.text,
output=output_messages,
)