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95
docs/static/deprecated-llama-stack-spec.html vendored
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@ -9056,6 +9056,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"
@ -9521,6 +9525,44 @@
"title": "OpenAIResponseText",
"description": "Text response configuration for OpenAI responses."
},
"Prompt": {
"type": "object",
"properties": {
"prompt": {
"type": "string",
"description": "The system prompt text with variable placeholders. Variables are only supported when using the Responses API."
},
"version": {
"type": "integer",
"description": "Version (integer starting at 1, incremented on save)"
},
"prompt_id": {
"type": "string",
"description": "Unique identifier formatted as 'pmpt_<48-digit-hash>'"
},
"variables": {
"type": "array",
"items": {
"type": "string"
},
"description": "List of prompt variable names that can be used in the prompt template"
},
"is_default": {
"type": "boolean",
"default": false,
"description": "Boolean indicating whether this version is the default version for this prompt"
}
},
"additionalProperties": false,
"required": [
"version",
"prompt_id",
"variables",
"is_default"
],
"title": "Prompt",
"description": "A prompt resource representing a stored OpenAI Compatible prompt template in Llama Stack."
},
"OpenAIResponseInputTool": {
"oneOf": [
{
@ -9824,6 +9866,51 @@
"title": "OpenAIResponseInputToolWebSearch",
"description": "Web search tool configuration for OpenAI response inputs."
},
"OpenAIResponsePromptParam": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier of the prompt template"
},
"variables": {
"type": "object",
"additionalProperties": {
"oneOf": [
{
"type": "null"
},
{
"type": "boolean"
},
{
"type": "number"
},
{
"type": "string"
},
{
"type": "array"
},
{
"type": "object"
}
]
},
"description": "Dictionary of variable names to values for template substitution"
},
"version": {
"type": "string",
"description": "Version number of the prompt to use (defaults to latest if not specified)"
}
},
"additionalProperties": false,
"required": [
"id"
],
"title": "OpenAIResponsePromptParam",
"description": "Prompt object that is used for OpenAI responses."
},
"CreateOpenaiResponseRequest": {
"type": "object",
"properties": {
@ -9845,6 +9932,10 @@
"type": "string",
"description": "The underlying LLM used for completions."
},
"prompt": {
"$ref": "#/components/schemas/OpenAIResponsePromptParam",
"description": "Prompt object with ID, version, and variables."
},
"instructions": {
"type": "string"
},
@ -9929,6 +10020,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"

78
docs/static/deprecated-llama-stack-spec.yaml vendored
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@ -6708,6 +6708,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-
@ -7076,6 +7080,44 @@ components:
title: OpenAIResponseText
description: >-
Text response configuration for OpenAI responses.
Prompt:
type: object
properties:
prompt:
type: string
description: >-
The system prompt text with variable placeholders. Variables are only
supported when using the Responses API.
version:
type: integer
description: >-
Version (integer starting at 1, incremented on save)
prompt_id:
type: string
description: >-
Unique identifier formatted as 'pmpt_<48-digit-hash>'
variables:
type: array
items:
type: string
description: >-
List of prompt variable names that can be used in the prompt template
is_default:
type: boolean
default: false
description: >-
Boolean indicating whether this version is the default version for this
prompt
additionalProperties: false
required:
- version
- prompt_id
- variables
- is_default
title: Prompt
description: >-
A prompt resource representing a stored OpenAI Compatible prompt template
in Llama Stack.
OpenAIResponseInputTool:
oneOf:
- $ref: '#/components/schemas/OpenAIResponseInputToolWebSearch'
@ -7286,6 +7328,34 @@ components:
title: OpenAIResponseInputToolWebSearch
description: >-
Web search tool configuration for OpenAI response inputs.
OpenAIResponsePromptParam:
type: object
properties:
id:
type: string
description: Unique identifier of the prompt template
variables:
type: object
additionalProperties:
oneOf:
- type: 'null'
- type: boolean
- type: number
- type: string
- type: array
- type: object
description: >-
Dictionary of variable names to values for template substitution
version:
type: string
description: >-
Version number of the prompt to use (defaults to latest if not specified)
additionalProperties: false
required:
- id
title: OpenAIResponsePromptParam
description: >-
Prompt object that is used for OpenAI responses.
CreateOpenaiResponseRequest:
type: object
properties:
@ -7299,6 +7369,10 @@ components:
model:
type: string
description: The underlying LLM used for completions.
prompt:
$ref: '#/components/schemas/OpenAIResponsePromptParam'
description: >-
Prompt object with ID, version, and variables.
instructions:
type: string
previous_response_id:
@ -7370,6 +7444,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-

57
docs/static/llama-stack-spec.html vendored
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@ -7463,6 +7463,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"
@ -7919,6 +7923,51 @@
"title": "OpenAIResponseInputToolWebSearch",
"description": "Web search tool configuration for OpenAI response inputs."
},
"OpenAIResponsePromptParam": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier of the prompt template"
},
"variables": {
"type": "object",
"additionalProperties": {
"oneOf": [
{
"type": "null"
},
{
"type": "boolean"
},
{
"type": "number"
},
{
"type": "string"
},
{
"type": "array"
},
{
"type": "object"
}
]
},
"description": "Dictionary of variable names to values for template substitution"
},
"version": {
"type": "string",
"description": "Version number of the prompt to use (defaults to latest if not specified)"
}
},
"additionalProperties": false,
"required": [
"id"
],
"title": "OpenAIResponsePromptParam",
"description": "Prompt object that is used for OpenAI responses."
},
"CreateOpenaiResponseRequest": {
"type": "object",
"properties": {
@ -7940,6 +7989,10 @@
"type": "string",
"description": "The underlying LLM used for completions."
},
"prompt": {
"$ref": "#/components/schemas/OpenAIResponsePromptParam",
"description": "Prompt object with ID, version, and variables."
},
"instructions": {
"type": "string"
},
@ -8024,6 +8077,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"

40
docs/static/llama-stack-spec.yaml vendored
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@ -5628,6 +5628,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-
@ -5949,6 +5953,34 @@ components:
title: OpenAIResponseInputToolWebSearch
description: >-
Web search tool configuration for OpenAI response inputs.
OpenAIResponsePromptParam:
type: object
properties:
id:
type: string
description: Unique identifier of the prompt template
variables:
type: object
additionalProperties:
oneOf:
- type: 'null'
- type: boolean
- type: number
- type: string
- type: array
- type: object
description: >-
Dictionary of variable names to values for template substitution
version:
type: string
description: >-
Version number of the prompt to use (defaults to latest if not specified)
additionalProperties: false
required:
- id
title: OpenAIResponsePromptParam
description: >-
Prompt object that is used for OpenAI responses.
CreateOpenaiResponseRequest:
type: object
properties:
@ -5962,6 +5994,10 @@ components:
model:
type: string
description: The underlying LLM used for completions.
prompt:
$ref: '#/components/schemas/OpenAIResponsePromptParam'
description: >-
Prompt object with ID, version, and variables.
instructions:
type: string
previous_response_id:
@ -6033,6 +6069,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-

57
docs/static/stainless-llama-stack-spec.html vendored
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@ -9472,6 +9472,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"
@ -9928,6 +9932,51 @@
"title": "OpenAIResponseInputToolWebSearch",
"description": "Web search tool configuration for OpenAI response inputs."
},
"OpenAIResponsePromptParam": {
"type": "object",
"properties": {
"id": {
"type": "string",
"description": "Unique identifier of the prompt template"
},
"variables": {
"type": "object",
"additionalProperties": {
"oneOf": [
{
"type": "null"
},
{
"type": "boolean"
},
{
"type": "number"
},
{
"type": "string"
},
{
"type": "array"
},
{
"type": "object"
}
]
},
"description": "Dictionary of variable names to values for template substitution"
},
"version": {
"type": "string",
"description": "Version number of the prompt to use (defaults to latest if not specified)"
}
},
"additionalProperties": false,
"required": [
"id"
],
"title": "OpenAIResponsePromptParam",
"description": "Prompt object that is used for OpenAI responses."
},
"CreateOpenaiResponseRequest": {
"type": "object",
"properties": {
@ -9949,6 +9998,10 @@
"type": "string",
"description": "The underlying LLM used for completions."
},
"prompt": {
"$ref": "#/components/schemas/OpenAIResponsePromptParam",
"description": "Prompt object with ID, version, and variables."
},
"instructions": {
"type": "string"
},
@ -10033,6 +10086,10 @@
"type": "string",
"description": "(Optional) ID of the previous response in a conversation"
},
"prompt": {
"$ref": "#/components/schemas/Prompt",
"description": "(Optional) Prompt object with ID, version, and variables"
},
"status": {
"type": "string",
"description": "Current status of the response generation"

40
docs/static/stainless-llama-stack-spec.yaml vendored
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@ -7073,6 +7073,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-
@ -7394,6 +7398,34 @@ components:
title: OpenAIResponseInputToolWebSearch
description: >-
Web search tool configuration for OpenAI response inputs.
OpenAIResponsePromptParam:
type: object
properties:
id:
type: string
description: Unique identifier of the prompt template
variables:
type: object
additionalProperties:
oneOf:
- type: 'null'
- type: boolean
- type: number
- type: string
- type: array
- type: object
description: >-
Dictionary of variable names to values for template substitution
version:
type: string
description: >-
Version number of the prompt to use (defaults to latest if not specified)
additionalProperties: false
required:
- id
title: OpenAIResponsePromptParam
description: >-
Prompt object that is used for OpenAI responses.
CreateOpenaiResponseRequest:
type: object
properties:
@ -7407,6 +7439,10 @@ components:
model:
type: string
description: The underlying LLM used for completions.
prompt:
$ref: '#/components/schemas/OpenAIResponsePromptParam'
description: >-
Prompt object with ID, version, and variables.
instructions:
type: string
previous_response_id:
@ -7478,6 +7514,10 @@ components:
type: string
description: >-
(Optional) ID of the previous response in a conversation
prompt:
$ref: '#/components/schemas/Prompt'
description: >-
(Optional) Prompt object with ID, version, and variables
status:
type: string
description: >-

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,
)

3
tests/unit/providers/agent/test_meta_reference_agent.py
View file

@ -59,7 +59,8 @@ async def agents_impl(config, mock_apis):
mock_apis["safety_api"],
mock_apis["tool_runtime_api"],
mock_apis["tool_groups_api"],
{},
None, # prompts_api (will be set later via set_prompts_api if needed)
[], # policy (empty list for tests)
)
await impl.initialize()
yield impl

68
tests/unit/providers/agents/meta_reference/test_openai_responses.py
View file

@ -38,6 +38,7 @@ from llama_stack.apis.inference import (
OpenAIResponseFormatJSONSchema,
OpenAIUserMessageParam,
)
from llama_stack.apis.prompts import Prompt
from llama_stack.apis.tools.tools import ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
from llama_stack.core.access_control.access_control import default_policy
from llama_stack.core.datatypes import ResponsesStoreConfig
@ -82,9 +83,20 @@ def mock_vector_io_api():
return vector_io_api
@pytest.fixture
def mock_prompts_api():
prompts_api = AsyncMock()
return prompts_api
@pytest.fixture
def openai_responses_impl(
mock_inference_api, mock_tool_groups_api, mock_tool_runtime_api, mock_responses_store, mock_vector_io_api
mock_inference_api,
mock_tool_groups_api,
mock_tool_runtime_api,
mock_responses_store,
mock_vector_io_api,
mock_prompts_api,
):
return OpenAIResponsesImpl(
inference_api=mock_inference_api,
@ -92,6 +104,7 @@ def openai_responses_impl(
tool_runtime_api=mock_tool_runtime_api,
responses_store=mock_responses_store,
vector_io_api=mock_vector_io_api,
prompts_api=mock_prompts_api,
)
@ -1004,3 +1017,56 @@ async def test_create_openai_response_with_invalid_text_format(openai_responses_
model=model,
text=OpenAIResponseText(format={"type": "invalid"}),
)
async def test_create_openai_response_with_prompt(openai_responses_impl, mock_inference_api, mock_prompts_api):
"""Test creating an OpenAI response with a prompt."""
input_text = "What is the capital of Ireland?"
model = "meta-llama/Llama-3.1-8B-Instruct"
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
prompt = Prompt(
prompt="You are a helpful {{ area_name }} assistant at {{ company_name }}. Always provide accurate information.",
prompt_id=prompt_id,
version=1,
variables=["area_name", "company_name"],
is_default=True,
)
from llama_stack.apis.agents.openai_responses import OpenAIResponsePromptParam
prompt_params_with_version_1 = OpenAIResponsePromptParam(
id=prompt_id, version="1", variables={"area_name": "geography", "company_name": "Dummy Company"}
)
mock_prompts_api.get_prompt.return_value = prompt
mock_inference_api.openai_chat_completion.return_value = fake_stream()
result = await openai_responses_impl.create_openai_response(
input=input_text,
model=model,
prompt=prompt_params_with_version_1,
)
mock_prompts_api.get_prompt.assert_called_with(prompt_id, 1)
mock_inference_api.openai_chat_completion.assert_called()
call_args = mock_inference_api.openai_chat_completion.call_args
sent_messages = call_args.kwargs["messages"]
assert len(sent_messages) == 2
system_messages = [msg for msg in sent_messages if msg.role == "system"]
assert len(system_messages) == 1
assert (
system_messages[0].content
== "You are a helpful geography assistant at Dummy Company. Always provide accurate information."
)
user_messages = [msg for msg in sent_messages if msg.role == "user"]
assert len(user_messages) == 1
assert user_messages[0].content == input_text
assert result.model == model
assert result.status == "completed"
assert result.prompt.prompt_id == prompt_id
assert result.prompt.variables == ["area_name", "company_name"]
assert result.prompt.version == 1
assert result.prompt.prompt == prompt.prompt