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fold openai responses into the Agents API

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Ashwin Bharambe 2025-04-28 10:27:28 -07:00
parent 207224a811
commit abd6280cb8
25 changed files with 967 additions and 199 deletions
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512
docs/_static/llama-stack-spec.html vendored
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@ -497,6 +497,54 @@
}
}
},
"/v1/openai/v1/responses": {
"post": {
"responses": {
"200": {
"description": "Runtime representation of an annotated type.",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAIResponseObject"
}
},
"text/event-stream": {
"schema": {
"$ref": "#/components/schemas/OpenAIResponseObjectStream"
}
}
}
},
"400": {
"$ref": "#/components/responses/BadRequest400"
},
"429": {
"$ref": "#/components/responses/TooManyRequests429"
},
"500": {
"$ref": "#/components/responses/InternalServerError500"
},
"default": {
"$ref": "#/components/responses/DefaultError"
}
},
"tags": [
"Agents"
],
"description": "Create a new OpenAI response.",
"parameters": [],
"requestBody": {
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/CreateOpenaiResponseRequest"
}
}
},
"required": true
}
}
},
"/v1/files": {
"get": {
"responses": {
@ -1278,6 +1326,49 @@
]
}
},
"/v1/openai/v1/responses/{id}": {
"get": {
"responses": {
"200": {
"description": "An OpenAIResponseObject.",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/OpenAIResponseObject"
}
}
}
},
"400": {
"$ref": "#/components/responses/BadRequest400"
},
"429": {
"$ref": "#/components/responses/TooManyRequests429"
},
"500": {
"$ref": "#/components/responses/InternalServerError500"
},
"default": {
"$ref": "#/components/responses/DefaultError"
}
},
"tags": [
"Agents"
],
"description": "Retrieve an OpenAI response by its ID.",
"parameters": [
{
"name": "id",
"in": "path",
"description": "The ID of the OpenAI response to retrieve.",
"required": true,
"schema": {
"type": "string"
}
}
]
}
},
"/v1/scoring-functions/{scoring_fn_id}": {
"get": {
"responses": {
@ -6192,6 +6283,427 @@
],
"title": "AgentTurnResponseTurnStartPayload"
},
"OpenAIResponseInputMessage": {
"type": "object",
"properties": {
"content": {
"oneOf": [
{
"type": "string"
},
{
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIResponseInputMessageContent"
}
}
]
},
"role": {
"oneOf": [
{
"type": "string",
"const": "system"
},
{
"type": "string",
"const": "developer"
},
{
"type": "string",
"const": "user"
},
{
"type": "string",
"const": "assistant"
}
]
},
"type": {
"type": "string",
"const": "message",
"default": "message"
}
},
"additionalProperties": false,
"required": [
"content",
"role"
],
"title": "OpenAIResponseInputMessage"
},
"OpenAIResponseInputMessageContent": {
"oneOf": [
{
"$ref": "#/components/schemas/OpenAIResponseInputMessageContentText"
},
{
"$ref": "#/components/schemas/OpenAIResponseInputMessageContentImage"
}
],
"discriminator": {
"propertyName": "type",
"mapping": {
"input_text": "#/components/schemas/OpenAIResponseInputMessageContentText",
"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage"
}
}
},
"OpenAIResponseInputMessageContentImage": {
"type": "object",
"properties": {
"detail": {
"oneOf": [
{
"type": "string",
"const": "low"
},
{
"type": "string",
"const": "high"
},
{
"type": "string",
"const": "auto"
}
],
"default": "auto"
},
"type": {
"type": "string",
"const": "input_image",
"default": "input_image"
},
"image_url": {
"type": "string"
}
},
"additionalProperties": false,
"required": [
"detail",
"type"
],
"title": "OpenAIResponseInputMessageContentImage"
},
"OpenAIResponseInputMessageContentText": {
"type": "object",
"properties": {
"text": {
"type": "string"
},
"type": {
"type": "string",
"const": "input_text",
"default": "input_text"
}
},
"additionalProperties": false,
"required": [
"text",
"type"
],
"title": "OpenAIResponseInputMessageContentText"
},
"OpenAIResponseInputTool": {
"type": "object",
"properties": {
"type": {
"oneOf": [
{
"type": "string",
"const": "web_search"
},
{
"type": "string",
"const": "web_search_preview_2025_03_11"
}
],
"default": "web_search"
},
"search_context_size": {
"type": "string",
"default": "medium"
}
},
"additionalProperties": false,
"required": [
"type"
],
"title": "OpenAIResponseInputToolWebSearch"
},
"CreateOpenaiResponseRequest": {
"type": "object",
"properties": {
"input": {
"oneOf": [
{
"type": "string"
},
{
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIResponseInputMessage"
}
}
],
"description": "Input message(s) to create the response."
},
"model": {
"type": "string",
"description": "The underlying LLM used for completions."
},
"previous_response_id": {
"type": "string",
"description": "(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."
},
"store": {
"type": "boolean"
},
"stream": {
"type": "boolean"
},
"tools": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIResponseInputTool"
}
}
},
"additionalProperties": false,
"required": [
"input",
"model"
],
"title": "CreateOpenaiResponseRequest"
},
"OpenAIResponseError": {
"type": "object",
"properties": {
"code": {
"type": "string"
},
"message": {
"type": "string"
}
},
"additionalProperties": false,
"required": [
"code",
"message"
],
"title": "OpenAIResponseError"
},
"OpenAIResponseObject": {
"type": "object",
"properties": {
"created_at": {
"type": "integer"
},
"error": {
"$ref": "#/components/schemas/OpenAIResponseError"
},
"id": {
"type": "string"
},
"model": {
"type": "string"
},
"object": {
"type": "string",
"const": "response",
"default": "response"
},
"output": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIResponseOutput"
}
},
"parallel_tool_calls": {
"type": "boolean",
"default": false
},
"previous_response_id": {
"type": "string"
},
"status": {
"type": "string"
},
"temperature": {
"type": "number"
},
"top_p": {
"type": "number"
},
"truncation": {
"type": "string"
},
"user": {
"type": "string"
}
},
"additionalProperties": false,
"required": [
"created_at",
"id",
"model",
"object",
"output",
"parallel_tool_calls",
"status"
],
"title": "OpenAIResponseObject"
},
"OpenAIResponseOutput": {
"oneOf": [
{
"$ref": "#/components/schemas/OpenAIResponseOutputMessage"
},
{
"$ref": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall"
}
],
"discriminator": {
"propertyName": "type",
"mapping": {
"message": "#/components/schemas/OpenAIResponseOutputMessage",
"web_search_call": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall"
}
}
},
"OpenAIResponseOutputMessage": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"content": {
"type": "array",
"items": {
"$ref": "#/components/schemas/OpenAIResponseOutputMessageContent"
}
},
"role": {
"type": "string",
"const": "assistant",
"default": "assistant"
},
"status": {
"type": "string"
},
"type": {
"type": "string",
"const": "message",
"default": "message"
}
},
"additionalProperties": false,
"required": [
"id",
"content",
"role",
"status",
"type"
],
"title": "OpenAIResponseOutputMessage"
},
"OpenAIResponseOutputMessageContent": {
"type": "object",
"properties": {
"text": {
"type": "string"
},
"type": {
"type": "string",
"const": "output_text",
"default": "output_text"
}
},
"additionalProperties": false,
"required": [
"text",
"type"
],
"title": "OpenAIResponseOutputMessageContentOutputText"
},
"OpenAIResponseOutputMessageWebSearchToolCall": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"status": {
"type": "string"
},
"type": {
"type": "string",
"const": "web_search_call",
"default": "web_search_call"
}
},
"additionalProperties": false,
"required": [
"id",
"status",
"type"
],
"title": "OpenAIResponseOutputMessageWebSearchToolCall"
},
"OpenAIResponseObjectStream": {
"oneOf": [
{
"$ref": "#/components/schemas/OpenAIResponseObjectStreamResponseCreated"
},
{
"$ref": "#/components/schemas/OpenAIResponseObjectStreamResponseCompleted"
}
],
"discriminator": {
"propertyName": "type",
"mapping": {
"response.created": "#/components/schemas/OpenAIResponseObjectStreamResponseCreated",
"response.completed": "#/components/schemas/OpenAIResponseObjectStreamResponseCompleted"
}
}
},
"OpenAIResponseObjectStreamResponseCompleted": {
"type": "object",
"properties": {
"response": {
"$ref": "#/components/schemas/OpenAIResponseObject"
},
"type": {
"type": "string",
"const": "response.completed",
"default": "response.completed"
}
},
"additionalProperties": false,
"required": [
"response",
"type"
],
"title": "OpenAIResponseObjectStreamResponseCompleted"
},
"OpenAIResponseObjectStreamResponseCreated": {
"type": "object",
"properties": {
"response": {
"$ref": "#/components/schemas/OpenAIResponseObject"
},
"type": {
"type": "string",
"const": "response.created",
"default": "response.created"
}
},
"additionalProperties": false,
"required": [
"response",
"type"
],
"title": "OpenAIResponseObjectStreamResponseCreated"
},
"CreateUploadSessionRequest": {
"type": "object",
"properties": {

350
docs/_static/llama-stack-spec.yaml vendored
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@ -330,6 +330,39 @@ paths:
schema:
$ref: '#/components/schemas/CreateAgentTurnRequest'
required: true
/v1/openai/v1/responses:
post:
responses:
'200':
description: >-
Runtime representation of an annotated type.
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIResponseObject'
text/event-stream:
schema:
$ref: '#/components/schemas/OpenAIResponseObjectStream'
'400':
$ref: '#/components/responses/BadRequest400'
'429':
$ref: >-
#/components/responses/TooManyRequests429
'500':
$ref: >-
#/components/responses/InternalServerError500
default:
$ref: '#/components/responses/DefaultError'
tags:
- Agents
description: Create a new OpenAI response.
parameters: []
requestBody:
content:
application/json:
schema:
$ref: '#/components/schemas/CreateOpenaiResponseRequest'
required: true
/v1/files:
get:
responses:
@ -875,6 +908,36 @@ paths:
required: true
schema:
type: string
/v1/openai/v1/responses/{id}:
get:
responses:
'200':
description: An OpenAIResponseObject.
content:
application/json:
schema:
$ref: '#/components/schemas/OpenAIResponseObject'
'400':
$ref: '#/components/responses/BadRequest400'
'429':
$ref: >-
#/components/responses/TooManyRequests429
'500':
$ref: >-
#/components/responses/InternalServerError500
default:
$ref: '#/components/responses/DefaultError'
tags:
- Agents
description: Retrieve an OpenAI response by its ID.
parameters:
- name: id
in: path
description: >-
The ID of the OpenAI response to retrieve.
required: true
schema:
type: string
/v1/scoring-functions/{scoring_fn_id}:
get:
responses:
@ -4329,6 +4392,293 @@ components:
- event_type
- turn_id
title: AgentTurnResponseTurnStartPayload
OpenAIResponseInputMessage:
type: object
properties:
content:
oneOf:
- type: string
- type: array
items:
$ref: '#/components/schemas/OpenAIResponseInputMessageContent'
role:
oneOf:
- type: string
const: system
- type: string
const: developer
- type: string
const: user
- type: string
const: assistant
type:
type: string
const: message
default: message
additionalProperties: false
required:
- content
- role
title: OpenAIResponseInputMessage
OpenAIResponseInputMessageContent:
oneOf:
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentImage'
discriminator:
propertyName: type
mapping:
input_text: '#/components/schemas/OpenAIResponseInputMessageContentText'
input_image: '#/components/schemas/OpenAIResponseInputMessageContentImage'
OpenAIResponseInputMessageContentImage:
type: object
properties:
detail:
oneOf:
- type: string
const: low
- type: string
const: high
- type: string
const: auto
default: auto
type:
type: string
const: input_image
default: input_image
image_url:
type: string
additionalProperties: false
required:
- detail
- type
title: OpenAIResponseInputMessageContentImage
OpenAIResponseInputMessageContentText:
type: object
properties:
text:
type: string
type:
type: string
const: input_text
default: input_text
additionalProperties: false
required:
- text
- type
title: OpenAIResponseInputMessageContentText
OpenAIResponseInputTool:
type: object
properties:
type:
oneOf:
- type: string
const: web_search
- type: string
const: web_search_preview_2025_03_11
default: web_search
search_context_size:
type: string
default: medium
additionalProperties: false
required:
- type
title: OpenAIResponseInputToolWebSearch
CreateOpenaiResponseRequest:
type: object
properties:
input:
oneOf:
- type: string
- type: array
items:
$ref: '#/components/schemas/OpenAIResponseInputMessage'
description: Input message(s) to create the response.
model:
type: string
description: The underlying LLM used for completions.
previous_response_id:
type: string
description: >-
(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.
store:
type: boolean
stream:
type: boolean
tools:
type: array
items:
$ref: '#/components/schemas/OpenAIResponseInputTool'
additionalProperties: false
required:
- input
- model
title: CreateOpenaiResponseRequest
OpenAIResponseError:
type: object
properties:
code:
type: string
message:
type: string
additionalProperties: false
required:
- code
- message
title: OpenAIResponseError
OpenAIResponseObject:
type: object
properties:
created_at:
type: integer
error:
$ref: '#/components/schemas/OpenAIResponseError'
id:
type: string
model:
type: string
object:
type: string
const: response
default: response
output:
type: array
items:
$ref: '#/components/schemas/OpenAIResponseOutput'
parallel_tool_calls:
type: boolean
default: false
previous_response_id:
type: string
status:
type: string
temperature:
type: number
top_p:
type: number
truncation:
type: string
user:
type: string
additionalProperties: false
required:
- created_at
- id
- model
- object
- output
- parallel_tool_calls
- status
title: OpenAIResponseObject
OpenAIResponseOutput:
oneOf:
- $ref: '#/components/schemas/OpenAIResponseOutputMessage'
- $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
discriminator:
propertyName: type
mapping:
message: '#/components/schemas/OpenAIResponseOutputMessage'
web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
OpenAIResponseOutputMessage:
type: object
properties:
id:
type: string
content:
type: array
items:
$ref: '#/components/schemas/OpenAIResponseOutputMessageContent'
role:
type: string
const: assistant
default: assistant
status:
type: string
type:
type: string
const: message
default: message
additionalProperties: false
required:
- id
- content
- role
- status
- type
title: OpenAIResponseOutputMessage
OpenAIResponseOutputMessageContent:
type: object
properties:
text:
type: string
type:
type: string
const: output_text
default: output_text
additionalProperties: false
required:
- text
- type
title: >-
OpenAIResponseOutputMessageContentOutputText
"OpenAIResponseOutputMessageWebSearchToolCall":
type: object
properties:
id:
type: string
status:
type: string
type:
type: string
const: web_search_call
default: web_search_call
additionalProperties: false
required:
- id
- status
- type
title: >-
OpenAIResponseOutputMessageWebSearchToolCall
OpenAIResponseObjectStream:
oneOf:
- $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated'
- $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCompleted'
discriminator:
propertyName: type
mapping:
response.created: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated'
response.completed: '#/components/schemas/OpenAIResponseObjectStreamResponseCompleted'
"OpenAIResponseObjectStreamResponseCompleted":
type: object
properties:
response:
$ref: '#/components/schemas/OpenAIResponseObject'
type:
type: string
const: response.completed
default: response.completed
additionalProperties: false
required:
- response
- type
title: >-
OpenAIResponseObjectStreamResponseCompleted
"OpenAIResponseObjectStreamResponseCreated":
type: object
properties:
response:
$ref: '#/components/schemas/OpenAIResponseObject'
type:
type: string
const: response.created
default: response.created
additionalProperties: false
required:
- response
- type
title: >-
OpenAIResponseObjectStreamResponseCreated
CreateUploadSessionRequest:
type: object
properties:

2
docs/openapi_generator/pyopenapi/generator.py
View file

@ -179,7 +179,7 @@ class ContentBuilder:
"Creates the content subtree for a request or response."
def is_iterator_type(t):
return "StreamChunk" in str(t)
return "StreamChunk" in str(t) or "OpenAIResponseObjectStream" in str(t)
def get_media_type(t):
if is_generic_list(t):

1
docs/source/distributions/self_hosted_distro/remote-vllm.md
View file

@ -18,7 +18,6 @@ The `llamastack/distribution-remote-vllm` distribution consists of the following
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::vllm`, `inline::sentence-transformers` |
| openai_responses | `inline::openai-responses` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |

1
docs/source/distributions/self_hosted_distro/together.md
View file

@ -19,7 +19,6 @@ The `llamastack/distribution-together` distribution consists of the following pr
| datasetio | `remote::huggingface`, `inline::localfs` |
| eval | `inline::meta-reference` |
| inference | `remote::together`, `inline::sentence-transformers` |
| openai_responses | `inline::openai-responses` |
| safety | `inline::llama-guard` |
| scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |
| telemetry | `inline::meta-reference` |

43
llama_stack/apis/agents/agents.py
View file

@ -38,6 +38,13 @@ from llama_stack.apis.safety import SafetyViolation
from llama_stack.apis.tools import ToolDef
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
from .openai_responses import (
OpenAIResponseInputMessage,
OpenAIResponseInputTool,
OpenAIResponseObject,
OpenAIResponseObjectStream,
)
class Attachment(BaseModel):
"""An attachment to an agent turn.
@ -593,3 +600,39 @@ class Agents(Protocol):
:returns: A ListAgentSessionsResponse.
"""
...
# We situate the OpenAI Responses API in the Agents API just like we did things
# for Inference. The Responses API, in its intent, serves the same purpose as
# the Agents API above -- it is essentially a lightweight "agentic loop" with
# integrated tool calling.
#
# Both of these APIs are inherently stateful.
@webmethod(route="/openai/v1/responses/{id}", method="GET")
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject:
"""Retrieve an OpenAI response by its ID.
:param id: The ID of the OpenAI response to retrieve.
:returns: An OpenAIResponseObject.
"""
...
@webmethod(route="/openai/v1/responses", method="POST")
async def create_openai_response(
self,
input: Union[str, List[OpenAIResponseInputMessage]],
model: str,
previous_response_id: Optional[str] = None,
store: Optional[bool] = True,
stream: Optional[bool] = False,
tools: Optional[List[OpenAIResponseInputTool]] = None,
) -> Union[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 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.
"""

34
llama_stack/apis/openai_responses/openai_responses.py → llama_stack/apis/agents/openai_responses.py
View file

@ -4,12 +4,12 @@
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import AsyncIterator, List, Literal, Optional, Protocol, Union, runtime_checkable
from typing import List, Literal, Optional, Union
from pydantic import BaseModel, Field
from typing_extensions import Annotated
from llama_stack.schema_utils import json_schema_type, register_schema, webmethod
from llama_stack.schema_utils import json_schema_type, register_schema
@json_schema_type
@ -104,7 +104,7 @@ class OpenAIResponseInputMessageContentText(BaseModel):
@json_schema_type
class OpenAIResponseInputMessageContentImage(BaseModel):
detail: Literal["low", "high", "auto"] = "auto"
detail: Literal["low"] | Literal["high"] | Literal["auto"] = "auto"
type: Literal["input_image"] = "input_image"
# TODO: handle file_id
image_url: Optional[str] = None
@ -121,13 +121,13 @@ register_schema(OpenAIResponseInputMessageContent, name="OpenAIResponseInputMess
@json_schema_type
class OpenAIResponseInputMessage(BaseModel):
content: Union[str, List[OpenAIResponseInputMessageContent]]
role: Literal["system", "developer", "user", "assistant"]
role: Literal["system"] | Literal["developer"] | Literal["user"] | Literal["assistant"]
type: Optional[Literal["message"]] = "message"
@json_schema_type
class OpenAIResponseInputToolWebSearch(BaseModel):
type: Literal["web_search", "web_search_preview_2025_03_11"] = "web_search"
type: Literal["web_search"] | Literal["web_search_preview_2025_03_11"] = "web_search"
# TODO: actually use search_context_size somewhere...
search_context_size: Optional[str] = Field(default="medium", pattern="^low|medium|high$")
# TODO: add user_location
@ -138,27 +138,3 @@ OpenAIResponseInputTool = Annotated[
Field(discriminator="type"),
]
register_schema(OpenAIResponseInputTool, name="OpenAIResponseInputTool")
@runtime_checkable
class OpenAIResponses(Protocol):
"""
OpenAI Responses API implementation.
"""
@webmethod(route="/openai/v1/responses/{id}", method="GET")
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject: ...
@webmethod(route="/openai/v1/responses", method="POST")
async def create_openai_response(
self,
input: Union[str, List[OpenAIResponseInputMessage]],
model: str,
previous_response_id: Optional[str] = None,
store: Optional[bool] = True,
stream: Optional[bool] = False,
tools: Optional[List[OpenAIResponseInputTool]] = None,
) -> Union[OpenAIResponseObject, AsyncIterator[OpenAIResponseObjectStream]]: ...

1
llama_stack/apis/datatypes.py
View file

@ -24,7 +24,6 @@ class Api(Enum):
eval = "eval"
post_training = "post_training"
tool_runtime = "tool_runtime"
openai_responses = "openai_responses"
telemetry = "telemetry"

7
llama_stack/apis/openai_responses/__init__.py
View file

@ -1,7 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from .openai_responses import * # noqa: F401 F403

2
llama_stack/distribution/resolver.py
View file

@ -16,7 +16,6 @@ from llama_stack.apis.files import Files
from llama_stack.apis.inference import Inference
from llama_stack.apis.inspect import Inspect
from llama_stack.apis.models import Models
from llama_stack.apis.openai_responses.openai_responses import OpenAIResponses
from llama_stack.apis.post_training import PostTraining
from llama_stack.apis.providers import Providers as ProvidersAPI
from llama_stack.apis.safety import Safety
@ -81,7 +80,6 @@ def api_protocol_map() -> Dict[Api, Any]:
Api.tool_groups: ToolGroups,
Api.tool_runtime: ToolRuntime,
Api.files: Files,
Api.openai_responses: OpenAIResponses,
}

2
llama_stack/distribution/routers/routing_tables.py
View file

@ -149,8 +149,6 @@ class CommonRoutingTableImpl(RoutingTable):
p.benchmark_store = self
elif api == Api.tool_runtime:
p.tool_store = self
elif api == Api.openai_responses:
p.model_store = self
async def shutdown(self) -> None:
for p in self.impls_by_provider_id.values():

31
llama_stack/providers/inline/agents/meta_reference/agents.py
View file

@ -23,6 +23,9 @@ from llama_stack.apis.agents import (
Document,
ListAgentSessionsResponse,
ListAgentsResponse,
OpenAIResponseInputMessage,
OpenAIResponseInputTool,
OpenAIResponseObject,
Session,
Turn,
)
@ -40,6 +43,7 @@ from llama_stack.providers.utils.kvstore import InmemoryKVStoreImpl, kvstore_imp
from .agent_instance import ChatAgent
from .config import MetaReferenceAgentsImplConfig
from .openai_responses import OpenAIResponsesImpl
logger = logging.getLogger()
logger.setLevel(logging.INFO)
@ -63,9 +67,16 @@ class MetaReferenceAgentsImpl(Agents):
self.tool_groups_api = tool_groups_api
self.in_memory_store = InmemoryKVStoreImpl()
self.openai_responses_impl = None
async def initialize(self) -> None:
self.persistence_store = await kvstore_impl(self.config.persistence_store)
self.openai_responses_impl = OpenAIResponsesImpl(
self.persistence_store,
inference_api=self.inference_api,
tool_groups_api=self.tool_groups_api,
tool_runtime_api=self.tool_runtime_api,
)
# check if "bwrap" is available
if not shutil.which("bwrap"):
@ -244,3 +255,23 @@ class MetaReferenceAgentsImpl(Agents):
agent_id: str,
) -> ListAgentSessionsResponse:
pass
# OpenAI responses
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject:
return await self.openai_responses_impl.get_openai_response(id)
async def create_openai_response(
self,
input: Union[str, List[OpenAIResponseInputMessage]],
model: str,
previous_response_id: Optional[str] = None,
store: Optional[bool] = True,
stream: Optional[bool] = False,
tools: Optional[List[OpenAIResponseInputTool]] = None,
) -> OpenAIResponseObject:
return await self.openai_responses_impl.create_openai_response(
input, model, previous_response_id, store, stream, tools
)

64
llama_stack/providers/inline/openai_responses/openai_responses.py → llama_stack/providers/inline/agents/meta_reference/openai_responses.py
View file

@ -10,6 +10,20 @@ from typing import AsyncIterator, List, Optional, Union, cast
from openai.types.chat import ChatCompletionToolParam
from llama_stack.apis.agents.openai_responses import (
OpenAIResponseInputMessage,
OpenAIResponseInputMessageContentImage,
OpenAIResponseInputMessageContentText,
OpenAIResponseInputTool,
OpenAIResponseObject,
OpenAIResponseObjectStream,
OpenAIResponseObjectStreamResponseCompleted,
OpenAIResponseObjectStreamResponseCreated,
OpenAIResponseOutput,
OpenAIResponseOutputMessage,
OpenAIResponseOutputMessageContentOutputText,
OpenAIResponseOutputMessageWebSearchToolCall,
)
from llama_stack.apis.inference.inference import (
Inference,
OpenAIAssistantMessageParam,
@ -24,29 +38,11 @@ from llama_stack.apis.inference.inference import (
OpenAIToolMessageParam,
OpenAIUserMessageParam,
)
from llama_stack.apis.models.models import Models, ModelType
from llama_stack.apis.openai_responses import OpenAIResponses
from llama_stack.apis.openai_responses.openai_responses import (
OpenAIResponseInputMessage,
OpenAIResponseInputMessageContentImage,
OpenAIResponseInputMessageContentText,
OpenAIResponseInputTool,
OpenAIResponseObject,
OpenAIResponseObjectStream,
OpenAIResponseObjectStreamResponseCompleted,
OpenAIResponseObjectStreamResponseCreated,
OpenAIResponseOutput,
OpenAIResponseOutputMessage,
OpenAIResponseOutputMessageContentOutputText,
OpenAIResponseOutputMessageWebSearchToolCall,
)
from llama_stack.apis.tools.tools import ToolGroups, ToolInvocationResult, ToolRuntime
from llama_stack.log import get_logger
from llama_stack.models.llama.datatypes import ToolDefinition, ToolParamDefinition
from llama_stack.providers.utils.inference.openai_compat import convert_tooldef_to_openai_tool
from llama_stack.providers.utils.kvstore import kvstore_impl
from .config import OpenAIResponsesImplConfig
from llama_stack.providers.utils.kvstore import KVStore
logger = get_logger(name=__name__, category="openai_responses")
@ -80,34 +76,25 @@ async def _openai_choices_to_output_messages(choices: List[OpenAIChoice]) -> Lis
return output_messages
class OpenAIResponsesImpl(OpenAIResponses):
class OpenAIResponsesImpl:
def __init__(
self,
config: OpenAIResponsesImplConfig,
models_api: Models,
persistence_store: KVStore,
inference_api: Inference,
tool_groups_api: ToolGroups,
tool_runtime_api: ToolRuntime,
):
self.config = config
self.models_api = models_api
self.persistence_store = persistence_store
self.inference_api = inference_api
self.tool_groups_api = tool_groups_api
self.tool_runtime_api = tool_runtime_api
async def initialize(self) -> None:
self.kvstore = await kvstore_impl(self.config.kvstore)
async def shutdown(self) -> None:
logger.debug("OpenAIResponsesImpl.shutdown")
pass
async def get_openai_response(
self,
id: str,
) -> OpenAIResponseObject:
key = f"{OPENAI_RESPONSES_PREFIX}{id}"
response_json = await self.kvstore.get(key=key)
response_json = await self.persistence_store.get(key=key)
if response_json is None:
raise ValueError(f"OpenAI response with id '{id}' not found")
return OpenAIResponseObject.model_validate_json(response_json)
@ -122,11 +109,6 @@ class OpenAIResponsesImpl(OpenAIResponses):
tools: Optional[List[OpenAIResponseInputTool]] = None,
):
stream = False if stream is None else stream
model_obj = await self.models_api.get_model(model)
if model_obj is None:
raise ValueError(f"Model '{model}' not found")
if model_obj.model_type == ModelType.embedding:
raise ValueError(f"Model '{model}' is an embedding model and does not support chat completions")
messages: List[OpenAIMessageParam] = []
if previous_response_id:
@ -155,7 +137,7 @@ class OpenAIResponsesImpl(OpenAIResponses):
chat_tools = await self._convert_response_tools_to_chat_tools(tools) if tools else None
chat_response = await self.inference_api.openai_chat_completion(
model=model_obj.identifier,
model=model,
messages=messages,
tools=chat_tools,
stream=stream,
@ -198,14 +180,14 @@ class OpenAIResponsesImpl(OpenAIResponses):
output_messages: List[OpenAIResponseOutput] = []
if chat_response.choices[0].finish_reason == "tool_calls":
output_messages.extend(
await self._execute_tool_and_return_final_output(model_obj.identifier, stream, chat_response, messages)
await self._execute_tool_and_return_final_output(model, stream, chat_response, messages)
)
else:
output_messages.extend(await _openai_choices_to_output_messages(chat_response.choices))
response = OpenAIResponseObject(
created_at=chat_response.created,
id=f"resp-{uuid.uuid4()}",
model=model_obj.identifier,
model=model,
object="response",
status="completed",
output=output_messages,
@ -214,7 +196,7 @@ class OpenAIResponsesImpl(OpenAIResponses):
if store:
# Store in kvstore
key = f"{OPENAI_RESPONSES_PREFIX}{response.id}"
await self.kvstore.set(
await self.persistence_store.set(
key=key,
value=response.model_dump_json(),
)

21
llama_stack/providers/inline/openai_responses/__init__.py
View file

@ -1,21 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any, Dict
from llama_stack.apis.datatypes import Api
from .config import OpenAIResponsesImplConfig
async def get_provider_impl(config: OpenAIResponsesImplConfig, deps: Dict[Api, Any]):
from .openai_responses import OpenAIResponsesImpl
impl = OpenAIResponsesImpl(
config, deps[Api.models], deps[Api.inference], deps[Api.tool_groups], deps[Api.tool_runtime]
)
await impl.initialize()
return impl

24
llama_stack/providers/inline/openai_responses/config.py
View file

@ -1,24 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import Any, Dict
from pydantic import BaseModel
from llama_stack.providers.utils.kvstore.config import KVStoreConfig, SqliteKVStoreConfig
class OpenAIResponsesImplConfig(BaseModel):
kvstore: KVStoreConfig
@classmethod
def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> Dict[str, Any]:
return {
"kvstore": SqliteKVStoreConfig.sample_run_config(
__distro_dir__=__distro_dir__,
db_name="openai_responses.db",
)
}

27
llama_stack/providers/registry/openai_responses.py
View file

@ -1,27 +0,0 @@
# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from typing import List
from llama_stack.providers.datatypes import Api, InlineProviderSpec, ProviderSpec
def available_providers() -> List[ProviderSpec]:
return [
InlineProviderSpec(
api=Api.openai_responses,
provider_type="inline::openai-responses",
pip_packages=[],
module="llama_stack.providers.inline.openai_responses",
config_class="llama_stack.providers.inline.openai_responses.config.OpenAIResponsesImplConfig",
api_dependencies=[
Api.models,
Api.inference,
Api.tool_groups,
Api.tool_runtime,
],
),
]

2
llama_stack/strong_typing/schema.py
View file

@ -478,6 +478,8 @@ class JsonSchemaGenerator:
}
return ret
elif origin_type is Literal:
if len(typing.get_args(typ)) != 1:
print(f"Literal type {typ} has {len(typing.get_args(typ))} arguments")
(literal_value,) = typing.get_args(typ) # unpack value of literal type
schema = self.type_to_schema(type(literal_value))
schema["const"] = literal_value

2
llama_stack/templates/remote-vllm/build.yaml
View file

@ -24,8 +24,6 @@ distribution_spec:
- inline::braintrust
telemetry:
- inline::meta-reference
openai_responses:
- inline::openai-responses
tool_runtime:
- remote::brave-search
- remote::tavily-search

9
llama_stack/templates/remote-vllm/run-with-safety.yaml
View file

@ -5,7 +5,6 @@ apis:
- datasetio
- eval
- inference
- openai_responses
- safety
- scoring
- telemetry
@ -92,14 +91,6 @@ providers:
service_name: "${env.OTEL_SERVICE_NAME:\u200B}"
sinks: ${env.TELEMETRY_SINKS:console,sqlite}
sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/remote-vllm/trace_store.db}
openai_responses:
- provider_id: openai-responses
provider_type: inline::openai-responses
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/remote-vllm}/openai_responses.db
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search

9
llama_stack/templates/remote-vllm/run.yaml
View file

@ -5,7 +5,6 @@ apis:
- datasetio
- eval
- inference
- openai_responses
- safety
- scoring
- telemetry
@ -85,14 +84,6 @@ providers:
service_name: "${env.OTEL_SERVICE_NAME:\u200B}"
sinks: ${env.TELEMETRY_SINKS:console,sqlite}
sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/remote-vllm/trace_store.db}
openai_responses:
- provider_id: openai-responses
provider_type: inline::openai-responses
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/remote-vllm}/openai_responses.db
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search

1
llama_stack/templates/remote-vllm/vllm.py
View file

@ -31,7 +31,6 @@ def get_distribution_template() -> DistributionTemplate:
"datasetio": ["remote::huggingface", "inline::localfs"],
"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
"telemetry": ["inline::meta-reference"],
"openai_responses": ["inline::openai-responses"],
"tool_runtime": [
"remote::brave-search",
"remote::tavily-search",

2
llama_stack/templates/together/build.yaml
View file

@ -24,8 +24,6 @@ distribution_spec:
- inline::basic
- inline::llm-as-judge
- inline::braintrust
openai_responses:
- inline::openai-responses
tool_runtime:
- remote::brave-search
- remote::tavily-search

9
llama_stack/templates/together/run-with-safety.yaml
View file

@ -5,7 +5,6 @@ apis:
- datasetio
- eval
- inference
- openai_responses
- safety
- scoring
- telemetry
@ -88,14 +87,6 @@ providers:
provider_type: inline::braintrust
config:
openai_api_key: ${env.OPENAI_API_KEY:}
openai_responses:
- provider_id: openai-responses
provider_type: inline::openai-responses
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/together}/openai_responses.db
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search

9
llama_stack/templates/together/run.yaml
View file

@ -5,7 +5,6 @@ apis:
- datasetio
- eval
- inference
- openai_responses
- safety
- scoring
- telemetry
@ -83,14 +82,6 @@ providers:
provider_type: inline::braintrust
config:
openai_api_key: ${env.OPENAI_API_KEY:}
openai_responses:
- provider_id: openai-responses
provider_type: inline::openai-responses
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/together}/openai_responses.db
tool_runtime:
- provider_id: brave-search
provider_type: remote::brave-search

1
llama_stack/templates/together/together.py
View file

@ -36,7 +36,6 @@ def get_distribution_template() -> DistributionTemplate:
"eval": ["inline::meta-reference"],
"datasetio": ["remote::huggingface", "inline::localfs"],
"scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
"openai_responses": ["inline::openai-responses"],
"tool_runtime": [
"remote::brave-search",
"remote::tavily-search",