mirror of
https://github.com/meta-llama/llama-stack.git
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feat(responses)!: add support for OpenAI compatible Prompts in Responses API
This commit is contained in:
r3v5
parent
bd3c473208
commit
59169bfd25
33 changed files with 1667 additions and 34 deletions
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@ -5574,11 +5574,44 @@ components:
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oneOf:
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentImage'
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentFile'
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discriminator:
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propertyName: type
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mapping:
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input_text: '#/components/schemas/OpenAIResponseInputMessageContentText'
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input_image: '#/components/schemas/OpenAIResponseInputMessageContentImage'
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input_file: '#/components/schemas/OpenAIResponseInputMessageContentFile'
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OpenAIResponseInputMessageContentFile:
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type: object
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properties:
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type:
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type: string
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const: input_file
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default: input_file
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description: >-
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The type of the input item. Always `input_file`.
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file_data:
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type: string
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description: >-
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The data of the file to be sent to the model.
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file_id:
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type: string
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description: >-
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(Optional) The ID of the file to be sent to the model.
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file_url:
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type: string
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description: >-
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The URL of the file to be sent to the model.
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filename:
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type: string
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description: >-
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The name of the file to be sent to the model.
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additionalProperties: false
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required:
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- type
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title: OpenAIResponseInputMessageContentFile
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description: >-
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File content for input messages in OpenAI response format.
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OpenAIResponseInputMessageContentImage:
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type: object
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properties:
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@ -5599,6 +5632,10 @@ components:
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default: input_image
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description: >-
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Content type identifier, always "input_image"
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file_id:
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type: string
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description: >-
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(Optional) The ID of the file to be sent to the model.
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image_url:
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type: string
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description: (Optional) URL of the image content
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@ -6998,6 +7035,10 @@ components:
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type: string
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description: >-
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(Optional) ID of the previous response in a conversation
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prompt:
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$ref: '#/components/schemas/Prompt'
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description: >-
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(Optional) Prompt object with ID, version, and variables
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status:
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type: string
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description: >-
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@ -7315,6 +7356,29 @@ components:
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title: OpenAIResponseInputToolMCP
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description: >-
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Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
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OpenAIResponsePromptParam:
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type: object
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properties:
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id:
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type: string
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description: Unique identifier of the prompt template
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variables:
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type: object
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additionalProperties:
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$ref: '#/components/schemas/OpenAIResponseInputMessageContent'
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description: >-
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Dictionary of variable names to OpenAIResponseInputMessageContent structure
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for template substitution
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version:
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type: string
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description: >-
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Version number of the prompt to use (defaults to latest if not specified)
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additionalProperties: false
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required:
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- id
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title: OpenAIResponsePromptParam
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description: >-
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Prompt object that is used for OpenAI responses.
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CreateOpenaiResponseRequest:
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type: object
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properties:
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@ -7328,6 +7392,10 @@ components:
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model:
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type: string
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description: The underlying LLM used for completions.
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prompt:
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$ref: '#/components/schemas/OpenAIResponsePromptParam'
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description: >-
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Prompt object with ID, version, and variables.
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instructions:
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type: string
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previous_response_id:
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@ -7405,6 +7473,10 @@ components:
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type: string
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description: >-
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(Optional) ID of the previous response in a conversation
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prompt:
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$ref: '#/components/schemas/Prompt'
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description: >-
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(Optional) Prompt object with ID, version, and variables
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status:
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type: string
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description: >-
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119
docs/static/deprecated-llama-stack-spec.html
vendored
119
docs/static/deprecated-llama-stack-spec.html
vendored
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@ -8593,16 +8593,53 @@
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseInputMessageContentImage"
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseInputMessageContentFile"
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}
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],
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"discriminator": {
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"propertyName": "type",
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"mapping": {
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"input_text": "#/components/schemas/OpenAIResponseInputMessageContentText",
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"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage"
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"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage",
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"input_file": "#/components/schemas/OpenAIResponseInputMessageContentFile"
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}
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}
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},
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"OpenAIResponseInputMessageContentFile": {
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"type": "object",
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"properties": {
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"type": {
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"type": "string",
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"const": "input_file",
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"default": "input_file",
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"description": "The type of the input item. Always `input_file`."
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},
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"file_data": {
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"type": "string",
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"description": "The data of the file to be sent to the model."
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},
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"file_id": {
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"type": "string",
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"description": "(Optional) The ID of the file to be sent to the model."
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},
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"file_url": {
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"type": "string",
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"description": "The URL of the file to be sent to the model."
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},
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"filename": {
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"type": "string",
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"description": "The name of the file to be sent to the model."
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}
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},
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"additionalProperties": false,
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"required": [
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"type"
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],
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"title": "OpenAIResponseInputMessageContentFile",
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"description": "File content for input messages in OpenAI response format."
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},
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"OpenAIResponseInputMessageContentImage": {
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"type": "object",
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"properties": {
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@ -8630,6 +8667,10 @@
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"default": "input_image",
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"description": "Content type identifier, always \"input_image\""
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},
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"file_id": {
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"type": "string",
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"description": "(Optional) The ID of the file to be sent to the model."
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},
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"image_url": {
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"type": "string",
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"description": "(Optional) URL of the image content"
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@ -8993,6 +9034,10 @@
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"type": "string",
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"description": "(Optional) ID of the previous response in a conversation"
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},
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"prompt": {
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"$ref": "#/components/schemas/Prompt",
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"description": "(Optional) Prompt object with ID, version, and variables"
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},
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"status": {
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"type": "string",
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"description": "Current status of the response generation"
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@ -9610,6 +9655,44 @@
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"title": "OpenAIResponseUsage",
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"description": "Usage information for OpenAI response."
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},
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"Prompt": {
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"type": "object",
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"properties": {
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"prompt": {
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"type": "string",
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"description": "The system prompt text with variable placeholders. Variables are only supported when using the Responses API."
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},
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"version": {
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"type": "integer",
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"description": "Version (integer starting at 1, incremented on save)"
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},
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"prompt_id": {
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"type": "string",
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"description": "Unique identifier formatted as 'pmpt_<48-digit-hash>'"
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},
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"variables": {
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"type": "array",
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"items": {
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"type": "string"
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},
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"description": "List of prompt variable names that can be used in the prompt template"
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},
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"is_default": {
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"type": "boolean",
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"default": false,
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"description": "Boolean indicating whether this version is the default version for this prompt"
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}
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},
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"additionalProperties": false,
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"required": [
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"version",
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"prompt_id",
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"variables",
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"is_default"
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],
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"title": "Prompt",
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"description": "A prompt resource representing a stored OpenAI Compatible prompt template in Llama Stack."
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},
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"ResponseGuardrailSpec": {
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"type": "object",
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"properties": {
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@ -9766,6 +9849,32 @@
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"title": "OpenAIResponseInputToolMCP",
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"description": "Model Context Protocol (MCP) tool configuration for OpenAI response inputs."
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},
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"OpenAIResponsePromptParam": {
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"type": "object",
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"properties": {
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"id": {
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"type": "string",
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"description": "Unique identifier of the prompt template"
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},
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"variables": {
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"type": "object",
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"additionalProperties": {
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"$ref": "#/components/schemas/OpenAIResponseInputMessageContent"
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},
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"description": "Dictionary of variable names to OpenAIResponseInputMessageContent structure for template substitution"
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},
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"version": {
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"type": "string",
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"description": "Version number of the prompt to use (defaults to latest if not specified)"
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}
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},
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"additionalProperties": false,
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"required": [
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"id"
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],
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"title": "OpenAIResponsePromptParam",
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"description": "Prompt object that is used for OpenAI responses."
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},
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"CreateOpenaiResponseRequest": {
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"type": "object",
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"properties": {
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@ -9787,6 +9896,10 @@
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"type": "string",
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"description": "The underlying LLM used for completions."
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},
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"prompt": {
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"$ref": "#/components/schemas/OpenAIResponsePromptParam",
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"description": "Prompt object with ID, version, and variables."
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},
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"instructions": {
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"type": "string"
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},
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@ -9875,6 +9988,10 @@
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"type": "string",
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"description": "(Optional) ID of the previous response in a conversation"
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},
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"prompt": {
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"$ref": "#/components/schemas/Prompt",
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"description": "(Optional) Prompt object with ID, version, and variables"
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},
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"status": {
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"type": "string",
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"description": "Current status of the response generation"
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110
docs/static/deprecated-llama-stack-spec.yaml
vendored
110
docs/static/deprecated-llama-stack-spec.yaml
vendored
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@ -6409,11 +6409,44 @@ components:
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oneOf:
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentImage'
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentFile'
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discriminator:
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propertyName: type
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mapping:
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input_text: '#/components/schemas/OpenAIResponseInputMessageContentText'
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input_image: '#/components/schemas/OpenAIResponseInputMessageContentImage'
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input_file: '#/components/schemas/OpenAIResponseInputMessageContentFile'
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OpenAIResponseInputMessageContentFile:
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type: object
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properties:
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type:
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type: string
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const: input_file
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default: input_file
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description: >-
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The type of the input item. Always `input_file`.
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file_data:
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type: string
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description: >-
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The data of the file to be sent to the model.
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file_id:
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type: string
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description: >-
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(Optional) The ID of the file to be sent to the model.
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file_url:
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type: string
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description: >-
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The URL of the file to be sent to the model.
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filename:
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type: string
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description: >-
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The name of the file to be sent to the model.
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additionalProperties: false
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required:
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- type
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title: OpenAIResponseInputMessageContentFile
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description: >-
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File content for input messages in OpenAI response format.
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OpenAIResponseInputMessageContentImage:
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type: object
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properties:
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@ -6434,6 +6467,10 @@ components:
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default: input_image
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description: >-
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Content type identifier, always "input_image"
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file_id:
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type: string
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description: >-
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(Optional) The ID of the file to be sent to the model.
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image_url:
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type: string
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description: (Optional) URL of the image content
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@ -6704,6 +6741,10 @@ components:
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type: string
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description: >-
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(Optional) ID of the previous response in a conversation
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prompt:
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$ref: '#/components/schemas/Prompt'
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description: >-
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(Optional) Prompt object with ID, version, and variables
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status:
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type: string
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description: >-
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@ -7181,6 +7222,44 @@ components:
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- total_tokens
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title: OpenAIResponseUsage
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description: Usage information for OpenAI response.
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Prompt:
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type: object
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properties:
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prompt:
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type: string
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description: >-
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The system prompt text with variable placeholders. Variables are only
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supported when using the Responses API.
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version:
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type: integer
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description: >-
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Version (integer starting at 1, incremented on save)
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prompt_id:
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type: string
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description: >-
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Unique identifier formatted as 'pmpt_<48-digit-hash>'
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variables:
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type: array
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items:
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type: string
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description: >-
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List of prompt variable names that can be used in the prompt template
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is_default:
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type: boolean
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default: false
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description: >-
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Boolean indicating whether this version is the default version for this
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prompt
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additionalProperties: false
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required:
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- version
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- prompt_id
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- variables
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- is_default
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title: Prompt
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description: >-
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A prompt resource representing a stored OpenAI Compatible prompt template
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in Llama Stack.
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ResponseGuardrailSpec:
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type: object
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properties:
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@ -7287,6 +7366,29 @@ components:
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title: OpenAIResponseInputToolMCP
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description: >-
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Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
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OpenAIResponsePromptParam:
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type: object
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properties:
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id:
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type: string
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description: Unique identifier of the prompt template
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variables:
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type: object
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additionalProperties:
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$ref: '#/components/schemas/OpenAIResponseInputMessageContent'
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description: >-
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Dictionary of variable names to OpenAIResponseInputMessageContent structure
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for template substitution
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version:
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type: string
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description: >-
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Version number of the prompt to use (defaults to latest if not specified)
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additionalProperties: false
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required:
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- id
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title: OpenAIResponsePromptParam
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description: >-
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Prompt object that is used for OpenAI responses.
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CreateOpenaiResponseRequest:
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type: object
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properties:
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|
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@ -7300,6 +7402,10 @@ components:
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model:
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type: string
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description: The underlying LLM used for completions.
|
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prompt:
|
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$ref: '#/components/schemas/OpenAIResponsePromptParam'
|
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description: >-
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Prompt object with ID, version, and variables.
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instructions:
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type: string
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previous_response_id:
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|
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@ -7377,6 +7483,10 @@ components:
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type: string
|
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description: >-
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(Optional) ID of the previous response in a conversation
|
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prompt:
|
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$ref: '#/components/schemas/Prompt'
|
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description: >-
|
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(Optional) Prompt object with ID, version, and variables
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status:
|
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type: string
|
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description: >-
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|
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81
docs/static/llama-stack-spec.html
vendored
81
docs/static/llama-stack-spec.html
vendored
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@ -5729,16 +5729,53 @@
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseInputMessageContentImage"
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseInputMessageContentFile"
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}
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],
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"discriminator": {
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"propertyName": "type",
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"mapping": {
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"input_text": "#/components/schemas/OpenAIResponseInputMessageContentText",
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"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage"
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"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage",
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"input_file": "#/components/schemas/OpenAIResponseInputMessageContentFile"
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}
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}
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},
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"OpenAIResponseInputMessageContentFile": {
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"type": "object",
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"properties": {
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"type": {
|
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"type": "string",
|
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"const": "input_file",
|
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"default": "input_file",
|
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"description": "The type of the input item. Always `input_file`."
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},
|
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"file_data": {
|
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"type": "string",
|
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"description": "The data of the file to be sent to the model."
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},
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"file_id": {
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"type": "string",
|
||||
"description": "(Optional) The ID of the file to be sent to the model."
|
||||
},
|
||||
"file_url": {
|
||||
"type": "string",
|
||||
"description": "The URL of the file to be sent to the model."
|
||||
},
|
||||
"filename": {
|
||||
"type": "string",
|
||||
"description": "The name of the file to be sent to the model."
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"required": [
|
||||
"type"
|
||||
],
|
||||
"title": "OpenAIResponseInputMessageContentFile",
|
||||
"description": "File content for input messages in OpenAI response format."
|
||||
},
|
||||
"OpenAIResponseInputMessageContentImage": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
|
|
@ -5766,6 +5803,10 @@
|
|||
"default": "input_image",
|
||||
"description": "Content type identifier, always \"input_image\""
|
||||
},
|
||||
"file_id": {
|
||||
"type": "string",
|
||||
"description": "(Optional) The ID of the file to be sent to the model."
|
||||
},
|
||||
"image_url": {
|
||||
"type": "string",
|
||||
"description": "(Optional) URL of the image content"
|
||||
|
|
@ -7569,6 +7610,10 @@
|
|||
"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"
|
||||
|
|
@ -8013,6 +8058,32 @@
|
|||
"title": "OpenAIResponseInputToolMCP",
|
||||
"description": "Model Context Protocol (MCP) tool configuration for OpenAI response inputs."
|
||||
},
|
||||
"OpenAIResponsePromptParam": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string",
|
||||
"description": "Unique identifier of the prompt template"
|
||||
},
|
||||
"variables": {
|
||||
"type": "object",
|
||||
"additionalProperties": {
|
||||
"$ref": "#/components/schemas/OpenAIResponseInputMessageContent"
|
||||
},
|
||||
"description": "Dictionary of variable names to OpenAIResponseInputMessageContent structure for template substitution"
|
||||
},
|
||||
"version": {
|
||||
"type": "string",
|
||||
"description": "Version number of the prompt to use (defaults to latest if not specified)"
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"required": [
|
||||
"id"
|
||||
],
|
||||
"title": "OpenAIResponsePromptParam",
|
||||
"description": "Prompt object that is used for OpenAI responses."
|
||||
},
|
||||
"CreateOpenaiResponseRequest": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
|
|
@ -8034,6 +8105,10 @@
|
|||
"type": "string",
|
||||
"description": "The underlying LLM used for completions."
|
||||
},
|
||||
"prompt": {
|
||||
"$ref": "#/components/schemas/OpenAIResponsePromptParam",
|
||||
"description": "Prompt object with ID, version, and variables."
|
||||
},
|
||||
"instructions": {
|
||||
"type": "string"
|
||||
},
|
||||
|
|
@ -8122,6 +8197,10 @@
|
|||
"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"
|
||||
|
|
|
|||
72
docs/static/llama-stack-spec.yaml
vendored
72
docs/static/llama-stack-spec.yaml
vendored
|
|
@ -4361,11 +4361,44 @@ components:
|
|||
oneOf:
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentImage'
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentFile'
|
||||
discriminator:
|
||||
propertyName: type
|
||||
mapping:
|
||||
input_text: '#/components/schemas/OpenAIResponseInputMessageContentText'
|
||||
input_image: '#/components/schemas/OpenAIResponseInputMessageContentImage'
|
||||
input_file: '#/components/schemas/OpenAIResponseInputMessageContentFile'
|
||||
OpenAIResponseInputMessageContentFile:
|
||||
type: object
|
||||
properties:
|
||||
type:
|
||||
type: string
|
||||
const: input_file
|
||||
default: input_file
|
||||
description: >-
|
||||
The type of the input item. Always `input_file`.
|
||||
file_data:
|
||||
type: string
|
||||
description: >-
|
||||
The data of the file to be sent to the model.
|
||||
file_id:
|
||||
type: string
|
||||
description: >-
|
||||
(Optional) The ID of the file to be sent to the model.
|
||||
file_url:
|
||||
type: string
|
||||
description: >-
|
||||
The URL of the file to be sent to the model.
|
||||
filename:
|
||||
type: string
|
||||
description: >-
|
||||
The name of the file to be sent to the model.
|
||||
additionalProperties: false
|
||||
required:
|
||||
- type
|
||||
title: OpenAIResponseInputMessageContentFile
|
||||
description: >-
|
||||
File content for input messages in OpenAI response format.
|
||||
OpenAIResponseInputMessageContentImage:
|
||||
type: object
|
||||
properties:
|
||||
|
|
@ -4386,6 +4419,10 @@ components:
|
|||
default: input_image
|
||||
description: >-
|
||||
Content type identifier, always "input_image"
|
||||
file_id:
|
||||
type: string
|
||||
description: >-
|
||||
(Optional) The ID of the file to be sent to the model.
|
||||
image_url:
|
||||
type: string
|
||||
description: (Optional) URL of the image content
|
||||
|
|
@ -5785,6 +5822,10 @@ 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: >-
|
||||
|
|
@ -6102,6 +6143,29 @@ components:
|
|||
title: OpenAIResponseInputToolMCP
|
||||
description: >-
|
||||
Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
|
||||
OpenAIResponsePromptParam:
|
||||
type: object
|
||||
properties:
|
||||
id:
|
||||
type: string
|
||||
description: Unique identifier of the prompt template
|
||||
variables:
|
||||
type: object
|
||||
additionalProperties:
|
||||
$ref: '#/components/schemas/OpenAIResponseInputMessageContent'
|
||||
description: >-
|
||||
Dictionary of variable names to OpenAIResponseInputMessageContent structure
|
||||
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:
|
||||
|
|
@ -6115,6 +6179,10 @@ 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:
|
||||
|
|
@ -6192,6 +6260,10 @@ components:
|
|||
type: string
|
||||
description: >-
|
||||
(Optional) ID of the previous response in a conversation
|
||||
prompt:
|
||||
$ref: '#/components/schemas/Prompt'
|
||||
description: >-
|
||||
(Optional) Prompt object with ID, version, and variables
|
||||
status:
|
||||
type: string
|
||||
description: >-
|
||||
|
|
|
|||
81
docs/static/stainless-llama-stack-spec.html
vendored
81
docs/static/stainless-llama-stack-spec.html
vendored
|
|
@ -7401,16 +7401,53 @@
|
|||
},
|
||||
{
|
||||
"$ref": "#/components/schemas/OpenAIResponseInputMessageContentImage"
|
||||
},
|
||||
{
|
||||
"$ref": "#/components/schemas/OpenAIResponseInputMessageContentFile"
|
||||
}
|
||||
],
|
||||
"discriminator": {
|
||||
"propertyName": "type",
|
||||
"mapping": {
|
||||
"input_text": "#/components/schemas/OpenAIResponseInputMessageContentText",
|
||||
"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage"
|
||||
"input_image": "#/components/schemas/OpenAIResponseInputMessageContentImage",
|
||||
"input_file": "#/components/schemas/OpenAIResponseInputMessageContentFile"
|
||||
}
|
||||
}
|
||||
},
|
||||
"OpenAIResponseInputMessageContentFile": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"type": {
|
||||
"type": "string",
|
||||
"const": "input_file",
|
||||
"default": "input_file",
|
||||
"description": "The type of the input item. Always `input_file`."
|
||||
},
|
||||
"file_data": {
|
||||
"type": "string",
|
||||
"description": "The data of the file to be sent to the model."
|
||||
},
|
||||
"file_id": {
|
||||
"type": "string",
|
||||
"description": "(Optional) The ID of the file to be sent to the model."
|
||||
},
|
||||
"file_url": {
|
||||
"type": "string",
|
||||
"description": "The URL of the file to be sent to the model."
|
||||
},
|
||||
"filename": {
|
||||
"type": "string",
|
||||
"description": "The name of the file to be sent to the model."
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"required": [
|
||||
"type"
|
||||
],
|
||||
"title": "OpenAIResponseInputMessageContentFile",
|
||||
"description": "File content for input messages in OpenAI response format."
|
||||
},
|
||||
"OpenAIResponseInputMessageContentImage": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
|
|
@ -7438,6 +7475,10 @@
|
|||
"default": "input_image",
|
||||
"description": "Content type identifier, always \"input_image\""
|
||||
},
|
||||
"file_id": {
|
||||
"type": "string",
|
||||
"description": "(Optional) The ID of the file to be sent to the model."
|
||||
},
|
||||
"image_url": {
|
||||
"type": "string",
|
||||
"description": "(Optional) URL of the image content"
|
||||
|
|
@ -9241,6 +9282,10 @@
|
|||
"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"
|
||||
|
|
@ -9685,6 +9730,32 @@
|
|||
"title": "OpenAIResponseInputToolMCP",
|
||||
"description": "Model Context Protocol (MCP) tool configuration for OpenAI response inputs."
|
||||
},
|
||||
"OpenAIResponsePromptParam": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
"id": {
|
||||
"type": "string",
|
||||
"description": "Unique identifier of the prompt template"
|
||||
},
|
||||
"variables": {
|
||||
"type": "object",
|
||||
"additionalProperties": {
|
||||
"$ref": "#/components/schemas/OpenAIResponseInputMessageContent"
|
||||
},
|
||||
"description": "Dictionary of variable names to OpenAIResponseInputMessageContent structure for template substitution"
|
||||
},
|
||||
"version": {
|
||||
"type": "string",
|
||||
"description": "Version number of the prompt to use (defaults to latest if not specified)"
|
||||
}
|
||||
},
|
||||
"additionalProperties": false,
|
||||
"required": [
|
||||
"id"
|
||||
],
|
||||
"title": "OpenAIResponsePromptParam",
|
||||
"description": "Prompt object that is used for OpenAI responses."
|
||||
},
|
||||
"CreateOpenaiResponseRequest": {
|
||||
"type": "object",
|
||||
"properties": {
|
||||
|
|
@ -9706,6 +9777,10 @@
|
|||
"type": "string",
|
||||
"description": "The underlying LLM used for completions."
|
||||
},
|
||||
"prompt": {
|
||||
"$ref": "#/components/schemas/OpenAIResponsePromptParam",
|
||||
"description": "Prompt object with ID, version, and variables."
|
||||
},
|
||||
"instructions": {
|
||||
"type": "string"
|
||||
},
|
||||
|
|
@ -9794,6 +9869,10 @@
|
|||
"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"
|
||||
|
|
|
|||
72
docs/static/stainless-llama-stack-spec.yaml
vendored
72
docs/static/stainless-llama-stack-spec.yaml
vendored
|
|
@ -5574,11 +5574,44 @@ components:
|
|||
oneOf:
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentImage'
|
||||
- $ref: '#/components/schemas/OpenAIResponseInputMessageContentFile'
|
||||
discriminator:
|
||||
propertyName: type
|
||||
mapping:
|
||||
input_text: '#/components/schemas/OpenAIResponseInputMessageContentText'
|
||||
input_image: '#/components/schemas/OpenAIResponseInputMessageContentImage'
|
||||
input_file: '#/components/schemas/OpenAIResponseInputMessageContentFile'
|
||||
OpenAIResponseInputMessageContentFile:
|
||||
type: object
|
||||
properties:
|
||||
type:
|
||||
type: string
|
||||
const: input_file
|
||||
default: input_file
|
||||
description: >-
|
||||
The type of the input item. Always `input_file`.
|
||||
file_data:
|
||||
type: string
|
||||
description: >-
|
||||
The data of the file to be sent to the model.
|
||||
file_id:
|
||||
type: string
|
||||
description: >-
|
||||
(Optional) The ID of the file to be sent to the model.
|
||||
file_url:
|
||||
type: string
|
||||
description: >-
|
||||
The URL of the file to be sent to the model.
|
||||
filename:
|
||||
type: string
|
||||
description: >-
|
||||
The name of the file to be sent to the model.
|
||||
additionalProperties: false
|
||||
required:
|
||||
- type
|
||||
title: OpenAIResponseInputMessageContentFile
|
||||
description: >-
|
||||
File content for input messages in OpenAI response format.
|
||||
OpenAIResponseInputMessageContentImage:
|
||||
type: object
|
||||
properties:
|
||||
|
|
@ -5599,6 +5632,10 @@ components:
|
|||
default: input_image
|
||||
description: >-
|
||||
Content type identifier, always "input_image"
|
||||
file_id:
|
||||
type: string
|
||||
description: >-
|
||||
(Optional) The ID of the file to be sent to the model.
|
||||
image_url:
|
||||
type: string
|
||||
description: (Optional) URL of the image content
|
||||
|
|
@ -6998,6 +7035,10 @@ 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: >-
|
||||
|
|
@ -7315,6 +7356,29 @@ components:
|
|||
title: OpenAIResponseInputToolMCP
|
||||
description: >-
|
||||
Model Context Protocol (MCP) tool configuration for OpenAI response inputs.
|
||||
OpenAIResponsePromptParam:
|
||||
type: object
|
||||
properties:
|
||||
id:
|
||||
type: string
|
||||
description: Unique identifier of the prompt template
|
||||
variables:
|
||||
type: object
|
||||
additionalProperties:
|
||||
$ref: '#/components/schemas/OpenAIResponseInputMessageContent'
|
||||
description: >-
|
||||
Dictionary of variable names to OpenAIResponseInputMessageContent structure
|
||||
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:
|
||||
|
|
@ -7328,6 +7392,10 @@ 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:
|
||||
|
|
@ -7405,6 +7473,10 @@ 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: >-
|
||||
|
|
|
|||
|
|
@ -38,6 +38,7 @@ from .openai_responses import (
|
|||
OpenAIResponseInputTool,
|
||||
OpenAIResponseObject,
|
||||
OpenAIResponseObjectStream,
|
||||
OpenAIResponsePromptParam,
|
||||
OpenAIResponseText,
|
||||
)
|
||||
|
||||
|
|
@ -810,6 +811,7 @@ class Agents(Protocol):
|
|||
self,
|
||||
input: str | list[OpenAIResponseInput],
|
||||
model: str,
|
||||
prompt: OpenAIResponsePromptParam | None = None,
|
||||
instructions: str | None = None,
|
||||
previous_response_id: str | None = None,
|
||||
conversation: str | None = None,
|
||||
|
|
@ -831,6 +833,7 @@ class Agents(Protocol):
|
|||
|
||||
: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 conversation: (Optional) The ID of a conversation to add the response to. Must begin with 'conv_'. Input and output messages will be automatically added to the conversation.
|
||||
:param include: (Optional) Additional fields to include in the response.
|
||||
|
|
|
|||
|
|
@ -6,9 +6,10 @@
|
|||
|
||||
from typing import Annotated, Any, Literal
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
from pydantic import BaseModel, Field, model_validator
|
||||
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
|
||||
|
||||
|
|
@ -46,18 +47,44 @@ class OpenAIResponseInputMessageContentImage(BaseModel):
|
|||
|
||||
:param detail: Level of detail for image processing, can be "low", "high", or "auto"
|
||||
:param type: Content type identifier, always "input_image"
|
||||
:param file_id: (Optional) The ID of the file to be sent to the model.
|
||||
:param image_url: (Optional) URL of the image content
|
||||
"""
|
||||
|
||||
detail: Literal["low"] | Literal["high"] | Literal["auto"] = "auto"
|
||||
type: Literal["input_image"] = "input_image"
|
||||
# TODO: handle file_id
|
||||
file_id: str | None = None
|
||||
image_url: str | None = None
|
||||
|
||||
|
||||
# TODO: handle file content types
|
||||
@json_schema_type
|
||||
class OpenAIResponseInputMessageContentFile(BaseModel):
|
||||
"""File content for input messages in OpenAI response format.
|
||||
|
||||
:param type: The type of the input item. Always `input_file`.
|
||||
:param file_data: The data of the file to be sent to the model.
|
||||
:param file_id: (Optional) The ID of the file to be sent to the model.
|
||||
:param file_url: The URL of the file to be sent to the model.
|
||||
:param filename: The name of the file to be sent to the model.
|
||||
"""
|
||||
|
||||
type: Literal["input_file"] = "input_file"
|
||||
file_data: str | None = None
|
||||
file_id: str | None = None
|
||||
file_url: str | None = None
|
||||
filename: str | None = None
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_file_source(self) -> "OpenAIResponseInputMessageContentFile":
|
||||
if not any([self.file_id, self.file_data, self.file_url]):
|
||||
raise ValueError("At least one of 'file_id', 'file_data', or 'file_url' must be provided for file content")
|
||||
return self
|
||||
|
||||
|
||||
OpenAIResponseInputMessageContent = Annotated[
|
||||
OpenAIResponseInputMessageContentText | OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponseInputMessageContentText
|
||||
| OpenAIResponseInputMessageContentImage
|
||||
| OpenAIResponseInputMessageContentFile,
|
||||
Field(discriminator="type"),
|
||||
]
|
||||
register_schema(OpenAIResponseInputMessageContent, name="OpenAIResponseInputMessageContent")
|
||||
|
|
@ -348,6 +375,20 @@ 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 OpenAIResponseInputMessageContent structure for template substitution
|
||||
:param version: Version number of the prompt to use (defaults to latest if not specified)
|
||||
"""
|
||||
|
||||
id: str
|
||||
variables: dict[str, OpenAIResponseInputMessageContent] | None = None
|
||||
version: str | None = None
|
||||
|
||||
|
||||
@json_schema_type
|
||||
class OpenAIResponseText(BaseModel):
|
||||
"""Text response configuration for OpenAI responses.
|
||||
|
|
@ -537,6 +578,7 @@ 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
|
||||
|
|
@ -556,6 +598,7 @@ 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
|
||||
|
|
|
|||
|
|
@ -247,6 +247,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models: []
|
||||
shields:
|
||||
|
|
|
|||
|
|
@ -109,6 +109,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -105,6 +105,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -122,6 +122,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -112,6 +112,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -111,6 +111,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -100,6 +100,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models: []
|
||||
shields: []
|
||||
|
|
|
|||
|
|
@ -142,6 +142,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -87,6 +87,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models:
|
||||
- metadata: {}
|
||||
|
|
|
|||
|
|
@ -250,6 +250,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models: []
|
||||
shields:
|
||||
|
|
|
|||
|
|
@ -247,6 +247,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models: []
|
||||
shields:
|
||||
|
|
|
|||
|
|
@ -257,6 +257,10 @@ class RunConfigSettings(BaseModel):
|
|||
backend="sql_default",
|
||||
table_name="openai_conversations",
|
||||
).model_dump(exclude_none=True),
|
||||
"prompts": SqlStoreReference(
|
||||
backend="sql_default",
|
||||
table_name="prompts",
|
||||
).model_dump(exclude_none=True),
|
||||
}
|
||||
|
||||
storage_config = dict(
|
||||
|
|
|
|||
|
|
@ -115,6 +115,9 @@ storage:
|
|||
conversations:
|
||||
table_name: openai_conversations
|
||||
backend: sql_default
|
||||
prompts:
|
||||
table_name: prompts
|
||||
backend: sql_default
|
||||
registered_resources:
|
||||
models: []
|
||||
shields: []
|
||||
|
|
|
|||
|
|
@ -20,15 +20,17 @@ async def get_provider_impl(
|
|||
from .agents import MetaReferenceAgentsImpl
|
||||
|
||||
impl = MetaReferenceAgentsImpl(
|
||||
config,
|
||||
deps[Api.inference],
|
||||
deps[Api.vector_io],
|
||||
deps[Api.safety],
|
||||
deps[Api.tool_runtime],
|
||||
deps[Api.tool_groups],
|
||||
deps[Api.conversations],
|
||||
policy,
|
||||
telemetry_enabled,
|
||||
config=config,
|
||||
inference_api=deps[Api.inference],
|
||||
vector_io_api=deps[Api.vector_io],
|
||||
safety_api=deps[Api.safety],
|
||||
tool_runtime_api=deps[Api.tool_runtime],
|
||||
tool_groups_api=deps[Api.tool_groups],
|
||||
conversations_api=deps[Api.conversations],
|
||||
prompts_api=deps[Api.prompts],
|
||||
files_api=deps[Api.files],
|
||||
telemetry_enabled=Api.telemetry in deps,
|
||||
policy=policy,
|
||||
)
|
||||
await impl.initialize()
|
||||
return impl
|
||||
|
|
|
|||
|
|
@ -29,9 +29,10 @@ from llama_stack.apis.agents import (
|
|||
Turn,
|
||||
)
|
||||
from llama_stack.apis.agents.agents import ResponseGuardrail
|
||||
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.conversations import Conversations
|
||||
from llama_stack.apis.files import Files
|
||||
from llama_stack.apis.inference import (
|
||||
Inference,
|
||||
ToolConfig,
|
||||
|
|
@ -39,6 +40,7 @@ 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
|
||||
|
|
@ -66,6 +68,8 @@ class MetaReferenceAgentsImpl(Agents):
|
|||
tool_runtime_api: ToolRuntime,
|
||||
tool_groups_api: ToolGroups,
|
||||
conversations_api: Conversations,
|
||||
prompts_api: Prompts,
|
||||
files_api: Files,
|
||||
policy: list[AccessRule],
|
||||
telemetry_enabled: bool = False,
|
||||
):
|
||||
|
|
@ -77,7 +81,8 @@ class MetaReferenceAgentsImpl(Agents):
|
|||
self.tool_groups_api = tool_groups_api
|
||||
self.conversations_api = conversations_api
|
||||
self.telemetry_enabled = telemetry_enabled
|
||||
|
||||
self.prompts_api = prompts_api
|
||||
self.files_api = files_api
|
||||
self.in_memory_store = InmemoryKVStoreImpl()
|
||||
self.openai_responses_impl: OpenAIResponsesImpl | None = None
|
||||
self.policy = policy
|
||||
|
|
@ -94,6 +99,8 @@ class MetaReferenceAgentsImpl(Agents):
|
|||
vector_io_api=self.vector_io_api,
|
||||
safety_api=self.safety_api,
|
||||
conversations_api=self.conversations_api,
|
||||
prompts_api=self.prompts_api,
|
||||
files_api=self.files_api,
|
||||
)
|
||||
|
||||
async def create_agent(
|
||||
|
|
@ -329,6 +336,7 @@ class MetaReferenceAgentsImpl(Agents):
|
|||
self,
|
||||
input: str | list[OpenAIResponseInput],
|
||||
model: str,
|
||||
prompt: OpenAIResponsePromptParam | None = None,
|
||||
instructions: str | None = None,
|
||||
previous_response_id: str | None = None,
|
||||
conversation: str | None = None,
|
||||
|
|
@ -344,6 +352,7 @@ class MetaReferenceAgentsImpl(Agents):
|
|||
return await self.openai_responses_impl.create_openai_response(
|
||||
input,
|
||||
model,
|
||||
prompt,
|
||||
instructions,
|
||||
previous_response_id,
|
||||
conversation,
|
||||
|
|
|
|||
|
|
@ -4,6 +4,7 @@
|
|||
# This source code is licensed under the terms described in the LICENSE file in
|
||||
# the root directory of this source tree.
|
||||
|
||||
import re
|
||||
import time
|
||||
import uuid
|
||||
from collections.abc import AsyncIterator
|
||||
|
|
@ -17,11 +18,14 @@ from llama_stack.apis.agents.openai_responses import (
|
|||
ListOpenAIResponseObject,
|
||||
OpenAIDeleteResponseObject,
|
||||
OpenAIResponseInput,
|
||||
OpenAIResponseInputMessageContentFile,
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponseInputTool,
|
||||
OpenAIResponseMessage,
|
||||
OpenAIResponseObject,
|
||||
OpenAIResponseObjectStream,
|
||||
OpenAIResponsePromptParam,
|
||||
OpenAIResponseText,
|
||||
OpenAIResponseTextFormat,
|
||||
)
|
||||
|
|
@ -30,11 +34,17 @@ from llama_stack.apis.common.errors import (
|
|||
)
|
||||
from llama_stack.apis.conversations import Conversations
|
||||
from llama_stack.apis.conversations.conversations import ConversationItem
|
||||
from llama_stack.apis.files import Files
|
||||
from llama_stack.apis.inference import (
|
||||
Inference,
|
||||
OpenAIChatCompletionContentPartParam,
|
||||
OpenAIChatCompletionContentPartTextParam,
|
||||
OpenAIMessageParam,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
from llama_stack.apis.prompts import Prompts
|
||||
from llama_stack.apis.prompts.prompts import Prompt
|
||||
from llama_stack.apis.safety import Safety
|
||||
from llama_stack.apis.tools import ToolGroups, ToolRuntime
|
||||
from llama_stack.apis.vector_io import VectorIO
|
||||
|
|
@ -71,6 +81,8 @@ class OpenAIResponsesImpl:
|
|||
vector_io_api: VectorIO, # VectorIO
|
||||
safety_api: Safety,
|
||||
conversations_api: Conversations,
|
||||
prompts_api: Prompts,
|
||||
files_api: Files,
|
||||
):
|
||||
self.inference_api = inference_api
|
||||
self.tool_groups_api = tool_groups_api
|
||||
|
|
@ -84,6 +96,8 @@ class OpenAIResponsesImpl:
|
|||
tool_runtime_api=tool_runtime_api,
|
||||
vector_io_api=vector_io_api,
|
||||
)
|
||||
self.prompts_api = prompts_api
|
||||
self.files_api = files_api
|
||||
|
||||
async def _prepend_previous_response(
|
||||
self,
|
||||
|
|
@ -123,11 +137,13 @@ class OpenAIResponsesImpl:
|
|||
# Use stored messages directly and convert only new input
|
||||
message_adapter = TypeAdapter(list[OpenAIMessageParam])
|
||||
messages = message_adapter.validate_python(previous_response.messages)
|
||||
new_messages = await convert_response_input_to_chat_messages(input, previous_messages=messages)
|
||||
new_messages = await convert_response_input_to_chat_messages(
|
||||
input, previous_messages=messages, files_api=self.files_api
|
||||
)
|
||||
messages.extend(new_messages)
|
||||
else:
|
||||
# Backward compatibility: reconstruct from inputs
|
||||
messages = await convert_response_input_to_chat_messages(all_input)
|
||||
messages = await convert_response_input_to_chat_messages(all_input, files_api=self.files_api)
|
||||
|
||||
tool_context.recover_tools_from_previous_response(previous_response)
|
||||
elif conversation is not None:
|
||||
|
|
@ -139,7 +155,7 @@ class OpenAIResponsesImpl:
|
|||
all_input = input
|
||||
if not conversation_items.data:
|
||||
# First turn - just convert the new input
|
||||
messages = await convert_response_input_to_chat_messages(input)
|
||||
messages = await convert_response_input_to_chat_messages(input, files_api=self.files_api)
|
||||
else:
|
||||
if not stored_messages:
|
||||
all_input = conversation_items.data
|
||||
|
|
@ -155,14 +171,114 @@ class OpenAIResponsesImpl:
|
|||
all_input = input
|
||||
|
||||
messages = stored_messages or []
|
||||
new_messages = await convert_response_input_to_chat_messages(all_input, previous_messages=messages)
|
||||
new_messages = await convert_response_input_to_chat_messages(
|
||||
all_input, previous_messages=messages, files_api=self.files_api
|
||||
)
|
||||
messages.extend(new_messages)
|
||||
else:
|
||||
all_input = input
|
||||
messages = await convert_response_input_to_chat_messages(all_input)
|
||||
messages = await convert_response_input_to_chat_messages(all_input, files_api=self.files_api)
|
||||
|
||||
return all_input, messages, tool_context
|
||||
|
||||
async def _prepend_prompt(
|
||||
self,
|
||||
messages: list[OpenAIMessageParam],
|
||||
prompt_params: OpenAIResponsePromptParam,
|
||||
) -> Prompt:
|
||||
"""Prepend prompt template to messages, resolving text/image/file variables.
|
||||
|
||||
For text-only prompts: Inserts as system message
|
||||
For prompts with media: Inserts text as system message + media into first user message
|
||||
"""
|
||||
if not prompt_params or not prompt_params.id:
|
||||
return None
|
||||
|
||||
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 not cur_prompt:
|
||||
return None
|
||||
|
||||
cur_prompt_text = cur_prompt.prompt
|
||||
cur_prompt_variables = cur_prompt.variables
|
||||
|
||||
if not prompt_params.variables:
|
||||
messages.insert(0, OpenAISystemMessageParam(content=cur_prompt_text))
|
||||
return cur_prompt
|
||||
|
||||
# Validate that all provided variables exist in the prompt
|
||||
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}")
|
||||
|
||||
# Separate text and media variables
|
||||
text_substitutions = {}
|
||||
media_content_parts = []
|
||||
|
||||
for name, value in prompt_params.variables.items():
|
||||
# Text variable found
|
||||
if isinstance(value, OpenAIResponseInputMessageContentText):
|
||||
text_substitutions[name] = value.text
|
||||
|
||||
# Media variable found
|
||||
elif isinstance(value, OpenAIResponseInputMessageContentImage | OpenAIResponseInputMessageContentFile):
|
||||
# use existing converter to achieve OpenAI Chat Completion format
|
||||
from .utils import convert_response_content_to_chat_content
|
||||
|
||||
converted_parts = await convert_response_content_to_chat_content([value], files_api=self.files_api)
|
||||
media_content_parts.extend(converted_parts)
|
||||
|
||||
# Eg: {{product_photo}} becomes "[Image: product_photo]"
|
||||
# This gives the model textual context about what media exists in the prompt
|
||||
var_type = value.type.replace("input_", "").replace("_", " ").title()
|
||||
text_substitutions[name] = f"[{var_type}: {name}]"
|
||||
|
||||
def replace_variable(match: re.Match[str]) -> str:
|
||||
var_name = match.group(1).strip()
|
||||
return str(text_substitutions.get(var_name, match.group(0)))
|
||||
|
||||
pattern = r"\{\{\s*(\w+)\s*\}\}"
|
||||
resolved_prompt_text = re.sub(pattern, replace_variable, cur_prompt_text)
|
||||
|
||||
# Insert system message with resolved text
|
||||
messages.insert(0, OpenAISystemMessageParam(content=resolved_prompt_text))
|
||||
|
||||
# If we have media, prepend to first user message
|
||||
if media_content_parts:
|
||||
self._prepend_media_into_first_user_message(messages, media_content_parts)
|
||||
|
||||
return cur_prompt
|
||||
|
||||
def _prepend_media_into_first_user_message(
|
||||
self, messages: list[OpenAIMessageParam], media_parts: list[OpenAIChatCompletionContentPartParam]
|
||||
) -> None:
|
||||
"""Prepend media content parts into the first user message."""
|
||||
|
||||
# Find first user message (skip the system message we just added)
|
||||
first_user_msg_index = None
|
||||
for i, message in enumerate(messages):
|
||||
if isinstance(message, OpenAIUserMessageParam):
|
||||
first_user_msg_index = i
|
||||
break
|
||||
|
||||
if first_user_msg_index is not None:
|
||||
user_msg = messages[first_user_msg_index]
|
||||
|
||||
# Convert string content to parts if needed, otherwise use existing parts directly
|
||||
if isinstance(user_msg.content, str):
|
||||
existing_parts = [OpenAIChatCompletionContentPartTextParam(text=user_msg.content)]
|
||||
else:
|
||||
existing_parts = user_msg.content
|
||||
|
||||
# Prepend media before user's content
|
||||
combined_parts = media_parts + existing_parts
|
||||
|
||||
messages[first_user_msg_index] = OpenAIUserMessageParam(content=combined_parts, name=user_msg.name)
|
||||
else:
|
||||
# No user message exists - append one with just media
|
||||
messages.append(OpenAIUserMessageParam(content=media_parts))
|
||||
|
||||
async def get_openai_response(
|
||||
self,
|
||||
response_id: str,
|
||||
|
|
@ -239,6 +355,7 @@ class OpenAIResponsesImpl:
|
|||
self,
|
||||
input: str | list[OpenAIResponseInput],
|
||||
model: str,
|
||||
prompt: OpenAIResponsePromptParam | None = None,
|
||||
instructions: str | None = None,
|
||||
previous_response_id: str | None = None,
|
||||
conversation: str | None = None,
|
||||
|
|
@ -269,6 +386,7 @@ class OpenAIResponsesImpl:
|
|||
input=input,
|
||||
conversation=conversation,
|
||||
model=model,
|
||||
prompt=prompt,
|
||||
instructions=instructions,
|
||||
previous_response_id=previous_response_id,
|
||||
store=store,
|
||||
|
|
@ -314,6 +432,7 @@ class OpenAIResponsesImpl:
|
|||
self,
|
||||
input: str | list[OpenAIResponseInput],
|
||||
model: str,
|
||||
prompt: OpenAIResponsePromptParam | None = None,
|
||||
instructions: str | None = None,
|
||||
previous_response_id: str | None = None,
|
||||
conversation: str | None = None,
|
||||
|
|
@ -332,6 +451,9 @@ class OpenAIResponsesImpl:
|
|||
if instructions:
|
||||
messages.insert(0, OpenAISystemMessageParam(content=instructions))
|
||||
|
||||
# Prepend reusable prompt (if provided)
|
||||
prompt_obj = await self._prepend_prompt(messages, prompt)
|
||||
|
||||
# Structured outputs
|
||||
response_format = await convert_response_text_to_chat_response_format(text)
|
||||
|
||||
|
|
@ -354,6 +476,7 @@ 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,
|
||||
|
|
|
|||
|
|
@ -65,6 +65,7 @@ from llama_stack.apis.inference import (
|
|||
OpenAIChoice,
|
||||
OpenAIMessageParam,
|
||||
)
|
||||
from llama_stack.apis.prompts.prompts import Prompt
|
||||
from llama_stack.log import get_logger
|
||||
from llama_stack.providers.utils.inference.prompt_adapter import interleaved_content_as_str
|
||||
from llama_stack.providers.utils.telemetry import tracing
|
||||
|
|
@ -107,6 +108,7 @@ 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
|
||||
|
|
@ -118,6 +120,7 @@ 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
|
||||
|
|
@ -175,6 +178,7 @@ class StreamingResponseOrchestrator:
|
|||
object="response",
|
||||
status=status,
|
||||
output=self._clone_outputs(outputs),
|
||||
prompt=self.prompt,
|
||||
text=self.text,
|
||||
tools=self.ctx.available_tools(),
|
||||
error=error,
|
||||
|
|
|
|||
|
|
@ -5,6 +5,7 @@
|
|||
# the root directory of this source tree.
|
||||
|
||||
import asyncio
|
||||
import base64
|
||||
import re
|
||||
import uuid
|
||||
|
||||
|
|
@ -14,6 +15,7 @@ from llama_stack.apis.agents.openai_responses import (
|
|||
OpenAIResponseInput,
|
||||
OpenAIResponseInputFunctionToolCallOutput,
|
||||
OpenAIResponseInputMessageContent,
|
||||
OpenAIResponseInputMessageContentFile,
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponseInputTool,
|
||||
|
|
@ -27,6 +29,7 @@ from llama_stack.apis.agents.openai_responses import (
|
|||
OpenAIResponseOutputMessageMCPListTools,
|
||||
OpenAIResponseText,
|
||||
)
|
||||
from llama_stack.apis.files import Files
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionContentPartImageParam,
|
||||
|
|
@ -36,6 +39,8 @@ from llama_stack.apis.inference import (
|
|||
OpenAIChatCompletionToolCallFunction,
|
||||
OpenAIChoice,
|
||||
OpenAIDeveloperMessageParam,
|
||||
OpenAIFile,
|
||||
OpenAIFileFile,
|
||||
OpenAIImageURL,
|
||||
OpenAIJSONSchema,
|
||||
OpenAIMessageParam,
|
||||
|
|
@ -50,6 +55,49 @@ from llama_stack.apis.inference import (
|
|||
from llama_stack.apis.safety import Safety
|
||||
|
||||
|
||||
async def extract_file_content(file_id: str, files_api: Files) -> bytes:
|
||||
"""
|
||||
Retrieve file content directly using the Files API.
|
||||
|
||||
:param file_id: The file identifier (e.g., "file-abc123")
|
||||
:param files_api: Files API instance
|
||||
:returns: Raw file content as bytes
|
||||
:raises: ValueError if file cannot be retrieved
|
||||
"""
|
||||
try:
|
||||
response = await files_api.openai_retrieve_file_content(file_id)
|
||||
if hasattr(response, "body"):
|
||||
return response.body
|
||||
elif hasattr(response, "content"):
|
||||
return response.content
|
||||
else:
|
||||
raise AttributeError(f"Response object has no 'body' or 'content' attribute. Type: {type(response)}")
|
||||
except Exception as e:
|
||||
raise ValueError(f"Failed to retrieve file content for file_id '{file_id}': {str(e)}") from e
|
||||
|
||||
|
||||
def get_mime_type_from_filename(filename: str | None) -> str:
|
||||
"""
|
||||
Determine MIME type from filename extension.
|
||||
|
||||
:param filename: The filename to analyze
|
||||
:returns: MIME type string (defaults to "application/octet-stream" if unknown)
|
||||
"""
|
||||
if not filename:
|
||||
return "application/octet-stream"
|
||||
|
||||
filename_lower = filename.lower()
|
||||
if filename_lower.endswith(".pdf"):
|
||||
return "application/pdf"
|
||||
elif filename_lower.endswith((".png", ".jpg", ".jpeg")):
|
||||
ext = filename_lower.split(".")[-1]
|
||||
return f"image/{ext.replace('jpg', 'jpeg')}"
|
||||
elif filename_lower.endswith(".txt"):
|
||||
return "text/plain"
|
||||
else:
|
||||
return "application/octet-stream"
|
||||
|
||||
|
||||
async def convert_chat_choice_to_response_message(
|
||||
choice: OpenAIChoice,
|
||||
citation_files: dict[str, str] | None = None,
|
||||
|
|
@ -79,11 +127,15 @@ async def convert_chat_choice_to_response_message(
|
|||
|
||||
async def convert_response_content_to_chat_content(
|
||||
content: (str | list[OpenAIResponseInputMessageContent] | list[OpenAIResponseOutputMessageContent]),
|
||||
files_api: Files,
|
||||
) -> str | list[OpenAIChatCompletionContentPartParam]:
|
||||
"""
|
||||
Convert the content parts from an OpenAI Response API request into OpenAI Chat Completion content parts.
|
||||
|
||||
The content schemas of each API look similar, but are not exactly the same.
|
||||
|
||||
:param content: The content to convert
|
||||
:param files_api: Files API for resolving file_id to raw file content (required)
|
||||
"""
|
||||
if isinstance(content, str):
|
||||
return content
|
||||
|
|
@ -95,9 +147,69 @@ async def convert_response_content_to_chat_content(
|
|||
elif isinstance(content_part, OpenAIResponseOutputMessageContentOutputText):
|
||||
converted_parts.append(OpenAIChatCompletionContentPartTextParam(text=content_part.text))
|
||||
elif isinstance(content_part, OpenAIResponseInputMessageContentImage):
|
||||
detail = content_part.detail
|
||||
|
||||
if content_part.image_url:
|
||||
image_url = OpenAIImageURL(url=content_part.image_url, detail=content_part.detail)
|
||||
image_url = OpenAIImageURL(url=content_part.image_url, detail=detail)
|
||||
converted_parts.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
|
||||
elif content_part.file_id:
|
||||
file_content = await extract_file_content(content_part.file_id, files_api)
|
||||
encoded_content = base64.b64encode(file_content).decode("utf-8")
|
||||
data_url = f"data:image/png;base64,{encoded_content}"
|
||||
image_url = OpenAIImageURL(url=data_url, detail=detail)
|
||||
converted_parts.append(OpenAIChatCompletionContentPartImageParam(image_url=image_url))
|
||||
else:
|
||||
raise ValueError(
|
||||
f"Image content must have either 'image_url' or 'file_id'. "
|
||||
f"Got image_url={content_part.image_url}, file_id={content_part.file_id}"
|
||||
)
|
||||
elif isinstance(content_part, OpenAIResponseInputMessageContentFile):
|
||||
file_data = getattr(content_part, "file_data", None)
|
||||
file_id = getattr(content_part, "file_id", None)
|
||||
file_url = getattr(content_part, "file_url", None)
|
||||
filename = getattr(content_part, "filename", None)
|
||||
|
||||
if not any([file_id, file_data, file_url]):
|
||||
raise ValueError(
|
||||
f"File content must have at least one of 'file_id', 'file_data', or 'file_url'. "
|
||||
f"Got file_id={file_id}, file_data={'<data>' if file_data else None}, file_url={file_url}"
|
||||
)
|
||||
|
||||
resolved_file_data = None
|
||||
|
||||
if file_id:
|
||||
file_content = await extract_file_content(file_id, files_api)
|
||||
|
||||
# If filename is not provided, fetch it from the Files API
|
||||
if not filename:
|
||||
file_metadata = await files_api.openai_retrieve_file(file_id)
|
||||
filename = file_metadata.filename
|
||||
|
||||
# Determine MIME type and encode as data URL
|
||||
mime_type = get_mime_type_from_filename(filename)
|
||||
base64_content = base64.b64encode(file_content).decode("utf-8")
|
||||
resolved_file_data = f"data:{mime_type};base64,{base64_content}"
|
||||
|
||||
elif file_data:
|
||||
# If file_data provided directly
|
||||
if file_data.startswith("data:"):
|
||||
resolved_file_data = file_data
|
||||
else:
|
||||
# Raw base64 data, wrap in data URL format
|
||||
mime_type = get_mime_type_from_filename(filename)
|
||||
resolved_file_data = f"data:{mime_type};base64,{file_data}"
|
||||
|
||||
elif file_url:
|
||||
resolved_file_data = file_url
|
||||
|
||||
converted_parts.append(
|
||||
OpenAIFile(
|
||||
file=OpenAIFileFile(
|
||||
file_data=resolved_file_data,
|
||||
filename=filename,
|
||||
)
|
||||
)
|
||||
)
|
||||
elif isinstance(content_part, str):
|
||||
converted_parts.append(OpenAIChatCompletionContentPartTextParam(text=content_part))
|
||||
else:
|
||||
|
|
@ -110,12 +222,14 @@ async def convert_response_content_to_chat_content(
|
|||
async def convert_response_input_to_chat_messages(
|
||||
input: str | list[OpenAIResponseInput],
|
||||
previous_messages: list[OpenAIMessageParam] | None = None,
|
||||
files_api: Files | None = None,
|
||||
) -> list[OpenAIMessageParam]:
|
||||
"""
|
||||
Convert the input from an OpenAI Response API request into OpenAI Chat Completion messages.
|
||||
|
||||
:param input: The input to convert
|
||||
:param previous_messages: Optional previous messages to check for function_call references
|
||||
:param files_api: Files API for resolving file_id to raw file content (optional, required for file/image content)
|
||||
"""
|
||||
messages: list[OpenAIMessageParam] = []
|
||||
if isinstance(input, list):
|
||||
|
|
@ -173,7 +287,7 @@ async def convert_response_input_to_chat_messages(
|
|||
# these are handled by the responses impl itself and not pass through to chat completions
|
||||
pass
|
||||
else:
|
||||
content = await convert_response_content_to_chat_content(input_item.content)
|
||||
content = await convert_response_content_to_chat_content(input_item.content, files_api)
|
||||
message_type = await get_message_type_by_role(input_item.role)
|
||||
if message_type is None:
|
||||
raise ValueError(
|
||||
|
|
|
|||
|
|
@ -35,6 +35,8 @@ def available_providers() -> list[ProviderSpec]:
|
|||
Api.tool_runtime,
|
||||
Api.tool_groups,
|
||||
Api.conversations,
|
||||
Api.prompts,
|
||||
Api.files,
|
||||
],
|
||||
description="Meta's reference implementation of an agent system that can use tools, access vector databases, and perform complex reasoning tasks.",
|
||||
),
|
||||
|
|
|
|||
|
|
@ -16,7 +16,9 @@ from llama_stack.apis.agents import (
|
|||
)
|
||||
from llama_stack.apis.common.responses import PaginatedResponse
|
||||
from llama_stack.apis.conversations import Conversations
|
||||
from llama_stack.apis.files import Files
|
||||
from llama_stack.apis.inference import Inference
|
||||
from llama_stack.apis.prompts import Prompts
|
||||
from llama_stack.apis.safety import Safety
|
||||
from llama_stack.apis.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolRuntime
|
||||
from llama_stack.apis.vector_io import VectorIO
|
||||
|
|
@ -49,6 +51,8 @@ def mock_apis():
|
|||
"tool_runtime_api": AsyncMock(spec=ToolRuntime),
|
||||
"tool_groups_api": AsyncMock(spec=ToolGroups),
|
||||
"conversations_api": AsyncMock(spec=Conversations),
|
||||
"prompts_api": AsyncMock(spec=Prompts),
|
||||
"files_api": AsyncMock(spec=Files),
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -81,7 +85,9 @@ async def agents_impl(config, mock_apis):
|
|||
mock_apis["tool_runtime_api"],
|
||||
mock_apis["tool_groups_api"],
|
||||
mock_apis["conversations_api"],
|
||||
[],
|
||||
mock_apis["prompts_api"],
|
||||
mock_apis["files_api"],
|
||||
[], # policy (empty list for tests)
|
||||
)
|
||||
await impl.initialize()
|
||||
yield impl
|
||||
|
|
|
|||
|
|
@ -40,6 +40,7 @@ from llama_stack.apis.inference import (
|
|||
OpenAIResponseFormatJSONSchema,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
from llama_stack.apis.prompts import Prompt
|
||||
from llama_stack.apis.tools.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
|
||||
from llama_stack.core.access_control.access_control import default_policy
|
||||
from llama_stack.core.storage.datatypes import ResponsesStoreReference, SqliteSqlStoreConfig
|
||||
|
|
@ -97,6 +98,19 @@ def mock_safety_api():
|
|||
return safety_api
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_prompts_api():
|
||||
prompts_api = AsyncMock()
|
||||
return prompts_api
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_files_api():
|
||||
"""Mock files API for testing."""
|
||||
files_api = AsyncMock()
|
||||
return files_api
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def openai_responses_impl(
|
||||
mock_inference_api,
|
||||
|
|
@ -106,6 +120,8 @@ def openai_responses_impl(
|
|||
mock_vector_io_api,
|
||||
mock_safety_api,
|
||||
mock_conversations_api,
|
||||
mock_prompts_api,
|
||||
mock_files_api,
|
||||
):
|
||||
return OpenAIResponsesImpl(
|
||||
inference_api=mock_inference_api,
|
||||
|
|
@ -115,6 +131,8 @@ def openai_responses_impl(
|
|||
vector_io_api=mock_vector_io_api,
|
||||
safety_api=mock_safety_api,
|
||||
conversations_api=mock_conversations_api,
|
||||
prompts_api=mock_prompts_api,
|
||||
files_api=mock_files_api,
|
||||
)
|
||||
|
||||
|
||||
|
|
@ -498,7 +516,7 @@ async def test_create_openai_response_with_tool_call_function_arguments_none(ope
|
|||
mock_inference_api.openai_chat_completion.return_value = fake_stream_toolcall()
|
||||
|
||||
|
||||
async def test_create_openai_response_with_multiple_messages(openai_responses_impl, mock_inference_api):
|
||||
async def test_create_openai_response_with_multiple_messages(openai_responses_impl, mock_inference_api, mock_files_api):
|
||||
"""Test creating an OpenAI response with multiple messages."""
|
||||
# Setup
|
||||
input_messages = [
|
||||
|
|
@ -709,7 +727,7 @@ async def test_create_openai_response_with_instructions(openai_responses_impl, m
|
|||
|
||||
|
||||
async def test_create_openai_response_with_instructions_and_multiple_messages(
|
||||
openai_responses_impl, mock_inference_api
|
||||
openai_responses_impl, mock_inference_api, mock_files_api
|
||||
):
|
||||
# Setup
|
||||
input_messages = [
|
||||
|
|
@ -1169,3 +1187,657 @@ 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 (
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
|
||||
prompt_params_with_version_1 = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"area_name": OpenAIResponseInputMessageContentText(text="geography"),
|
||||
"company_name": OpenAIResponseInputMessageContentText(text="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.args[0].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
|
||||
|
||||
|
||||
async def test_prepend_prompt_successful_without_variables(openai_responses_impl, mock_prompts_api):
|
||||
"""Test prepend_prompt function without variables."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="You are a helpful assistant. Always provide accurate information.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=[],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import OpenAIResponsePromptParam
|
||||
from llama_stack.apis.inference import OpenAISystemMessageParam, OpenAIUserMessageParam
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(id=prompt_id, version="1")
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Hello")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
mock_prompts_api.get_prompt.assert_called_once_with(prompt_id, 1)
|
||||
|
||||
# Check that prompt was returned
|
||||
assert result == prompt
|
||||
|
||||
# Check that system message was prepended
|
||||
assert len(messages) == 2
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
assert messages[0].content == "You are a helpful assistant. Always provide accurate information."
|
||||
|
||||
|
||||
async def test_prepend_prompt_no_version_specified(openai_responses_impl, mock_prompts_api):
|
||||
"""Test prepend_prompt function when no version is specified (should use None)."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Default prompt text.",
|
||||
prompt_id=prompt_id,
|
||||
version=3,
|
||||
variables=[],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import OpenAIResponsePromptParam
|
||||
from llama_stack.apis.inference import OpenAIUserMessageParam
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(id=prompt_id) # No version specified
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Test")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
mock_prompts_api.get_prompt.assert_called_once_with(prompt_id, None)
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
|
||||
|
||||
async def test_prepend_prompt_invalid_variable(openai_responses_impl, mock_prompts_api):
|
||||
"""Test error handling in prepend_prompt function when prompt parameters contain invalid variables."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="You are a {{ role }} assistant.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["role"], # Only "role" is valid
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import OpenAIUserMessageParam
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"role": OpenAIResponseInputMessageContentText(text="helpful"),
|
||||
"company": OpenAIResponseInputMessageContentText(
|
||||
text="Dummy Company"
|
||||
), # company is not in prompt.variables
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Test prompt")]
|
||||
|
||||
# Execute - should raise ValueError for invalid variable
|
||||
with pytest.raises(ValueError, match="Variable company not found in prompt"):
|
||||
await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
mock_prompts_api.get_prompt.assert_called_once_with(prompt_id, 1)
|
||||
|
||||
|
||||
async def test_prepend_prompt_not_found(openai_responses_impl, mock_prompts_api):
|
||||
"""Test prepend_prompt function when prompt is not found."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_nonexistent"
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import OpenAIResponsePromptParam
|
||||
from llama_stack.apis.inference import OpenAIUserMessageParam
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(id=prompt_id, version="1")
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = None # Prompt not found
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Test prompt")]
|
||||
initial_length = len(messages)
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
mock_prompts_api.get_prompt.assert_called_once_with(prompt_id, 1)
|
||||
|
||||
# Should return None when prompt not found
|
||||
assert result is None
|
||||
|
||||
# Messages should not be modified
|
||||
assert len(messages) == initial_length
|
||||
assert messages[0].content == "Test prompt"
|
||||
|
||||
|
||||
async def test_prepend_prompt_no_params(openai_responses_impl, mock_prompts_api):
|
||||
"""Test handling in prepend_prompt function when prompt_params is None."""
|
||||
# Setup
|
||||
from llama_stack.apis.inference import OpenAIUserMessageParam
|
||||
|
||||
messages = [OpenAIUserMessageParam(content="Test")]
|
||||
initial_length = len(messages)
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, None)
|
||||
|
||||
# Verify
|
||||
mock_prompts_api.get_prompt.assert_not_called()
|
||||
|
||||
# Should return None when no prompt params
|
||||
assert result is None
|
||||
|
||||
# Messages should not be modified
|
||||
assert len(messages) == initial_length
|
||||
|
||||
|
||||
async def test_prepend_prompt_variable_substitution(openai_responses_impl, mock_prompts_api):
|
||||
"""Test complex variable substitution with multiple occurrences and special characters in prepend_prompt function."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
|
||||
# Support all whitespace variations: {{name}}, {{ name }}, {{ name}}, {{name }}, etc.
|
||||
prompt = Prompt(
|
||||
prompt="Hello {{name}}! You are working at {{ company}}. Your role is {{role}} at {{company}}. Remember, {{ name }}, to be {{ tone }}.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["name", "company", "role", "tone"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import OpenAISystemMessageParam, OpenAIUserMessageParam
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"name": OpenAIResponseInputMessageContentText(text="Alice"),
|
||||
"company": OpenAIResponseInputMessageContentText(text="Dummy Company"),
|
||||
"role": OpenAIResponseInputMessageContentText(text="AI Assistant"),
|
||||
"tone": OpenAIResponseInputMessageContentText(text="professional"),
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Test")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
expected_content = "Hello Alice! You are working at Dummy Company. Your role is AI Assistant at Dummy Company. Remember, Alice, to be professional."
|
||||
assert messages[0].content == expected_content
|
||||
|
||||
|
||||
async def test_prepend_prompt_with_image_variable(openai_responses_impl, mock_prompts_api, mock_files_api):
|
||||
"""Test prepend_prompt with image variable - should create placeholder in system message and inject image into user message."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Analyze this {{product_image}} and describe what you see.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["product_image"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIChatCompletionContentPartImageParam,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
|
||||
# Mock file content
|
||||
mock_file_content = b"fake_image_data"
|
||||
mock_files_api.openai_retrieve_file_content.return_value = type("obj", (object,), {"body": mock_file_content})()
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"product_image": OpenAIResponseInputMessageContentImage(
|
||||
file_id="file-abc123",
|
||||
detail="high",
|
||||
)
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="What do you think?")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
|
||||
# Check system message has placeholder
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
assert messages[0].content == "Analyze this [Image: product_image] and describe what you see."
|
||||
|
||||
# Check user message has image prepended
|
||||
assert isinstance(messages[1], OpenAIUserMessageParam)
|
||||
assert isinstance(messages[1].content, list)
|
||||
assert len(messages[1].content) == 2 # Image + original text
|
||||
|
||||
# First part should be image with data URL
|
||||
assert isinstance(messages[1].content[0], OpenAIChatCompletionContentPartImageParam)
|
||||
assert messages[1].content[0].image_url.url.startswith("data:image/")
|
||||
assert messages[1].content[0].image_url.detail == "high"
|
||||
|
||||
# Second part should be original text
|
||||
assert messages[1].content[1].text == "What do you think?"
|
||||
|
||||
|
||||
async def test_prepend_prompt_with_file_variable(openai_responses_impl, mock_prompts_api, mock_files_api):
|
||||
"""Test prepend_prompt with file variable - should create placeholder in system message and inject file into user message."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Review the document {{contract_file}} and summarize key points.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["contract_file"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentFile,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.files import OpenAIFileObject
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIFile,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
|
||||
# Mock file retrieval
|
||||
mock_file_content = b"fake_pdf_content"
|
||||
mock_files_api.openai_retrieve_file_content.return_value = type("obj", (object,), {"body": mock_file_content})()
|
||||
mock_files_api.openai_retrieve_file.return_value = OpenAIFileObject(
|
||||
object="file",
|
||||
id="file-contract-789",
|
||||
bytes=len(mock_file_content),
|
||||
created_at=1234567890,
|
||||
expires_at=1234567890,
|
||||
filename="contract.pdf",
|
||||
purpose="assistants",
|
||||
)
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"contract_file": OpenAIResponseInputMessageContentFile(
|
||||
file_id="file-contract-789",
|
||||
filename="contract.pdf",
|
||||
)
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Please review this.")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
|
||||
# Check system message has placeholder
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
assert messages[0].content == "Review the document [File: contract_file] and summarize key points."
|
||||
|
||||
# Check user message has file prepended
|
||||
assert isinstance(messages[1], OpenAIUserMessageParam)
|
||||
assert isinstance(messages[1].content, list)
|
||||
assert len(messages[1].content) == 2 # File + original text
|
||||
|
||||
# First part should be file with data URL (not file_id)
|
||||
assert isinstance(messages[1].content[0], OpenAIFile)
|
||||
assert messages[1].content[0].file.file_data.startswith("data:application/pdf;base64,")
|
||||
assert messages[1].content[0].file.filename == "contract.pdf"
|
||||
# file_id should NOT be set in the OpenAI request
|
||||
assert messages[1].content[0].file.file_id is None
|
||||
|
||||
# Second part should be original text
|
||||
assert messages[1].content[1].text == "Please review this."
|
||||
|
||||
|
||||
async def test_prepend_prompt_with_mixed_variables(openai_responses_impl, mock_prompts_api, mock_files_api):
|
||||
"""Test prepend_prompt with text, image, and file variables mixed together."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Hello {{name}}! Analyze {{photo}} and review {{document}}. Provide insights for {{company}}.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["name", "photo", "document", "company"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentFile,
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponseInputMessageContentText,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.files import OpenAIFileObject
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIChatCompletionContentPartImageParam,
|
||||
OpenAIFile,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
|
||||
# Mock file retrieval for document
|
||||
mock_file_content = b"fake_doc_content"
|
||||
mock_files_api.openai_retrieve_file_content.return_value = type("obj", (object,), {"body": mock_file_content})()
|
||||
mock_files_api.openai_retrieve_file.return_value = OpenAIFileObject(
|
||||
object="file",
|
||||
id="file-doc-456",
|
||||
bytes=len(mock_file_content),
|
||||
created_at=1234567890,
|
||||
expires_at=1234567890,
|
||||
filename="doc.pdf",
|
||||
purpose="assistants",
|
||||
)
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"name": OpenAIResponseInputMessageContentText(text="Alice"),
|
||||
"photo": OpenAIResponseInputMessageContentImage(file_id="file-photo-123", detail="auto"),
|
||||
"document": OpenAIResponseInputMessageContentFile(file_id="file-doc-456", filename="doc.pdf"),
|
||||
"company": OpenAIResponseInputMessageContentText(text="Acme Corp"),
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="Here's my question.")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
|
||||
# Check system message has text and placeholders
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
expected_system = "Hello Alice! Analyze [Image: photo] and review [File: document]. Provide insights for Acme Corp."
|
||||
assert messages[0].content == expected_system
|
||||
|
||||
# Check user message has media prepended (2 media items + original text)
|
||||
assert isinstance(messages[1], OpenAIUserMessageParam)
|
||||
assert isinstance(messages[1].content, list)
|
||||
assert len(messages[1].content) == 3 # Image + File + original text
|
||||
|
||||
# First part should be image with data URL
|
||||
assert isinstance(messages[1].content[0], OpenAIChatCompletionContentPartImageParam)
|
||||
assert messages[1].content[0].image_url.url.startswith("data:image/")
|
||||
|
||||
# Second part should be file with data URL
|
||||
assert isinstance(messages[1].content[1], OpenAIFile)
|
||||
assert messages[1].content[1].file.file_data.startswith("data:application/pdf;base64,")
|
||||
assert messages[1].content[1].file.filename == "doc.pdf"
|
||||
assert messages[1].content[1].file.file_id is None # file_id should NOT be sent
|
||||
|
||||
# Third part should be original text
|
||||
assert messages[1].content[2].text == "Here's my question."
|
||||
|
||||
|
||||
async def test_prepend_prompt_with_image_using_image_url(openai_responses_impl, mock_prompts_api):
|
||||
"""Test prepend_prompt with image variable using image_url instead of file_id."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Describe {{screenshot}}.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["screenshot"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIChatCompletionContentPartImageParam,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={
|
||||
"screenshot": OpenAIResponseInputMessageContentImage(
|
||||
image_url="https://example.com/screenshot.png",
|
||||
detail="low",
|
||||
)
|
||||
},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages
|
||||
messages = [OpenAIUserMessageParam(content="What is this?")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 2
|
||||
|
||||
# Check system message has placeholder
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
assert messages[0].content == "Describe [Image: screenshot]."
|
||||
|
||||
# Check user message has image with URL
|
||||
assert isinstance(messages[1], OpenAIUserMessageParam)
|
||||
assert isinstance(messages[1].content, list)
|
||||
|
||||
# Image should use the provided URL
|
||||
assert isinstance(messages[1].content[0], OpenAIChatCompletionContentPartImageParam)
|
||||
assert messages[1].content[0].image_url.url == "https://example.com/screenshot.png"
|
||||
assert messages[1].content[0].image_url.detail == "low"
|
||||
|
||||
|
||||
async def test_prepend_prompt_with_media_no_user_message(openai_responses_impl, mock_prompts_api, mock_files_api):
|
||||
"""Test prepend_prompt with media when there's no existing user message - should create one."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Analyze {{image}}.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["image"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import (
|
||||
OpenAIAssistantMessageParam,
|
||||
OpenAIChatCompletionContentPartImageParam,
|
||||
OpenAISystemMessageParam,
|
||||
OpenAIUserMessageParam,
|
||||
)
|
||||
|
||||
# Mock file content
|
||||
mock_file_content = b"fake_image_data"
|
||||
mock_files_api.openai_retrieve_file_content.return_value = type("obj", (object,), {"body": mock_file_content})()
|
||||
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={"image": OpenAIResponseInputMessageContentImage(file_id="file-img-999")},
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
|
||||
# Initial messages - only assistant message, no user message
|
||||
messages = [OpenAIAssistantMessageParam(content="Previous response")]
|
||||
|
||||
# Execute
|
||||
result = await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
||||
# Verify
|
||||
assert result == prompt
|
||||
assert len(messages) == 3 # System + Assistant + New User
|
||||
|
||||
# Check system message
|
||||
assert isinstance(messages[0], OpenAISystemMessageParam)
|
||||
assert messages[0].content == "Analyze [Image: image]."
|
||||
|
||||
# Original assistant message should still be there
|
||||
assert isinstance(messages[1], OpenAIAssistantMessageParam)
|
||||
assert messages[1].content == "Previous response"
|
||||
|
||||
# New user message with just the image should be appended
|
||||
assert isinstance(messages[2], OpenAIUserMessageParam)
|
||||
assert isinstance(messages[2].content, list)
|
||||
assert len(messages[2].content) == 1
|
||||
assert isinstance(messages[2].content[0], OpenAIChatCompletionContentPartImageParam)
|
||||
assert messages[2].content[0].image_url.url.startswith("data:image/")
|
||||
|
||||
|
||||
async def test_prepend_prompt_image_variable_missing_required_fields(openai_responses_impl, mock_prompts_api):
|
||||
"""Test prepend_prompt with image variable that has neither file_id nor image_url - should raise error."""
|
||||
# Setup
|
||||
prompt_id = "pmpt_1234567890abcdef1234567890abcdef1234567890abcdef"
|
||||
prompt = Prompt(
|
||||
prompt="Analyze {{bad_image}}.",
|
||||
prompt_id=prompt_id,
|
||||
version=1,
|
||||
variables=["bad_image"],
|
||||
is_default=True,
|
||||
)
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
OpenAIResponseInputMessageContentImage,
|
||||
OpenAIResponsePromptParam,
|
||||
)
|
||||
from llama_stack.apis.inference import OpenAIUserMessageParam
|
||||
|
||||
# Create image content with neither file_id nor image_url
|
||||
prompt_params = OpenAIResponsePromptParam(
|
||||
id=prompt_id,
|
||||
version="1",
|
||||
variables={"bad_image": OpenAIResponseInputMessageContentImage()}, # No file_id or image_url
|
||||
)
|
||||
|
||||
mock_prompts_api.get_prompt.return_value = prompt
|
||||
messages = [OpenAIUserMessageParam(content="Test")]
|
||||
|
||||
# Execute - should raise ValueError
|
||||
with pytest.raises(ValueError, match="Image content must have either 'image_url' or 'file_id'"):
|
||||
await openai_responses_impl._prepend_prompt(messages, prompt_params)
|
||||
|
|
|
|||
|
|
@ -39,6 +39,8 @@ def responses_impl_with_conversations(
|
|||
mock_vector_io_api,
|
||||
mock_conversations_api,
|
||||
mock_safety_api,
|
||||
mock_prompts_api,
|
||||
mock_files_api,
|
||||
):
|
||||
"""Create OpenAIResponsesImpl instance with conversations API."""
|
||||
return OpenAIResponsesImpl(
|
||||
|
|
@ -49,6 +51,8 @@ def responses_impl_with_conversations(
|
|||
vector_io_api=mock_vector_io_api,
|
||||
conversations_api=mock_conversations_api,
|
||||
safety_api=mock_safety_api,
|
||||
prompts_api=mock_prompts_api,
|
||||
files_api=mock_files_api,
|
||||
)
|
||||
|
||||
|
||||
|
|
|
|||
|
|
@ -5,6 +5,8 @@
|
|||
# the root directory of this source tree.
|
||||
|
||||
|
||||
from unittest.mock import AsyncMock
|
||||
|
||||
import pytest
|
||||
|
||||
from llama_stack.apis.agents.openai_responses import (
|
||||
|
|
@ -46,6 +48,12 @@ from llama_stack.providers.inline.agents.meta_reference.responses.utils import (
|
|||
)
|
||||
|
||||
|
||||
@pytest.fixture
|
||||
def mock_files_api():
|
||||
"""Mock files API for testing."""
|
||||
return AsyncMock()
|
||||
|
||||
|
||||
class TestConvertChatChoiceToResponseMessage:
|
||||
async def test_convert_string_content(self):
|
||||
choice = OpenAIChoice(
|
||||
|
|
@ -78,17 +86,17 @@ class TestConvertChatChoiceToResponseMessage:
|
|||
|
||||
|
||||
class TestConvertResponseContentToChatContent:
|
||||
async def test_convert_string_content(self):
|
||||
result = await convert_response_content_to_chat_content("Simple string")
|
||||
async def test_convert_string_content(self, mock_files_api):
|
||||
result = await convert_response_content_to_chat_content("Simple string", mock_files_api)
|
||||
assert result == "Simple string"
|
||||
|
||||
async def test_convert_text_content_parts(self):
|
||||
async def test_convert_text_content_parts(self, mock_files_api):
|
||||
content = [
|
||||
OpenAIResponseInputMessageContentText(text="First part"),
|
||||
OpenAIResponseOutputMessageContentOutputText(text="Second part"),
|
||||
]
|
||||
|
||||
result = await convert_response_content_to_chat_content(content)
|
||||
result = await convert_response_content_to_chat_content(content, mock_files_api)
|
||||
|
||||
assert len(result) == 2
|
||||
assert isinstance(result[0], OpenAIChatCompletionContentPartTextParam)
|
||||
|
|
@ -96,10 +104,10 @@ class TestConvertResponseContentToChatContent:
|
|||
assert isinstance(result[1], OpenAIChatCompletionContentPartTextParam)
|
||||
assert result[1].text == "Second part"
|
||||
|
||||
async def test_convert_image_content(self):
|
||||
async def test_convert_image_content(self, mock_files_api):
|
||||
content = [OpenAIResponseInputMessageContentImage(image_url="https://example.com/image.jpg", detail="high")]
|
||||
|
||||
result = await convert_response_content_to_chat_content(content)
|
||||
result = await convert_response_content_to_chat_content(content, mock_files_api)
|
||||
|
||||
assert len(result) == 1
|
||||
assert isinstance(result[0], OpenAIChatCompletionContentPartImageParam)
|
||||
|
|
|
|||
|
|
@ -30,6 +30,8 @@ def mock_apis():
|
|||
"vector_io_api": AsyncMock(),
|
||||
"conversations_api": AsyncMock(),
|
||||
"safety_api": AsyncMock(),
|
||||
"prompts_api": AsyncMock(),
|
||||
"files_api": AsyncMock(),
|
||||
}
|
||||
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue