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Fixes for multi-turn tool calls in Responses API
Testing with Codex locally, I found another issue in how we were plumbing through tool calls in multi-turn scenarios and the way tool call inputs and outputs from previous turns were passed back into future turns. This led me to realize we were missing the function tool call output type in the Responses API, so this adds that and plumbs handling of it through the responses API to chat completion conversion code. Signed-off-by: Ben Browning <bbrownin@redhat.com>
This commit is contained in:
Ben Browning
parent
65c56d0ee8
commit
4df8caab41
4 changed files with 187 additions and 69 deletions
106
docs/_static/llama-stack-spec.html
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106
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@ -6471,11 +6471,47 @@
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{
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"$ref": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall"
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall"
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseInputFunctionToolCallOutput"
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},
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{
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"$ref": "#/components/schemas/OpenAIResponseMessage"
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}
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]
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},
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"OpenAIResponseInputFunctionToolCallOutput": {
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"type": "object",
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"properties": {
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"call_id": {
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"type": "string"
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},
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"output": {
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"type": "string"
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},
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"type": {
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"type": "string",
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"const": "function_call_output",
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"default": "function_call_output"
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},
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"id": {
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"type": "string"
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},
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"status": {
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"type": "string"
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}
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},
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"additionalProperties": false,
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"required": [
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"call_id",
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"output",
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"type"
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],
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"title": "OpenAIResponseInputFunctionToolCallOutput",
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"description": "This represents the output of a function call that gets passed back to the model."
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},
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"OpenAIResponseInputMessageContent": {
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"oneOf": [
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{
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@ -6764,6 +6800,41 @@
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],
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"title": "OpenAIResponseOutputMessageContentOutputText"
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},
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"OpenAIResponseOutputMessageFunctionToolCall": {
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"type": "object",
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"properties": {
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"arguments": {
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"type": "string"
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},
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"call_id": {
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"type": "string"
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},
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"name": {
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"type": "string"
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},
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"type": {
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"type": "string",
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"const": "function_call",
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"default": "function_call"
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},
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"id": {
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"type": "string"
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},
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"status": {
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"type": "string"
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}
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},
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"additionalProperties": false,
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"required": [
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"arguments",
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"call_id",
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"name",
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"type",
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"id",
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"status"
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],
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"title": "OpenAIResponseOutputMessageFunctionToolCall"
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},
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"OpenAIResponseOutputMessageWebSearchToolCall": {
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"type": "object",
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"properties": {
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@ -6934,41 +7005,6 @@
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}
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}
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},
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"OpenAIResponseOutputMessageFunctionToolCall": {
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"type": "object",
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"properties": {
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"arguments": {
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"type": "string"
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},
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"call_id": {
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"type": "string"
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},
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"name": {
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"type": "string"
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},
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"type": {
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"type": "string",
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"const": "function_call",
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"default": "function_call"
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},
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"id": {
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"type": "string"
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},
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"status": {
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"type": "string"
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}
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},
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"additionalProperties": false,
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"required": [
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"arguments",
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"call_id",
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"name",
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"type",
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"id",
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"status"
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],
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"title": "OpenAIResponseOutputMessageFunctionToolCall"
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},
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"OpenAIResponseObjectStream": {
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"oneOf": [
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{
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81
docs/_static/llama-stack-spec.yaml
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81
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@ -4537,7 +4537,34 @@ components:
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OpenAIResponseInput:
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oneOf:
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- $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
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- $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
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- $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput'
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- $ref: '#/components/schemas/OpenAIResponseMessage'
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"OpenAIResponseInputFunctionToolCallOutput":
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type: object
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properties:
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call_id:
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type: string
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output:
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type: string
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type:
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type: string
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const: function_call_output
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default: function_call_output
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id:
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type: string
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status:
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type: string
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additionalProperties: false
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required:
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- call_id
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- output
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- type
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title: >-
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OpenAIResponseInputFunctionToolCallOutput
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description: >-
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This represents the output of a function call that gets passed back to the
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model.
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OpenAIResponseInputMessageContent:
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oneOf:
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- $ref: '#/components/schemas/OpenAIResponseInputMessageContentText'
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@ -4721,6 +4748,33 @@ components:
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- type
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title: >-
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OpenAIResponseOutputMessageContentOutputText
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"OpenAIResponseOutputMessageFunctionToolCall":
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type: object
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properties:
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arguments:
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type: string
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call_id:
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type: string
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name:
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type: string
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type:
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type: string
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const: function_call
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default: function_call
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id:
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type: string
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status:
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type: string
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additionalProperties: false
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required:
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- arguments
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- call_id
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- name
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- type
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- id
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- status
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title: >-
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OpenAIResponseOutputMessageFunctionToolCall
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"OpenAIResponseOutputMessageWebSearchToolCall":
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type: object
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properties:
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@ -4840,33 +4894,6 @@ components:
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message: '#/components/schemas/OpenAIResponseMessage'
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web_search_call: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall'
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function_call: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall'
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"OpenAIResponseOutputMessageFunctionToolCall":
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type: object
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properties:
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arguments:
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type: string
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call_id:
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type: string
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name:
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type: string
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type:
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type: string
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const: function_call
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default: function_call
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id:
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type: string
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status:
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type: string
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additionalProperties: false
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required:
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- arguments
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- call_id
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- name
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- type
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- id
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- status
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title: >-
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OpenAIResponseOutputMessageFunctionToolCall
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OpenAIResponseObjectStream:
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oneOf:
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- $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated'
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@ -130,9 +130,24 @@ OpenAIResponseObjectStream = Annotated[
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register_schema(OpenAIResponseObjectStream, name="OpenAIResponseObjectStream")
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@json_schema_type
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class OpenAIResponseInputFunctionToolCallOutput(BaseModel):
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"""
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This represents the output of a function call that gets passed back to the model.
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"""
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call_id: str
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output: str
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type: Literal["function_call_output"] = "function_call_output"
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id: str | None = None
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status: str | None = None
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OpenAIResponseInput = Annotated[
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# Responses API allows output messages to be passed in as input
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OpenAIResponseOutputMessageWebSearchToolCall
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| OpenAIResponseOutputMessageFunctionToolCall
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| OpenAIResponseInputFunctionToolCallOutput
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# Fallback to the generic message type as a last resort
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OpenAIResponseMessage,
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@ -14,6 +14,7 @@ from pydantic import BaseModel
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from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseInput,
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OpenAIResponseInputFunctionToolCallOutput,
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OpenAIResponseInputItemList,
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OpenAIResponseInputMessageContent,
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OpenAIResponseInputMessageContentImage,
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@ -38,6 +39,7 @@ from llama_stack.apis.inference.inference import (
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OpenAIChatCompletionContentPartImageParam,
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OpenAIChatCompletionContentPartParam,
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OpenAIChatCompletionContentPartTextParam,
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OpenAIChatCompletionToolCall,
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OpenAIChatCompletionToolCallFunction,
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OpenAIChoice,
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OpenAIDeveloperMessageParam,
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@ -97,13 +99,31 @@ async def _convert_response_input_to_chat_messages(
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messages: list[OpenAIMessageParam] = []
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if isinstance(input, list):
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for input_message in input:
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content = await _convert_response_content_to_chat_content(input_message.content)
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message_type = await _get_message_type_by_role(input_message.role)
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if message_type is None:
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raise ValueError(
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f"Llama Stack OpenAI Responses does not yet support message role '{input_message.role}' in this context"
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if isinstance(input_message, OpenAIResponseInputFunctionToolCallOutput):
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messages.append(
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OpenAIToolMessageParam(
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content=input_message.output,
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tool_call_id=input_message.call_id,
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)
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)
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messages.append(message_type(content=content))
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elif isinstance(input_message, OpenAIResponseOutputMessageFunctionToolCall):
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tool_call = OpenAIChatCompletionToolCall(
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index=0,
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id=input_message.call_id,
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function=OpenAIChatCompletionToolCallFunction(
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name=input_message.name,
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arguments=input_message.arguments,
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),
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)
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messages.append(OpenAIAssistantMessageParam(tool_calls=[tool_call]))
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else:
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content = await _convert_response_content_to_chat_content(input_message.content)
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message_type = await _get_message_type_by_role(input_message.role)
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if message_type is None:
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raise ValueError(
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f"Llama Stack OpenAI Responses does not yet support message role '{input_message.role}' in this context"
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)
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messages.append(message_type(content=content))
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else:
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messages.append(OpenAIUserMessageParam(content=input))
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return messages
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@ -222,6 +242,7 @@ class OpenAIResponsesImpl:
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# TODO: refactor this into a separate method that handles streaming
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chat_response_id = ""
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chat_response_content = []
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chat_response_tool_calls: dict[int, OpenAIChatCompletionToolCall] = {}
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# TODO: these chunk_ fields are hacky and only take the last chunk into account
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chunk_created = 0
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chunk_model = ""
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@ -235,7 +256,26 @@ class OpenAIResponsesImpl:
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chat_response_content.append(chunk_choice.delta.content or "")
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if chunk_choice.finish_reason:
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chunk_finish_reason = chunk_choice.finish_reason
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assistant_message = OpenAIAssistantMessageParam(content="".join(chat_response_content))
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if chunk_choice.delta.tool_calls:
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for tool_call in chunk_choice.delta.tool_calls:
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if tool_call.index not in chat_response_tool_calls:
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chat_response_tool_calls[tool_call.index] = OpenAIChatCompletionToolCall(
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**tool_call.model_dump()
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)
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chat_response_tool_calls[tool_call.index].function.arguments = (
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chat_response_tool_calls[tool_call.index].function.arguments
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+ tool_call.function.arguments
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)
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if chat_response_tool_calls:
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tool_calls = [chat_response_tool_calls[i] for i in sorted(chat_response_tool_calls.keys())]
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else:
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tool_calls = None
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assistant_message = OpenAIAssistantMessageParam(
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content="".join(chat_response_content),
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tool_calls=tool_calls,
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)
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chat_response = OpenAIChatCompletion(
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id=chat_response_id,
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choices=[
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