From 99141c29b10b45925acc39d70b3701a7de434c85 Mon Sep 17 00:00:00 2001 From: slekkala1 Date: Wed, 15 Oct 2025 15:01:37 -0700 Subject: [PATCH] feat: Add responses and safety impl extra_body (#3781) # What does this PR do? Have closed the previous PR due to merge conflicts with multiple PRs Addressed all comments from https://github.com/llamastack/llama-stack/pull/3768 (sorry for carrying over to this one) ## Test Plan Added UTs and integration tests --- docs/static/deprecated-llama-stack-spec.html | 75 +- docs/static/deprecated-llama-stack-spec.yaml | 63 +- docs/static/llama-stack-spec.html | 75 +- docs/static/llama-stack-spec.yaml | 63 +- docs/static/stainless-llama-stack-spec.html | 75 +- docs/static/stainless-llama-stack-spec.yaml | 63 +- llama_stack/apis/agents/agents.py | 18 +- llama_stack/apis/agents/openai_responses.py | 26 +- .../inline/agents/meta_reference/agents.py | 6 +- .../responses/openai_responses.py | 15 +- .../meta_reference/responses/streaming.py | 75 +- .../agents/meta_reference/responses/utils.py | 58 +- ...b3b0a3dd2150681781018d1dda3aba98650b2.json | 59 + ...b9753e850967eb2271313f15b3ad6c76d5cd3.json | 59 + ...13e16e172176a0a6638064b5747ac18522a6e.json | 59 + 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b/docs/static/deprecated-llama-stack-spec.html @@ -2135,7 +2135,7 @@ "deprecated": true, "x-llama-stack-extra-body-params": [ { - "name": "shields", + "name": "guardrails", "schema": { "type": "array", "items": { @@ -2144,12 +2144,12 @@ "type": "string" }, { - "$ref": "#/components/schemas/ResponseShieldSpec" + "$ref": "#/components/schemas/ResponseGuardrailSpec" } ] } }, - "description": "List of shields to apply during response generation. Shields provide safety and content moderation.", + "description": "List of guardrails to apply during response generation. Guardrails provide safety and content moderation.", "required": false } ] @@ -8483,6 +8483,28 @@ } } }, + "OpenAIResponseContentPartRefusal": { + "type": "object", + "properties": { + "type": { + "type": "string", + "const": "refusal", + "default": "refusal", + "description": "Content part type identifier, always \"refusal\"" + }, + "refusal": { + "type": "string", + "description": "Refusal text supplied by the model" + } + }, + "additionalProperties": false, + "required": [ + "type", + "refusal" + ], + "title": "OpenAIResponseContentPartRefusal", + "description": "Refusal content within a streamed response part." + }, "OpenAIResponseError": { "type": "object", "properties": { @@ -9063,6 +9085,23 @@ } }, "OpenAIResponseOutputMessageContent": { + "oneOf": [ + { + "$ref": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText" + }, + { + "$ref": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + ], + "discriminator": { + "propertyName": "type", + "mapping": { + "output_text": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText", + "refusal": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + } + }, + "OpenAIResponseOutputMessageContentOutputText": { "type": "object", "properties": { "text": { @@ -9567,20 +9606,20 @@ "title": "OpenAIResponseUsage", "description": "Usage information for OpenAI response." }, - "ResponseShieldSpec": { + "ResponseGuardrailSpec": { "type": "object", "properties": { "type": { "type": "string", - "description": "The type/identifier of the shield." + "description": "The type/identifier of the guardrail." } }, "additionalProperties": false, "required": [ "type" ], - "title": "ResponseShieldSpec", - "description": "Specification for a shield to apply during response generation." + "title": "ResponseGuardrailSpec", + "description": "Specification for a guardrail to apply during response generation." }, "OpenAIResponseInputTool": { "oneOf": [ @@ -9981,28 +10020,6 @@ "title": "OpenAIResponseContentPartReasoningText", "description": "Reasoning text emitted as part of a streamed response." }, - "OpenAIResponseContentPartRefusal": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "refusal", - "default": "refusal", - "description": "Content part type identifier, always \"refusal\"" - }, - "refusal": { - "type": "string", - "description": "Refusal text supplied by the model" - } - }, - "additionalProperties": false, - "required": [ - "type", - "refusal" - ], - "title": "OpenAIResponseContentPartRefusal", - "description": "Refusal content within a streamed response part." - }, "OpenAIResponseObjectStream": { "oneOf": [ { diff --git a/docs/static/deprecated-llama-stack-spec.yaml b/docs/static/deprecated-llama-stack-spec.yaml index b3a68e1ba..43f748d14 100644 --- a/docs/static/deprecated-llama-stack-spec.yaml +++ b/docs/static/deprecated-llama-stack-spec.yaml @@ -1569,16 +1569,16 @@ paths: required: true deprecated: true x-llama-stack-extra-body-params: - - name: shields + - name: guardrails schema: type: array items: oneOf: - type: string - - $ref: '#/components/schemas/ResponseShieldSpec' + - $ref: '#/components/schemas/ResponseGuardrailSpec' description: >- - List of shields to apply during response generation. Shields provide safety - and content moderation. + List of guardrails to apply during response generation. Guardrails provide + safety and content moderation. required: false /v1/openai/v1/responses/{response_id}: get: @@ -6332,6 +6332,25 @@ components: url_citation: '#/components/schemas/OpenAIResponseAnnotationCitation' container_file_citation: '#/components/schemas/OpenAIResponseAnnotationContainerFileCitation' file_path: '#/components/schemas/OpenAIResponseAnnotationFilePath' + OpenAIResponseContentPartRefusal: + type: object + properties: + type: + type: string + const: refusal + default: refusal + description: >- + Content part type identifier, always "refusal" + refusal: + type: string + description: Refusal text supplied by the model + additionalProperties: false + required: + - type + - refusal + title: OpenAIResponseContentPartRefusal + description: >- + Refusal content within a streamed response part. OpenAIResponseError: type: object properties: @@ -6755,6 +6774,15 @@ components: mcp_list_tools: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools' mcp_approval_request: '#/components/schemas/OpenAIResponseMCPApprovalRequest' OpenAIResponseOutputMessageContent: + oneOf: + - $ref: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + - $ref: '#/components/schemas/OpenAIResponseContentPartRefusal' + discriminator: + propertyName: type + mapping: + output_text: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + refusal: '#/components/schemas/OpenAIResponseContentPartRefusal' + "OpenAIResponseOutputMessageContentOutputText": type: object properties: text: @@ -7149,18 +7177,18 @@ components: - total_tokens title: OpenAIResponseUsage description: Usage information for OpenAI response. - ResponseShieldSpec: + ResponseGuardrailSpec: type: object properties: type: type: string - description: The type/identifier of the shield. + description: The type/identifier of the guardrail. additionalProperties: false required: - type - title: ResponseShieldSpec + title: ResponseGuardrailSpec description: >- - Specification for a shield to apply during response generation. + Specification for a guardrail to apply during response generation. OpenAIResponseInputTool: oneOf: - $ref: '#/components/schemas/OpenAIResponseInputToolWebSearch' @@ -7466,25 +7494,6 @@ components: title: OpenAIResponseContentPartReasoningText description: >- Reasoning text emitted as part of a streamed response. - OpenAIResponseContentPartRefusal: - type: object - properties: - type: - type: string - const: refusal - default: refusal - description: >- - Content part type identifier, always "refusal" - refusal: - type: string - description: Refusal text supplied by the model - additionalProperties: false - required: - - type - - refusal - title: OpenAIResponseContentPartRefusal - description: >- - Refusal content within a streamed response part. OpenAIResponseObjectStream: oneOf: - $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated' diff --git a/docs/static/llama-stack-spec.html b/docs/static/llama-stack-spec.html index 12e71d05d..92ba11d58 100644 --- a/docs/static/llama-stack-spec.html +++ b/docs/static/llama-stack-spec.html @@ -1833,7 +1833,7 @@ "deprecated": false, "x-llama-stack-extra-body-params": [ { - "name": "shields", + "name": "guardrails", "schema": { "type": "array", "items": { @@ -1842,12 +1842,12 @@ "type": "string" }, { - "$ref": "#/components/schemas/ResponseShieldSpec" + "$ref": "#/components/schemas/ResponseGuardrailSpec" } ] } }, - "description": "List of shields to apply during response generation. Shields provide safety and content moderation.", + "description": "List of guardrails to apply during response generation. Guardrails provide safety and content moderation.", "required": false } ] @@ -5670,6 +5670,28 @@ } } }, + "OpenAIResponseContentPartRefusal": { + "type": "object", + "properties": { + "type": { + "type": "string", + "const": "refusal", + "default": "refusal", + "description": "Content part type identifier, always \"refusal\"" + }, + "refusal": { + "type": "string", + "description": "Refusal text supplied by the model" + } + }, + "additionalProperties": false, + "required": [ + "type", + "refusal" + ], + "title": "OpenAIResponseContentPartRefusal", + "description": "Refusal content within a streamed response part." + }, "OpenAIResponseInputFunctionToolCallOutput": { "type": "object", "properties": { @@ -5905,6 +5927,23 @@ "description": "Corresponds to the various Message types in the Responses API. They are all under one type because the Responses API gives them all the same \"type\" value, and there is no way to tell them apart in certain scenarios." }, "OpenAIResponseOutputMessageContent": { + "oneOf": [ + { + "$ref": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText" + }, + { + "$ref": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + ], + "discriminator": { + "propertyName": "type", + "mapping": { + "output_text": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText", + "refusal": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + } + }, + "OpenAIResponseOutputMessageContentOutputText": { "type": "object", "properties": { "text": { @@ -7814,20 +7853,20 @@ "title": "OpenAIResponseUsage", "description": "Usage information for OpenAI response." }, - "ResponseShieldSpec": { + "ResponseGuardrailSpec": { "type": "object", "properties": { "type": { "type": "string", - "description": "The type/identifier of the shield." + "description": "The type/identifier of the guardrail." } }, "additionalProperties": false, "required": [ "type" ], - "title": "ResponseShieldSpec", - "description": "Specification for a shield to apply during response generation." + "title": "ResponseGuardrailSpec", + "description": "Specification for a guardrail to apply during response generation." }, "OpenAIResponseInputTool": { "oneOf": [ @@ -8228,28 +8267,6 @@ "title": "OpenAIResponseContentPartReasoningText", "description": "Reasoning text emitted as part of a streamed response." }, - "OpenAIResponseContentPartRefusal": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "refusal", - "default": "refusal", - "description": "Content part type identifier, always \"refusal\"" - }, - "refusal": { - "type": "string", - "description": "Refusal text supplied by the model" - } - }, - "additionalProperties": false, - "required": [ - "type", - "refusal" - ], - "title": "OpenAIResponseContentPartRefusal", - "description": "Refusal content within a streamed response part." - }, "OpenAIResponseObjectStream": { "oneOf": [ { diff --git a/docs/static/llama-stack-spec.yaml b/docs/static/llama-stack-spec.yaml index b589729bf..f7f77e635 100644 --- a/docs/static/llama-stack-spec.yaml +++ b/docs/static/llama-stack-spec.yaml @@ -1448,16 +1448,16 @@ paths: required: true deprecated: false x-llama-stack-extra-body-params: - - name: shields + - name: guardrails schema: type: array items: oneOf: - type: string - - $ref: '#/components/schemas/ResponseShieldSpec' + - $ref: '#/components/schemas/ResponseGuardrailSpec' description: >- - List of shields to apply during response generation. Shields provide safety - and content moderation. + List of guardrails to apply during response generation. Guardrails provide + safety and content moderation. required: false /v1/responses/{response_id}: get: @@ -4291,6 +4291,25 @@ components: url_citation: '#/components/schemas/OpenAIResponseAnnotationCitation' container_file_citation: '#/components/schemas/OpenAIResponseAnnotationContainerFileCitation' file_path: '#/components/schemas/OpenAIResponseAnnotationFilePath' + OpenAIResponseContentPartRefusal: + type: object + properties: + type: + type: string + const: refusal + default: refusal + description: >- + Content part type identifier, always "refusal" + refusal: + type: string + description: Refusal text supplied by the model + additionalProperties: false + required: + - type + - refusal + title: OpenAIResponseContentPartRefusal + description: >- + Refusal content within a streamed response part. "OpenAIResponseInputFunctionToolCallOutput": type: object properties: @@ -4462,6 +4481,15 @@ components: under one type because the Responses API gives them all the same "type" value, and there is no way to tell them apart in certain scenarios. OpenAIResponseOutputMessageContent: + oneOf: + - $ref: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + - $ref: '#/components/schemas/OpenAIResponseContentPartRefusal' + discriminator: + propertyName: type + mapping: + output_text: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + refusal: '#/components/schemas/OpenAIResponseContentPartRefusal' + "OpenAIResponseOutputMessageContentOutputText": type: object properties: text: @@ -5942,18 +5970,18 @@ components: - total_tokens title: OpenAIResponseUsage description: Usage information for OpenAI response. - ResponseShieldSpec: + ResponseGuardrailSpec: type: object properties: type: type: string - description: The type/identifier of the shield. + description: The type/identifier of the guardrail. additionalProperties: false required: - type - title: ResponseShieldSpec + title: ResponseGuardrailSpec description: >- - Specification for a shield to apply during response generation. + Specification for a guardrail to apply during response generation. OpenAIResponseInputTool: oneOf: - $ref: '#/components/schemas/OpenAIResponseInputToolWebSearch' @@ -6259,25 +6287,6 @@ components: title: OpenAIResponseContentPartReasoningText description: >- Reasoning text emitted as part of a streamed response. - OpenAIResponseContentPartRefusal: - type: object - properties: - type: - type: string - const: refusal - default: refusal - description: >- - Content part type identifier, always "refusal" - refusal: - type: string - description: Refusal text supplied by the model - additionalProperties: false - required: - - type - - refusal - title: OpenAIResponseContentPartRefusal - description: >- - Refusal content within a streamed response part. OpenAIResponseObjectStream: oneOf: - $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated' diff --git a/docs/static/stainless-llama-stack-spec.html b/docs/static/stainless-llama-stack-spec.html index 0562ac235..08f19ff59 100644 --- a/docs/static/stainless-llama-stack-spec.html +++ b/docs/static/stainless-llama-stack-spec.html @@ -1833,7 +1833,7 @@ "deprecated": false, "x-llama-stack-extra-body-params": [ { - "name": "shields", + "name": "guardrails", "schema": { "type": "array", "items": { @@ -1842,12 +1842,12 @@ "type": "string" }, { - "$ref": "#/components/schemas/ResponseShieldSpec" + "$ref": "#/components/schemas/ResponseGuardrailSpec" } ] } }, - "description": "List of shields to apply during response generation. Shields provide safety and content moderation.", + "description": "List of guardrails to apply during response generation. Guardrails provide safety and content moderation.", "required": false } ] @@ -7342,6 +7342,28 @@ } } }, + "OpenAIResponseContentPartRefusal": { + "type": "object", + "properties": { + "type": { + "type": "string", + "const": "refusal", + "default": "refusal", + "description": "Content part type identifier, always \"refusal\"" + }, + "refusal": { + "type": "string", + "description": "Refusal text supplied by the model" + } + }, + "additionalProperties": false, + "required": [ + "type", + "refusal" + ], + "title": "OpenAIResponseContentPartRefusal", + "description": "Refusal content within a streamed response part." + }, "OpenAIResponseInputFunctionToolCallOutput": { "type": "object", "properties": { @@ -7577,6 +7599,23 @@ "description": "Corresponds to the various Message types in the Responses API. They are all under one type because the Responses API gives them all the same \"type\" value, and there is no way to tell them apart in certain scenarios." }, "OpenAIResponseOutputMessageContent": { + "oneOf": [ + { + "$ref": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText" + }, + { + "$ref": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + ], + "discriminator": { + "propertyName": "type", + "mapping": { + "output_text": "#/components/schemas/OpenAIResponseOutputMessageContentOutputText", + "refusal": "#/components/schemas/OpenAIResponseContentPartRefusal" + } + } + }, + "OpenAIResponseOutputMessageContentOutputText": { "type": "object", "properties": { "text": { @@ -9486,20 +9525,20 @@ "title": "OpenAIResponseUsage", "description": "Usage information for OpenAI response." }, - "ResponseShieldSpec": { + "ResponseGuardrailSpec": { "type": "object", "properties": { "type": { "type": "string", - "description": "The type/identifier of the shield." + "description": "The type/identifier of the guardrail." } }, "additionalProperties": false, "required": [ "type" ], - "title": "ResponseShieldSpec", - "description": "Specification for a shield to apply during response generation." + "title": "ResponseGuardrailSpec", + "description": "Specification for a guardrail to apply during response generation." }, "OpenAIResponseInputTool": { "oneOf": [ @@ -9900,28 +9939,6 @@ "title": "OpenAIResponseContentPartReasoningText", "description": "Reasoning text emitted as part of a streamed response." }, - "OpenAIResponseContentPartRefusal": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "refusal", - "default": "refusal", - "description": "Content part type identifier, always \"refusal\"" - }, - "refusal": { - "type": "string", - "description": "Refusal text supplied by the model" - } - }, - "additionalProperties": false, - "required": [ - "type", - "refusal" - ], - "title": "OpenAIResponseContentPartRefusal", - "description": "Refusal content within a streamed response part." - }, "OpenAIResponseObjectStream": { "oneOf": [ { diff --git a/docs/static/stainless-llama-stack-spec.yaml b/docs/static/stainless-llama-stack-spec.yaml index e7819c47a..5469b3cc2 100644 --- a/docs/static/stainless-llama-stack-spec.yaml +++ b/docs/static/stainless-llama-stack-spec.yaml @@ -1451,16 +1451,16 @@ paths: required: true deprecated: false x-llama-stack-extra-body-params: - - name: shields + - name: guardrails schema: type: array items: oneOf: - type: string - - $ref: '#/components/schemas/ResponseShieldSpec' + - $ref: '#/components/schemas/ResponseGuardrailSpec' description: >- - List of shields to apply during response generation. Shields provide safety - and content moderation. + List of guardrails to apply during response generation. Guardrails provide + safety and content moderation. required: false /v1/responses/{response_id}: get: @@ -5504,6 +5504,25 @@ components: url_citation: '#/components/schemas/OpenAIResponseAnnotationCitation' container_file_citation: '#/components/schemas/OpenAIResponseAnnotationContainerFileCitation' file_path: '#/components/schemas/OpenAIResponseAnnotationFilePath' + OpenAIResponseContentPartRefusal: + type: object + properties: + type: + type: string + const: refusal + default: refusal + description: >- + Content part type identifier, always "refusal" + refusal: + type: string + description: Refusal text supplied by the model + additionalProperties: false + required: + - type + - refusal + title: OpenAIResponseContentPartRefusal + description: >- + Refusal content within a streamed response part. "OpenAIResponseInputFunctionToolCallOutput": type: object properties: @@ -5675,6 +5694,15 @@ components: under one type because the Responses API gives them all the same "type" value, and there is no way to tell them apart in certain scenarios. OpenAIResponseOutputMessageContent: + oneOf: + - $ref: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + - $ref: '#/components/schemas/OpenAIResponseContentPartRefusal' + discriminator: + propertyName: type + mapping: + output_text: '#/components/schemas/OpenAIResponseOutputMessageContentOutputText' + refusal: '#/components/schemas/OpenAIResponseContentPartRefusal' + "OpenAIResponseOutputMessageContentOutputText": type: object properties: text: @@ -7155,18 +7183,18 @@ components: - total_tokens title: OpenAIResponseUsage description: Usage information for OpenAI response. - ResponseShieldSpec: + ResponseGuardrailSpec: type: object properties: type: type: string - description: The type/identifier of the shield. + description: The type/identifier of the guardrail. additionalProperties: false required: - type - title: ResponseShieldSpec + title: ResponseGuardrailSpec description: >- - Specification for a shield to apply during response generation. + Specification for a guardrail to apply during response generation. OpenAIResponseInputTool: oneOf: - $ref: '#/components/schemas/OpenAIResponseInputToolWebSearch' @@ -7472,25 +7500,6 @@ components: title: OpenAIResponseContentPartReasoningText description: >- Reasoning text emitted as part of a streamed response. - OpenAIResponseContentPartRefusal: - type: object - properties: - type: - type: string - const: refusal - default: refusal - description: >- - Content part type identifier, always "refusal" - refusal: - type: string - description: Refusal text supplied by the model - additionalProperties: false - required: - - type - - refusal - title: OpenAIResponseContentPartRefusal - description: >- - Refusal content within a streamed response part. OpenAIResponseObjectStream: oneOf: - $ref: '#/components/schemas/OpenAIResponseObjectStreamResponseCreated' diff --git a/llama_stack/apis/agents/agents.py b/llama_stack/apis/agents/agents.py index ff4412c12..6ad45cf99 100644 --- a/llama_stack/apis/agents/agents.py +++ b/llama_stack/apis/agents/agents.py @@ -43,17 +43,17 @@ from .openai_responses import ( @json_schema_type -class ResponseShieldSpec(BaseModel): - """Specification for a shield to apply during response generation. +class ResponseGuardrailSpec(BaseModel): + """Specification for a guardrail to apply during response generation. - :param type: The type/identifier of the shield. + :param type: The type/identifier of the guardrail. """ type: str - # TODO: more fields to be added for shield configuration + # TODO: more fields to be added for guardrail configuration -ResponseShield = str | ResponseShieldSpec +ResponseGuardrail = str | ResponseGuardrailSpec class Attachment(BaseModel): @@ -820,10 +820,10 @@ class Agents(Protocol): tools: list[OpenAIResponseInputTool] | None = None, include: list[str] | None = None, max_infer_iters: int | None = 10, # this is an extension to the OpenAI API - shields: Annotated[ - list[ResponseShield] | None, + guardrails: Annotated[ + list[ResponseGuardrail] | None, ExtraBodyField( - "List of shields to apply during response generation. Shields provide safety and content moderation." + "List of guardrails to apply during response generation. Guardrails provide safety and content moderation." ), ] = None, ) -> OpenAIResponseObject | AsyncIterator[OpenAIResponseObjectStream]: @@ -834,7 +834,7 @@ class Agents(Protocol): :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. - :param shields: (Optional) List of shields to apply during response generation. Can be shield IDs (strings) or shield specifications. + :param guardrails: (Optional) List of guardrails to apply during response generation. Can be guardrail IDs (strings) or guardrail specifications. :returns: An OpenAIResponseObject. """ ... diff --git a/llama_stack/apis/agents/openai_responses.py b/llama_stack/apis/agents/openai_responses.py index 46f73db48..25dc89a6b 100644 --- a/llama_stack/apis/agents/openai_responses.py +++ b/llama_stack/apis/agents/openai_responses.py @@ -131,8 +131,20 @@ class OpenAIResponseOutputMessageContentOutputText(BaseModel): annotations: list[OpenAIResponseAnnotations] = Field(default_factory=list) +@json_schema_type +class OpenAIResponseContentPartRefusal(BaseModel): + """Refusal content within a streamed response part. + + :param type: Content part type identifier, always "refusal" + :param refusal: Refusal text supplied by the model + """ + + type: Literal["refusal"] = "refusal" + refusal: str + + OpenAIResponseOutputMessageContent = Annotated[ - OpenAIResponseOutputMessageContentOutputText, + OpenAIResponseOutputMessageContentOutputText | OpenAIResponseContentPartRefusal, Field(discriminator="type"), ] register_schema(OpenAIResponseOutputMessageContent, name="OpenAIResponseOutputMessageContent") @@ -878,18 +890,6 @@ class OpenAIResponseContentPartOutputText(BaseModel): logprobs: list[dict[str, Any]] | None = None -@json_schema_type -class OpenAIResponseContentPartRefusal(BaseModel): - """Refusal content within a streamed response part. - - :param type: Content part type identifier, always "refusal" - :param refusal: Refusal text supplied by the model - """ - - type: Literal["refusal"] = "refusal" - refusal: str - - @json_schema_type class OpenAIResponseContentPartReasoningText(BaseModel): """Reasoning text emitted as part of a streamed response. diff --git a/llama_stack/providers/inline/agents/meta_reference/agents.py b/llama_stack/providers/inline/agents/meta_reference/agents.py index 27d3a94cc..810c063e6 100644 --- a/llama_stack/providers/inline/agents/meta_reference/agents.py +++ b/llama_stack/providers/inline/agents/meta_reference/agents.py @@ -28,6 +28,7 @@ from llama_stack.apis.agents import ( Session, Turn, ) +from llama_stack.apis.agents.agents import ResponseGuardrail from llama_stack.apis.agents.openai_responses import OpenAIResponseText from llama_stack.apis.common.responses import PaginatedResponse from llama_stack.apis.conversations import Conversations @@ -91,6 +92,7 @@ class MetaReferenceAgentsImpl(Agents): tool_runtime_api=self.tool_runtime_api, responses_store=self.responses_store, vector_io_api=self.vector_io_api, + safety_api=self.safety_api, conversations_api=self.conversations_api, ) @@ -337,7 +339,7 @@ class MetaReferenceAgentsImpl(Agents): tools: list[OpenAIResponseInputTool] | None = None, include: list[str] | None = None, max_infer_iters: int | None = 10, - shields: list | None = None, + guardrails: list[ResponseGuardrail] | None = None, ) -> OpenAIResponseObject: return await self.openai_responses_impl.create_openai_response( input, @@ -352,7 +354,7 @@ class MetaReferenceAgentsImpl(Agents): tools, include, max_infer_iters, - shields, + guardrails, ) async def list_openai_responses( diff --git a/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py b/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py index cd04963b4..851e6ef28 100644 --- a/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py +++ b/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py @@ -11,6 +11,7 @@ from collections.abc import AsyncIterator from pydantic import BaseModel, TypeAdapter from llama_stack.apis.agents import Order +from llama_stack.apis.agents.agents import ResponseGuardrailSpec from llama_stack.apis.agents.openai_responses import ( ListOpenAIResponseInputItem, ListOpenAIResponseObject, @@ -34,6 +35,7 @@ from llama_stack.apis.inference import ( OpenAIMessageParam, OpenAISystemMessageParam, ) +from llama_stack.apis.safety import Safety from llama_stack.apis.tools import ToolGroups, ToolRuntime from llama_stack.apis.vector_io import VectorIO from llama_stack.log import get_logger @@ -48,6 +50,7 @@ from .types import ChatCompletionContext, ToolContext from .utils import ( convert_response_input_to_chat_messages, convert_response_text_to_chat_response_format, + extract_guardrail_ids, ) logger = get_logger(name=__name__, category="openai_responses") @@ -66,6 +69,7 @@ class OpenAIResponsesImpl: tool_runtime_api: ToolRuntime, responses_store: ResponsesStore, vector_io_api: VectorIO, # VectorIO + safety_api: Safety, conversations_api: Conversations, ): self.inference_api = inference_api @@ -73,6 +77,7 @@ class OpenAIResponsesImpl: self.tool_runtime_api = tool_runtime_api self.responses_store = responses_store self.vector_io_api = vector_io_api + self.safety_api = safety_api self.conversations_api = conversations_api self.tool_executor = ToolExecutor( tool_groups_api=tool_groups_api, @@ -244,14 +249,12 @@ class OpenAIResponsesImpl: tools: list[OpenAIResponseInputTool] | None = None, include: list[str] | None = None, max_infer_iters: int | None = 10, - shields: list | None = None, + guardrails: list[ResponseGuardrailSpec] | None = None, ): stream = bool(stream) text = OpenAIResponseText(format=OpenAIResponseTextFormat(type="text")) if text is None else text - # Shields parameter received via extra_body - not yet implemented - if shields is not None: - raise NotImplementedError("Shields parameter is not yet implemented in the meta-reference provider") + guardrail_ids = extract_guardrail_ids(guardrails) if guardrails else [] if conversation is not None: if previous_response_id is not None: @@ -273,6 +276,7 @@ class OpenAIResponsesImpl: text=text, tools=tools, max_infer_iters=max_infer_iters, + guardrail_ids=guardrail_ids, ) if stream: @@ -318,6 +322,7 @@ class OpenAIResponsesImpl: text: OpenAIResponseText | None = None, tools: list[OpenAIResponseInputTool] | None = None, max_infer_iters: int | None = 10, + guardrail_ids: list[str] | None = None, ) -> AsyncIterator[OpenAIResponseObjectStream]: # Input preprocessing all_input, messages, tool_context = await self._process_input_with_previous_response( @@ -352,6 +357,8 @@ class OpenAIResponsesImpl: text=text, max_infer_iters=max_infer_iters, tool_executor=self.tool_executor, + safety_api=self.safety_api, + guardrail_ids=guardrail_ids, ) # Stream the response diff --git a/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py b/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py index 4dd92b293..cd6a8184e 100644 --- a/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py +++ b/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py @@ -66,10 +66,15 @@ from llama_stack.apis.inference import ( OpenAIMessageParam, ) 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 from .types import ChatCompletionContext, ChatCompletionResult -from .utils import convert_chat_choice_to_response_message, is_function_tool_call +from .utils import ( + convert_chat_choice_to_response_message, + is_function_tool_call, + run_guardrails, +) logger = get_logger(name=__name__, category="agents::meta_reference") @@ -105,6 +110,8 @@ class StreamingResponseOrchestrator: text: OpenAIResponseText, max_infer_iters: int, tool_executor, # Will be the tool execution logic from the main class + safety_api, + guardrail_ids: list[str] | None = None, ): self.inference_api = inference_api self.ctx = ctx @@ -113,6 +120,8 @@ class StreamingResponseOrchestrator: self.text = text self.max_infer_iters = max_infer_iters self.tool_executor = tool_executor + self.safety_api = safety_api + self.guardrail_ids = guardrail_ids or [] self.sequence_number = 0 # Store MCP tool mapping that gets built during tool processing self.mcp_tool_to_server: dict[str, OpenAIResponseInputToolMCP] = ctx.tool_context.previous_tools or {} @@ -122,6 +131,23 @@ class StreamingResponseOrchestrator: self.citation_files: dict[str, str] = {} # Track accumulated usage across all inference calls self.accumulated_usage: OpenAIResponseUsage | None = None + # Track if we've sent a refusal response + self.violation_detected = False + + async def _create_refusal_response(self, violation_message: str) -> OpenAIResponseObjectStream: + """Create a refusal response to replace streaming content.""" + refusal_content = OpenAIResponseContentPartRefusal(refusal=violation_message) + + # Create a completed refusal response + refusal_response = OpenAIResponseObject( + id=self.response_id, + created_at=self.created_at, + model=self.ctx.model, + status="completed", + output=[OpenAIResponseMessage(role="assistant", content=[refusal_content], type="message")], + ) + + return OpenAIResponseObjectStreamResponseCompleted(response=refusal_response) def _clone_outputs(self, outputs: list[OpenAIResponseOutput]) -> list[OpenAIResponseOutput]: cloned: list[OpenAIResponseOutput] = [] @@ -166,6 +192,15 @@ class StreamingResponseOrchestrator: sequence_number=self.sequence_number, ) + # Input safety validation - check messages before processing + if self.guardrail_ids: + combined_text = interleaved_content_as_str([msg.content for msg in self.ctx.messages]) + input_violation_message = await run_guardrails(self.safety_api, combined_text, self.guardrail_ids) + if input_violation_message: + logger.info(f"Input guardrail violation: {input_violation_message}") + yield await self._create_refusal_response(input_violation_message) + return + async for stream_event in self._process_tools(output_messages): yield stream_event @@ -201,6 +236,11 @@ class StreamingResponseOrchestrator: completion_result_data = stream_event_or_result else: yield stream_event_or_result + + # If violation detected, skip the rest of processing since we already sent refusal + if self.violation_detected: + return + if not completion_result_data: raise ValueError("Streaming chunk processor failed to return completion data") last_completion_result = completion_result_data @@ -525,6 +565,9 @@ class StreamingResponseOrchestrator: # Accumulate usage from chunks (typically in final chunk with stream_options) self._accumulate_chunk_usage(chunk) + # Track deltas for this specific chunk for guardrail validation + chunk_events: list[OpenAIResponseObjectStream] = [] + for chunk_choice in chunk.choices: # Emit incremental text content as delta events if chunk_choice.delta.content: @@ -560,13 +603,19 @@ class StreamingResponseOrchestrator: sequence_number=self.sequence_number, ) self.sequence_number += 1 - yield OpenAIResponseObjectStreamResponseOutputTextDelta( + + text_delta_event = OpenAIResponseObjectStreamResponseOutputTextDelta( content_index=content_index, delta=chunk_choice.delta.content, item_id=message_item_id, output_index=message_output_index, sequence_number=self.sequence_number, ) + # Buffer text delta events for guardrail check + if self.guardrail_ids: + chunk_events.append(text_delta_event) + else: + yield text_delta_event # Collect content for final response chat_response_content.append(chunk_choice.delta.content or "") @@ -582,7 +631,11 @@ class StreamingResponseOrchestrator: message_item_id=message_item_id, message_output_index=message_output_index, ): - yield event + # Buffer reasoning events for guardrail check + if self.guardrail_ids: + chunk_events.append(event) + else: + yield event reasoning_part_emitted = True reasoning_text_accumulated.append(chunk_choice.delta.reasoning_content) @@ -664,6 +717,22 @@ class StreamingResponseOrchestrator: response_tool_call.function.arguments or "" ) + tool_call.function.arguments + # Output Safety Validation for this chunk + if self.guardrail_ids: + # Check guardrails on accumulated text so far + accumulated_text = "".join(chat_response_content) + violation_message = await run_guardrails(self.safety_api, accumulated_text, self.guardrail_ids) + if violation_message: + logger.info(f"Output guardrail violation: {violation_message}") + chunk_events.clear() + yield await self._create_refusal_response(violation_message) + self.violation_detected = True + return + else: + # No violation detected, emit all content events for this chunk + for event in chunk_events: + yield event + # Emit arguments.done events for completed tool calls (differentiate between MCP and function calls) for tool_call_index in sorted(chat_response_tool_calls.keys()): tool_call = chat_response_tool_calls[tool_call_index] diff --git a/llama_stack/providers/inline/agents/meta_reference/responses/utils.py b/llama_stack/providers/inline/agents/meta_reference/responses/utils.py index e67e9bdca..7ca8af632 100644 --- a/llama_stack/providers/inline/agents/meta_reference/responses/utils.py +++ b/llama_stack/providers/inline/agents/meta_reference/responses/utils.py @@ -4,9 +4,11 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. +import asyncio import re import uuid +from llama_stack.apis.agents.agents import ResponseGuardrailSpec from llama_stack.apis.agents.openai_responses import ( OpenAIResponseAnnotationFileCitation, OpenAIResponseInput, @@ -45,6 +47,7 @@ from llama_stack.apis.inference import ( OpenAIToolMessageParam, OpenAIUserMessageParam, ) +from llama_stack.apis.safety import Safety async def convert_chat_choice_to_response_message( @@ -240,7 +243,8 @@ async def convert_response_text_to_chat_response_format( raise ValueError(f"Unsupported text format: {text.format}") -async def get_message_type_by_role(role: str): +async def get_message_type_by_role(role: str) -> type[OpenAIMessageParam] | None: + """Get the appropriate OpenAI message parameter type for a given role.""" role_to_type = { "user": OpenAIUserMessageParam, "system": OpenAISystemMessageParam, @@ -307,3 +311,55 @@ def is_function_tool_call( if t.type == "function" and t.name == tool_call.function.name: return True return False + + +async def run_guardrails(safety_api: Safety, messages: str, guardrail_ids: list[str]) -> str | None: + """Run guardrails against messages and return violation message if blocked.""" + if not messages: + return None + + # Look up shields to get their provider_resource_id (actual model ID) + model_ids = [] + shields_list = await safety_api.routing_table.list_shields() + + for guardrail_id in guardrail_ids: + matching_shields = [shield for shield in shields_list.data if shield.identifier == guardrail_id] + if matching_shields: + model_id = matching_shields[0].provider_resource_id + model_ids.append(model_id) + else: + raise ValueError(f"No shield found with identifier '{guardrail_id}'") + + guardrail_tasks = [safety_api.run_moderation(messages, model=model_id) for model_id in model_ids] + responses = await asyncio.gather(*guardrail_tasks) + + for response in responses: + for result in response.results: + if result.flagged: + message = result.user_message or "Content blocked by safety guardrails" + flagged_categories = [cat for cat, flagged in result.categories.items() if flagged] + violation_type = result.metadata.get("violation_type", []) if result.metadata else [] + + if flagged_categories: + message += f" (flagged for: {', '.join(flagged_categories)})" + if violation_type: + message += f" (violation type: {', '.join(violation_type)})" + + return message + + +def extract_guardrail_ids(guardrails: list | None) -> list[str]: + """Extract guardrail IDs from guardrails parameter, handling both string IDs and ResponseGuardrailSpec objects.""" + if not guardrails: + return [] + + guardrail_ids = [] + for guardrail in guardrails: + if isinstance(guardrail, str): + guardrail_ids.append(guardrail) + elif isinstance(guardrail, ResponseGuardrailSpec): + guardrail_ids.append(guardrail.type) + else: + raise ValueError(f"Unknown guardrail format: {guardrail}, expected str or ResponseGuardrailSpec") + + return guardrail_ids diff --git a/tests/integration/agents/recordings/01bf932b8a65a67fef755e75e11b3b0a3dd2150681781018d1dda3aba98650b2.json b/tests/integration/agents/recordings/01bf932b8a65a67fef755e75e11b3b0a3dd2150681781018d1dda3aba98650b2.json new file mode 100644 index 000000000..5b1789116 --- /dev/null +++ b/tests/integration/agents/recordings/01bf932b8a65a67fef755e75e11b3b0a3dd2150681781018d1dda3aba98650b2.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to media, such as films, television shows, video games, and literature, that depict graphic violence, gore, or intensity of conflict. 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First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-f948ecb568b7", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 396, + "total_tokens": 398, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/fa35d855767b5d1215614329c981e2a9fec458c8df022db01860a27f07a176e4.json b/tests/integration/agents/recordings/fa35d855767b5d1215614329c981e2a9fec458c8df022db01860a27f07a176e4.json new file mode 100644 index 000000000..113235471 --- /dev/null +++ b/tests/integration/agents/recordings/fa35d855767b5d1215614329c981e2a9fec458c8df022db01860a27f07a176e4.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to media, such as films, television shows, video games,\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-fa35d855767b", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 400, + "total_tokens": 402, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/fb2fe81813e47193bb1f45b13698a7d56ad4813738aa045ece453ce0557e1bf6.json b/tests/integration/agents/recordings/fb2fe81813e47193bb1f45b13698a7d56ad4813738aa045ece453ce0557e1bf6.json new file mode 100644 index 000000000..5533b6e25 --- /dev/null +++ b/tests/integration/agents/recordings/fb2fe81813e47193bb1f45b13698a7d56ad4813738aa045ece453ce0557e1bf6.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_safe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: I'm an artificial intelligence model known as Llama. L\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-fb2fe81813e4", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 396, + "total_tokens": 398, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/fdb8dc15344af25a04007bf40b1a0c83d9b54da75853366d9e9fb31009c6acae.json b/tests/integration/agents/recordings/fdb8dc15344af25a04007bf40b1a0c83d9b54da75853366d9e9fb31009c6acae.json new file mode 100644 index 000000000..be1b27225 --- /dev/null +++ b/tests/integration/agents/recordings/fdb8dc15344af25a04007bf40b1a0c83d9b54da75853366d9e9fb31009c6acae.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_safe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: I'm an artificial intelligence model known as Llama. Llama\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-fdb8dc15344a", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 397, + "total_tokens": 399, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/fea1ea5622f42cfe111201b01a72a1c144ec096d718b508f0fbf883378835933.json b/tests/integration/agents/recordings/fea1ea5622f42cfe111201b01a72a1c144ec096d718b508f0fbf883378835933.json new file mode 100644 index 000000000..b13d4c359 --- /dev/null +++ b/tests/integration/agents/recordings/fea1ea5622f42cfe111201b01a72a1c144ec096d718b508f0fbf883378835933.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to materials, such as films, videos, television\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-fea1ea5622f4", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 398, + "total_tokens": 400, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/test_openai_responses.py b/tests/integration/agents/test_openai_responses.py index 6648257e6..675e2b904 100644 --- a/tests/integration/agents/test_openai_responses.py +++ b/tests/integration/agents/test_openai_responses.py @@ -297,3 +297,172 @@ def test_function_call_output_response_with_none_arguments(openai_client, client assert response.output[0].type == "function_call" assert response.output[0].arguments == "{}" _ = response.output[0].call_id + + +@pytest.mark.parametrize("stream", [True, False]) +def test_input_safety_guardrails(compat_client, text_model_id, stream): + """Test that input safety guardrails block inappropriate content.""" + if not isinstance(compat_client, OpenAI): + pytest.skip("OpenAI client is required until responses API exists in llama-stack-client") + + # Test with guardrail that should block inappropriate content + # Note: This test assumes guardrails are configured in the test environment + inappropriate_message = "How can I hurt someone?" + + response = compat_client.responses.create( + model=text_model_id, + input=[ + { + "role": "user", + "content": inappropriate_message, + } + ], + stream=stream, + extra_body={"guardrails": ["llama-guard"]}, # Guardrails passed via extra_body + ) + + if stream: + # Input violations cause immediate refusal - only one completion chunk + final_response = None + for chunk in response: + if chunk.type == "response.completed": + final_response = chunk.response + break + + assert final_response is not None + response_to_check = final_response + else: + response_to_check = response + + # Check if the response contains a refusal (indicating guardrail blocked content) + assert response_to_check.output[0].type == "message" + message = response_to_check.output[0] + + # Guardrail should ALWAYS block inappropriate input - expect refusal response + assert len(message.content) > 0, "Content should not be empty" + content_item = message.content[0] + assert content_item.type == "refusal", f"Expected refusal content, but got: {content_item.type}" + assert len(content_item.refusal.strip()) > 0, "Refusal message should not be empty" + + +@pytest.mark.parametrize("stream", [True, False]) +def test_output_safety_guardrails_unsafe_content(compat_client, text_model_id, stream): + """Test that output safety guardrails block unsafe content.""" + if not isinstance(compat_client, OpenAI): + pytest.skip("OpenAI client is required until responses API exists in llama-stack-client") + + # Use an unsafe prompt that should be blocked by guardrail evaluation + response = compat_client.responses.create( + model=text_model_id, + input=[ + { + "role": "user", + "content": "Describe violent content", + } + ], + stream=stream, + extra_body={"guardrails": ["llama-guard"]}, # Output guardrail validation + ) + + if stream: + # For streaming, collect the final response + last_chunk = None + for chunk in response: + last_chunk = chunk + + assert last_chunk is not None + assert last_chunk.type == "response.completed", f"Expected final chunk to be completion, got {last_chunk.type}" + response_to_check = last_chunk.response + else: + response_to_check = response + + assert response_to_check.output[0].type == "message" + message = response_to_check.output[0] + + assert len(message.content) > 0, "Message should have content" + content_item = message.content[0] + assert content_item.type == "refusal", ( + f"Content type should be 'refusal' for unsafe output, got {content_item.type}" + ) + assert len(content_item.refusal.strip()) > 0, "Refusal message should not be empty" + + +@pytest.mark.parametrize("stream", [True, False]) +def test_output_safety_guardrails_safe_content(compat_client, text_model_id, stream): + """Test that output safety guardrails allow safe content.""" + if not isinstance(compat_client, OpenAI): + pytest.skip("OpenAI client is required until responses API exists in llama-stack-client") + + # Use a safe prompt that should pass guardrail evaluation + response = compat_client.responses.create( + model=text_model_id, + input=[ + { + "role": "user", + "content": "What's your name?", + } + ], + stream=stream, + extra_body={"guardrails": ["llama-guard"]}, # Output guardrail validation + ) + + if stream: + # For streaming, collect the final response + last_chunk = None + for chunk in response: + last_chunk = chunk + + assert last_chunk is not None + assert last_chunk.type == "response.completed", f"Expected final chunk to be completion, got {last_chunk.type}" + response_to_check = last_chunk.response + else: + response_to_check = response + + assert response_to_check.output[0].type == "message" + message = response_to_check.output[0] + + assert len(message.content) > 0, "Message should have content" + content_item = message.content[0] + assert content_item.type == "output_text", ( + f"Content type should be 'output_text' for safe output, got {content_item.type}" + ) + assert len(content_item.text.strip()) > 0, "Text content should not be empty" + + +def test_guardrails_with_tools(compat_client, text_model_id): + """Test that guardrails work correctly when tools are present.""" + if not isinstance(compat_client, OpenAI): + pytest.skip("OpenAI client is required until responses API exists in llama-stack-client") + + response = compat_client.responses.create( + model=text_model_id, + input=[ + { + "role": "user", + "content": "What's the weather like? Please help me in a safe and appropriate way.", + } + ], + tools=[ + { + "type": "function", + "name": "get_weather", + "description": "Get the weather in a given city", + "parameters": { + "type": "object", + "properties": { + "city": {"type": "string", "description": "The city to get the weather for"}, + }, + }, + } + ], + extra_body={"guardrails": ["llama-guard"]}, + stream=False, + ) + + # Verify response completes successfully with tools and guardrails + assert response.id is not None + assert len(response.output) > 0 + + # Response should be either a function call or a message + output_type = response.output[0].type + assert output_type in ["function_call", "message"] diff --git a/tests/integration/common/recordings/02c93bb3c314427bae2b7a7a6f054792b9f22d2cb4522eab802810be8672d3dc.json b/tests/integration/common/recordings/02c93bb3c314427bae2b7a7a6f054792b9f22d2cb4522eab802810be8672d3dc.json index 2b2afeee4..4ea0ee13f 100644 --- a/tests/integration/common/recordings/02c93bb3c314427bae2b7a7a6f054792b9f22d2cb4522eab802810be8672d3dc.json +++ b/tests/integration/common/recordings/02c93bb3c314427bae2b7a7a6f054792b9f22d2cb4522eab802810be8672d3dc.json @@ -12,7 +12,26 @@ "body": { "__type__": "ollama._types.ProcessResponse", "__data__": { - "models": [] + "models": [ + { + "model": "llama-guard3:1b", + "name": "llama-guard3:1b", + "digest": "494147e06bf99e10dbe67b63a07ac81c162f18ef3341aa3390007ac828571b3b", + "expires_at": "2025-10-13T14:07:12.309717-07:00", + "size": 2279663616, + "size_vram": 2279663616, + "details": { + "parent_model": "", + "format": "gguf", + "family": "llama", + "families": [ + "llama" + ], + "parameter_size": "1.5B", + "quantization_level": "Q8_0" + } + } + ] } }, "is_streaming": false diff --git a/tests/integration/common/recordings/models-64a2277c90f0f42576f60c1030e3a020403d34a95f56931b792d5939f4cebc57-a282c3d2.json b/tests/integration/common/recordings/models-64a2277c90f0f42576f60c1030e3a020403d34a95f56931b792d5939f4cebc57-a282c3d2.json new file mode 100644 index 000000000..14211fc18 --- /dev/null +++ b/tests/integration/common/recordings/models-64a2277c90f0f42576f60c1030e3a020403d34a95f56931b792d5939f4cebc57-a282c3d2.json @@ -0,0 +1,35 @@ +{ + "test_id": null, + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/models", + "headers": {}, + "body": {}, + "endpoint": "/v1/models", + "model": "" + }, + "response": { + "body": [ + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "llama3.2:3b-instruct-fp16", + "created": 1760378164, + "object": "model", + "owned_by": "library" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "llama-guard3:1b", + "created": 1760377649, + "object": "model", + "owned_by": "library" + } + } + ], + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/responses/test_extra_body_shields.py b/tests/integration/responses/test_extra_body_shields.py deleted file mode 100644 index eb41cc150..000000000 --- a/tests/integration/responses/test_extra_body_shields.py +++ /dev/null @@ -1,34 +0,0 @@ -# Copyright (c) Meta Platforms, Inc. and affiliates. -# All rights reserved. -# -# This source code is licensed under the terms described in the LICENSE file in -# the root directory of this source tree. - -""" -Test for extra_body parameter support with shields example. - -This test demonstrates that parameters marked with ExtraBodyField annotation -can be passed via extra_body in the client SDK and are received by the -server-side implementation. -""" - -import pytest -from llama_stack_client import APIStatusError - - -@pytest.mark.xfail(reason="Shields are not yet implemented inside responses") -def test_shields_via_extra_body(compat_client, text_model_id): - """Test that shields parameter is received by the server and raises NotImplementedError.""" - - # Test with shields as list of strings (shield IDs) - with pytest.raises((APIStatusError, NotImplementedError)) as exc_info: - compat_client.responses.create( - model=text_model_id, - input="What is the capital of France?", - stream=False, - extra_body={"shields": ["test-shield-1", "test-shield-2"]}, - ) - - # Verify the error message indicates shields are not implemented - error_message = str(exc_info.value) - assert "not yet implemented" in error_message.lower() or "not implemented" in error_message.lower() diff --git a/tests/unit/providers/agents/meta_reference/test_openai_responses.py b/tests/unit/providers/agents/meta_reference/test_openai_responses.py index 81978c60c..e93668a62 100644 --- a/tests/unit/providers/agents/meta_reference/test_openai_responses.py +++ b/tests/unit/providers/agents/meta_reference/test_openai_responses.py @@ -91,6 +91,12 @@ def mock_conversations_api(): return mock_api +@pytest.fixture +def mock_safety_api(): + safety_api = AsyncMock() + return safety_api + + @pytest.fixture def openai_responses_impl( mock_inference_api, @@ -98,6 +104,7 @@ def openai_responses_impl( mock_tool_runtime_api, mock_responses_store, mock_vector_io_api, + mock_safety_api, mock_conversations_api, ): return OpenAIResponsesImpl( @@ -106,6 +113,7 @@ def openai_responses_impl( tool_runtime_api=mock_tool_runtime_api, responses_store=mock_responses_store, vector_io_api=mock_vector_io_api, + safety_api=mock_safety_api, conversations_api=mock_conversations_api, ) diff --git a/tests/unit/providers/agents/meta_reference/test_openai_responses_conversations.py b/tests/unit/providers/agents/meta_reference/test_openai_responses_conversations.py index f9ae2b54d..2ca350862 100644 --- a/tests/unit/providers/agents/meta_reference/test_openai_responses_conversations.py +++ b/tests/unit/providers/agents/meta_reference/test_openai_responses_conversations.py @@ -38,6 +38,7 @@ def responses_impl_with_conversations( mock_responses_store, mock_vector_io_api, mock_conversations_api, + mock_safety_api, ): """Create OpenAIResponsesImpl instance with conversations API.""" return OpenAIResponsesImpl( @@ -47,6 +48,7 @@ def responses_impl_with_conversations( responses_store=mock_responses_store, vector_io_api=mock_vector_io_api, conversations_api=mock_conversations_api, + safety_api=mock_safety_api, ) diff --git a/tests/unit/providers/agents/meta_reference/test_responses_safety_utils.py b/tests/unit/providers/agents/meta_reference/test_responses_safety_utils.py new file mode 100644 index 000000000..9c5cc853c --- /dev/null +++ b/tests/unit/providers/agents/meta_reference/test_responses_safety_utils.py @@ -0,0 +1,155 @@ +# Copyright (c) Meta Platforms, Inc. and affiliates. +# All rights reserved. +# +# This source code is licensed under the terms described in the LICENSE file in +# the root directory of this source tree. + +from unittest.mock import AsyncMock + +import pytest + +from llama_stack.apis.agents.agents import ResponseGuardrailSpec +from llama_stack.apis.safety import ModerationObject, ModerationObjectResults +from llama_stack.providers.inline.agents.meta_reference.responses.openai_responses import ( + OpenAIResponsesImpl, +) +from llama_stack.providers.inline.agents.meta_reference.responses.utils import ( + extract_guardrail_ids, + run_guardrails, +) + + +@pytest.fixture +def mock_apis(): + """Create mock APIs for testing.""" + return { + "inference_api": AsyncMock(), + "tool_groups_api": AsyncMock(), + "tool_runtime_api": AsyncMock(), + "responses_store": AsyncMock(), + "vector_io_api": AsyncMock(), + "conversations_api": AsyncMock(), + "safety_api": AsyncMock(), + } + + +@pytest.fixture +def responses_impl(mock_apis): + """Create OpenAIResponsesImpl instance with mocked dependencies.""" + return OpenAIResponsesImpl(**mock_apis) + + +def test_extract_guardrail_ids_from_strings(responses_impl): + """Test extraction from simple string guardrail IDs.""" + guardrails = ["llama-guard", "content-filter", "nsfw-detector"] + result = extract_guardrail_ids(guardrails) + assert result == ["llama-guard", "content-filter", "nsfw-detector"] + + +def test_extract_guardrail_ids_from_objects(responses_impl): + """Test extraction from ResponseGuardrailSpec objects.""" + guardrails = [ + ResponseGuardrailSpec(type="llama-guard"), + ResponseGuardrailSpec(type="content-filter"), + ] + result = extract_guardrail_ids(guardrails) + assert result == ["llama-guard", "content-filter"] + + +def test_extract_guardrail_ids_mixed_formats(responses_impl): + """Test extraction from mixed string and object formats.""" + guardrails = [ + "llama-guard", + ResponseGuardrailSpec(type="content-filter"), + "nsfw-detector", + ] + result = extract_guardrail_ids(guardrails) + assert result == ["llama-guard", "content-filter", "nsfw-detector"] + + +def test_extract_guardrail_ids_none_input(responses_impl): + """Test extraction with None input.""" + result = extract_guardrail_ids(None) + assert result == [] + + +def test_extract_guardrail_ids_empty_list(responses_impl): + """Test extraction with empty list.""" + result = extract_guardrail_ids([]) + assert result == [] + + +def test_extract_guardrail_ids_unknown_format(responses_impl): + """Test extraction with unknown guardrail format raises ValueError.""" + # Create an object that's neither string nor ResponseGuardrailSpec + unknown_object = {"invalid": "format"} # Plain dict, not ResponseGuardrailSpec + guardrails = ["valid-guardrail", unknown_object, "another-guardrail"] + with pytest.raises(ValueError, match="Unknown guardrail format.*expected str or ResponseGuardrailSpec"): + extract_guardrail_ids(guardrails) + + +@pytest.fixture +def mock_safety_api(): + """Create mock safety API for guardrails testing.""" + safety_api = AsyncMock() + # Mock the routing table and shields list for guardrails lookup + safety_api.routing_table = AsyncMock() + shield = AsyncMock() + shield.identifier = "llama-guard" + shield.provider_resource_id = "llama-guard-model" + safety_api.routing_table.list_shields.return_value = AsyncMock(data=[shield]) + return safety_api + + +async def test_run_guardrails_no_violation(mock_safety_api): + """Test guardrails validation with no violations.""" + text = "Hello world" + guardrail_ids = ["llama-guard"] + + # Mock moderation to return non-flagged content + unflagged_result = ModerationObjectResults(flagged=False, categories={"violence": False}) + mock_moderation_object = ModerationObject(id="test-mod-id", model="llama-guard-model", results=[unflagged_result]) + mock_safety_api.run_moderation.return_value = mock_moderation_object + + result = await run_guardrails(mock_safety_api, text, guardrail_ids) + + assert result is None + # Verify run_moderation was called with the correct model + mock_safety_api.run_moderation.assert_called_once() + call_args = mock_safety_api.run_moderation.call_args + assert call_args[1]["model"] == "llama-guard-model" + + +async def test_run_guardrails_with_violation(mock_safety_api): + """Test guardrails validation with safety violation.""" + text = "Harmful content" + guardrail_ids = ["llama-guard"] + + # Mock moderation to return flagged content + flagged_result = ModerationObjectResults( + flagged=True, + categories={"violence": True}, + user_message="Content flagged by moderation", + metadata={"violation_type": ["S1"]}, + ) + mock_moderation_object = ModerationObject(id="test-mod-id", model="llama-guard-model", results=[flagged_result]) + mock_safety_api.run_moderation.return_value = mock_moderation_object + + result = await run_guardrails(mock_safety_api, text, guardrail_ids) + + assert result == "Content flagged by moderation (flagged for: violence) (violation type: S1)" + + +async def test_run_guardrails_empty_inputs(mock_safety_api): + """Test guardrails validation with empty inputs.""" + # Test empty guardrail_ids + result = await run_guardrails(mock_safety_api, "test", []) + assert result is None + + # Test empty text + result = await run_guardrails(mock_safety_api, "", ["llama-guard"]) + assert result is None + + # Test both empty + result = await run_guardrails(mock_safety_api, "", []) + assert result is None diff --git a/tests/unit/providers/inline/agents/meta_reference/responses/test_streaming.py b/tests/unit/providers/inline/agents/meta_reference/responses/test_streaming.py index 4b706717d..fff29928c 100644 --- a/tests/unit/providers/inline/agents/meta_reference/responses/test_streaming.py +++ b/tests/unit/providers/inline/agents/meta_reference/responses/test_streaming.py @@ -4,10 +4,45 @@ # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. +from unittest.mock import AsyncMock + +import pytest + from llama_stack.apis.tools import ToolDef from llama_stack.providers.inline.agents.meta_reference.responses.streaming import ( convert_tooldef_to_chat_tool, ) +from llama_stack.providers.inline.agents.meta_reference.responses.types import ChatCompletionContext + + +@pytest.fixture +def mock_safety_api(): + safety_api = AsyncMock() + # Mock the routing table and shields list for guardrails lookup + safety_api.routing_table = AsyncMock() + shield = AsyncMock() + shield.identifier = "llama-guard" + shield.provider_resource_id = "llama-guard-model" + safety_api.routing_table.list_shields.return_value = AsyncMock(data=[shield]) + # Mock run_moderation to return non-flagged result by default + safety_api.run_moderation.return_value = AsyncMock(flagged=False) + return safety_api + + +@pytest.fixture +def mock_inference_api(): + inference_api = AsyncMock() + return inference_api + + +@pytest.fixture +def mock_context(): + context = AsyncMock(spec=ChatCompletionContext) + # Add required attributes that StreamingResponseOrchestrator expects + context.tool_context = AsyncMock() + context.tool_context.previous_tools = {} + context.messages = [] + return context def test_convert_tooldef_to_chat_tool_preserves_items_field():