diff --git a/docs/docs/providers/agents/index.mdx b/docs/docs/providers/agents/index.mdx index 06eb104af..200d0119f 100644 --- a/docs/docs/providers/agents/index.mdx +++ b/docs/docs/providers/agents/index.mdx @@ -14,4 +14,4 @@ Agents APIs for creating and interacting with agentic systems. -This section contains documentation for all available providers for the **agents** API. +This section contains documentation for all available providers for the **agents** API. \ No newline at end of file diff --git a/docs/static/experimental-llama-stack-spec.html b/docs/static/experimental-llama-stack-spec.html index a84226c05..574107a6d 100644 --- a/docs/static/experimental-llama-stack-spec.html +++ b/docs/static/experimental-llama-stack-spec.html @@ -4992,7 +4992,7 @@ "properties": { "model": { "type": "string", - "description": "The identifier of the reranking model to use." + "description": "The identifier of the reranking model to use. The model must be a reranking model registered with Llama Stack and available via the /models endpoint." }, "query": { "oneOf": [ diff --git a/docs/static/experimental-llama-stack-spec.yaml b/docs/static/experimental-llama-stack-spec.yaml index a08c0cc87..aae356d6d 100644 --- a/docs/static/experimental-llama-stack-spec.yaml +++ b/docs/static/experimental-llama-stack-spec.yaml @@ -3657,7 +3657,8 @@ components: model: type: string description: >- - The identifier of the reranking model to use. + The identifier of the reranking model to use. The model must be a reranking + model registered with Llama Stack and available via the /models endpoint. query: oneOf: - type: string diff --git a/docs/static/llama-stack-spec.html b/docs/static/llama-stack-spec.html index 0fdf3f415..2ee665123 100644 --- a/docs/static/llama-stack-spec.html +++ b/docs/static/llama-stack-spec.html @@ -4819,2834 +4819,6 @@ "title": "OpenAIUserMessageParam", "description": "A message from the user in an OpenAI-compatible chat completion request." }, - "OpenAICompletionWithInputMessages": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The ID of the chat completion" - }, - "choices": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIChoice" - }, - "description": "List of choices" - }, - "object": { - "type": "string", - "const": "chat.completion", - "default": "chat.completion", - "description": "The object type, which will be \"chat.completion\"" - }, - "created": { - "type": "integer", - "description": "The Unix timestamp in seconds when the chat completion was created" - }, - "model": { - "type": "string", - "description": "The model that was used to generate the chat completion" - }, - "input_messages": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIMessageParam" - } - } - }, - "additionalProperties": false, - "required": [ - "id", - "choices", - "object", - "created", - "model", - "input_messages" - ], - "title": "OpenAICompletionWithInputMessages" - }, - "DataSource": { - "oneOf": [ - { - "$ref": "#/components/schemas/URIDataSource" - }, - { - "$ref": "#/components/schemas/RowsDataSource" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "uri": "#/components/schemas/URIDataSource", - "rows": "#/components/schemas/RowsDataSource" - } - } - }, - "Dataset": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "dataset", - "default": "dataset", - "description": "Type of resource, always 'dataset' for datasets" - }, - "purpose": { - "type": "string", - "enum": [ - "post-training/messages", - "eval/question-answer", - "eval/messages-answer" - ], - "description": "Purpose of the dataset indicating its intended use" - }, - "source": { - "$ref": "#/components/schemas/DataSource", - "description": "Data source configuration for the dataset" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Additional metadata for the dataset" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type", - "purpose", - "source", - "metadata" - ], - "title": "Dataset", - "description": "Dataset resource for storing and accessing training or evaluation data." - }, - "RowsDataSource": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "rows", - "default": "rows" - }, - "rows": { - "type": "array", - "items": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - }, - "description": "The dataset is stored in rows. E.g. - [ {\"messages\": [{\"role\": \"user\", \"content\": \"Hello, world!\"}, {\"role\": \"assistant\", \"content\": \"Hello, world!\"}]} ]" - } - }, - "additionalProperties": false, - "required": [ - "type", - "rows" - ], - "title": "RowsDataSource", - "description": "A dataset stored in rows." - }, - "URIDataSource": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "uri", - "default": "uri" - }, - "uri": { - "type": "string", - "description": "The dataset can be obtained from a URI. E.g. - \"https://mywebsite.com/mydata.jsonl\" - \"lsfs://mydata.jsonl\" - \"data:csv;base64,{base64_content}\"" - } - }, - "additionalProperties": false, - "required": [ - "type", - "uri" - ], - "title": "URIDataSource", - "description": "A dataset that can be obtained from a URI." - }, - "Model": { - "type": "object", - "properties": { - "identifier": { - "type": "string", - "description": "Unique identifier for this resource in llama stack" - }, - "provider_resource_id": { - "type": "string", - "description": "Unique identifier for this resource in the provider" - }, - "provider_id": { - "type": "string", - "description": "ID of the provider that owns this resource" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "model", - "default": "model", - "description": "The resource type, always 'model' for model resources" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Any additional metadata for this model" - }, - "model_type": { - "$ref": "#/components/schemas/ModelType", - "default": "llm", - "description": "The type of model (LLM or embedding model)" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type", - "metadata", - "model_type" - ], - "title": "Model", - "description": "A model resource representing an AI model registered in Llama Stack." - }, - "ModelType": { - "type": "string", - "enum": [ - "llm", - "embedding", - "rerank" - ], - "title": "ModelType", - "description": "Enumeration of supported model types in Llama Stack." - }, - "AgentTurnInputType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "agent_turn_input", - "default": "agent_turn_input", - "description": "Discriminator type. Always \"agent_turn_input\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "AgentTurnInputType", - "description": "Parameter type for agent turn input." - }, - "ArrayType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "array", - "default": "array", - "description": "Discriminator type. Always \"array\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "ArrayType", - "description": "Parameter type for array values." - }, - "BooleanType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "boolean", - "default": "boolean", - "description": "Discriminator type. Always \"boolean\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "BooleanType", - "description": "Parameter type for boolean values." - }, - "ChatCompletionInputType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "chat_completion_input", - "default": "chat_completion_input", - "description": "Discriminator type. Always \"chat_completion_input\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "ChatCompletionInputType", - "description": "Parameter type for chat completion input." - }, - "CompletionInputType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "completion_input", - "default": "completion_input", - "description": "Discriminator type. Always \"completion_input\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "CompletionInputType", - "description": "Parameter type for completion input." - }, - "JsonType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "json", - "default": "json", - "description": "Discriminator type. Always \"json\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "JsonType", - "description": "Parameter type for JSON values." - }, - "NumberType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "number", - "default": "number", - "description": "Discriminator type. Always \"number\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "NumberType", - "description": "Parameter type for numeric values." - }, - "ObjectType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "object", - "default": "object", - "description": "Discriminator type. Always \"object\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "ObjectType", - "description": "Parameter type for object values." - }, - "ParamType": { - "oneOf": [ - { - "$ref": "#/components/schemas/StringType" - }, - { - "$ref": "#/components/schemas/NumberType" - }, - { - "$ref": "#/components/schemas/BooleanType" - }, - { - "$ref": "#/components/schemas/ArrayType" - }, - { - "$ref": "#/components/schemas/ObjectType" - }, - { - "$ref": "#/components/schemas/JsonType" - }, - { - "$ref": "#/components/schemas/UnionType" - }, - { - "$ref": "#/components/schemas/ChatCompletionInputType" - }, - { - "$ref": "#/components/schemas/CompletionInputType" - }, - { - "$ref": "#/components/schemas/AgentTurnInputType" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "string": "#/components/schemas/StringType", - "number": "#/components/schemas/NumberType", - "boolean": "#/components/schemas/BooleanType", - "array": "#/components/schemas/ArrayType", - "object": "#/components/schemas/ObjectType", - "json": "#/components/schemas/JsonType", - "union": "#/components/schemas/UnionType", - "chat_completion_input": "#/components/schemas/ChatCompletionInputType", - "completion_input": "#/components/schemas/CompletionInputType", - "agent_turn_input": "#/components/schemas/AgentTurnInputType" - } - } - }, - "ScoringFn": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "scoring_function", - "default": "scoring_function", - "description": "The resource type, always scoring_function" - }, - "description": { - "type": "string" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - }, - "return_type": { - "$ref": "#/components/schemas/ParamType" - }, - "params": { - "$ref": "#/components/schemas/ScoringFnParams" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type", - "metadata", - "return_type" - ], - "title": "ScoringFn", - "description": "A scoring function resource for evaluating model outputs." - }, - "StringType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "string", - "default": "string", - "description": "Discriminator type. Always \"string\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "StringType", - "description": "Parameter type for string values." - }, - "UnionType": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "union", - "default": "union", - "description": "Discriminator type. Always \"union\"" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "UnionType", - "description": "Parameter type for union values." - }, - "Shield": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "shield", - "default": "shield", - "description": "The resource type, always shield" - }, - "params": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Configuration parameters for the shield" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type" - ], - "title": "Shield", - "description": "A safety shield resource that can be used to check content." - }, - "Span": { - "type": "object", - "properties": { - "span_id": { - "type": "string", - "description": "Unique identifier for the span" - }, - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace this span belongs to" - }, - "parent_span_id": { - "type": "string", - "description": "(Optional) Unique identifier for the parent span, if this is a child span" - }, - "name": { - "type": "string", - "description": "Human-readable name describing the operation this span represents" - }, - "start_time": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the operation began" - }, - "end_time": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the operation finished, if completed" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Key-value pairs containing additional metadata about the span" - } - }, - "additionalProperties": false, - "required": [ - "span_id", - "trace_id", - "name", - "start_time" - ], - "title": "Span", - "description": "A span representing a single operation within a trace." - }, - "GetSpanTreeRequest": { - "type": "object", - "properties": { - "attributes_to_return": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The attributes to return in the tree." - }, - "max_depth": { - "type": "integer", - "description": "The maximum depth of the tree." - } - }, - "additionalProperties": false, - "title": "GetSpanTreeRequest" - }, - "SpanStatus": { - "type": "string", - "enum": [ - "ok", - "error" - ], - "title": "SpanStatus", - "description": "The status of a span indicating whether it completed successfully or with an error." - }, - "SpanWithStatus": { - "type": "object", - "properties": { - "span_id": { - "type": "string", - "description": "Unique identifier for the span" - }, - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace this span belongs to" - }, - "parent_span_id": { - "type": "string", - "description": "(Optional) Unique identifier for the parent span, if this is a child span" - }, - "name": { - "type": "string", - "description": "Human-readable name describing the operation this span represents" - }, - "start_time": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the operation began" - }, - "end_time": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the operation finished, if completed" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Key-value pairs containing additional metadata about the span" - }, - "status": { - "$ref": "#/components/schemas/SpanStatus", - "description": "(Optional) The current status of the span" - } - }, - "additionalProperties": false, - "required": [ - "span_id", - "trace_id", - "name", - "start_time" - ], - "title": "SpanWithStatus", - "description": "A span that includes status information." - }, - "QuerySpanTreeResponse": { - "type": "object", - "properties": { - "data": { - "type": "object", - "additionalProperties": { - "$ref": "#/components/schemas/SpanWithStatus" - }, - "description": "Dictionary mapping span IDs to spans with status information" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "QuerySpanTreeResponse", - "description": "Response containing a tree structure of spans." - }, - "Tool": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "tool", - "default": "tool", - "description": "Type of resource, always 'tool'" - }, - "toolgroup_id": { - "type": "string", - "description": "ID of the tool group this tool belongs to" - }, - "description": { - "type": "string", - "description": "Human-readable description of what the tool does" - }, - "parameters": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ToolParameter" - }, - "description": "List of parameters this tool accepts" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Additional metadata about the tool" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type", - "toolgroup_id", - "description", - "parameters" - ], - "title": "Tool", - "description": "A tool that can be invoked by agents." - }, - "ToolGroup": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "tool_group", - "default": "tool_group", - "description": "Type of resource, always 'tool_group'" - }, - "mcp_endpoint": { - "$ref": "#/components/schemas/URL", - "description": "(Optional) Model Context Protocol endpoint for remote tools" - }, - "args": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Additional arguments for the tool group" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type" - ], - "title": "ToolGroup", - "description": "A group of related tools managed together." - }, - "Trace": { - "type": "object", - "properties": { - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace" - }, - "root_span_id": { - "type": "string", - "description": "Unique identifier for the root span that started this trace" - }, - "start_time": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the trace began" - }, - "end_time": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the trace finished, if completed" - } - }, - "additionalProperties": false, - "required": [ - "trace_id", - "root_span_id", - "start_time" - ], - "title": "Trace", - "description": "A trace representing the complete execution path of a request across multiple operations." - }, - "Checkpoint": { - "type": "object", - "properties": { - "identifier": { - "type": "string", - "description": "Unique identifier for the checkpoint" - }, - "created_at": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the checkpoint was created" - }, - "epoch": { - "type": "integer", - "description": "Training epoch when the checkpoint was saved" - }, - "post_training_job_id": { - "type": "string", - "description": "Identifier of the training job that created this checkpoint" - }, - "path": { - "type": "string", - "description": "File system path where the checkpoint is stored" - }, - "training_metrics": { - "$ref": "#/components/schemas/PostTrainingMetric", - "description": "(Optional) Training metrics associated with this checkpoint" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "created_at", - "epoch", - "post_training_job_id", - "path" - ], - "title": "Checkpoint", - "description": "Checkpoint created during training runs." - }, - "PostTrainingJobArtifactsResponse": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string", - "description": "Unique identifier for the training job" - }, - "checkpoints": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Checkpoint" - }, - "description": "List of model checkpoints created during training" - } - }, - "additionalProperties": false, - "required": [ - "job_uuid", - "checkpoints" - ], - "title": "PostTrainingJobArtifactsResponse", - "description": "Artifacts of a finetuning job." - }, - "PostTrainingMetric": { - "type": "object", - "properties": { - "epoch": { - "type": "integer", - "description": "Training epoch number" - }, - "train_loss": { - "type": "number", - "description": "Loss value on the training dataset" - }, - "validation_loss": { - "type": "number", - "description": "Loss value on the validation dataset" - }, - "perplexity": { - "type": "number", - "description": "Perplexity metric indicating model confidence" - } - }, - "additionalProperties": false, - "required": [ - "epoch", - "train_loss", - "validation_loss", - "perplexity" - ], - "title": "PostTrainingMetric", - "description": "Training metrics captured during post-training jobs." - }, - "PostTrainingJobStatusResponse": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string", - "description": "Unique identifier for the training job" - }, - "status": { - "type": "string", - "enum": [ - "completed", - "in_progress", - "failed", - "scheduled", - "cancelled" - ], - "description": "Current status of the training job" - }, - "scheduled_at": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the job was scheduled" - }, - "started_at": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the job execution began" - }, - "completed_at": { - "type": "string", - "format": "date-time", - "description": "(Optional) Timestamp when the job finished, if completed" - }, - "resources_allocated": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Information about computational resources allocated to the job" - }, - "checkpoints": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Checkpoint" - }, - "description": "List of model checkpoints created during training" - } - }, - "additionalProperties": false, - "required": [ - "job_uuid", - "status", - "checkpoints" - ], - "title": "PostTrainingJobStatusResponse", - "description": "Status of a finetuning job." - }, - "ListPostTrainingJobsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "job_uuid" - ], - "title": "PostTrainingJob" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListPostTrainingJobsResponse" - }, - "VectorDB": { - "type": "object", - "properties": { - "identifier": { - "type": "string" - }, - "provider_resource_id": { - "type": "string" - }, - "provider_id": { - "type": "string" - }, - "type": { - "type": "string", - "enum": [ - "model", - "shield", - "vector_db", - "dataset", - "scoring_function", - "benchmark", - "tool", - "tool_group", - "prompt" - ], - "const": "vector_db", - "default": "vector_db", - "description": "Type of resource, always 'vector_db' for vector databases" - }, - "embedding_model": { - "type": "string", - "description": "Name of the embedding model to use for vector generation" - }, - "embedding_dimension": { - "type": "integer", - "description": "Dimension of the embedding vectors" - }, - "vector_db_name": { - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "identifier", - "provider_id", - "type", - "embedding_model", - "embedding_dimension" - ], - "title": "VectorDB", - "description": "Vector database resource for storing and querying vector embeddings." - }, - "HealthInfo": { - "type": "object", - "properties": { - "status": { - "type": "string", - "enum": [ - "OK", - "Error", - "Not Implemented" - ], - "description": "Current health status of the service" - } - }, - "additionalProperties": false, - "required": [ - "status" - ], - "title": "HealthInfo", - "description": "Health status information for the service." - }, - "RAGDocument": { - "type": "object", - "properties": { - "document_id": { - "type": "string", - "description": "The unique identifier for the document." - }, - "content": { - "oneOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/InterleavedContentItem" - }, - { - "type": "array", - "items": { - "$ref": "#/components/schemas/InterleavedContentItem" - } - }, - { - "$ref": "#/components/schemas/URL" - } - ], - "description": "The content of the document." - }, - "mime_type": { - "type": "string", - "description": "The MIME type of the document." - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Additional metadata for the document." - } - }, - "additionalProperties": false, - "required": [ - "document_id", - "content", - "metadata" - ], - "title": "RAGDocument", - "description": "A document to be used for document ingestion in the RAG Tool." - }, - "InsertRequest": { - "type": "object", - "properties": { - "documents": { - "type": "array", - "items": { - "$ref": "#/components/schemas/RAGDocument" - }, - "description": "List of documents to index in the RAG system" - }, - "vector_db_id": { - "type": "string", - "description": "ID of the vector database to store the document embeddings" - }, - "chunk_size_in_tokens": { - "type": "integer", - "description": "(Optional) Size in tokens for document chunking during indexing" - } - }, - "additionalProperties": false, - "required": [ - "documents", - "vector_db_id", - "chunk_size_in_tokens" - ], - "title": "InsertRequest" - }, - "Chunk": { - "type": "object", - "properties": { - "content": { - "$ref": "#/components/schemas/InterleavedContent", - "description": "The content of the chunk, which can be interleaved text, images, or other types." - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Metadata associated with the chunk that will be used in the model context during inference." - }, - "embedding": { - "type": "array", - "items": { - "type": "number" - }, - "description": "Optional embedding for the chunk. If not provided, it will be computed later." - }, - "stored_chunk_id": { - "type": "string", - "description": "The chunk ID that is stored in the vector database. Used for backend functionality." - }, - "chunk_metadata": { - "$ref": "#/components/schemas/ChunkMetadata", - "description": "Metadata for the chunk that will NOT be used in the context during inference. The `chunk_metadata` is required backend functionality." - } - }, - "additionalProperties": false, - "required": [ - "content", - "metadata" - ], - "title": "Chunk", - "description": "A chunk of content that can be inserted into a vector database." - }, - "ChunkMetadata": { - "type": "object", - "properties": { - "chunk_id": { - "type": "string", - "description": "The ID of the chunk. If not set, it will be generated based on the document ID and content." - }, - "document_id": { - "type": "string", - "description": "The ID of the document this chunk belongs to." - }, - "source": { - "type": "string", - "description": "The source of the content, such as a URL, file path, or other identifier." - }, - "created_timestamp": { - "type": "integer", - "description": "An optional timestamp indicating when the chunk was created." - }, - "updated_timestamp": { - "type": "integer", - "description": "An optional timestamp indicating when the chunk was last updated." - }, - "chunk_window": { - "type": "string", - "description": "The window of the chunk, which can be used to group related chunks together." - }, - "chunk_tokenizer": { - "type": "string", - "description": "The tokenizer used to create the chunk. Default is Tiktoken." - }, - "chunk_embedding_model": { - "type": "string", - "description": "The embedding model used to create the chunk's embedding." - }, - "chunk_embedding_dimension": { - "type": "integer", - "description": "The dimension of the embedding vector for the chunk." - }, - "content_token_count": { - "type": "integer", - "description": "The number of tokens in the content of the chunk." - }, - "metadata_token_count": { - "type": "integer", - "description": "The number of tokens in the metadata of the chunk." - } - }, - "additionalProperties": false, - "title": "ChunkMetadata", - "description": "`ChunkMetadata` is backend metadata for a `Chunk` that is used to store additional information about the chunk that will not be used in the context during inference, but is required for backend functionality. The `ChunkMetadata` is set during chunk creation in `MemoryToolRuntimeImpl().insert()`and is not expected to change after. Use `Chunk.metadata` for metadata that will be used in the context during inference." - }, - "InsertChunksRequest": { - "type": "object", - "properties": { - "vector_db_id": { - "type": "string", - "description": "The identifier of the vector database to insert the chunks into." - }, - "chunks": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Chunk" - }, - "description": "The chunks to insert. Each `Chunk` should contain content which can be interleaved text, images, or other types. `metadata`: `dict[str, Any]` and `embedding`: `List[float]` are optional. If `metadata` is provided, you configure how Llama Stack formats the chunk during generation. If `embedding` is not provided, it will be computed later." - }, - "ttl_seconds": { - "type": "integer", - "description": "The time to live of the chunks." - } - }, - "additionalProperties": false, - "required": [ - "vector_db_id", - "chunks" - ], - "title": "InsertChunksRequest" - }, - "ProviderInfo": { - "type": "object", - "properties": { - "api": { - "type": "string", - "description": "The API name this provider implements" - }, - "provider_id": { - "type": "string", - "description": "Unique identifier for the provider" - }, - "provider_type": { - "type": "string", - "description": "The type of provider implementation" - }, - "config": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Configuration parameters for the provider" - }, - "health": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Current health status of the provider" - } - }, - "additionalProperties": false, - "required": [ - "api", - "provider_id", - "provider_type", - "config", - "health" - ], - "title": "ProviderInfo", - "description": "Information about a registered provider including its configuration and health status." - }, - "InvokeToolRequest": { - "type": "object", - "properties": { - "tool_name": { - "type": "string", - "description": "The name of the tool to invoke." - }, - "kwargs": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "A dictionary of arguments to pass to the tool." - } - }, - "additionalProperties": false, - "required": [ - "tool_name", - "kwargs" - ], - "title": "InvokeToolRequest" - }, - "ToolInvocationResult": { - "type": "object", - "properties": { - "content": { - "$ref": "#/components/schemas/InterleavedContent", - "description": "(Optional) The output content from the tool execution" - }, - "error_message": { - "type": "string", - "description": "(Optional) Error message if the tool execution failed" - }, - "error_code": { - "type": "integer", - "description": "(Optional) Numeric error code if the tool execution failed" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Additional metadata about the tool execution" - } - }, - "additionalProperties": false, - "title": "ToolInvocationResult", - "description": "Result of a tool invocation." - }, - "PaginatedResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - }, - "description": "The list of items for the current page" - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more items available after this set" - }, - "url": { - "type": "string", - "description": "The URL for accessing this list" - } - }, - "additionalProperties": false, - "required": [ - "data", - "has_more" - ], - "title": "PaginatedResponse", - "description": "A generic paginated response that follows a simple format." - }, - "Job": { - "type": "object", - "properties": { - "job_id": { - "type": "string", - "description": "Unique identifier for the job" - }, - "status": { - "type": "string", - "enum": [ - "completed", - "in_progress", - "failed", - "scheduled", - "cancelled" - ], - "description": "Current execution status of the job" - } - }, - "additionalProperties": false, - "required": [ - "job_id", - "status" - ], - "title": "Job", - "description": "A job execution instance with status tracking." - }, - "ListBenchmarksResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Benchmark" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListBenchmarksResponse" - }, - "Order": { - "type": "string", - "enum": [ - "asc", - "desc" - ], - "title": "Order", - "description": "Sort order for paginated responses." - }, - "ListOpenAIChatCompletionResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The ID of the chat completion" - }, - "choices": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIChoice" - }, - "description": "List of choices" - }, - "object": { - "type": "string", - "const": "chat.completion", - "default": "chat.completion", - "description": "The object type, which will be \"chat.completion\"" - }, - "created": { - "type": "integer", - "description": "The Unix timestamp in seconds when the chat completion was created" - }, - "model": { - "type": "string", - "description": "The model that was used to generate the chat completion" - }, - "input_messages": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIMessageParam" - } - } - }, - "additionalProperties": false, - "required": [ - "id", - "choices", - "object", - "created", - "model", - "input_messages" - ], - "title": "OpenAICompletionWithInputMessages" - }, - "description": "List of chat completion objects with their input messages" - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more completions available beyond this list" - }, - "first_id": { - "type": "string", - "description": "ID of the first completion in this list" - }, - "last_id": { - "type": "string", - "description": "ID of the last completion in this list" - }, - "object": { - "type": "string", - "const": "list", - "default": "list", - "description": "Must be \"list\" to identify this as a list response" - } - }, - "additionalProperties": false, - "required": [ - "data", - "has_more", - "first_id", - "last_id", - "object" - ], - "title": "ListOpenAIChatCompletionResponse", - "description": "Response from listing OpenAI-compatible chat completions." - }, - "ListDatasetsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Dataset" - }, - "description": "List of datasets" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListDatasetsResponse", - "description": "Response from listing datasets." - }, - "ListModelsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Model" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListModelsResponse" - }, - "ListOpenAIResponseInputItem": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIResponseInput" - }, - "description": "List of input items" - }, - "object": { - "type": "string", - "const": "list", - "default": "list", - "description": "Object type identifier, always \"list\"" - } - }, - "additionalProperties": false, - "required": [ - "data", - "object" - ], - "title": "ListOpenAIResponseInputItem", - "description": "List container for OpenAI response input items." - }, - "ListOpenAIResponseObject": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIResponseObjectWithInput" - }, - "description": "List of response objects with their input context" - }, - "has_more": { - "type": "boolean", - "description": "Whether there are more results available beyond this page" - }, - "first_id": { - "type": "string", - "description": "Identifier of the first item in this page" - }, - "last_id": { - "type": "string", - "description": "Identifier of the last item in this page" - }, - "object": { - "type": "string", - "const": "list", - "default": "list", - "description": "Object type identifier, always \"list\"" - } - }, - "additionalProperties": false, - "required": [ - "data", - "has_more", - "first_id", - "last_id", - "object" - ], - "title": "ListOpenAIResponseObject", - "description": "Paginated list of OpenAI response objects with navigation metadata." - }, - "OpenAIResponseObjectWithInput": { - "type": "object", - "properties": { - "created_at": { - "type": "integer", - "description": "Unix timestamp when the response was created" - }, - "error": { - "$ref": "#/components/schemas/OpenAIResponseError", - "description": "(Optional) Error details if the response generation failed" - }, - "id": { - "type": "string", - "description": "Unique identifier for this response" - }, - "model": { - "type": "string", - "description": "Model identifier used for generation" - }, - "object": { - "type": "string", - "const": "response", - "default": "response", - "description": "Object type identifier, always \"response\"" - }, - "output": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIResponseOutput" - }, - "description": "List of generated output items (messages, tool calls, etc.)" - }, - "parallel_tool_calls": { - "type": "boolean", - "default": false, - "description": "Whether tool calls can be executed in parallel" - }, - "previous_response_id": { - "type": "string", - "description": "(Optional) ID of the previous response in a conversation" - }, - "status": { - "type": "string", - "description": "Current status of the response generation" - }, - "temperature": { - "type": "number", - "description": "(Optional) Sampling temperature used for generation" - }, - "text": { - "$ref": "#/components/schemas/OpenAIResponseText", - "description": "Text formatting configuration for the response" - }, - "top_p": { - "type": "number", - "description": "(Optional) Nucleus sampling parameter used for generation" - }, - "truncation": { - "type": "string", - "description": "(Optional) Truncation strategy applied to the response" - }, - "user": { - "type": "string", - "description": "(Optional) User identifier associated with the request" - }, - "input": { - "type": "array", - "items": { - "$ref": "#/components/schemas/OpenAIResponseInput" - }, - "description": "List of input items that led to this response" - } - }, - "additionalProperties": false, - "required": [ - "created_at", - "id", - "model", - "object", - "output", - "parallel_tool_calls", - "status", - "text", - "input" - ], - "title": "OpenAIResponseObjectWithInput", - "description": "OpenAI response object extended with input context information." - }, - "ListPromptsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Prompt" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListPromptsResponse", - "description": "Response model to list prompts." - }, - "ListProvidersResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ProviderInfo" - }, - "description": "List of provider information objects" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListProvidersResponse", - "description": "Response containing a list of all available providers." - }, - "RouteInfo": { - "type": "object", - "properties": { - "route": { - "type": "string", - "description": "The API endpoint path" - }, - "method": { - "type": "string", - "description": "HTTP method for the route" - }, - "provider_types": { - "type": "array", - "items": { - "type": "string" - }, - "description": "List of provider types that implement this route" - } - }, - "additionalProperties": false, - "required": [ - "route", - "method", - "provider_types" - ], - "title": "RouteInfo", - "description": "Information about an API route including its path, method, and implementing providers." - }, - "ListRoutesResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/RouteInfo" - }, - "description": "List of available route information objects" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListRoutesResponse", - "description": "Response containing a list of all available API routes." - }, - "ListToolDefsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ToolDef" - }, - "description": "List of tool definitions" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListToolDefsResponse", - "description": "Response containing a list of tool definitions." - }, - "ListScoringFunctionsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ScoringFn" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListScoringFunctionsResponse" - }, - "ListShieldsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Shield" - } - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListShieldsResponse" - }, - "ListToolGroupsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ToolGroup" - }, - "description": "List of tool groups" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListToolGroupsResponse", - "description": "Response containing a list of tool groups." - }, - "ListToolsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Tool" - }, - "description": "List of tools" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListToolsResponse", - "description": "Response containing a list of tools." - }, - "ListVectorDBsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/VectorDB" - }, - "description": "List of vector databases" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "ListVectorDBsResponse", - "description": "Response from listing vector databases." - }, - "Event": { - "oneOf": [ - { - "$ref": "#/components/schemas/UnstructuredLogEvent" - }, - { - "$ref": "#/components/schemas/MetricEvent" - }, - { - "$ref": "#/components/schemas/StructuredLogEvent" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "unstructured_log": "#/components/schemas/UnstructuredLogEvent", - "metric": "#/components/schemas/MetricEvent", - "structured_log": "#/components/schemas/StructuredLogEvent" - } - } - }, - "EventType": { - "type": "string", - "enum": [ - "unstructured_log", - "structured_log", - "metric" - ], - "title": "EventType", - "description": "The type of telemetry event being logged." - }, - "LogSeverity": { - "type": "string", - "enum": [ - "verbose", - "debug", - "info", - "warn", - "error", - "critical" - ], - "title": "LogSeverity", - "description": "The severity level of a log message." - }, - "MetricEvent": { - "type": "object", - "properties": { - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace this event belongs to" - }, - "span_id": { - "type": "string", - "description": "Unique identifier for the span this event belongs to" - }, - "timestamp": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the event occurred" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "string" - }, - { - "type": "integer" - }, - { - "type": "number" - }, - { - "type": "boolean" - }, - { - "type": "null" - } - ] - }, - "description": "(Optional) Key-value pairs containing additional metadata about the event" - }, - "type": { - "$ref": "#/components/schemas/EventType", - "const": "metric", - "default": "metric", - "description": "Event type identifier set to METRIC" - }, - "metric": { - "type": "string", - "description": "The name of the metric being measured" - }, - "value": { - "oneOf": [ - { - "type": "integer" - }, - { - "type": "number" - } - ], - "description": "The numeric value of the metric measurement" - }, - "unit": { - "type": "string", - "description": "The unit of measurement for the metric value" - } - }, - "additionalProperties": false, - "required": [ - "trace_id", - "span_id", - "timestamp", - "type", - "metric", - "value", - "unit" - ], - "title": "MetricEvent", - "description": "A metric event containing a measured value." - }, - "SpanEndPayload": { - "type": "object", - "properties": { - "type": { - "$ref": "#/components/schemas/StructuredLogType", - "const": "span_end", - "default": "span_end", - "description": "Payload type identifier set to SPAN_END" - }, - "status": { - "$ref": "#/components/schemas/SpanStatus", - "description": "The final status of the span indicating success or failure" - } - }, - "additionalProperties": false, - "required": [ - "type", - "status" - ], - "title": "SpanEndPayload", - "description": "Payload for a span end event." - }, - "SpanStartPayload": { - "type": "object", - "properties": { - "type": { - "$ref": "#/components/schemas/StructuredLogType", - "const": "span_start", - "default": "span_start", - "description": "Payload type identifier set to SPAN_START" - }, - "name": { - "type": "string", - "description": "Human-readable name describing the operation this span represents" - }, - "parent_span_id": { - "type": "string", - "description": "(Optional) Unique identifier for the parent span, if this is a child span" - } - }, - "additionalProperties": false, - "required": [ - "type", - "name" - ], - "title": "SpanStartPayload", - "description": "Payload for a span start event." - }, - "StructuredLogEvent": { - "type": "object", - "properties": { - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace this event belongs to" - }, - "span_id": { - "type": "string", - "description": "Unique identifier for the span this event belongs to" - }, - "timestamp": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the event occurred" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "string" - }, - { - "type": "integer" - }, - { - "type": "number" - }, - { - "type": "boolean" - }, - { - "type": "null" - } - ] - }, - "description": "(Optional) Key-value pairs containing additional metadata about the event" - }, - "type": { - "$ref": "#/components/schemas/EventType", - "const": "structured_log", - "default": "structured_log", - "description": "Event type identifier set to STRUCTURED_LOG" - }, - "payload": { - "$ref": "#/components/schemas/StructuredLogPayload", - "description": "The structured payload data for the log event" - } - }, - "additionalProperties": false, - "required": [ - "trace_id", - "span_id", - "timestamp", - "type", - "payload" - ], - "title": "StructuredLogEvent", - "description": "A structured log event containing typed payload data." - }, - "StructuredLogPayload": { - "oneOf": [ - { - "$ref": "#/components/schemas/SpanStartPayload" - }, - { - "$ref": "#/components/schemas/SpanEndPayload" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "span_start": "#/components/schemas/SpanStartPayload", - "span_end": "#/components/schemas/SpanEndPayload" - } - } - }, - "StructuredLogType": { - "type": "string", - "enum": [ - "span_start", - "span_end" - ], - "title": "StructuredLogType", - "description": "The type of structured log event payload." - }, - "UnstructuredLogEvent": { - "type": "object", - "properties": { - "trace_id": { - "type": "string", - "description": "Unique identifier for the trace this event belongs to" - }, - "span_id": { - "type": "string", - "description": "Unique identifier for the span this event belongs to" - }, - "timestamp": { - "type": "string", - "format": "date-time", - "description": "Timestamp when the event occurred" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "string" - }, - { - "type": "integer" - }, - { - "type": "number" - }, - { - "type": "boolean" - }, - { - "type": "null" - } - ] - }, - "description": "(Optional) Key-value pairs containing additional metadata about the event" - }, - "type": { - "$ref": "#/components/schemas/EventType", - "const": "unstructured_log", - "default": "unstructured_log", - "description": "Event type identifier set to UNSTRUCTURED_LOG" - }, - "message": { - "type": "string", - "description": "The log message text" - }, - "severity": { - "$ref": "#/components/schemas/LogSeverity", - "description": "The severity level of the log message" - } - }, - "additionalProperties": false, - "required": [ - "trace_id", - "span_id", - "timestamp", - "type", - "message", - "severity" - ], - "title": "UnstructuredLogEvent", - "description": "An unstructured log event containing a simple text message." - }, - "LogEventRequest": { - "type": "object", - "properties": { - "event": { - "$ref": "#/components/schemas/Event", - "description": "The event to log." - }, - "ttl_seconds": { - "type": "integer", - "description": "The time to live of the event." - } - }, - "additionalProperties": false, - "required": [ - "event", - "ttl_seconds" - ], - "title": "LogEventRequest" - }, - "VectorStoreChunkingStrategy": { - "oneOf": [ - { - "$ref": "#/components/schemas/VectorStoreChunkingStrategyAuto" - }, - { - "$ref": "#/components/schemas/VectorStoreChunkingStrategyStatic" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "auto": "#/components/schemas/VectorStoreChunkingStrategyAuto", - "static": "#/components/schemas/VectorStoreChunkingStrategyStatic" - } - } - }, - "VectorStoreChunkingStrategyAuto": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "auto", - "default": "auto", - "description": "Strategy type, always \"auto\" for automatic chunking" - } - }, - "additionalProperties": false, - "required": [ - "type" - ], - "title": "VectorStoreChunkingStrategyAuto", - "description": "Automatic chunking strategy for vector store files." - }, - "VectorStoreChunkingStrategyStatic": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "static", - "default": "static", - "description": "Strategy type, always \"static\" for static chunking" - }, - "static": { - "$ref": "#/components/schemas/VectorStoreChunkingStrategyStaticConfig", - "description": "Configuration parameters for the static chunking strategy" - } - }, - "additionalProperties": false, - "required": [ - "type", - "static" - ], - "title": "VectorStoreChunkingStrategyStatic", - "description": "Static chunking strategy with configurable parameters." - }, - "VectorStoreChunkingStrategyStaticConfig": { - "type": "object", - "properties": { - "chunk_overlap_tokens": { - "type": "integer", - "default": 400, - "description": "Number of tokens to overlap between adjacent chunks" - }, - "max_chunk_size_tokens": { - "type": "integer", - "default": 800, - "description": "Maximum number of tokens per chunk, must be between 100 and 4096" - } - }, - "additionalProperties": false, - "required": [ - "chunk_overlap_tokens", - "max_chunk_size_tokens" - ], - "title": "VectorStoreChunkingStrategyStaticConfig", - "description": "Configuration for static chunking strategy." - }, - "OpenaiAttachFileToVectorStoreRequest": { - "type": "object", - "properties": { - "file_id": { - "type": "string", - "description": "The ID of the file to attach to the vector store." - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The key-value attributes stored with the file, which can be used for filtering." - }, - "chunking_strategy": { - "$ref": "#/components/schemas/VectorStoreChunkingStrategy", - "description": "The chunking strategy to use for the file." - } - }, - "additionalProperties": false, - "required": [ - "file_id" - ], - "title": "OpenaiAttachFileToVectorStoreRequest" - }, - "VectorStoreFileLastError": { - "type": "object", - "properties": { - "code": { - "oneOf": [ - { - "type": "string", - "const": "server_error" - }, - { - "type": "string", - "const": "rate_limit_exceeded" - } - ], - "description": "Error code indicating the type of failure" - }, - "message": { - "type": "string", - "description": "Human-readable error message describing the failure" - } - }, - "additionalProperties": false, - "required": [ - "code", - "message" - ], - "title": "VectorStoreFileLastError", - "description": "Error information for failed vector store file processing." - }, - "VectorStoreFileObject": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "Unique identifier for the file" - }, - "object": { - "type": "string", - "default": "vector_store.file", - "description": "Object type identifier, always \"vector_store.file\"" - }, - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Key-value attributes associated with the file" - }, - "chunking_strategy": { - "$ref": "#/components/schemas/VectorStoreChunkingStrategy", - "description": "Strategy used for splitting the file into chunks" - }, - "created_at": { - "type": "integer", - "description": "Timestamp when the file was added to the vector store" - }, - "last_error": { - "$ref": "#/components/schemas/VectorStoreFileLastError", - "description": "(Optional) Error information if file processing failed" - }, - "status": { - "$ref": "#/components/schemas/VectorStoreFileStatus", - "description": "Current processing status of the file" - }, - "usage_bytes": { - "type": "integer", - "default": 0, - "description": "Storage space used by this file in bytes" - }, - "vector_store_id": { - "type": "string", - "description": "ID of the vector store containing this file" - } - }, - "additionalProperties": false, - "required": [ - "id", - "object", - "attributes", - "chunking_strategy", - "created_at", - "status", - "usage_bytes", - "vector_store_id" - ], - "title": "VectorStoreFileObject", - "description": "OpenAI Vector Store File object." - }, - "VectorStoreFileStatus": { - "oneOf": [ - { - "type": "string", - "const": "completed" - }, - { - "type": "string", - "const": "in_progress" - }, - { - "type": "string", - "const": "cancelled" - }, - { - "type": "string", - "const": "failed" - } - ] - }, "OpenAIJSONSchema": { "type": "object", "properties": { @@ -9657,7 +6829,8 @@ "type": "string", "enum": [ "llm", - "embedding" + "embedding", + "rerank" ], "title": "ModelType", "description": "Enumeration of supported model types in Llama Stack." @@ -15610,2170 +12783,6 @@ "title": "VectorStoreSearchResponsePage", "description": "Paginated response from searching a vector store." }, -<<<<<<< HEAD -======= - "OpenaiUpdateVectorStoreRequest": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the vector store." - }, - "expires_after": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The expiration policy for a vector store." - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Set of 16 key-value pairs that can be attached to an object." - } - }, - "additionalProperties": false, - "title": "OpenaiUpdateVectorStoreRequest" - }, - "OpenaiUpdateVectorStoreFileRequest": { - "type": "object", - "properties": { - "attributes": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The updated key-value attributes to store with the file." - } - }, - "additionalProperties": false, - "required": [ - "attributes" - ], - "title": "OpenaiUpdateVectorStoreFileRequest" - }, - "DPOAlignmentConfig": { - "type": "object", - "properties": { - "beta": { - "type": "number", - "description": "Temperature parameter for the DPO loss" - }, - "loss_type": { - "$ref": "#/components/schemas/DPOLossType", - "default": "sigmoid", - "description": "The type of loss function to use for DPO" - } - }, - "additionalProperties": false, - "required": [ - "beta", - "loss_type" - ], - "title": "DPOAlignmentConfig", - "description": "Configuration for Direct Preference Optimization (DPO) alignment." - }, - "DPOLossType": { - "type": "string", - "enum": [ - "sigmoid", - "hinge", - "ipo", - "kto_pair" - ], - "title": "DPOLossType" - }, - "DataConfig": { - "type": "object", - "properties": { - "dataset_id": { - "type": "string", - "description": "Unique identifier for the training dataset" - }, - "batch_size": { - "type": "integer", - "description": "Number of samples per training batch" - }, - "shuffle": { - "type": "boolean", - "description": "Whether to shuffle the dataset during training" - }, - "data_format": { - "$ref": "#/components/schemas/DatasetFormat", - "description": "Format of the dataset (instruct or dialog)" - }, - "validation_dataset_id": { - "type": "string", - "description": "(Optional) Unique identifier for the validation dataset" - }, - "packed": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to pack multiple samples into a single sequence for efficiency" - }, - "train_on_input": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to compute loss on input tokens as well as output tokens" - } - }, - "additionalProperties": false, - "required": [ - "dataset_id", - "batch_size", - "shuffle", - "data_format" - ], - "title": "DataConfig", - "description": "Configuration for training data and data loading." - }, - "DatasetFormat": { - "type": "string", - "enum": [ - "instruct", - "dialog" - ], - "title": "DatasetFormat", - "description": "Format of the training dataset." - }, - "EfficiencyConfig": { - "type": "object", - "properties": { - "enable_activation_checkpointing": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to use activation checkpointing to reduce memory usage" - }, - "enable_activation_offloading": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to offload activations to CPU to save GPU memory" - }, - "memory_efficient_fsdp_wrap": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to use memory-efficient FSDP wrapping" - }, - "fsdp_cpu_offload": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to offload FSDP parameters to CPU" - } - }, - "additionalProperties": false, - "title": "EfficiencyConfig", - "description": "Configuration for memory and compute efficiency optimizations." - }, - "OptimizerConfig": { - "type": "object", - "properties": { - "optimizer_type": { - "$ref": "#/components/schemas/OptimizerType", - "description": "Type of optimizer to use (adam, adamw, or sgd)" - }, - "lr": { - "type": "number", - "description": "Learning rate for the optimizer" - }, - "weight_decay": { - "type": "number", - "description": "Weight decay coefficient for regularization" - }, - "num_warmup_steps": { - "type": "integer", - "description": "Number of steps for learning rate warmup" - } - }, - "additionalProperties": false, - "required": [ - "optimizer_type", - "lr", - "weight_decay", - "num_warmup_steps" - ], - "title": "OptimizerConfig", - "description": "Configuration parameters for the optimization algorithm." - }, - "OptimizerType": { - "type": "string", - "enum": [ - "adam", - "adamw", - "sgd" - ], - "title": "OptimizerType", - "description": "Available optimizer algorithms for training." - }, - "TrainingConfig": { - "type": "object", - "properties": { - "n_epochs": { - "type": "integer", - "description": "Number of training epochs to run" - }, - "max_steps_per_epoch": { - "type": "integer", - "default": 1, - "description": "Maximum number of steps to run per epoch" - }, - "gradient_accumulation_steps": { - "type": "integer", - "default": 1, - "description": "Number of steps to accumulate gradients before updating" - }, - "max_validation_steps": { - "type": "integer", - "default": 1, - "description": "(Optional) Maximum number of validation steps per epoch" - }, - "data_config": { - "$ref": "#/components/schemas/DataConfig", - "description": "(Optional) Configuration for data loading and formatting" - }, - "optimizer_config": { - "$ref": "#/components/schemas/OptimizerConfig", - "description": "(Optional) Configuration for the optimization algorithm" - }, - "efficiency_config": { - "$ref": "#/components/schemas/EfficiencyConfig", - "description": "(Optional) Configuration for memory and compute optimizations" - }, - "dtype": { - "type": "string", - "default": "bf16", - "description": "(Optional) Data type for model parameters (bf16, fp16, fp32)" - } - }, - "additionalProperties": false, - "required": [ - "n_epochs", - "max_steps_per_epoch", - "gradient_accumulation_steps" - ], - "title": "TrainingConfig", - "description": "Comprehensive configuration for the training process." - }, - "PreferenceOptimizeRequest": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string", - "description": "The UUID of the job to create." - }, - "finetuned_model": { - "type": "string", - "description": "The model to fine-tune." - }, - "algorithm_config": { - "$ref": "#/components/schemas/DPOAlignmentConfig", - "description": "The algorithm configuration." - }, - "training_config": { - "$ref": "#/components/schemas/TrainingConfig", - "description": "The training configuration." - }, - "hyperparam_search_config": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The hyperparam search configuration." - }, - "logger_config": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The logger configuration." - } - }, - "additionalProperties": false, - "required": [ - "job_uuid", - "finetuned_model", - "algorithm_config", - "training_config", - "hyperparam_search_config", - "logger_config" - ], - "title": "PreferenceOptimizeRequest" - }, - "PostTrainingJob": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "job_uuid" - ], - "title": "PostTrainingJob" - }, - "DefaultRAGQueryGeneratorConfig": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "default", - "default": "default", - "description": "Type of query generator, always 'default'" - }, - "separator": { - "type": "string", - "default": " ", - "description": "String separator used to join query terms" - } - }, - "additionalProperties": false, - "required": [ - "type", - "separator" - ], - "title": "DefaultRAGQueryGeneratorConfig", - "description": "Configuration for the default RAG query generator." - }, - "LLMRAGQueryGeneratorConfig": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "llm", - "default": "llm", - "description": "Type of query generator, always 'llm'" - }, - "model": { - "type": "string", - "description": "Name of the language model to use for query generation" - }, - "template": { - "type": "string", - "description": "Template string for formatting the query generation prompt" - } - }, - "additionalProperties": false, - "required": [ - "type", - "model", - "template" - ], - "title": "LLMRAGQueryGeneratorConfig", - "description": "Configuration for the LLM-based RAG query generator." - }, - "RAGQueryConfig": { - "type": "object", - "properties": { - "query_generator_config": { - "$ref": "#/components/schemas/RAGQueryGeneratorConfig", - "description": "Configuration for the query generator." - }, - "max_tokens_in_context": { - "type": "integer", - "default": 4096, - "description": "Maximum number of tokens in the context." - }, - "max_chunks": { - "type": "integer", - "default": 5, - "description": "Maximum number of chunks to retrieve." - }, - "chunk_template": { - "type": "string", - "default": "Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n", - "description": "Template for formatting each retrieved chunk in the context. Available placeholders: {index} (1-based chunk ordinal), {chunk.content} (chunk content string), {metadata} (chunk metadata dict). Default: \"Result {index}\\nContent: {chunk.content}\\nMetadata: {metadata}\\n\"" - }, - "mode": { - "$ref": "#/components/schemas/RAGSearchMode", - "default": "vector", - "description": "Search mode for retrieval—either \"vector\", \"keyword\", or \"hybrid\". Default \"vector\"." - }, - "ranker": { - "$ref": "#/components/schemas/Ranker", - "description": "Configuration for the ranker to use in hybrid search. Defaults to RRF ranker." - } - }, - "additionalProperties": false, - "required": [ - "query_generator_config", - "max_tokens_in_context", - "max_chunks", - "chunk_template" - ], - "title": "RAGQueryConfig", - "description": "Configuration for the RAG query generation." - }, - "RAGQueryGeneratorConfig": { - "oneOf": [ - { - "$ref": "#/components/schemas/DefaultRAGQueryGeneratorConfig" - }, - { - "$ref": "#/components/schemas/LLMRAGQueryGeneratorConfig" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "default": "#/components/schemas/DefaultRAGQueryGeneratorConfig", - "llm": "#/components/schemas/LLMRAGQueryGeneratorConfig" - } - } - }, - "RAGSearchMode": { - "type": "string", - "enum": [ - "vector", - "keyword", - "hybrid" - ], - "title": "RAGSearchMode", - "description": "Search modes for RAG query retrieval: - VECTOR: Uses vector similarity search for semantic matching - KEYWORD: Uses keyword-based search for exact matching - HYBRID: Combines both vector and keyword search for better results" - }, - "RRFRanker": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "rrf", - "default": "rrf", - "description": "The type of ranker, always \"rrf\"" - }, - "impact_factor": { - "type": "number", - "default": 60.0, - "description": "The impact factor for RRF scoring. Higher values give more weight to higher-ranked results. Must be greater than 0" - } - }, - "additionalProperties": false, - "required": [ - "type", - "impact_factor" - ], - "title": "RRFRanker", - "description": "Reciprocal Rank Fusion (RRF) ranker configuration." - }, - "Ranker": { - "oneOf": [ - { - "$ref": "#/components/schemas/RRFRanker" - }, - { - "$ref": "#/components/schemas/WeightedRanker" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "rrf": "#/components/schemas/RRFRanker", - "weighted": "#/components/schemas/WeightedRanker" - } - } - }, - "WeightedRanker": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "weighted", - "default": "weighted", - "description": "The type of ranker, always \"weighted\"" - }, - "alpha": { - "type": "number", - "default": 0.5, - "description": "Weight factor between 0 and 1. 0 means only use keyword scores, 1 means only use vector scores, values in between blend both scores." - } - }, - "additionalProperties": false, - "required": [ - "type", - "alpha" - ], - "title": "WeightedRanker", - "description": "Weighted ranker configuration that combines vector and keyword scores." - }, - "QueryRequest": { - "type": "object", - "properties": { - "content": { - "$ref": "#/components/schemas/InterleavedContent", - "description": "The query content to search for in the indexed documents" - }, - "vector_db_ids": { - "type": "array", - "items": { - "type": "string" - }, - "description": "List of vector database IDs to search within" - }, - "query_config": { - "$ref": "#/components/schemas/RAGQueryConfig", - "description": "(Optional) Configuration parameters for the query operation" - } - }, - "additionalProperties": false, - "required": [ - "content", - "vector_db_ids" - ], - "title": "QueryRequest" - }, - "RAGQueryResult": { - "type": "object", - "properties": { - "content": { - "$ref": "#/components/schemas/InterleavedContent", - "description": "(Optional) The retrieved content from the query" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Additional metadata about the query result" - } - }, - "additionalProperties": false, - "required": [ - "metadata" - ], - "title": "RAGQueryResult", - "description": "Result of a RAG query containing retrieved content and metadata." - }, - "QueryChunksRequest": { - "type": "object", - "properties": { - "vector_db_id": { - "type": "string", - "description": "The identifier of the vector database to query." - }, - "query": { - "$ref": "#/components/schemas/InterleavedContent", - "description": "The query to search for." - }, - "params": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The parameters of the query." - } - }, - "additionalProperties": false, - "required": [ - "vector_db_id", - "query" - ], - "title": "QueryChunksRequest" - }, - "QueryChunksResponse": { - "type": "object", - "properties": { - "chunks": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Chunk" - }, - "description": "List of content chunks returned from the query" - }, - "scores": { - "type": "array", - "items": { - "type": "number" - }, - "description": "Relevance scores corresponding to each returned chunk" - } - }, - "additionalProperties": false, - "required": [ - "chunks", - "scores" - ], - "title": "QueryChunksResponse", - "description": "Response from querying chunks in a vector database." - }, - "QueryMetricsRequest": { - "type": "object", - "properties": { - "start_time": { - "type": "integer", - "description": "The start time of the metric to query." - }, - "end_time": { - "type": "integer", - "description": "The end time of the metric to query." - }, - "granularity": { - "type": "string", - "description": "The granularity of the metric to query." - }, - "query_type": { - "type": "string", - "enum": [ - "range", - "instant" - ], - "description": "The type of query to perform." - }, - "label_matchers": { - "type": "array", - "items": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the label to match" - }, - "value": { - "type": "string", - "description": "The value to match against" - }, - "operator": { - "type": "string", - "enum": [ - "=", - "!=", - "=~", - "!~" - ], - "description": "The comparison operator to use for matching", - "default": "=" - } - }, - "additionalProperties": false, - "required": [ - "name", - "value", - "operator" - ], - "title": "MetricLabelMatcher", - "description": "A matcher for filtering metrics by label values." - }, - "description": "The label matchers to apply to the metric." - } - }, - "additionalProperties": false, - "required": [ - "start_time", - "query_type" - ], - "title": "QueryMetricsRequest" - }, - "MetricDataPoint": { - "type": "object", - "properties": { - "timestamp": { - "type": "integer", - "description": "Unix timestamp when the metric value was recorded" - }, - "value": { - "type": "number", - "description": "The numeric value of the metric at this timestamp" - }, - "unit": { - "type": "string" - } - }, - "additionalProperties": false, - "required": [ - "timestamp", - "value", - "unit" - ], - "title": "MetricDataPoint", - "description": "A single data point in a metric time series." - }, - "MetricLabel": { - "type": "object", - "properties": { - "name": { - "type": "string", - "description": "The name of the label" - }, - "value": { - "type": "string", - "description": "The value of the label" - } - }, - "additionalProperties": false, - "required": [ - "name", - "value" - ], - "title": "MetricLabel", - "description": "A label associated with a metric." - }, - "MetricSeries": { - "type": "object", - "properties": { - "metric": { - "type": "string", - "description": "The name of the metric" - }, - "labels": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MetricLabel" - }, - "description": "List of labels associated with this metric series" - }, - "values": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MetricDataPoint" - }, - "description": "List of data points in chronological order" - } - }, - "additionalProperties": false, - "required": [ - "metric", - "labels", - "values" - ], - "title": "MetricSeries", - "description": "A time series of metric data points." - }, - "QueryMetricsResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/MetricSeries" - }, - "description": "List of metric series matching the query criteria" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "QueryMetricsResponse", - "description": "Response containing metric time series data." - }, - "QueryCondition": { - "type": "object", - "properties": { - "key": { - "type": "string", - "description": "The attribute key to filter on" - }, - "op": { - "$ref": "#/components/schemas/QueryConditionOp", - "description": "The comparison operator to apply" - }, - "value": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ], - "description": "The value to compare against" - } - }, - "additionalProperties": false, - "required": [ - "key", - "op", - "value" - ], - "title": "QueryCondition", - "description": "A condition for filtering query results." - }, - "QueryConditionOp": { - "type": "string", - "enum": [ - "eq", - "ne", - "gt", - "lt" - ], - "title": "QueryConditionOp", - "description": "Comparison operators for query conditions." - }, - "QuerySpansRequest": { - "type": "object", - "properties": { - "attribute_filters": { - "type": "array", - "items": { - "$ref": "#/components/schemas/QueryCondition" - }, - "description": "The attribute filters to apply to the spans." - }, - "attributes_to_return": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The attributes to return in the spans." - }, - "max_depth": { - "type": "integer", - "description": "The maximum depth of the tree." - } - }, - "additionalProperties": false, - "required": [ - "attribute_filters", - "attributes_to_return" - ], - "title": "QuerySpansRequest" - }, - "QuerySpansResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Span" - }, - "description": "List of spans matching the query criteria" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "QuerySpansResponse", - "description": "Response containing a list of spans." - }, - "QueryTracesRequest": { - "type": "object", - "properties": { - "attribute_filters": { - "type": "array", - "items": { - "$ref": "#/components/schemas/QueryCondition" - }, - "description": "The attribute filters to apply to the traces." - }, - "limit": { - "type": "integer", - "description": "The limit of traces to return." - }, - "offset": { - "type": "integer", - "description": "The offset of the traces to return." - }, - "order_by": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The order by of the traces to return." - } - }, - "additionalProperties": false, - "title": "QueryTracesRequest" - }, - "QueryTracesResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Trace" - }, - "description": "List of traces matching the query criteria" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "QueryTracesResponse", - "description": "Response containing a list of traces." - }, - "RegisterBenchmarkRequest": { - "type": "object", - "properties": { - "benchmark_id": { - "type": "string", - "description": "The ID of the benchmark to register." - }, - "dataset_id": { - "type": "string", - "description": "The ID of the dataset to use for the benchmark." - }, - "scoring_functions": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The scoring functions to use for the benchmark." - }, - "provider_benchmark_id": { - "type": "string", - "description": "The ID of the provider benchmark to use for the benchmark." - }, - "provider_id": { - "type": "string", - "description": "The ID of the provider to use for the benchmark." - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The metadata to use for the benchmark." - } - }, - "additionalProperties": false, - "required": [ - "benchmark_id", - "dataset_id", - "scoring_functions" - ], - "title": "RegisterBenchmarkRequest" - }, - "RegisterDatasetRequest": { - "type": "object", - "properties": { - "purpose": { - "type": "string", - "enum": [ - "post-training/messages", - "eval/question-answer", - "eval/messages-answer" - ], - "description": "The purpose of the dataset. One of: - \"post-training/messages\": The dataset contains a messages column with list of messages for post-training. { \"messages\": [ {\"role\": \"user\", \"content\": \"Hello, world!\"}, {\"role\": \"assistant\", \"content\": \"Hello, world!\"}, ] } - \"eval/question-answer\": The dataset contains a question column and an answer column for evaluation. { \"question\": \"What is the capital of France?\", \"answer\": \"Paris\" } - \"eval/messages-answer\": The dataset contains a messages column with list of messages and an answer column for evaluation. { \"messages\": [ {\"role\": \"user\", \"content\": \"Hello, my name is John Doe.\"}, {\"role\": \"assistant\", \"content\": \"Hello, John Doe. How can I help you today?\"}, {\"role\": \"user\", \"content\": \"What's my name?\"}, ], \"answer\": \"John Doe\" }" - }, - "source": { - "$ref": "#/components/schemas/DataSource", - "description": "The data source of the dataset. Ensure that the data source schema is compatible with the purpose of the dataset. Examples: - { \"type\": \"uri\", \"uri\": \"https://mywebsite.com/mydata.jsonl\" } - { \"type\": \"uri\", \"uri\": \"lsfs://mydata.jsonl\" } - { \"type\": \"uri\", \"uri\": \"data:csv;base64,{base64_content}\" } - { \"type\": \"uri\", \"uri\": \"huggingface://llamastack/simpleqa?split=train\" } - { \"type\": \"rows\", \"rows\": [ { \"messages\": [ {\"role\": \"user\", \"content\": \"Hello, world!\"}, {\"role\": \"assistant\", \"content\": \"Hello, world!\"}, ] } ] }" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The metadata for the dataset. - E.g. {\"description\": \"My dataset\"}." - }, - "dataset_id": { - "type": "string", - "description": "The ID of the dataset. If not provided, an ID will be generated." - } - }, - "additionalProperties": false, - "required": [ - "purpose", - "source" - ], - "title": "RegisterDatasetRequest" - }, - "RegisterModelRequest": { - "type": "object", - "properties": { - "model_id": { - "type": "string", - "description": "The identifier of the model to register." - }, - "provider_model_id": { - "type": "string", - "description": "The identifier of the model in the provider." - }, - "provider_id": { - "type": "string", - "description": "The identifier of the provider." - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "Any additional metadata for this model." - }, - "model_type": { - "$ref": "#/components/schemas/ModelType", - "description": "The type of model to register." - } - }, - "additionalProperties": false, - "required": [ - "model_id" - ], - "title": "RegisterModelRequest" - }, - "RegisterScoringFunctionRequest": { - "type": "object", - "properties": { - "scoring_fn_id": { - "type": "string", - "description": "The ID of the scoring function to register." - }, - "description": { - "type": "string", - "description": "The description of the scoring function." - }, - "return_type": { - "$ref": "#/components/schemas/ParamType", - "description": "The return type of the scoring function." - }, - "provider_scoring_fn_id": { - "type": "string", - "description": "The ID of the provider scoring function to use for the scoring function." - }, - "provider_id": { - "type": "string", - "description": "The ID of the provider to use for the scoring function." - }, - "params": { - "$ref": "#/components/schemas/ScoringFnParams", - "description": "The parameters for the scoring function for benchmark eval, these can be overridden for app eval." - } - }, - "additionalProperties": false, - "required": [ - "scoring_fn_id", - "description", - "return_type" - ], - "title": "RegisterScoringFunctionRequest" - }, - "RegisterShieldRequest": { - "type": "object", - "properties": { - "shield_id": { - "type": "string", - "description": "The identifier of the shield to register." - }, - "provider_shield_id": { - "type": "string", - "description": "The identifier of the shield in the provider." - }, - "provider_id": { - "type": "string", - "description": "The identifier of the provider." - }, - "params": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The parameters of the shield." - } - }, - "additionalProperties": false, - "required": [ - "shield_id" - ], - "title": "RegisterShieldRequest" - }, - "RegisterToolGroupRequest": { - "type": "object", - "properties": { - "toolgroup_id": { - "type": "string", - "description": "The ID of the tool group to register." - }, - "provider_id": { - "type": "string", - "description": "The ID of the provider to use for the tool group." - }, - "mcp_endpoint": { - "$ref": "#/components/schemas/URL", - "description": "The MCP endpoint to use for the tool group." - }, - "args": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "A dictionary of arguments to pass to the tool group." - } - }, - "additionalProperties": false, - "required": [ - "toolgroup_id", - "provider_id" - ], - "title": "RegisterToolGroupRequest" - }, - "RegisterVectorDbRequest": { - "type": "object", - "properties": { - "vector_db_id": { - "type": "string", - "description": "The identifier of the vector database to register." - }, - "embedding_model": { - "type": "string", - "description": "The embedding model to use." - }, - "embedding_dimension": { - "type": "integer", - "description": "The dimension of the embedding model." - }, - "provider_id": { - "type": "string", - "description": "The identifier of the provider." - }, - "vector_db_name": { - "type": "string", - "description": "The name of the vector database." - }, - "provider_vector_db_id": { - "type": "string", - "description": "The identifier of the vector database in the provider." - } - }, - "additionalProperties": false, - "required": [ - "vector_db_id", - "embedding_model" - ], - "title": "RegisterVectorDbRequest" - }, - "RerankRequest": { - "type": "object", - "properties": { - "model": { - "type": "string", - "description": "The identifier of the reranking model to use. The model must be a reranking model registered with Llama Stack and available via the /models endpoint." - }, - "query": { - "oneOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam" - }, - { - "$ref": "#/components/schemas/OpenAIChatCompletionContentPartImageParam" - } - ], - "description": "The search query to rank items against. Can be a string, text content part, or image content part. The input must not exceed the model's max input token length." - }, - "items": { - "type": "array", - "items": { - "oneOf": [ - { - "type": "string" - }, - { - "$ref": "#/components/schemas/OpenAIChatCompletionContentPartTextParam" - }, - { - "$ref": "#/components/schemas/OpenAIChatCompletionContentPartImageParam" - } - ] - }, - "description": "List of items to rerank. Each item can be a string, text content part, or image content part. Each input must not exceed the model's max input token length." - }, - "max_num_results": { - "type": "integer", - "description": "(Optional) Maximum number of results to return. Default: returns all." - } - }, - "additionalProperties": false, - "required": [ - "model", - "query", - "items" - ], - "title": "RerankRequest" - }, - "RerankData": { - "type": "object", - "properties": { - "index": { - "type": "integer", - "description": "The original index of the document in the input list" - }, - "relevance_score": { - "type": "number", - "description": "The relevance score from the model output. Values are inverted when applicable so that higher scores indicate greater relevance." - } - }, - "additionalProperties": false, - "required": [ - "index", - "relevance_score" - ], - "title": "RerankData", - "description": "A single rerank result from a reranking response." - }, - "RerankResponse": { - "type": "object", - "properties": { - "data": { - "type": "array", - "items": { - "$ref": "#/components/schemas/RerankData" - }, - "description": "List of rerank result objects, sorted by relevance score (descending)" - } - }, - "additionalProperties": false, - "required": [ - "data" - ], - "title": "RerankResponse", - "description": "Response from a reranking request." - }, - "ResumeAgentTurnRequest": { - "type": "object", - "properties": { - "tool_responses": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ToolResponse" - }, - "description": "The tool call responses to resume the turn with." - }, - "stream": { - "type": "boolean", - "description": "Whether to stream the response." - } - }, - "additionalProperties": false, - "required": [ - "tool_responses" - ], - "title": "ResumeAgentTurnRequest" - }, - "RunEvalRequest": { - "type": "object", - "properties": { - "benchmark_config": { - "$ref": "#/components/schemas/BenchmarkConfig", - "description": "The configuration for the benchmark." - } - }, - "additionalProperties": false, - "required": [ - "benchmark_config" - ], - "title": "RunEvalRequest" - }, - "RunModerationRequest": { - "type": "object", - "properties": { - "input": { - "oneOf": [ - { - "type": "string" - }, - { - "type": "array", - "items": { - "type": "string" - } - } - ], - "description": "Input (or inputs) to classify. Can be a single string, an array of strings, or an array of multi-modal input objects similar to other models." - }, - "model": { - "type": "string", - "description": "The content moderation model you would like to use." - } - }, - "additionalProperties": false, - "required": [ - "input", - "model" - ], - "title": "RunModerationRequest" - }, - "ModerationObject": { - "type": "object", - "properties": { - "id": { - "type": "string", - "description": "The unique identifier for the moderation request." - }, - "model": { - "type": "string", - "description": "The model used to generate the moderation results." - }, - "results": { - "type": "array", - "items": { - "$ref": "#/components/schemas/ModerationObjectResults" - }, - "description": "A list of moderation objects" - } - }, - "additionalProperties": false, - "required": [ - "id", - "model", - "results" - ], - "title": "ModerationObject", - "description": "A moderation object." - }, - "ModerationObjectResults": { - "type": "object", - "properties": { - "flagged": { - "type": "boolean", - "description": "Whether any of the below categories are flagged." - }, - "categories": { - "type": "object", - "additionalProperties": { - "type": "boolean" - }, - "description": "A list of the categories, and whether they are flagged or not." - }, - "category_applied_input_types": { - "type": "object", - "additionalProperties": { - "type": "array", - "items": { - "type": "string" - } - }, - "description": "A list of the categories along with the input type(s) that the score applies to." - }, - "category_scores": { - "type": "object", - "additionalProperties": { - "type": "number" - }, - "description": "A list of the categories along with their scores as predicted by model." - }, - "user_message": { - "type": "string" - }, - "metadata": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - } - }, - "additionalProperties": false, - "required": [ - "flagged", - "metadata" - ], - "title": "ModerationObjectResults", - "description": "A moderation object." - }, - "RunShieldRequest": { - "type": "object", - "properties": { - "shield_id": { - "type": "string", - "description": "The identifier of the shield to run." - }, - "messages": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Message" - }, - "description": "The messages to run the shield on." - }, - "params": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The parameters of the shield." - } - }, - "additionalProperties": false, - "required": [ - "shield_id", - "messages", - "params" - ], - "title": "RunShieldRequest" - }, - "RunShieldResponse": { - "type": "object", - "properties": { - "violation": { - "$ref": "#/components/schemas/SafetyViolation", - "description": "(Optional) Safety violation detected by the shield, if any" - } - }, - "additionalProperties": false, - "title": "RunShieldResponse", - "description": "Response from running a safety shield." - }, - "SaveSpansToDatasetRequest": { - "type": "object", - "properties": { - "attribute_filters": { - "type": "array", - "items": { - "$ref": "#/components/schemas/QueryCondition" - }, - "description": "The attribute filters to apply to the spans." - }, - "attributes_to_save": { - "type": "array", - "items": { - "type": "string" - }, - "description": "The attributes to save to the dataset." - }, - "dataset_id": { - "type": "string", - "description": "The ID of the dataset to save the spans to." - }, - "max_depth": { - "type": "integer", - "description": "The maximum depth of the tree." - } - }, - "additionalProperties": false, - "required": [ - "attribute_filters", - "attributes_to_save", - "dataset_id" - ], - "title": "SaveSpansToDatasetRequest" - }, - "ScoreRequest": { - "type": "object", - "properties": { - "input_rows": { - "type": "array", - "items": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - }, - "description": "The rows to score." - }, - "scoring_functions": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "$ref": "#/components/schemas/ScoringFnParams" - }, - { - "type": "null" - } - ] - }, - "description": "The scoring functions to use for the scoring." - } - }, - "additionalProperties": false, - "required": [ - "input_rows", - "scoring_functions" - ], - "title": "ScoreRequest" - }, - "ScoreResponse": { - "type": "object", - "properties": { - "results": { - "type": "object", - "additionalProperties": { - "$ref": "#/components/schemas/ScoringResult" - }, - "description": "A map of scoring function name to ScoringResult." - } - }, - "additionalProperties": false, - "required": [ - "results" - ], - "title": "ScoreResponse", - "description": "The response from scoring." - }, - "ScoreBatchRequest": { - "type": "object", - "properties": { - "dataset_id": { - "type": "string", - "description": "The ID of the dataset to score." - }, - "scoring_functions": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "$ref": "#/components/schemas/ScoringFnParams" - }, - { - "type": "null" - } - ] - }, - "description": "The scoring functions to use for the scoring." - }, - "save_results_dataset": { - "type": "boolean", - "description": "Whether to save the results to a dataset." - } - }, - "additionalProperties": false, - "required": [ - "dataset_id", - "scoring_functions", - "save_results_dataset" - ], - "title": "ScoreBatchRequest" - }, - "ScoreBatchResponse": { - "type": "object", - "properties": { - "dataset_id": { - "type": "string", - "description": "(Optional) The identifier of the dataset that was scored" - }, - "results": { - "type": "object", - "additionalProperties": { - "$ref": "#/components/schemas/ScoringResult" - }, - "description": "A map of scoring function name to ScoringResult" - } - }, - "additionalProperties": false, - "required": [ - "results" - ], - "title": "ScoreBatchResponse", - "description": "Response from batch scoring operations on datasets." - }, - "SetDefaultVersionRequest": { - "type": "object", - "properties": { - "version": { - "type": "integer", - "description": "The version to set as default." - } - }, - "additionalProperties": false, - "required": [ - "version" - ], - "title": "SetDefaultVersionRequest" - }, - "AlgorithmConfig": { - "oneOf": [ - { - "$ref": "#/components/schemas/LoraFinetuningConfig" - }, - { - "$ref": "#/components/schemas/QATFinetuningConfig" - } - ], - "discriminator": { - "propertyName": "type", - "mapping": { - "LoRA": "#/components/schemas/LoraFinetuningConfig", - "QAT": "#/components/schemas/QATFinetuningConfig" - } - } - }, - "LoraFinetuningConfig": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "LoRA", - "default": "LoRA", - "description": "Algorithm type identifier, always \"LoRA\"" - }, - "lora_attn_modules": { - "type": "array", - "items": { - "type": "string" - }, - "description": "List of attention module names to apply LoRA to" - }, - "apply_lora_to_mlp": { - "type": "boolean", - "description": "Whether to apply LoRA to MLP layers" - }, - "apply_lora_to_output": { - "type": "boolean", - "description": "Whether to apply LoRA to output projection layers" - }, - "rank": { - "type": "integer", - "description": "Rank of the LoRA adaptation (lower rank = fewer parameters)" - }, - "alpha": { - "type": "integer", - "description": "LoRA scaling parameter that controls adaptation strength" - }, - "use_dora": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to use DoRA (Weight-Decomposed Low-Rank Adaptation)" - }, - "quantize_base": { - "type": "boolean", - "default": false, - "description": "(Optional) Whether to quantize the base model weights" - } - }, - "additionalProperties": false, - "required": [ - "type", - "lora_attn_modules", - "apply_lora_to_mlp", - "apply_lora_to_output", - "rank", - "alpha" - ], - "title": "LoraFinetuningConfig", - "description": "Configuration for Low-Rank Adaptation (LoRA) fine-tuning." - }, - "QATFinetuningConfig": { - "type": "object", - "properties": { - "type": { - "type": "string", - "const": "QAT", - "default": "QAT", - "description": "Algorithm type identifier, always \"QAT\"" - }, - "quantizer_name": { - "type": "string", - "description": "Name of the quantization algorithm to use" - }, - "group_size": { - "type": "integer", - "description": "Size of groups for grouped quantization" - } - }, - "additionalProperties": false, - "required": [ - "type", - "quantizer_name", - "group_size" - ], - "title": "QATFinetuningConfig", - "description": "Configuration for Quantization-Aware Training (QAT) fine-tuning." - }, - "SupervisedFineTuneRequest": { - "type": "object", - "properties": { - "job_uuid": { - "type": "string", - "description": "The UUID of the job to create." - }, - "training_config": { - "$ref": "#/components/schemas/TrainingConfig", - "description": "The training configuration." - }, - "hyperparam_search_config": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The hyperparam search configuration." - }, - "logger_config": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "The logger configuration." - }, - "model": { - "type": "string", - "description": "The model to fine-tune." - }, - "checkpoint_dir": { - "type": "string", - "description": "The directory to save checkpoint(s) to." - }, - "algorithm_config": { - "$ref": "#/components/schemas/AlgorithmConfig", - "description": "The algorithm configuration." - } - }, - "additionalProperties": false, - "required": [ - "job_uuid", - "training_config", - "hyperparam_search_config", - "logger_config" - ], - "title": "SupervisedFineTuneRequest" - }, - "SyntheticDataGenerateRequest": { - "type": "object", - "properties": { - "dialogs": { - "type": "array", - "items": { - "$ref": "#/components/schemas/Message" - }, - "description": "List of conversation messages to use as input for synthetic data generation" - }, - "filtering_function": { - "type": "string", - "enum": [ - "none", - "random", - "top_k", - "top_p", - "top_k_top_p", - "sigmoid" - ], - "description": "Type of filtering to apply to generated synthetic data samples" - }, - "model": { - "type": "string", - "description": "(Optional) The identifier of the model to use. The model must be registered with Llama Stack and available via the /models endpoint" - } - }, - "additionalProperties": false, - "required": [ - "dialogs", - "filtering_function" - ], - "title": "SyntheticDataGenerateRequest" - }, - "SyntheticDataGenerationResponse": { - "type": "object", - "properties": { - "synthetic_data": { - "type": "array", - "items": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - } - }, - "description": "List of generated synthetic data samples that passed the filtering criteria" - }, - "statistics": { - "type": "object", - "additionalProperties": { - "oneOf": [ - { - "type": "null" - }, - { - "type": "boolean" - }, - { - "type": "number" - }, - { - "type": "string" - }, - { - "type": "array" - }, - { - "type": "object" - } - ] - }, - "description": "(Optional) Statistical information about the generation process and filtering results" - } - }, - "additionalProperties": false, - "required": [ - "synthetic_data" - ], - "title": "SyntheticDataGenerationResponse", - "description": "Response from the synthetic data generation. Batch of (prompt, response, score) tuples that pass the threshold." - }, - "UpdatePromptRequest": { - "type": "object", - "properties": { - "prompt": { - "type": "string", - "description": "The updated prompt text content." - }, - "version": { - "type": "integer", - "description": "The current version of the prompt being updated." - }, - "variables": { - "type": "array", - "items": { - "type": "string" - }, - "description": "Updated list of variable names that can be used in the prompt template." - }, - "set_as_default": { - "type": "boolean", - "description": "Set the new version as the default (default=True)." - } - }, - "additionalProperties": false, - "required": [ - "prompt", - "version", - "set_as_default" - ], - "title": "UpdatePromptRequest" - }, ->>>>>>> f7acfa0f (Add rerank API for NVIDIA Inference Provider) "VersionInfo": { "type": "object", "properties": { diff --git a/docs/static/llama-stack-spec.yaml b/docs/static/llama-stack-spec.yaml index ec0409849..566ac7de9 100644 --- a/docs/static/llama-stack-spec.yaml +++ b/docs/static/llama-stack-spec.yaml @@ -3634,2130 +3634,6 @@ components: title: OpenAIUserMessageParam description: >- A message from the user in an OpenAI-compatible chat completion request. -<<<<<<< HEAD -======= - OpenAICompletionWithInputMessages: - type: object - properties: - id: - type: string - description: The ID of the chat completion - choices: - type: array - items: - $ref: '#/components/schemas/OpenAIChoice' - description: List of choices - object: - type: string - const: chat.completion - default: chat.completion - description: >- - The object type, which will be "chat.completion" - created: - type: integer - description: >- - The Unix timestamp in seconds when the chat completion was created - model: - type: string - description: >- - The model that was used to generate the chat completion - input_messages: - type: array - items: - $ref: '#/components/schemas/OpenAIMessageParam' - additionalProperties: false - required: - - id - - choices - - object - - created - - model - - input_messages - title: OpenAICompletionWithInputMessages - DataSource: - oneOf: - - $ref: '#/components/schemas/URIDataSource' - - $ref: '#/components/schemas/RowsDataSource' - discriminator: - propertyName: type - mapping: - uri: '#/components/schemas/URIDataSource' - rows: '#/components/schemas/RowsDataSource' - Dataset: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: dataset - default: dataset - description: >- - Type of resource, always 'dataset' for datasets - purpose: - type: string - enum: - - post-training/messages - - eval/question-answer - - eval/messages-answer - description: >- - Purpose of the dataset indicating its intended use - source: - $ref: '#/components/schemas/DataSource' - description: >- - Data source configuration for the dataset - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: Additional metadata for the dataset - additionalProperties: false - required: - - identifier - - provider_id - - type - - purpose - - source - - metadata - title: Dataset - description: >- - Dataset resource for storing and accessing training or evaluation data. - RowsDataSource: - type: object - properties: - type: - type: string - const: rows - default: rows - rows: - type: array - items: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - The dataset is stored in rows. E.g. - [ {"messages": [{"role": "user", - "content": "Hello, world!"}, {"role": "assistant", "content": "Hello, - world!"}]} ] - additionalProperties: false - required: - - type - - rows - title: RowsDataSource - description: A dataset stored in rows. - URIDataSource: - type: object - properties: - type: - type: string - const: uri - default: uri - uri: - type: string - description: >- - The dataset can be obtained from a URI. E.g. - "https://mywebsite.com/mydata.jsonl" - - "lsfs://mydata.jsonl" - "data:csv;base64,{base64_content}" - additionalProperties: false - required: - - type - - uri - title: URIDataSource - description: >- - A dataset that can be obtained from a URI. - Model: - type: object - properties: - identifier: - type: string - description: >- - Unique identifier for this resource in llama stack - provider_resource_id: - type: string - description: >- - Unique identifier for this resource in the provider - provider_id: - type: string - description: >- - ID of the provider that owns this resource - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: model - default: model - description: >- - The resource type, always 'model' for model resources - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: Any additional metadata for this model - model_type: - $ref: '#/components/schemas/ModelType' - default: llm - description: >- - The type of model (LLM or embedding model) - additionalProperties: false - required: - - identifier - - provider_id - - type - - metadata - - model_type - title: Model - description: >- - A model resource representing an AI model registered in Llama Stack. - ModelType: - type: string - enum: - - llm - - embedding - - rerank - title: ModelType - description: >- - Enumeration of supported model types in Llama Stack. - AgentTurnInputType: - type: object - properties: - type: - type: string - const: agent_turn_input - default: agent_turn_input - description: >- - Discriminator type. Always "agent_turn_input" - additionalProperties: false - required: - - type - title: AgentTurnInputType - description: Parameter type for agent turn input. - ArrayType: - type: object - properties: - type: - type: string - const: array - default: array - description: Discriminator type. Always "array" - additionalProperties: false - required: - - type - title: ArrayType - description: Parameter type for array values. - BooleanType: - type: object - properties: - type: - type: string - const: boolean - default: boolean - description: Discriminator type. Always "boolean" - additionalProperties: false - required: - - type - title: BooleanType - description: Parameter type for boolean values. - ChatCompletionInputType: - type: object - properties: - type: - type: string - const: chat_completion_input - default: chat_completion_input - description: >- - Discriminator type. Always "chat_completion_input" - additionalProperties: false - required: - - type - title: ChatCompletionInputType - description: >- - Parameter type for chat completion input. - CompletionInputType: - type: object - properties: - type: - type: string - const: completion_input - default: completion_input - description: >- - Discriminator type. Always "completion_input" - additionalProperties: false - required: - - type - title: CompletionInputType - description: Parameter type for completion input. - JsonType: - type: object - properties: - type: - type: string - const: json - default: json - description: Discriminator type. Always "json" - additionalProperties: false - required: - - type - title: JsonType - description: Parameter type for JSON values. - NumberType: - type: object - properties: - type: - type: string - const: number - default: number - description: Discriminator type. Always "number" - additionalProperties: false - required: - - type - title: NumberType - description: Parameter type for numeric values. - ObjectType: - type: object - properties: - type: - type: string - const: object - default: object - description: Discriminator type. Always "object" - additionalProperties: false - required: - - type - title: ObjectType - description: Parameter type for object values. - ParamType: - oneOf: - - $ref: '#/components/schemas/StringType' - - $ref: '#/components/schemas/NumberType' - - $ref: '#/components/schemas/BooleanType' - - $ref: '#/components/schemas/ArrayType' - - $ref: '#/components/schemas/ObjectType' - - $ref: '#/components/schemas/JsonType' - - $ref: '#/components/schemas/UnionType' - - $ref: '#/components/schemas/ChatCompletionInputType' - - $ref: '#/components/schemas/CompletionInputType' - - $ref: '#/components/schemas/AgentTurnInputType' - discriminator: - propertyName: type - mapping: - string: '#/components/schemas/StringType' - number: '#/components/schemas/NumberType' - boolean: '#/components/schemas/BooleanType' - array: '#/components/schemas/ArrayType' - object: '#/components/schemas/ObjectType' - json: '#/components/schemas/JsonType' - union: '#/components/schemas/UnionType' - chat_completion_input: '#/components/schemas/ChatCompletionInputType' - completion_input: '#/components/schemas/CompletionInputType' - agent_turn_input: '#/components/schemas/AgentTurnInputType' - ScoringFn: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: scoring_function - default: scoring_function - description: >- - The resource type, always scoring_function - description: - type: string - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - return_type: - $ref: '#/components/schemas/ParamType' - params: - $ref: '#/components/schemas/ScoringFnParams' - additionalProperties: false - required: - - identifier - - provider_id - - type - - metadata - - return_type - title: ScoringFn - description: >- - A scoring function resource for evaluating model outputs. - StringType: - type: object - properties: - type: - type: string - const: string - default: string - description: Discriminator type. Always "string" - additionalProperties: false - required: - - type - title: StringType - description: Parameter type for string values. - UnionType: - type: object - properties: - type: - type: string - const: union - default: union - description: Discriminator type. Always "union" - additionalProperties: false - required: - - type - title: UnionType - description: Parameter type for union values. - Shield: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: shield - default: shield - description: The resource type, always shield - params: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Configuration parameters for the shield - additionalProperties: false - required: - - identifier - - provider_id - - type - title: Shield - description: >- - A safety shield resource that can be used to check content. - Span: - type: object - properties: - span_id: - type: string - description: Unique identifier for the span - trace_id: - type: string - description: >- - Unique identifier for the trace this span belongs to - parent_span_id: - type: string - description: >- - (Optional) Unique identifier for the parent span, if this is a child span - name: - type: string - description: >- - Human-readable name describing the operation this span represents - start_time: - type: string - format: date-time - description: Timestamp when the operation began - end_time: - type: string - format: date-time - description: >- - (Optional) Timestamp when the operation finished, if completed - attributes: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Key-value pairs containing additional metadata about the span - additionalProperties: false - required: - - span_id - - trace_id - - name - - start_time - title: Span - description: >- - A span representing a single operation within a trace. - GetSpanTreeRequest: - type: object - properties: - attributes_to_return: - type: array - items: - type: string - description: The attributes to return in the tree. - max_depth: - type: integer - description: The maximum depth of the tree. - additionalProperties: false - title: GetSpanTreeRequest - SpanStatus: - type: string - enum: - - ok - - error - title: SpanStatus - description: >- - The status of a span indicating whether it completed successfully or with - an error. - SpanWithStatus: - type: object - properties: - span_id: - type: string - description: Unique identifier for the span - trace_id: - type: string - description: >- - Unique identifier for the trace this span belongs to - parent_span_id: - type: string - description: >- - (Optional) Unique identifier for the parent span, if this is a child span - name: - type: string - description: >- - Human-readable name describing the operation this span represents - start_time: - type: string - format: date-time - description: Timestamp when the operation began - end_time: - type: string - format: date-time - description: >- - (Optional) Timestamp when the operation finished, if completed - attributes: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Key-value pairs containing additional metadata about the span - status: - $ref: '#/components/schemas/SpanStatus' - description: >- - (Optional) The current status of the span - additionalProperties: false - required: - - span_id - - trace_id - - name - - start_time - title: SpanWithStatus - description: A span that includes status information. - QuerySpanTreeResponse: - type: object - properties: - data: - type: object - additionalProperties: - $ref: '#/components/schemas/SpanWithStatus' - description: >- - Dictionary mapping span IDs to spans with status information - additionalProperties: false - required: - - data - title: QuerySpanTreeResponse - description: >- - Response containing a tree structure of spans. - Tool: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: tool - default: tool - description: Type of resource, always 'tool' - toolgroup_id: - type: string - description: >- - ID of the tool group this tool belongs to - description: - type: string - description: >- - Human-readable description of what the tool does - parameters: - type: array - items: - $ref: '#/components/schemas/ToolParameter' - description: List of parameters this tool accepts - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Additional metadata about the tool - additionalProperties: false - required: - - identifier - - provider_id - - type - - toolgroup_id - - description - - parameters - title: Tool - description: A tool that can be invoked by agents. - ToolGroup: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: tool_group - default: tool_group - description: Type of resource, always 'tool_group' - mcp_endpoint: - $ref: '#/components/schemas/URL' - description: >- - (Optional) Model Context Protocol endpoint for remote tools - args: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Additional arguments for the tool group - additionalProperties: false - required: - - identifier - - provider_id - - type - title: ToolGroup - description: >- - A group of related tools managed together. - Trace: - type: object - properties: - trace_id: - type: string - description: Unique identifier for the trace - root_span_id: - type: string - description: >- - Unique identifier for the root span that started this trace - start_time: - type: string - format: date-time - description: Timestamp when the trace began - end_time: - type: string - format: date-time - description: >- - (Optional) Timestamp when the trace finished, if completed - additionalProperties: false - required: - - trace_id - - root_span_id - - start_time - title: Trace - description: >- - A trace representing the complete execution path of a request across multiple - operations. - Checkpoint: - type: object - properties: - identifier: - type: string - description: Unique identifier for the checkpoint - created_at: - type: string - format: date-time - description: >- - Timestamp when the checkpoint was created - epoch: - type: integer - description: >- - Training epoch when the checkpoint was saved - post_training_job_id: - type: string - description: >- - Identifier of the training job that created this checkpoint - path: - type: string - description: >- - File system path where the checkpoint is stored - training_metrics: - $ref: '#/components/schemas/PostTrainingMetric' - description: >- - (Optional) Training metrics associated with this checkpoint - additionalProperties: false - required: - - identifier - - created_at - - epoch - - post_training_job_id - - path - title: Checkpoint - description: Checkpoint created during training runs. - PostTrainingJobArtifactsResponse: - type: object - properties: - job_uuid: - type: string - description: Unique identifier for the training job - checkpoints: - type: array - items: - $ref: '#/components/schemas/Checkpoint' - description: >- - List of model checkpoints created during training - additionalProperties: false - required: - - job_uuid - - checkpoints - title: PostTrainingJobArtifactsResponse - description: Artifacts of a finetuning job. - PostTrainingMetric: - type: object - properties: - epoch: - type: integer - description: Training epoch number - train_loss: - type: number - description: Loss value on the training dataset - validation_loss: - type: number - description: Loss value on the validation dataset - perplexity: - type: number - description: >- - Perplexity metric indicating model confidence - additionalProperties: false - required: - - epoch - - train_loss - - validation_loss - - perplexity - title: PostTrainingMetric - description: >- - Training metrics captured during post-training jobs. - PostTrainingJobStatusResponse: - type: object - properties: - job_uuid: - type: string - description: Unique identifier for the training job - status: - type: string - enum: - - completed - - in_progress - - failed - - scheduled - - cancelled - description: Current status of the training job - scheduled_at: - type: string - format: date-time - description: >- - (Optional) Timestamp when the job was scheduled - started_at: - type: string - format: date-time - description: >- - (Optional) Timestamp when the job execution began - completed_at: - type: string - format: date-time - description: >- - (Optional) Timestamp when the job finished, if completed - resources_allocated: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Information about computational resources allocated to the - job - checkpoints: - type: array - items: - $ref: '#/components/schemas/Checkpoint' - description: >- - List of model checkpoints created during training - additionalProperties: false - required: - - job_uuid - - status - - checkpoints - title: PostTrainingJobStatusResponse - description: Status of a finetuning job. - ListPostTrainingJobsResponse: - type: object - properties: - data: - type: array - items: - type: object - properties: - job_uuid: - type: string - additionalProperties: false - required: - - job_uuid - title: PostTrainingJob - additionalProperties: false - required: - - data - title: ListPostTrainingJobsResponse - VectorDB: - type: object - properties: - identifier: - type: string - provider_resource_id: - type: string - provider_id: - type: string - type: - type: string - enum: - - model - - shield - - vector_db - - dataset - - scoring_function - - benchmark - - tool - - tool_group - - prompt - const: vector_db - default: vector_db - description: >- - Type of resource, always 'vector_db' for vector databases - embedding_model: - type: string - description: >- - Name of the embedding model to use for vector generation - embedding_dimension: - type: integer - description: Dimension of the embedding vectors - vector_db_name: - type: string - additionalProperties: false - required: - - identifier - - provider_id - - type - - embedding_model - - embedding_dimension - title: VectorDB - description: >- - Vector database resource for storing and querying vector embeddings. - HealthInfo: - type: object - properties: - status: - type: string - enum: - - OK - - Error - - Not Implemented - description: Current health status of the service - additionalProperties: false - required: - - status - title: HealthInfo - description: >- - Health status information for the service. - RAGDocument: - type: object - properties: - document_id: - type: string - description: The unique identifier for the document. - content: - oneOf: - - type: string - - $ref: '#/components/schemas/InterleavedContentItem' - - type: array - items: - $ref: '#/components/schemas/InterleavedContentItem' - - $ref: '#/components/schemas/URL' - description: The content of the document. - mime_type: - type: string - description: The MIME type of the document. - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: Additional metadata for the document. - additionalProperties: false - required: - - document_id - - content - - metadata - title: RAGDocument - description: >- - A document to be used for document ingestion in the RAG Tool. - InsertRequest: - type: object - properties: - documents: - type: array - items: - $ref: '#/components/schemas/RAGDocument' - description: >- - List of documents to index in the RAG system - vector_db_id: - type: string - description: >- - ID of the vector database to store the document embeddings - chunk_size_in_tokens: - type: integer - description: >- - (Optional) Size in tokens for document chunking during indexing - additionalProperties: false - required: - - documents - - vector_db_id - - chunk_size_in_tokens - title: InsertRequest - Chunk: - type: object - properties: - content: - $ref: '#/components/schemas/InterleavedContent' - description: >- - The content of the chunk, which can be interleaved text, images, or other - types. - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - Metadata associated with the chunk that will be used in the model context - during inference. - embedding: - type: array - items: - type: number - description: >- - Optional embedding for the chunk. If not provided, it will be computed - later. - stored_chunk_id: - type: string - description: >- - The chunk ID that is stored in the vector database. Used for backend functionality. - chunk_metadata: - $ref: '#/components/schemas/ChunkMetadata' - description: >- - Metadata for the chunk that will NOT be used in the context during inference. - The `chunk_metadata` is required backend functionality. - additionalProperties: false - required: - - content - - metadata - title: Chunk - description: >- - A chunk of content that can be inserted into a vector database. - ChunkMetadata: - type: object - properties: - chunk_id: - type: string - description: >- - The ID of the chunk. If not set, it will be generated based on the document - ID and content. - document_id: - type: string - description: >- - The ID of the document this chunk belongs to. - source: - type: string - description: >- - The source of the content, such as a URL, file path, or other identifier. - created_timestamp: - type: integer - description: >- - An optional timestamp indicating when the chunk was created. - updated_timestamp: - type: integer - description: >- - An optional timestamp indicating when the chunk was last updated. - chunk_window: - type: string - description: >- - The window of the chunk, which can be used to group related chunks together. - chunk_tokenizer: - type: string - description: >- - The tokenizer used to create the chunk. Default is Tiktoken. - chunk_embedding_model: - type: string - description: >- - The embedding model used to create the chunk's embedding. - chunk_embedding_dimension: - type: integer - description: >- - The dimension of the embedding vector for the chunk. - content_token_count: - type: integer - description: >- - The number of tokens in the content of the chunk. - metadata_token_count: - type: integer - description: >- - The number of tokens in the metadata of the chunk. - additionalProperties: false - title: ChunkMetadata - description: >- - `ChunkMetadata` is backend metadata for a `Chunk` that is used to store additional - information about the chunk that will not be used in the context during - inference, but is required for backend functionality. The `ChunkMetadata` is - set during chunk creation in `MemoryToolRuntimeImpl().insert()`and is not - expected to change after. Use `Chunk.metadata` for metadata that will - be used in the context during inference. - InsertChunksRequest: - type: object - properties: - vector_db_id: - type: string - description: >- - The identifier of the vector database to insert the chunks into. - chunks: - type: array - items: - $ref: '#/components/schemas/Chunk' - description: >- - The chunks to insert. Each `Chunk` should contain content which can be - interleaved text, images, or other types. `metadata`: `dict[str, Any]` - and `embedding`: `List[float]` are optional. If `metadata` is provided, - you configure how Llama Stack formats the chunk during generation. If - `embedding` is not provided, it will be computed later. - ttl_seconds: - type: integer - description: The time to live of the chunks. - additionalProperties: false - required: - - vector_db_id - - chunks - title: InsertChunksRequest - ProviderInfo: - type: object - properties: - api: - type: string - description: The API name this provider implements - provider_id: - type: string - description: Unique identifier for the provider - provider_type: - type: string - description: The type of provider implementation - config: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - Configuration parameters for the provider - health: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: Current health status of the provider - additionalProperties: false - required: - - api - - provider_id - - provider_type - - config - - health - title: ProviderInfo - description: >- - Information about a registered provider including its configuration and health - status. - InvokeToolRequest: - type: object - properties: - tool_name: - type: string - description: The name of the tool to invoke. - kwargs: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - A dictionary of arguments to pass to the tool. - additionalProperties: false - required: - - tool_name - - kwargs - title: InvokeToolRequest - ToolInvocationResult: - type: object - properties: - content: - $ref: '#/components/schemas/InterleavedContent' - description: >- - (Optional) The output content from the tool execution - error_message: - type: string - description: >- - (Optional) Error message if the tool execution failed - error_code: - type: integer - description: >- - (Optional) Numeric error code if the tool execution failed - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Additional metadata about the tool execution - additionalProperties: false - title: ToolInvocationResult - description: Result of a tool invocation. - PaginatedResponse: - type: object - properties: - data: - type: array - items: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The list of items for the current page - has_more: - type: boolean - description: >- - Whether there are more items available after this set - url: - type: string - description: The URL for accessing this list - additionalProperties: false - required: - - data - - has_more - title: PaginatedResponse - description: >- - A generic paginated response that follows a simple format. - Job: - type: object - properties: - job_id: - type: string - description: Unique identifier for the job - status: - type: string - enum: - - completed - - in_progress - - failed - - scheduled - - cancelled - description: Current execution status of the job - additionalProperties: false - required: - - job_id - - status - title: Job - description: >- - A job execution instance with status tracking. - ListBenchmarksResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Benchmark' - additionalProperties: false - required: - - data - title: ListBenchmarksResponse - Order: - type: string - enum: - - asc - - desc - title: Order - description: Sort order for paginated responses. - ListOpenAIChatCompletionResponse: - type: object - properties: - data: - type: array - items: - type: object - properties: - id: - type: string - description: The ID of the chat completion - choices: - type: array - items: - $ref: '#/components/schemas/OpenAIChoice' - description: List of choices - object: - type: string - const: chat.completion - default: chat.completion - description: >- - The object type, which will be "chat.completion" - created: - type: integer - description: >- - The Unix timestamp in seconds when the chat completion was created - model: - type: string - description: >- - The model that was used to generate the chat completion - input_messages: - type: array - items: - $ref: '#/components/schemas/OpenAIMessageParam' - additionalProperties: false - required: - - id - - choices - - object - - created - - model - - input_messages - title: OpenAICompletionWithInputMessages - description: >- - List of chat completion objects with their input messages - has_more: - type: boolean - description: >- - Whether there are more completions available beyond this list - first_id: - type: string - description: ID of the first completion in this list - last_id: - type: string - description: ID of the last completion in this list - object: - type: string - const: list - default: list - description: >- - Must be "list" to identify this as a list response - additionalProperties: false - required: - - data - - has_more - - first_id - - last_id - - object - title: ListOpenAIChatCompletionResponse - description: >- - Response from listing OpenAI-compatible chat completions. - ListDatasetsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Dataset' - description: List of datasets - additionalProperties: false - required: - - data - title: ListDatasetsResponse - description: Response from listing datasets. - ListModelsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Model' - additionalProperties: false - required: - - data - title: ListModelsResponse - ListOpenAIResponseInputItem: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/OpenAIResponseInput' - description: List of input items - object: - type: string - const: list - default: list - description: Object type identifier, always "list" - additionalProperties: false - required: - - data - - object - title: ListOpenAIResponseInputItem - description: >- - List container for OpenAI response input items. - ListOpenAIResponseObject: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/OpenAIResponseObjectWithInput' - description: >- - List of response objects with their input context - has_more: - type: boolean - description: >- - Whether there are more results available beyond this page - first_id: - type: string - description: >- - Identifier of the first item in this page - last_id: - type: string - description: Identifier of the last item in this page - object: - type: string - const: list - default: list - description: Object type identifier, always "list" - additionalProperties: false - required: - - data - - has_more - - first_id - - last_id - - object - title: ListOpenAIResponseObject - description: >- - Paginated list of OpenAI response objects with navigation metadata. - OpenAIResponseObjectWithInput: - type: object - properties: - created_at: - type: integer - description: >- - Unix timestamp when the response was created - error: - $ref: '#/components/schemas/OpenAIResponseError' - description: >- - (Optional) Error details if the response generation failed - id: - type: string - description: Unique identifier for this response - model: - type: string - description: Model identifier used for generation - object: - type: string - const: response - default: response - description: >- - Object type identifier, always "response" - output: - type: array - items: - $ref: '#/components/schemas/OpenAIResponseOutput' - description: >- - List of generated output items (messages, tool calls, etc.) - parallel_tool_calls: - type: boolean - default: false - description: >- - Whether tool calls can be executed in parallel - previous_response_id: - type: string - description: >- - (Optional) ID of the previous response in a conversation - status: - type: string - description: >- - Current status of the response generation - temperature: - type: number - description: >- - (Optional) Sampling temperature used for generation - text: - $ref: '#/components/schemas/OpenAIResponseText' - description: >- - Text formatting configuration for the response - top_p: - type: number - description: >- - (Optional) Nucleus sampling parameter used for generation - truncation: - type: string - description: >- - (Optional) Truncation strategy applied to the response - user: - type: string - description: >- - (Optional) User identifier associated with the request - input: - type: array - items: - $ref: '#/components/schemas/OpenAIResponseInput' - description: >- - List of input items that led to this response - additionalProperties: false - required: - - created_at - - id - - model - - object - - output - - parallel_tool_calls - - status - - text - - input - title: OpenAIResponseObjectWithInput - description: >- - OpenAI response object extended with input context information. - ListPromptsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Prompt' - additionalProperties: false - required: - - data - title: ListPromptsResponse - description: Response model to list prompts. - ListProvidersResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/ProviderInfo' - description: List of provider information objects - additionalProperties: false - required: - - data - title: ListProvidersResponse - description: >- - Response containing a list of all available providers. - RouteInfo: - type: object - properties: - route: - type: string - description: The API endpoint path - method: - type: string - description: HTTP method for the route - provider_types: - type: array - items: - type: string - description: >- - List of provider types that implement this route - additionalProperties: false - required: - - route - - method - - provider_types - title: RouteInfo - description: >- - Information about an API route including its path, method, and implementing - providers. - ListRoutesResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/RouteInfo' - description: >- - List of available route information objects - additionalProperties: false - required: - - data - title: ListRoutesResponse - description: >- - Response containing a list of all available API routes. - ListToolDefsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/ToolDef' - description: List of tool definitions - additionalProperties: false - required: - - data - title: ListToolDefsResponse - description: >- - Response containing a list of tool definitions. - ListScoringFunctionsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/ScoringFn' - additionalProperties: false - required: - - data - title: ListScoringFunctionsResponse - ListShieldsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Shield' - additionalProperties: false - required: - - data - title: ListShieldsResponse - ListToolGroupsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/ToolGroup' - description: List of tool groups - additionalProperties: false - required: - - data - title: ListToolGroupsResponse - description: >- - Response containing a list of tool groups. - ListToolsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Tool' - description: List of tools - additionalProperties: false - required: - - data - title: ListToolsResponse - description: Response containing a list of tools. - ListVectorDBsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/VectorDB' - description: List of vector databases - additionalProperties: false - required: - - data - title: ListVectorDBsResponse - description: Response from listing vector databases. - Event: - oneOf: - - $ref: '#/components/schemas/UnstructuredLogEvent' - - $ref: '#/components/schemas/MetricEvent' - - $ref: '#/components/schemas/StructuredLogEvent' - discriminator: - propertyName: type - mapping: - unstructured_log: '#/components/schemas/UnstructuredLogEvent' - metric: '#/components/schemas/MetricEvent' - structured_log: '#/components/schemas/StructuredLogEvent' - EventType: - type: string - enum: - - unstructured_log - - structured_log - - metric - title: EventType - description: >- - The type of telemetry event being logged. - LogSeverity: - type: string - enum: - - verbose - - debug - - info - - warn - - error - - critical - title: LogSeverity - description: The severity level of a log message. - MetricEvent: - type: object - properties: - trace_id: - type: string - description: >- - Unique identifier for the trace this event belongs to - span_id: - type: string - description: >- - Unique identifier for the span this event belongs to - timestamp: - type: string - format: date-time - description: Timestamp when the event occurred - attributes: - type: object - additionalProperties: - oneOf: - - type: string - - type: integer - - type: number - - type: boolean - - type: 'null' - description: >- - (Optional) Key-value pairs containing additional metadata about the event - type: - $ref: '#/components/schemas/EventType' - const: metric - default: metric - description: Event type identifier set to METRIC - metric: - type: string - description: The name of the metric being measured - value: - oneOf: - - type: integer - - type: number - description: >- - The numeric value of the metric measurement - unit: - type: string - description: >- - The unit of measurement for the metric value - additionalProperties: false - required: - - trace_id - - span_id - - timestamp - - type - - metric - - value - - unit - title: MetricEvent - description: >- - A metric event containing a measured value. - SpanEndPayload: - type: object - properties: - type: - $ref: '#/components/schemas/StructuredLogType' - const: span_end - default: span_end - description: Payload type identifier set to SPAN_END - status: - $ref: '#/components/schemas/SpanStatus' - description: >- - The final status of the span indicating success or failure - additionalProperties: false - required: - - type - - status - title: SpanEndPayload - description: Payload for a span end event. - SpanStartPayload: - type: object - properties: - type: - $ref: '#/components/schemas/StructuredLogType' - const: span_start - default: span_start - description: >- - Payload type identifier set to SPAN_START - name: - type: string - description: >- - Human-readable name describing the operation this span represents - parent_span_id: - type: string - description: >- - (Optional) Unique identifier for the parent span, if this is a child span - additionalProperties: false - required: - - type - - name - title: SpanStartPayload - description: Payload for a span start event. - StructuredLogEvent: - type: object - properties: - trace_id: - type: string - description: >- - Unique identifier for the trace this event belongs to - span_id: - type: string - description: >- - Unique identifier for the span this event belongs to - timestamp: - type: string - format: date-time - description: Timestamp when the event occurred - attributes: - type: object - additionalProperties: - oneOf: - - type: string - - type: integer - - type: number - - type: boolean - - type: 'null' - description: >- - (Optional) Key-value pairs containing additional metadata about the event - type: - $ref: '#/components/schemas/EventType' - const: structured_log - default: structured_log - description: >- - Event type identifier set to STRUCTURED_LOG - payload: - $ref: '#/components/schemas/StructuredLogPayload' - description: >- - The structured payload data for the log event - additionalProperties: false - required: - - trace_id - - span_id - - timestamp - - type - - payload - title: StructuredLogEvent - description: >- - A structured log event containing typed payload data. - StructuredLogPayload: - oneOf: - - $ref: '#/components/schemas/SpanStartPayload' - - $ref: '#/components/schemas/SpanEndPayload' - discriminator: - propertyName: type - mapping: - span_start: '#/components/schemas/SpanStartPayload' - span_end: '#/components/schemas/SpanEndPayload' - StructuredLogType: - type: string - enum: - - span_start - - span_end - title: StructuredLogType - description: >- - The type of structured log event payload. - UnstructuredLogEvent: - type: object - properties: - trace_id: - type: string - description: >- - Unique identifier for the trace this event belongs to - span_id: - type: string - description: >- - Unique identifier for the span this event belongs to - timestamp: - type: string - format: date-time - description: Timestamp when the event occurred - attributes: - type: object - additionalProperties: - oneOf: - - type: string - - type: integer - - type: number - - type: boolean - - type: 'null' - description: >- - (Optional) Key-value pairs containing additional metadata about the event - type: - $ref: '#/components/schemas/EventType' - const: unstructured_log - default: unstructured_log - description: >- - Event type identifier set to UNSTRUCTURED_LOG - message: - type: string - description: The log message text - severity: - $ref: '#/components/schemas/LogSeverity' - description: The severity level of the log message - additionalProperties: false - required: - - trace_id - - span_id - - timestamp - - type - - message - - severity - title: UnstructuredLogEvent - description: >- - An unstructured log event containing a simple text message. - LogEventRequest: - type: object - properties: - event: - $ref: '#/components/schemas/Event' - description: The event to log. - ttl_seconds: - type: integer - description: The time to live of the event. - additionalProperties: false - required: - - event - - ttl_seconds - title: LogEventRequest - VectorStoreChunkingStrategy: - oneOf: - - $ref: '#/components/schemas/VectorStoreChunkingStrategyAuto' - - $ref: '#/components/schemas/VectorStoreChunkingStrategyStatic' - discriminator: - propertyName: type - mapping: - auto: '#/components/schemas/VectorStoreChunkingStrategyAuto' - static: '#/components/schemas/VectorStoreChunkingStrategyStatic' - VectorStoreChunkingStrategyAuto: - type: object - properties: - type: - type: string - const: auto - default: auto - description: >- - Strategy type, always "auto" for automatic chunking - additionalProperties: false - required: - - type - title: VectorStoreChunkingStrategyAuto - description: >- - Automatic chunking strategy for vector store files. - VectorStoreChunkingStrategyStatic: - type: object - properties: - type: - type: string - const: static - default: static - description: >- - Strategy type, always "static" for static chunking - static: - $ref: '#/components/schemas/VectorStoreChunkingStrategyStaticConfig' - description: >- - Configuration parameters for the static chunking strategy - additionalProperties: false - required: - - type - - static - title: VectorStoreChunkingStrategyStatic - description: >- - Static chunking strategy with configurable parameters. - VectorStoreChunkingStrategyStaticConfig: - type: object - properties: - chunk_overlap_tokens: - type: integer - default: 400 - description: >- - Number of tokens to overlap between adjacent chunks - max_chunk_size_tokens: - type: integer - default: 800 - description: >- - Maximum number of tokens per chunk, must be between 100 and 4096 - additionalProperties: false - required: - - chunk_overlap_tokens - - max_chunk_size_tokens - title: VectorStoreChunkingStrategyStaticConfig - description: >- - Configuration for static chunking strategy. - OpenaiAttachFileToVectorStoreRequest: - type: object - properties: - file_id: - type: string - description: >- - The ID of the file to attach to the vector store. - attributes: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - The key-value attributes stored with the file, which can be used for filtering. - chunking_strategy: - $ref: '#/components/schemas/VectorStoreChunkingStrategy' - description: >- - The chunking strategy to use for the file. - additionalProperties: false - required: - - file_id - title: OpenaiAttachFileToVectorStoreRequest - VectorStoreFileLastError: - type: object - properties: - code: - oneOf: - - type: string - const: server_error - - type: string - const: rate_limit_exceeded - description: >- - Error code indicating the type of failure - message: - type: string - description: >- - Human-readable error message describing the failure - additionalProperties: false - required: - - code - - message - title: VectorStoreFileLastError - description: >- - Error information for failed vector store file processing. - VectorStoreFileObject: - type: object - properties: - id: - type: string - description: Unique identifier for the file - object: - type: string - default: vector_store.file - description: >- - Object type identifier, always "vector_store.file" - attributes: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - Key-value attributes associated with the file - chunking_strategy: - $ref: '#/components/schemas/VectorStoreChunkingStrategy' - description: >- - Strategy used for splitting the file into chunks - created_at: - type: integer - description: >- - Timestamp when the file was added to the vector store - last_error: - $ref: '#/components/schemas/VectorStoreFileLastError' - description: >- - (Optional) Error information if file processing failed - status: - $ref: '#/components/schemas/VectorStoreFileStatus' - description: Current processing status of the file - usage_bytes: - type: integer - default: 0 - description: Storage space used by this file in bytes - vector_store_id: - type: string - description: >- - ID of the vector store containing this file - additionalProperties: false - required: - - id - - object - - attributes - - chunking_strategy - - created_at - - status - - usage_bytes - - vector_store_id - title: VectorStoreFileObject - description: OpenAI Vector Store File object. - VectorStoreFileStatus: - oneOf: - - type: string - const: completed - - type: string - const: in_progress - - type: string - const: cancelled - - type: string - const: failed ->>>>>>> f7acfa0f (Add rerank API for NVIDIA Inference Provider) OpenAIJSONSchema: type: object properties: @@ -7282,6 +5158,7 @@ components: enum: - llm - embedding + - rerank title: ModelType description: >- Enumeration of supported model types in Llama Stack. @@ -11706,1606 +9583,6 @@ components: title: VectorStoreSearchResponsePage description: >- Paginated response from searching a vector store. -<<<<<<< HEAD -======= - OpenaiUpdateVectorStoreRequest: - type: object - properties: - name: - type: string - description: The name of the vector store. - expires_after: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - The expiration policy for a vector store. - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - Set of 16 key-value pairs that can be attached to an object. - additionalProperties: false - title: OpenaiUpdateVectorStoreRequest - OpenaiUpdateVectorStoreFileRequest: - type: object - properties: - attributes: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - The updated key-value attributes to store with the file. - additionalProperties: false - required: - - attributes - title: OpenaiUpdateVectorStoreFileRequest - DPOAlignmentConfig: - type: object - properties: - beta: - type: number - description: Temperature parameter for the DPO loss - loss_type: - $ref: '#/components/schemas/DPOLossType' - default: sigmoid - description: The type of loss function to use for DPO - additionalProperties: false - required: - - beta - - loss_type - title: DPOAlignmentConfig - description: >- - Configuration for Direct Preference Optimization (DPO) alignment. - DPOLossType: - type: string - enum: - - sigmoid - - hinge - - ipo - - kto_pair - title: DPOLossType - DataConfig: - type: object - properties: - dataset_id: - type: string - description: >- - Unique identifier for the training dataset - batch_size: - type: integer - description: Number of samples per training batch - shuffle: - type: boolean - description: >- - Whether to shuffle the dataset during training - data_format: - $ref: '#/components/schemas/DatasetFormat' - description: >- - Format of the dataset (instruct or dialog) - validation_dataset_id: - type: string - description: >- - (Optional) Unique identifier for the validation dataset - packed: - type: boolean - default: false - description: >- - (Optional) Whether to pack multiple samples into a single sequence for - efficiency - train_on_input: - type: boolean - default: false - description: >- - (Optional) Whether to compute loss on input tokens as well as output tokens - additionalProperties: false - required: - - dataset_id - - batch_size - - shuffle - - data_format - title: DataConfig - description: >- - Configuration for training data and data loading. - DatasetFormat: - type: string - enum: - - instruct - - dialog - title: DatasetFormat - description: Format of the training dataset. - EfficiencyConfig: - type: object - properties: - enable_activation_checkpointing: - type: boolean - default: false - description: >- - (Optional) Whether to use activation checkpointing to reduce memory usage - enable_activation_offloading: - type: boolean - default: false - description: >- - (Optional) Whether to offload activations to CPU to save GPU memory - memory_efficient_fsdp_wrap: - type: boolean - default: false - description: >- - (Optional) Whether to use memory-efficient FSDP wrapping - fsdp_cpu_offload: - type: boolean - default: false - description: >- - (Optional) Whether to offload FSDP parameters to CPU - additionalProperties: false - title: EfficiencyConfig - description: >- - Configuration for memory and compute efficiency optimizations. - OptimizerConfig: - type: object - properties: - optimizer_type: - $ref: '#/components/schemas/OptimizerType' - description: >- - Type of optimizer to use (adam, adamw, or sgd) - lr: - type: number - description: Learning rate for the optimizer - weight_decay: - type: number - description: >- - Weight decay coefficient for regularization - num_warmup_steps: - type: integer - description: Number of steps for learning rate warmup - additionalProperties: false - required: - - optimizer_type - - lr - - weight_decay - - num_warmup_steps - title: OptimizerConfig - description: >- - Configuration parameters for the optimization algorithm. - OptimizerType: - type: string - enum: - - adam - - adamw - - sgd - title: OptimizerType - description: >- - Available optimizer algorithms for training. - TrainingConfig: - type: object - properties: - n_epochs: - type: integer - description: Number of training epochs to run - max_steps_per_epoch: - type: integer - default: 1 - description: Maximum number of steps to run per epoch - gradient_accumulation_steps: - type: integer - default: 1 - description: >- - Number of steps to accumulate gradients before updating - max_validation_steps: - type: integer - default: 1 - description: >- - (Optional) Maximum number of validation steps per epoch - data_config: - $ref: '#/components/schemas/DataConfig' - description: >- - (Optional) Configuration for data loading and formatting - optimizer_config: - $ref: '#/components/schemas/OptimizerConfig' - description: >- - (Optional) Configuration for the optimization algorithm - efficiency_config: - $ref: '#/components/schemas/EfficiencyConfig' - description: >- - (Optional) Configuration for memory and compute optimizations - dtype: - type: string - default: bf16 - description: >- - (Optional) Data type for model parameters (bf16, fp16, fp32) - additionalProperties: false - required: - - n_epochs - - max_steps_per_epoch - - gradient_accumulation_steps - title: TrainingConfig - description: >- - Comprehensive configuration for the training process. - PreferenceOptimizeRequest: - type: object - properties: - job_uuid: - type: string - description: The UUID of the job to create. - finetuned_model: - type: string - description: The model to fine-tune. - algorithm_config: - $ref: '#/components/schemas/DPOAlignmentConfig' - description: The algorithm configuration. - training_config: - $ref: '#/components/schemas/TrainingConfig' - description: The training configuration. - hyperparam_search_config: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The hyperparam search configuration. - logger_config: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The logger configuration. - additionalProperties: false - required: - - job_uuid - - finetuned_model - - algorithm_config - - training_config - - hyperparam_search_config - - logger_config - title: PreferenceOptimizeRequest - PostTrainingJob: - type: object - properties: - job_uuid: - type: string - additionalProperties: false - required: - - job_uuid - title: PostTrainingJob - DefaultRAGQueryGeneratorConfig: - type: object - properties: - type: - type: string - const: default - default: default - description: >- - Type of query generator, always 'default' - separator: - type: string - default: ' ' - description: >- - String separator used to join query terms - additionalProperties: false - required: - - type - - separator - title: DefaultRAGQueryGeneratorConfig - description: >- - Configuration for the default RAG query generator. - LLMRAGQueryGeneratorConfig: - type: object - properties: - type: - type: string - const: llm - default: llm - description: Type of query generator, always 'llm' - model: - type: string - description: >- - Name of the language model to use for query generation - template: - type: string - description: >- - Template string for formatting the query generation prompt - additionalProperties: false - required: - - type - - model - - template - title: LLMRAGQueryGeneratorConfig - description: >- - Configuration for the LLM-based RAG query generator. - RAGQueryConfig: - type: object - properties: - query_generator_config: - $ref: '#/components/schemas/RAGQueryGeneratorConfig' - description: Configuration for the query generator. - max_tokens_in_context: - type: integer - default: 4096 - description: Maximum number of tokens in the context. - max_chunks: - type: integer - default: 5 - description: Maximum number of chunks to retrieve. - chunk_template: - type: string - default: > - Result {index} - - Content: {chunk.content} - - Metadata: {metadata} - description: >- - Template for formatting each retrieved chunk in the context. Available - placeholders: {index} (1-based chunk ordinal), {chunk.content} (chunk - content string), {metadata} (chunk metadata dict). Default: "Result {index}\nContent: - {chunk.content}\nMetadata: {metadata}\n" - mode: - $ref: '#/components/schemas/RAGSearchMode' - default: vector - description: >- - Search mode for retrieval—either "vector", "keyword", or "hybrid". Default - "vector". - ranker: - $ref: '#/components/schemas/Ranker' - description: >- - Configuration for the ranker to use in hybrid search. Defaults to RRF - ranker. - additionalProperties: false - required: - - query_generator_config - - max_tokens_in_context - - max_chunks - - chunk_template - title: RAGQueryConfig - description: >- - Configuration for the RAG query generation. - RAGQueryGeneratorConfig: - oneOf: - - $ref: '#/components/schemas/DefaultRAGQueryGeneratorConfig' - - $ref: '#/components/schemas/LLMRAGQueryGeneratorConfig' - discriminator: - propertyName: type - mapping: - default: '#/components/schemas/DefaultRAGQueryGeneratorConfig' - llm: '#/components/schemas/LLMRAGQueryGeneratorConfig' - RAGSearchMode: - type: string - enum: - - vector - - keyword - - hybrid - title: RAGSearchMode - description: >- - Search modes for RAG query retrieval: - VECTOR: Uses vector similarity search - for semantic matching - KEYWORD: Uses keyword-based search for exact matching - - HYBRID: Combines both vector and keyword search for better results - RRFRanker: - type: object - properties: - type: - type: string - const: rrf - default: rrf - description: The type of ranker, always "rrf" - impact_factor: - type: number - default: 60.0 - description: >- - The impact factor for RRF scoring. Higher values give more weight to higher-ranked - results. Must be greater than 0 - additionalProperties: false - required: - - type - - impact_factor - title: RRFRanker - description: >- - Reciprocal Rank Fusion (RRF) ranker configuration. - Ranker: - oneOf: - - $ref: '#/components/schemas/RRFRanker' - - $ref: '#/components/schemas/WeightedRanker' - discriminator: - propertyName: type - mapping: - rrf: '#/components/schemas/RRFRanker' - weighted: '#/components/schemas/WeightedRanker' - WeightedRanker: - type: object - properties: - type: - type: string - const: weighted - default: weighted - description: The type of ranker, always "weighted" - alpha: - type: number - default: 0.5 - description: >- - Weight factor between 0 and 1. 0 means only use keyword scores, 1 means - only use vector scores, values in between blend both scores. - additionalProperties: false - required: - - type - - alpha - title: WeightedRanker - description: >- - Weighted ranker configuration that combines vector and keyword scores. - QueryRequest: - type: object - properties: - content: - $ref: '#/components/schemas/InterleavedContent' - description: >- - The query content to search for in the indexed documents - vector_db_ids: - type: array - items: - type: string - description: >- - List of vector database IDs to search within - query_config: - $ref: '#/components/schemas/RAGQueryConfig' - description: >- - (Optional) Configuration parameters for the query operation - additionalProperties: false - required: - - content - - vector_db_ids - title: QueryRequest - RAGQueryResult: - type: object - properties: - content: - $ref: '#/components/schemas/InterleavedContent' - description: >- - (Optional) The retrieved content from the query - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - Additional metadata about the query result - additionalProperties: false - required: - - metadata - title: RAGQueryResult - description: >- - Result of a RAG query containing retrieved content and metadata. - QueryChunksRequest: - type: object - properties: - vector_db_id: - type: string - description: >- - The identifier of the vector database to query. - query: - $ref: '#/components/schemas/InterleavedContent' - description: The query to search for. - params: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The parameters of the query. - additionalProperties: false - required: - - vector_db_id - - query - title: QueryChunksRequest - QueryChunksResponse: - type: object - properties: - chunks: - type: array - items: - $ref: '#/components/schemas/Chunk' - description: >- - List of content chunks returned from the query - scores: - type: array - items: - type: number - description: >- - Relevance scores corresponding to each returned chunk - additionalProperties: false - required: - - chunks - - scores - title: QueryChunksResponse - description: >- - Response from querying chunks in a vector database. - QueryMetricsRequest: - type: object - properties: - start_time: - type: integer - description: The start time of the metric to query. - end_time: - type: integer - description: The end time of the metric to query. - granularity: - type: string - description: The granularity of the metric to query. - query_type: - type: string - enum: - - range - - instant - description: The type of query to perform. - label_matchers: - type: array - items: - type: object - properties: - name: - type: string - description: The name of the label to match - value: - type: string - description: The value to match against - operator: - type: string - enum: - - '=' - - '!=' - - =~ - - '!~' - description: >- - The comparison operator to use for matching - default: '=' - additionalProperties: false - required: - - name - - value - - operator - title: MetricLabelMatcher - description: >- - A matcher for filtering metrics by label values. - description: >- - The label matchers to apply to the metric. - additionalProperties: false - required: - - start_time - - query_type - title: QueryMetricsRequest - MetricDataPoint: - type: object - properties: - timestamp: - type: integer - description: >- - Unix timestamp when the metric value was recorded - value: - type: number - description: >- - The numeric value of the metric at this timestamp - unit: - type: string - additionalProperties: false - required: - - timestamp - - value - - unit - title: MetricDataPoint - description: >- - A single data point in a metric time series. - MetricLabel: - type: object - properties: - name: - type: string - description: The name of the label - value: - type: string - description: The value of the label - additionalProperties: false - required: - - name - - value - title: MetricLabel - description: A label associated with a metric. - MetricSeries: - type: object - properties: - metric: - type: string - description: The name of the metric - labels: - type: array - items: - $ref: '#/components/schemas/MetricLabel' - description: >- - List of labels associated with this metric series - values: - type: array - items: - $ref: '#/components/schemas/MetricDataPoint' - description: >- - List of data points in chronological order - additionalProperties: false - required: - - metric - - labels - - values - title: MetricSeries - description: A time series of metric data points. - QueryMetricsResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/MetricSeries' - description: >- - List of metric series matching the query criteria - additionalProperties: false - required: - - data - title: QueryMetricsResponse - description: >- - Response containing metric time series data. - QueryCondition: - type: object - properties: - key: - type: string - description: The attribute key to filter on - op: - $ref: '#/components/schemas/QueryConditionOp' - description: The comparison operator to apply - value: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The value to compare against - additionalProperties: false - required: - - key - - op - - value - title: QueryCondition - description: A condition for filtering query results. - QueryConditionOp: - type: string - enum: - - eq - - ne - - gt - - lt - title: QueryConditionOp - description: >- - Comparison operators for query conditions. - QuerySpansRequest: - type: object - properties: - attribute_filters: - type: array - items: - $ref: '#/components/schemas/QueryCondition' - description: >- - The attribute filters to apply to the spans. - attributes_to_return: - type: array - items: - type: string - description: The attributes to return in the spans. - max_depth: - type: integer - description: The maximum depth of the tree. - additionalProperties: false - required: - - attribute_filters - - attributes_to_return - title: QuerySpansRequest - QuerySpansResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Span' - description: >- - List of spans matching the query criteria - additionalProperties: false - required: - - data - title: QuerySpansResponse - description: Response containing a list of spans. - QueryTracesRequest: - type: object - properties: - attribute_filters: - type: array - items: - $ref: '#/components/schemas/QueryCondition' - description: >- - The attribute filters to apply to the traces. - limit: - type: integer - description: The limit of traces to return. - offset: - type: integer - description: The offset of the traces to return. - order_by: - type: array - items: - type: string - description: The order by of the traces to return. - additionalProperties: false - title: QueryTracesRequest - QueryTracesResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/Trace' - description: >- - List of traces matching the query criteria - additionalProperties: false - required: - - data - title: QueryTracesResponse - description: Response containing a list of traces. - RegisterBenchmarkRequest: - type: object - properties: - benchmark_id: - type: string - description: The ID of the benchmark to register. - dataset_id: - type: string - description: >- - The ID of the dataset to use for the benchmark. - scoring_functions: - type: array - items: - type: string - description: >- - The scoring functions to use for the benchmark. - provider_benchmark_id: - type: string - description: >- - The ID of the provider benchmark to use for the benchmark. - provider_id: - type: string - description: >- - The ID of the provider to use for the benchmark. - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The metadata to use for the benchmark. - additionalProperties: false - required: - - benchmark_id - - dataset_id - - scoring_functions - title: RegisterBenchmarkRequest - RegisterDatasetRequest: - type: object - properties: - purpose: - type: string - enum: - - post-training/messages - - eval/question-answer - - eval/messages-answer - description: >- - The purpose of the dataset. One of: - "post-training/messages": The dataset - contains a messages column with list of messages for post-training. { - "messages": [ {"role": "user", "content": "Hello, world!"}, {"role": "assistant", - "content": "Hello, world!"}, ] } - "eval/question-answer": The dataset - contains a question column and an answer column for evaluation. { "question": - "What is the capital of France?", "answer": "Paris" } - "eval/messages-answer": - The dataset contains a messages column with list of messages and an answer - column for evaluation. { "messages": [ {"role": "user", "content": "Hello, - my name is John Doe."}, {"role": "assistant", "content": "Hello, John - Doe. How can I help you today?"}, {"role": "user", "content": "What's - my name?"}, ], "answer": "John Doe" } - source: - $ref: '#/components/schemas/DataSource' - description: >- - The data source of the dataset. Ensure that the data source schema is - compatible with the purpose of the dataset. Examples: - { "type": "uri", - "uri": "https://mywebsite.com/mydata.jsonl" } - { "type": "uri", "uri": - "lsfs://mydata.jsonl" } - { "type": "uri", "uri": "data:csv;base64,{base64_content}" - } - { "type": "uri", "uri": "huggingface://llamastack/simpleqa?split=train" - } - { "type": "rows", "rows": [ { "messages": [ {"role": "user", "content": - "Hello, world!"}, {"role": "assistant", "content": "Hello, world!"}, ] - } ] } - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - The metadata for the dataset. - E.g. {"description": "My dataset"}. - dataset_id: - type: string - description: >- - The ID of the dataset. If not provided, an ID will be generated. - additionalProperties: false - required: - - purpose - - source - title: RegisterDatasetRequest - RegisterModelRequest: - type: object - properties: - model_id: - type: string - description: The identifier of the model to register. - provider_model_id: - type: string - description: >- - The identifier of the model in the provider. - provider_id: - type: string - description: The identifier of the provider. - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: Any additional metadata for this model. - model_type: - $ref: '#/components/schemas/ModelType' - description: The type of model to register. - additionalProperties: false - required: - - model_id - title: RegisterModelRequest - RegisterScoringFunctionRequest: - type: object - properties: - scoring_fn_id: - type: string - description: >- - The ID of the scoring function to register. - description: - type: string - description: The description of the scoring function. - return_type: - $ref: '#/components/schemas/ParamType' - description: The return type of the scoring function. - provider_scoring_fn_id: - type: string - description: >- - The ID of the provider scoring function to use for the scoring function. - provider_id: - type: string - description: >- - The ID of the provider to use for the scoring function. - params: - $ref: '#/components/schemas/ScoringFnParams' - description: >- - The parameters for the scoring function for benchmark eval, these can - be overridden for app eval. - additionalProperties: false - required: - - scoring_fn_id - - description - - return_type - title: RegisterScoringFunctionRequest - RegisterShieldRequest: - type: object - properties: - shield_id: - type: string - description: >- - The identifier of the shield to register. - provider_shield_id: - type: string - description: >- - The identifier of the shield in the provider. - provider_id: - type: string - description: The identifier of the provider. - params: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The parameters of the shield. - additionalProperties: false - required: - - shield_id - title: RegisterShieldRequest - RegisterToolGroupRequest: - type: object - properties: - toolgroup_id: - type: string - description: The ID of the tool group to register. - provider_id: - type: string - description: >- - The ID of the provider to use for the tool group. - mcp_endpoint: - $ref: '#/components/schemas/URL' - description: >- - The MCP endpoint to use for the tool group. - args: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - A dictionary of arguments to pass to the tool group. - additionalProperties: false - required: - - toolgroup_id - - provider_id - title: RegisterToolGroupRequest - RegisterVectorDbRequest: - type: object - properties: - vector_db_id: - type: string - description: >- - The identifier of the vector database to register. - embedding_model: - type: string - description: The embedding model to use. - embedding_dimension: - type: integer - description: The dimension of the embedding model. - provider_id: - type: string - description: The identifier of the provider. - vector_db_name: - type: string - description: The name of the vector database. - provider_vector_db_id: - type: string - description: >- - The identifier of the vector database in the provider. - additionalProperties: false - required: - - vector_db_id - - embedding_model - title: RegisterVectorDbRequest - RerankRequest: - type: object - properties: - model: - type: string - description: >- - The identifier of the reranking model to use. The model must be a reranking - model registered with Llama Stack and available via the /models endpoint. - query: - oneOf: - - type: string - - $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam' - - $ref: '#/components/schemas/OpenAIChatCompletionContentPartImageParam' - description: >- - The search query to rank items against. Can be a string, text content - part, or image content part. The input must not exceed the model's max - input token length. - items: - type: array - items: - oneOf: - - type: string - - $ref: '#/components/schemas/OpenAIChatCompletionContentPartTextParam' - - $ref: '#/components/schemas/OpenAIChatCompletionContentPartImageParam' - description: >- - List of items to rerank. Each item can be a string, text content part, - or image content part. Each input must not exceed the model's max input - token length. - max_num_results: - type: integer - description: >- - (Optional) Maximum number of results to return. Default: returns all. - additionalProperties: false - required: - - model - - query - - items - title: RerankRequest - RerankData: - type: object - properties: - index: - type: integer - description: >- - The original index of the document in the input list - relevance_score: - type: number - description: >- - The relevance score from the model output. Values are inverted when applicable - so that higher scores indicate greater relevance. - additionalProperties: false - required: - - index - - relevance_score - title: RerankData - description: >- - A single rerank result from a reranking response. - RerankResponse: - type: object - properties: - data: - type: array - items: - $ref: '#/components/schemas/RerankData' - description: >- - List of rerank result objects, sorted by relevance score (descending) - additionalProperties: false - required: - - data - title: RerankResponse - description: Response from a reranking request. - ResumeAgentTurnRequest: - type: object - properties: - tool_responses: - type: array - items: - $ref: '#/components/schemas/ToolResponse' - description: >- - The tool call responses to resume the turn with. - stream: - type: boolean - description: Whether to stream the response. - additionalProperties: false - required: - - tool_responses - title: ResumeAgentTurnRequest - RunEvalRequest: - type: object - properties: - benchmark_config: - $ref: '#/components/schemas/BenchmarkConfig' - description: The configuration for the benchmark. - additionalProperties: false - required: - - benchmark_config - title: RunEvalRequest - RunModerationRequest: - type: object - properties: - input: - oneOf: - - type: string - - type: array - items: - type: string - description: >- - Input (or inputs) to classify. Can be a single string, an array of strings, - or an array of multi-modal input objects similar to other models. - model: - type: string - description: >- - The content moderation model you would like to use. - additionalProperties: false - required: - - input - - model - title: RunModerationRequest - ModerationObject: - type: object - properties: - id: - type: string - description: >- - The unique identifier for the moderation request. - model: - type: string - description: >- - The model used to generate the moderation results. - results: - type: array - items: - $ref: '#/components/schemas/ModerationObjectResults' - description: A list of moderation objects - additionalProperties: false - required: - - id - - model - - results - title: ModerationObject - description: A moderation object. - ModerationObjectResults: - type: object - properties: - flagged: - type: boolean - description: >- - Whether any of the below categories are flagged. - categories: - type: object - additionalProperties: - type: boolean - description: >- - A list of the categories, and whether they are flagged or not. - category_applied_input_types: - type: object - additionalProperties: - type: array - items: - type: string - description: >- - A list of the categories along with the input type(s) that the score applies - to. - category_scores: - type: object - additionalProperties: - type: number - description: >- - A list of the categories along with their scores as predicted by model. - user_message: - type: string - metadata: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - additionalProperties: false - required: - - flagged - - metadata - title: ModerationObjectResults - description: A moderation object. - RunShieldRequest: - type: object - properties: - shield_id: - type: string - description: The identifier of the shield to run. - messages: - type: array - items: - $ref: '#/components/schemas/Message' - description: The messages to run the shield on. - params: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The parameters of the shield. - additionalProperties: false - required: - - shield_id - - messages - - params - title: RunShieldRequest - RunShieldResponse: - type: object - properties: - violation: - $ref: '#/components/schemas/SafetyViolation' - description: >- - (Optional) Safety violation detected by the shield, if any - additionalProperties: false - title: RunShieldResponse - description: Response from running a safety shield. - SaveSpansToDatasetRequest: - type: object - properties: - attribute_filters: - type: array - items: - $ref: '#/components/schemas/QueryCondition' - description: >- - The attribute filters to apply to the spans. - attributes_to_save: - type: array - items: - type: string - description: The attributes to save to the dataset. - dataset_id: - type: string - description: >- - The ID of the dataset to save the spans to. - max_depth: - type: integer - description: The maximum depth of the tree. - additionalProperties: false - required: - - attribute_filters - - attributes_to_save - - dataset_id - title: SaveSpansToDatasetRequest - ScoreRequest: - type: object - properties: - input_rows: - type: array - items: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The rows to score. - scoring_functions: - type: object - additionalProperties: - oneOf: - - $ref: '#/components/schemas/ScoringFnParams' - - type: 'null' - description: >- - The scoring functions to use for the scoring. - additionalProperties: false - required: - - input_rows - - scoring_functions - title: ScoreRequest - ScoreResponse: - type: object - properties: - results: - type: object - additionalProperties: - $ref: '#/components/schemas/ScoringResult' - description: >- - A map of scoring function name to ScoringResult. - additionalProperties: false - required: - - results - title: ScoreResponse - description: The response from scoring. - ScoreBatchRequest: - type: object - properties: - dataset_id: - type: string - description: The ID of the dataset to score. - scoring_functions: - type: object - additionalProperties: - oneOf: - - $ref: '#/components/schemas/ScoringFnParams' - - type: 'null' - description: >- - The scoring functions to use for the scoring. - save_results_dataset: - type: boolean - description: >- - Whether to save the results to a dataset. - additionalProperties: false - required: - - dataset_id - - scoring_functions - - save_results_dataset - title: ScoreBatchRequest - ScoreBatchResponse: - type: object - properties: - dataset_id: - type: string - description: >- - (Optional) The identifier of the dataset that was scored - results: - type: object - additionalProperties: - $ref: '#/components/schemas/ScoringResult' - description: >- - A map of scoring function name to ScoringResult - additionalProperties: false - required: - - results - title: ScoreBatchResponse - description: >- - Response from batch scoring operations on datasets. - SetDefaultVersionRequest: - type: object - properties: - version: - type: integer - description: The version to set as default. - additionalProperties: false - required: - - version - title: SetDefaultVersionRequest - AlgorithmConfig: - oneOf: - - $ref: '#/components/schemas/LoraFinetuningConfig' - - $ref: '#/components/schemas/QATFinetuningConfig' - discriminator: - propertyName: type - mapping: - LoRA: '#/components/schemas/LoraFinetuningConfig' - QAT: '#/components/schemas/QATFinetuningConfig' - LoraFinetuningConfig: - type: object - properties: - type: - type: string - const: LoRA - default: LoRA - description: Algorithm type identifier, always "LoRA" - lora_attn_modules: - type: array - items: - type: string - description: >- - List of attention module names to apply LoRA to - apply_lora_to_mlp: - type: boolean - description: Whether to apply LoRA to MLP layers - apply_lora_to_output: - type: boolean - description: >- - Whether to apply LoRA to output projection layers - rank: - type: integer - description: >- - Rank of the LoRA adaptation (lower rank = fewer parameters) - alpha: - type: integer - description: >- - LoRA scaling parameter that controls adaptation strength - use_dora: - type: boolean - default: false - description: >- - (Optional) Whether to use DoRA (Weight-Decomposed Low-Rank Adaptation) - quantize_base: - type: boolean - default: false - description: >- - (Optional) Whether to quantize the base model weights - additionalProperties: false - required: - - type - - lora_attn_modules - - apply_lora_to_mlp - - apply_lora_to_output - - rank - - alpha - title: LoraFinetuningConfig - description: >- - Configuration for Low-Rank Adaptation (LoRA) fine-tuning. - QATFinetuningConfig: - type: object - properties: - type: - type: string - const: QAT - default: QAT - description: Algorithm type identifier, always "QAT" - quantizer_name: - type: string - description: >- - Name of the quantization algorithm to use - group_size: - type: integer - description: Size of groups for grouped quantization - additionalProperties: false - required: - - type - - quantizer_name - - group_size - title: QATFinetuningConfig - description: >- - Configuration for Quantization-Aware Training (QAT) fine-tuning. - SupervisedFineTuneRequest: - type: object - properties: - job_uuid: - type: string - description: The UUID of the job to create. - training_config: - $ref: '#/components/schemas/TrainingConfig' - description: The training configuration. - hyperparam_search_config: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The hyperparam search configuration. - logger_config: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: The logger configuration. - model: - type: string - description: The model to fine-tune. - checkpoint_dir: - type: string - description: The directory to save checkpoint(s) to. - algorithm_config: - $ref: '#/components/schemas/AlgorithmConfig' - description: The algorithm configuration. - additionalProperties: false - required: - - job_uuid - - training_config - - hyperparam_search_config - - logger_config - title: SupervisedFineTuneRequest - SyntheticDataGenerateRequest: - type: object - properties: - dialogs: - type: array - items: - $ref: '#/components/schemas/Message' - description: >- - List of conversation messages to use as input for synthetic data generation - filtering_function: - type: string - enum: - - none - - random - - top_k - - top_p - - top_k_top_p - - sigmoid - description: >- - Type of filtering to apply to generated synthetic data samples - model: - type: string - description: >- - (Optional) The identifier of the model to use. The model must be registered - with Llama Stack and available via the /models endpoint - additionalProperties: false - required: - - dialogs - - filtering_function - title: SyntheticDataGenerateRequest - SyntheticDataGenerationResponse: - type: object - properties: - synthetic_data: - type: array - items: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - List of generated synthetic data samples that passed the filtering criteria - statistics: - type: object - additionalProperties: - oneOf: - - type: 'null' - - type: boolean - - type: number - - type: string - - type: array - - type: object - description: >- - (Optional) Statistical information about the generation process and filtering - results - additionalProperties: false - required: - - synthetic_data - title: SyntheticDataGenerationResponse - description: >- - Response from the synthetic data generation. Batch of (prompt, response, score) - tuples that pass the threshold. - UpdatePromptRequest: - type: object - properties: - prompt: - type: string - description: The updated prompt text content. - version: - type: integer - description: >- - The current version of the prompt being updated. - variables: - type: array - items: - type: string - description: >- - Updated list of variable names that can be used in the prompt template. - set_as_default: - type: boolean - description: >- - Set the new version as the default (default=True). - additionalProperties: false - required: - - prompt - - version - - set_as_default - title: UpdatePromptRequest ->>>>>>> f7acfa0f (Add rerank API for NVIDIA Inference Provider) VersionInfo: type: object properties: diff --git a/llama_stack/core/routers/inference.py b/llama_stack/core/routers/inference.py index c1d4203c2..fcc16332f 100644 --- a/llama_stack/core/routers/inference.py +++ b/llama_stack/core/routers/inference.py @@ -201,7 +201,6 @@ class InferenceRouter(Inference): max_num_results=max_num_results, ) - async def openai_completion( self, model: str, diff --git a/tests/integration/fixtures/common.py b/tests/integration/fixtures/common.py index 8f4c564c8..dfbcf476d 100644 --- a/tests/integration/fixtures/common.py +++ b/tests/integration/fixtures/common.py @@ -181,7 +181,14 @@ def model_providers(llama_stack_client): @pytest.fixture(autouse=True) def skip_if_no_model(request): - model_fixtures = ["text_model_id", "vision_model_id", "embedding_model_id", "judge_model_id", "shield_id", "rerank_model_id"] + model_fixtures = [ + "text_model_id", + "vision_model_id", + "embedding_model_id", + "judge_model_id", + "shield_id", + "rerank_model_id", + ] test_func = request.node.function actual_params = inspect.signature(test_func).parameters.keys()