diff --git a/.github/workflows/integration-sql-store-tests.yml b/.github/workflows/integration-sql-store-tests.yml index 3efd970e1..47f6d546a 100644 --- a/.github/workflows/integration-sql-store-tests.yml +++ b/.github/workflows/integration-sql-store-tests.yml @@ -64,7 +64,7 @@ jobs: - name: Upload test logs if: ${{ always() }} - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 + uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0 with: name: postgres-test-logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ matrix.python-version }} path: | diff --git a/.github/workflows/integration-vector-io-tests.yml b/.github/workflows/integration-vector-io-tests.yml index a6a86b15f..ee837a159 100644 --- a/.github/workflows/integration-vector-io-tests.yml +++ b/.github/workflows/integration-vector-io-tests.yml @@ -194,7 +194,7 @@ jobs: - name: Upload all logs to artifacts if: ${{ always() }} - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 + uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0 with: name: vector-io-logs-${{ github.run_id }}-${{ github.run_attempt }}-${{ env.SANITIZED_PROVIDER }}-${{ matrix.python-version }} path: | diff --git a/.github/workflows/python-build-test.yml b/.github/workflows/python-build-test.yml index 96243285f..e36ea8780 100644 --- a/.github/workflows/python-build-test.yml +++ b/.github/workflows/python-build-test.yml @@ -24,7 +24,7 @@ jobs: uses: actions/checkout@08c6903cd8c0fde910a37f88322edcfb5dd907a8 # v5.0.0 - name: Install uv - uses: astral-sh/setup-uv@3259c6206f993105e3a61b142c2d97bf4b9ef83d # v7.1.0 + uses: astral-sh/setup-uv@2ddd2b9cb38ad8efd50337e8ab201519a34c9f24 # v7.1.1 with: python-version: ${{ matrix.python-version }} activate-environment: true diff --git a/.github/workflows/test-external-provider-module.yml b/.github/workflows/test-external-provider-module.yml index 21fedd06f..ded29dc8f 100644 --- a/.github/workflows/test-external-provider-module.yml +++ b/.github/workflows/test-external-provider-module.yml @@ -78,7 +78,7 @@ jobs: - name: Upload all logs to artifacts if: ${{ always() }} - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 + uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0 with: name: logs-${{ github.run_id }}-${{ github.run_attempt }}-external-provider-module-test path: | diff --git a/.github/workflows/test-external.yml b/.github/workflows/test-external.yml index 3ae6793ea..19cc2057d 100644 --- a/.github/workflows/test-external.yml +++ b/.github/workflows/test-external.yml @@ -84,7 +84,7 @@ jobs: - name: Upload all logs to artifacts if: ${{ always() }} - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 + uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0 with: name: logs-${{ github.run_id }}-${{ github.run_attempt }}-external-test path: | diff --git a/.github/workflows/unit-tests.yml b/.github/workflows/unit-tests.yml index dd2097a45..4c3b68624 100644 --- a/.github/workflows/unit-tests.yml +++ b/.github/workflows/unit-tests.yml @@ -45,7 +45,7 @@ jobs: - name: Upload test results if: always() - uses: actions/upload-artifact@ea165f8d65b6e75b540449e92b4886f43607fa02 # v4.6.2 + uses: actions/upload-artifact@330a01c490aca151604b8cf639adc76d48f6c5d4 # v5.0.0 with: name: test-results-${{ matrix.python }} path: | diff --git a/benchmarking/k8s-benchmark/stack-configmap.yaml b/benchmarking/k8s-benchmark/stack-configmap.yaml index e1ca170f5..8fbf09fce 100644 --- a/benchmarking/k8s-benchmark/stack-configmap.yaml +++ b/benchmarking/k8s-benchmark/stack-configmap.yaml @@ -44,14 +44,6 @@ data: db: ${env.POSTGRES_DB:=llamastack} user: ${env.POSTGRES_USER:=llamastack} password: ${env.POSTGRES_PASSWORD:=llamastack} - files: - - provider_id: meta-reference-files - provider_type: inline::localfs - config: - storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files} - metadata_store: - type: sqlite - db_path: ${env.SQLITE_STORE_DIR:=~/.llama/distributions/starter}/files_metadata.db safety: - provider_id: llama-guard provider_type: inline::llama-guard diff --git a/benchmarking/k8s-benchmark/stack_run_config.yaml b/benchmarking/k8s-benchmark/stack_run_config.yaml index 96907543a..88f4b0fef 100644 --- a/benchmarking/k8s-benchmark/stack_run_config.yaml +++ b/benchmarking/k8s-benchmark/stack_run_config.yaml @@ -36,14 +36,6 @@ providers: persistence: namespace: vector_io::chroma_remote backend: kv_default - files: - - provider_id: meta-reference-files - provider_type: inline::localfs - config: - storage_dir: ${env.FILES_STORAGE_DIR:=~/.llama/distributions/starter/files} - metadata_store: - table_name: files_metadata - backend: sql_default safety: - provider_id: llama-guard provider_type: inline::llama-guard diff --git a/client-sdks/stainless/openapi.yml b/client-sdks/stainless/openapi.yml index bd2d4b7a4..7b03cd03e 100644 --- a/client-sdks/stainless/openapi.yml +++ b/client-sdks/stainless/openapi.yml @@ -6735,14 +6735,9 @@ components: Error details for failed OpenAI response requests. OpenAIResponseInput: oneOf: - - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall' + - $ref: '#/components/schemas/OpenAIResponseOutput' - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput' - - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest' - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools' - $ref: '#/components/schemas/OpenAIResponseMessage' OpenAIResponseInputToolFileSearch: type: object @@ -11600,7 +11595,6 @@ components: description: The sampling strategy. max_tokens: type: integer - default: 0 description: >- The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's diff --git a/docs/static/deprecated-llama-stack-spec.html b/docs/static/deprecated-llama-stack-spec.html index 8bd8ecf3f..4ae6add60 100644 --- a/docs/static/deprecated-llama-stack-spec.html +++ b/docs/static/deprecated-llama-stack-spec.html @@ -3901,7 +3901,6 @@ }, "max_tokens": { "type": "integer", - "default": 0, "description": "The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length." }, "repetition_penalty": { @@ -8527,29 +8526,14 @@ "OpenAIResponseInput": { "oneOf": [ { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall" + "$ref": "#/components/schemas/OpenAIResponseOutput" }, { "$ref": "#/components/schemas/OpenAIResponseInputFunctionToolCallOutput" }, - { - "$ref": "#/components/schemas/OpenAIResponseMCPApprovalRequest" - }, { "$ref": "#/components/schemas/OpenAIResponseMCPApprovalResponse" }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPListTools" - }, { "$ref": "#/components/schemas/OpenAIResponseMessage" } diff --git a/docs/static/deprecated-llama-stack-spec.yaml b/docs/static/deprecated-llama-stack-spec.yaml index cd86239e8..3bcfde02e 100644 --- a/docs/static/deprecated-llama-stack-spec.yaml +++ b/docs/static/deprecated-llama-stack-spec.yaml @@ -2862,7 +2862,6 @@ components: description: The sampling strategy. max_tokens: type: integer - default: 0 description: >- The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's @@ -6370,14 +6369,9 @@ components: Error details for failed OpenAI response requests. OpenAIResponseInput: oneOf: - - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall' + - $ref: '#/components/schemas/OpenAIResponseOutput' - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput' - - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest' - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools' - $ref: '#/components/schemas/OpenAIResponseMessage' "OpenAIResponseInputFunctionToolCallOutput": type: object diff --git a/docs/static/experimental-llama-stack-spec.html b/docs/static/experimental-llama-stack-spec.html index ab474180e..2ad81d4f2 100644 --- a/docs/static/experimental-llama-stack-spec.html +++ b/docs/static/experimental-llama-stack-spec.html @@ -2376,7 +2376,6 @@ }, "max_tokens": { "type": "integer", - "default": 0, "description": "The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length." }, "repetition_penalty": { diff --git a/docs/static/experimental-llama-stack-spec.yaml b/docs/static/experimental-llama-stack-spec.yaml index dd9e43cc5..f15add8cf 100644 --- a/docs/static/experimental-llama-stack-spec.yaml +++ b/docs/static/experimental-llama-stack-spec.yaml @@ -1695,7 +1695,6 @@ components: description: The sampling strategy. max_tokens: type: integer - default: 0 description: >- The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's diff --git a/docs/static/llama-stack-spec.html b/docs/static/llama-stack-spec.html index d9dbe27c9..5d8b62db3 100644 --- a/docs/static/llama-stack-spec.html +++ b/docs/static/llama-stack-spec.html @@ -7305,29 +7305,14 @@ "OpenAIResponseInput": { "oneOf": [ { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall" + "$ref": "#/components/schemas/OpenAIResponseOutput" }, { "$ref": "#/components/schemas/OpenAIResponseInputFunctionToolCallOutput" }, - { - "$ref": "#/components/schemas/OpenAIResponseMCPApprovalRequest" - }, { "$ref": "#/components/schemas/OpenAIResponseMCPApprovalResponse" }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPListTools" - }, { "$ref": "#/components/schemas/OpenAIResponseMessage" } diff --git a/docs/static/llama-stack-spec.yaml b/docs/static/llama-stack-spec.yaml index 604a4eace..435520356 100644 --- a/docs/static/llama-stack-spec.yaml +++ b/docs/static/llama-stack-spec.yaml @@ -5522,14 +5522,9 @@ components: Error details for failed OpenAI response requests. OpenAIResponseInput: oneOf: - - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall' + - $ref: '#/components/schemas/OpenAIResponseOutput' - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput' - - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest' - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools' - $ref: '#/components/schemas/OpenAIResponseMessage' OpenAIResponseInputToolFileSearch: type: object diff --git a/docs/static/stainless-llama-stack-spec.html b/docs/static/stainless-llama-stack-spec.html index 687c35db8..2616a9917 100644 --- a/docs/static/stainless-llama-stack-spec.html +++ b/docs/static/stainless-llama-stack-spec.html @@ -8977,29 +8977,14 @@ "OpenAIResponseInput": { "oneOf": [ { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall" + "$ref": "#/components/schemas/OpenAIResponseOutput" }, { "$ref": "#/components/schemas/OpenAIResponseInputFunctionToolCallOutput" }, - { - "$ref": "#/components/schemas/OpenAIResponseMCPApprovalRequest" - }, { "$ref": "#/components/schemas/OpenAIResponseMCPApprovalResponse" }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPCall" - }, - { - "$ref": "#/components/schemas/OpenAIResponseOutputMessageMCPListTools" - }, { "$ref": "#/components/schemas/OpenAIResponseMessage" } @@ -15452,7 +15437,6 @@ }, "max_tokens": { "type": "integer", - "default": 0, "description": "The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's context length." }, "repetition_penalty": { diff --git a/docs/static/stainless-llama-stack-spec.yaml b/docs/static/stainless-llama-stack-spec.yaml index bd2d4b7a4..7b03cd03e 100644 --- a/docs/static/stainless-llama-stack-spec.yaml +++ b/docs/static/stainless-llama-stack-spec.yaml @@ -6735,14 +6735,9 @@ components: Error details for failed OpenAI response requests. OpenAIResponseInput: oneOf: - - $ref: '#/components/schemas/OpenAIResponseOutputMessageWebSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFileSearchToolCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageFunctionToolCall' + - $ref: '#/components/schemas/OpenAIResponseOutput' - $ref: '#/components/schemas/OpenAIResponseInputFunctionToolCallOutput' - - $ref: '#/components/schemas/OpenAIResponseMCPApprovalRequest' - $ref: '#/components/schemas/OpenAIResponseMCPApprovalResponse' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPCall' - - $ref: '#/components/schemas/OpenAIResponseOutputMessageMCPListTools' - $ref: '#/components/schemas/OpenAIResponseMessage' OpenAIResponseInputToolFileSearch: type: object @@ -11600,7 +11595,6 @@ components: description: The sampling strategy. max_tokens: type: integer - default: 0 description: >- The maximum number of tokens that can be generated in the completion. The token count of your prompt plus max_tokens cannot exceed the model's diff --git a/llama_stack/apis/agents/openai_responses.py b/llama_stack/apis/agents/openai_responses.py index 821d6a8af..d77948526 100644 --- a/llama_stack/apis/agents/openai_responses.py +++ b/llama_stack/apis/agents/openai_responses.py @@ -1254,14 +1254,9 @@ class OpenAIResponseInputFunctionToolCallOutput(BaseModel): OpenAIResponseInput = Annotated[ # Responses API allows output messages to be passed in as input - OpenAIResponseOutputMessageWebSearchToolCall - | OpenAIResponseOutputMessageFileSearchToolCall - | OpenAIResponseOutputMessageFunctionToolCall + OpenAIResponseOutput | OpenAIResponseInputFunctionToolCallOutput - | OpenAIResponseMCPApprovalRequest | OpenAIResponseMCPApprovalResponse - | OpenAIResponseOutputMessageMCPCall - | OpenAIResponseOutputMessageMCPListTools | OpenAIResponseMessage, Field(union_mode="left_to_right"), ] diff --git a/llama_stack/apis/inference/inference.py b/llama_stack/apis/inference/inference.py index 7dc565244..519fa0eb1 100644 --- a/llama_stack/apis/inference/inference.py +++ b/llama_stack/apis/inference/inference.py @@ -21,8 +21,8 @@ from typing_extensions import TypedDict from llama_stack.apis.common.content_types import ContentDelta, InterleavedContent from llama_stack.apis.common.responses import Order from llama_stack.apis.models import Model -from llama_stack.apis.telemetry import MetricResponseMixin from llama_stack.apis.version import LLAMA_STACK_API_V1, LLAMA_STACK_API_V1ALPHA +from llama_stack.core.telemetry.telemetry import MetricResponseMixin from llama_stack.core.telemetry.trace_protocol import trace_protocol from llama_stack.models.llama.datatypes import ( BuiltinTool, @@ -97,7 +97,7 @@ class SamplingParams(BaseModel): strategy: SamplingStrategy = Field(default_factory=GreedySamplingStrategy) - max_tokens: int | None = 0 + max_tokens: int | None = None repetition_penalty: float | None = 1.0 stop: list[str] | None = None diff --git a/llama_stack/apis/telemetry/__init__.py b/llama_stack/apis/telemetry/__init__.py deleted file mode 100644 index 1250767f7..000000000 --- a/llama_stack/apis/telemetry/__init__.py +++ /dev/null @@ -1,7 +0,0 @@ -# Copyright (c) Meta Platforms, Inc. and affiliates. -# All rights reserved. -# -# This source code is licensed under the terms described in the LICENSE file in -# the root directory of this source tree. - -from .telemetry import * diff --git a/llama_stack/apis/telemetry/telemetry.py b/llama_stack/apis/telemetry/telemetry.py deleted file mode 100644 index 53387639b..000000000 --- a/llama_stack/apis/telemetry/telemetry.py +++ /dev/null @@ -1,423 +0,0 @@ -# Copyright (c) Meta Platforms, Inc. and affiliates. -# All rights reserved. -# -# This source code is licensed under the terms described in the LICENSE file in -# the root directory of this source tree. - -from datetime import datetime -from enum import Enum -from typing import ( - Annotated, - Any, - Literal, - Protocol, - runtime_checkable, -) - -from pydantic import BaseModel, Field - -from llama_stack.models.llama.datatypes import Primitive -from llama_stack.schema_utils import json_schema_type, register_schema - -# Add this constant near the top of the file, after the imports -DEFAULT_TTL_DAYS = 7 - - -@json_schema_type -class SpanStatus(Enum): - """The status of a span indicating whether it completed successfully or with an error. - :cvar OK: Span completed successfully without errors - :cvar ERROR: Span completed with an error or failure - """ - - OK = "ok" - ERROR = "error" - - -@json_schema_type -class Span(BaseModel): - """A span representing a single operation within a trace. - :param span_id: Unique identifier for the span - :param trace_id: Unique identifier for the trace this span belongs to - :param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span - :param name: Human-readable name describing the operation this span represents - :param start_time: Timestamp when the operation began - :param end_time: (Optional) Timestamp when the operation finished, if completed - :param attributes: (Optional) Key-value pairs containing additional metadata about the span - """ - - span_id: str - trace_id: str - parent_span_id: str | None = None - name: str - start_time: datetime - end_time: datetime | None = None - attributes: dict[str, Any] | None = Field(default_factory=lambda: {}) - - def set_attribute(self, key: str, value: Any): - if self.attributes is None: - self.attributes = {} - self.attributes[key] = value - - -@json_schema_type -class Trace(BaseModel): - """A trace representing the complete execution path of a request across multiple operations. - :param trace_id: Unique identifier for the trace - :param root_span_id: Unique identifier for the root span that started this trace - :param start_time: Timestamp when the trace began - :param end_time: (Optional) Timestamp when the trace finished, if completed - """ - - trace_id: str - root_span_id: str - start_time: datetime - end_time: datetime | None = None - - -@json_schema_type -class EventType(Enum): - """The type of telemetry event being logged. - :cvar UNSTRUCTURED_LOG: A simple log message with severity level - :cvar STRUCTURED_LOG: A structured log event with typed payload data - :cvar METRIC: A metric measurement with value and unit - """ - - UNSTRUCTURED_LOG = "unstructured_log" - STRUCTURED_LOG = "structured_log" - METRIC = "metric" - - -@json_schema_type -class LogSeverity(Enum): - """The severity level of a log message. - :cvar VERBOSE: Detailed diagnostic information for troubleshooting - :cvar DEBUG: Debug information useful during development - :cvar INFO: General informational messages about normal operation - :cvar WARN: Warning messages about potentially problematic situations - :cvar ERROR: Error messages indicating failures that don't stop execution - :cvar CRITICAL: Critical error messages indicating severe failures - """ - - VERBOSE = "verbose" - DEBUG = "debug" - INFO = "info" - WARN = "warn" - ERROR = "error" - CRITICAL = "critical" - - -class EventCommon(BaseModel): - """Common fields shared by all telemetry events. - :param trace_id: Unique identifier for the trace this event belongs to - :param span_id: Unique identifier for the span this event belongs to - :param timestamp: Timestamp when the event occurred - :param attributes: (Optional) Key-value pairs containing additional metadata about the event - """ - - trace_id: str - span_id: str - timestamp: datetime - attributes: dict[str, Primitive] | None = Field(default_factory=lambda: {}) - - -@json_schema_type -class UnstructuredLogEvent(EventCommon): - """An unstructured log event containing a simple text message. - :param type: Event type identifier set to UNSTRUCTURED_LOG - :param message: The log message text - :param severity: The severity level of the log message - """ - - type: Literal[EventType.UNSTRUCTURED_LOG] = EventType.UNSTRUCTURED_LOG - message: str - severity: LogSeverity - - -@json_schema_type -class MetricEvent(EventCommon): - """A metric event containing a measured value. - :param type: Event type identifier set to METRIC - :param metric: The name of the metric being measured - :param value: The numeric value of the metric measurement - :param unit: The unit of measurement for the metric value - """ - - type: Literal[EventType.METRIC] = EventType.METRIC - metric: str # this would be an enum - value: int | float - unit: str - - -@json_schema_type -class MetricInResponse(BaseModel): - """A metric value included in API responses. - :param metric: The name of the metric - :param value: The numeric value of the metric - :param unit: (Optional) The unit of measurement for the metric value - """ - - metric: str - value: int | float - unit: str | None = None - - -# This is a short term solution to allow inference API to return metrics -# The ideal way to do this is to have a way for all response types to include metrics -# and all metric events logged to the telemetry API to be included with the response -# To do this, we will need to augment all response types with a metrics field. -# We have hit a blocker from stainless SDK that prevents us from doing this. -# The blocker is that if we were to augment the response types that have a data field -# in them like so -# class ListModelsResponse(BaseModel): -# metrics: Optional[List[MetricEvent]] = None -# data: List[Models] -# ... -# The client SDK will need to access the data by using a .data field, which is not -# ergonomic. Stainless SDK does support unwrapping the response type, but it -# requires that the response type to only have a single field. - -# We will need a way in the client SDK to signal that the metrics are needed -# and if they are needed, the client SDK has to return the full response type -# without unwrapping it. - - -class MetricResponseMixin(BaseModel): - """Mixin class for API responses that can include metrics. - :param metrics: (Optional) List of metrics associated with the API response - """ - - metrics: list[MetricInResponse] | None = None - - -@json_schema_type -class StructuredLogType(Enum): - """The type of structured log event payload. - :cvar SPAN_START: Event indicating the start of a new span - :cvar SPAN_END: Event indicating the completion of a span - """ - - SPAN_START = "span_start" - SPAN_END = "span_end" - - -@json_schema_type -class SpanStartPayload(BaseModel): - """Payload for a span start event. - :param type: Payload type identifier set to SPAN_START - :param name: Human-readable name describing the operation this span represents - :param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span - """ - - type: Literal[StructuredLogType.SPAN_START] = StructuredLogType.SPAN_START - name: str - parent_span_id: str | None = None - - -@json_schema_type -class SpanEndPayload(BaseModel): - """Payload for a span end event. - :param type: Payload type identifier set to SPAN_END - :param status: The final status of the span indicating success or failure - """ - - type: Literal[StructuredLogType.SPAN_END] = StructuredLogType.SPAN_END - status: SpanStatus - - -StructuredLogPayload = Annotated[ - SpanStartPayload | SpanEndPayload, - Field(discriminator="type"), -] -register_schema(StructuredLogPayload, name="StructuredLogPayload") - - -@json_schema_type -class StructuredLogEvent(EventCommon): - """A structured log event containing typed payload data. - :param type: Event type identifier set to STRUCTURED_LOG - :param payload: The structured payload data for the log event - """ - - type: Literal[EventType.STRUCTURED_LOG] = EventType.STRUCTURED_LOG - payload: StructuredLogPayload - - -Event = Annotated[ - UnstructuredLogEvent | MetricEvent | StructuredLogEvent, - Field(discriminator="type"), -] -register_schema(Event, name="Event") - - -@json_schema_type -class EvalTrace(BaseModel): - """A trace record for evaluation purposes. - :param session_id: Unique identifier for the evaluation session - :param step: The evaluation step or phase identifier - :param input: The input data for the evaluation - :param output: The actual output produced during evaluation - :param expected_output: The expected output for comparison during evaluation - """ - - session_id: str - step: str - input: str - output: str - expected_output: str - - -@json_schema_type -class SpanWithStatus(Span): - """A span that includes status information. - :param status: (Optional) The current status of the span - """ - - status: SpanStatus | None = None - - -@json_schema_type -class QueryConditionOp(Enum): - """Comparison operators for query conditions. - :cvar EQ: Equal to comparison - :cvar NE: Not equal to comparison - :cvar GT: Greater than comparison - :cvar LT: Less than comparison - """ - - EQ = "eq" - NE = "ne" - GT = "gt" - LT = "lt" - - -@json_schema_type -class QueryCondition(BaseModel): - """A condition for filtering query results. - :param key: The attribute key to filter on - :param op: The comparison operator to apply - :param value: The value to compare against - """ - - key: str - op: QueryConditionOp - value: Any - - -class QueryTracesResponse(BaseModel): - """Response containing a list of traces. - :param data: List of traces matching the query criteria - """ - - data: list[Trace] - - -class QuerySpansResponse(BaseModel): - """Response containing a list of spans. - :param data: List of spans matching the query criteria - """ - - data: list[Span] - - -class QuerySpanTreeResponse(BaseModel): - """Response containing a tree structure of spans. - :param data: Dictionary mapping span IDs to spans with status information - """ - - data: dict[str, SpanWithStatus] - - -class MetricQueryType(Enum): - """The type of metric query to perform. - :cvar RANGE: Query metrics over a time range - :cvar INSTANT: Query metrics at a specific point in time - """ - - RANGE = "range" - INSTANT = "instant" - - -class MetricLabelOperator(Enum): - """Operators for matching metric labels. - :cvar EQUALS: Label value must equal the specified value - :cvar NOT_EQUALS: Label value must not equal the specified value - :cvar REGEX_MATCH: Label value must match the specified regular expression - :cvar REGEX_NOT_MATCH: Label value must not match the specified regular expression - """ - - EQUALS = "=" - NOT_EQUALS = "!=" - REGEX_MATCH = "=~" - REGEX_NOT_MATCH = "!~" - - -class MetricLabelMatcher(BaseModel): - """A matcher for filtering metrics by label values. - :param name: The name of the label to match - :param value: The value to match against - :param operator: The comparison operator to use for matching - """ - - name: str - value: str - operator: MetricLabelOperator = MetricLabelOperator.EQUALS - - -@json_schema_type -class MetricLabel(BaseModel): - """A label associated with a metric. - :param name: The name of the label - :param value: The value of the label - """ - - name: str - value: str - - -@json_schema_type -class MetricDataPoint(BaseModel): - """A single data point in a metric time series. - :param timestamp: Unix timestamp when the metric value was recorded - :param value: The numeric value of the metric at this timestamp - """ - - timestamp: int - value: float - unit: str - - -@json_schema_type -class MetricSeries(BaseModel): - """A time series of metric data points. - :param metric: The name of the metric - :param labels: List of labels associated with this metric series - :param values: List of data points in chronological order - """ - - metric: str - labels: list[MetricLabel] - values: list[MetricDataPoint] - - -class QueryMetricsResponse(BaseModel): - """Response containing metric time series data. - :param data: List of metric series matching the query criteria - """ - - data: list[MetricSeries] - - -@runtime_checkable -class Telemetry(Protocol): - async def log_event( - self, - event: Event, - ttl_seconds: int = DEFAULT_TTL_DAYS * 86400, - ) -> None: - """Log an event. - - :param event: The event to log. - :param ttl_seconds: The time to live of the event. - """ - ... diff --git a/llama_stack/core/routers/inference.py b/llama_stack/core/routers/inference.py index d532bc622..dfd5e8e54 100644 --- a/llama_stack/core/routers/inference.py +++ b/llama_stack/core/routers/inference.py @@ -53,7 +53,7 @@ from llama_stack.apis.inference.inference import ( OpenAIChatCompletionContentPartTextParam, ) from llama_stack.apis.models import Model, ModelType -from llama_stack.apis.telemetry import MetricEvent, MetricInResponse +from llama_stack.core.telemetry.telemetry import MetricEvent, MetricInResponse from llama_stack.core.telemetry.tracing import enqueue_event, get_current_span from llama_stack.log import get_logger from llama_stack.models.llama.llama3.chat_format import ChatFormat diff --git a/llama_stack/core/stack.py b/llama_stack/core/stack.py index ebfd59a05..92a62f3ef 100644 --- a/llama_stack/core/stack.py +++ b/llama_stack/core/stack.py @@ -31,7 +31,6 @@ from llama_stack.apis.scoring import Scoring from llama_stack.apis.scoring_functions import ScoringFunctions from llama_stack.apis.shields import Shields from llama_stack.apis.synthetic_data_generation import SyntheticDataGeneration -from llama_stack.apis.telemetry import Telemetry from llama_stack.apis.tools import RAGToolRuntime, ToolGroups, ToolRuntime from llama_stack.apis.vector_io import VectorIO from llama_stack.core.conversations.conversations import ConversationServiceConfig, ConversationServiceImpl @@ -67,7 +66,6 @@ class LlamaStack( Safety, SyntheticDataGeneration, Datasets, - Telemetry, PostTraining, VectorIO, Eval, diff --git a/llama_stack/core/telemetry/telemetry.py b/llama_stack/core/telemetry/telemetry.py index f0cec08ec..dbd10e89c 100644 --- a/llama_stack/core/telemetry/telemetry.py +++ b/llama_stack/core/telemetry/telemetry.py @@ -6,7 +6,13 @@ import os import threading -from typing import Any +from datetime import datetime +from enum import Enum +from typing import ( + Annotated, + Any, + Literal, +) from opentelemetry import metrics, trace from opentelemetry.exporter.otlp.proto.http.metric_exporter import OTLPMetricExporter @@ -16,21 +22,399 @@ from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader from opentelemetry.sdk.trace import TracerProvider from opentelemetry.sdk.trace.export import BatchSpanProcessor from opentelemetry.trace.propagation.tracecontext import TraceContextTextMapPropagator +from pydantic import BaseModel, Field -from llama_stack.apis.telemetry import ( - Event, - MetricEvent, - SpanEndPayload, - SpanStartPayload, - SpanStatus, - StructuredLogEvent, - UnstructuredLogEvent, -) -from llama_stack.apis.telemetry import ( - Telemetry as TelemetryBase, -) -from llama_stack.core.telemetry.tracing import ROOT_SPAN_MARKERS from llama_stack.log import get_logger +from llama_stack.models.llama.datatypes import Primitive +from llama_stack.schema_utils import json_schema_type, register_schema + +ROOT_SPAN_MARKERS = ["__root__", "__root_span__"] + + +@json_schema_type +class SpanStatus(Enum): + """The status of a span indicating whether it completed successfully or with an error. + :cvar OK: Span completed successfully without errors + :cvar ERROR: Span completed with an error or failure + """ + + OK = "ok" + ERROR = "error" + + +@json_schema_type +class Span(BaseModel): + """A span representing a single operation within a trace. + :param span_id: Unique identifier for the span + :param trace_id: Unique identifier for the trace this span belongs to + :param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span + :param name: Human-readable name describing the operation this span represents + :param start_time: Timestamp when the operation began + :param end_time: (Optional) Timestamp when the operation finished, if completed + :param attributes: (Optional) Key-value pairs containing additional metadata about the span + """ + + span_id: str + trace_id: str + parent_span_id: str | None = None + name: str + start_time: datetime + end_time: datetime | None = None + attributes: dict[str, Any] | None = Field(default_factory=lambda: {}) + + def set_attribute(self, key: str, value: Any): + if self.attributes is None: + self.attributes = {} + self.attributes[key] = value + + +@json_schema_type +class Trace(BaseModel): + """A trace representing the complete execution path of a request across multiple operations. + :param trace_id: Unique identifier for the trace + :param root_span_id: Unique identifier for the root span that started this trace + :param start_time: Timestamp when the trace began + :param end_time: (Optional) Timestamp when the trace finished, if completed + """ + + trace_id: str + root_span_id: str + start_time: datetime + end_time: datetime | None = None + + +@json_schema_type +class EventType(Enum): + """The type of telemetry event being logged. + :cvar UNSTRUCTURED_LOG: A simple log message with severity level + :cvar STRUCTURED_LOG: A structured log event with typed payload data + :cvar METRIC: A metric measurement with value and unit + """ + + UNSTRUCTURED_LOG = "unstructured_log" + STRUCTURED_LOG = "structured_log" + METRIC = "metric" + + +@json_schema_type +class LogSeverity(Enum): + """The severity level of a log message. + :cvar VERBOSE: Detailed diagnostic information for troubleshooting + :cvar DEBUG: Debug information useful during development + :cvar INFO: General informational messages about normal operation + :cvar WARN: Warning messages about potentially problematic situations + :cvar ERROR: Error messages indicating failures that don't stop execution + :cvar CRITICAL: Critical error messages indicating severe failures + """ + + VERBOSE = "verbose" + DEBUG = "debug" + INFO = "info" + WARN = "warn" + ERROR = "error" + CRITICAL = "critical" + + +class EventCommon(BaseModel): + """Common fields shared by all telemetry events. + :param trace_id: Unique identifier for the trace this event belongs to + :param span_id: Unique identifier for the span this event belongs to + :param timestamp: Timestamp when the event occurred + :param attributes: (Optional) Key-value pairs containing additional metadata about the event + """ + + trace_id: str + span_id: str + timestamp: datetime + attributes: dict[str, Primitive] | None = Field(default_factory=lambda: {}) + + +@json_schema_type +class UnstructuredLogEvent(EventCommon): + """An unstructured log event containing a simple text message. + :param type: Event type identifier set to UNSTRUCTURED_LOG + :param message: The log message text + :param severity: The severity level of the log message + """ + + type: Literal[EventType.UNSTRUCTURED_LOG] = EventType.UNSTRUCTURED_LOG + message: str + severity: LogSeverity + + +@json_schema_type +class MetricEvent(EventCommon): + """A metric event containing a measured value. + :param type: Event type identifier set to METRIC + :param metric: The name of the metric being measured + :param value: The numeric value of the metric measurement + :param unit: The unit of measurement for the metric value + """ + + type: Literal[EventType.METRIC] = EventType.METRIC + metric: str # this would be an enum + value: int | float + unit: str + + +@json_schema_type +class MetricInResponse(BaseModel): + """A metric value included in API responses. + :param metric: The name of the metric + :param value: The numeric value of the metric + :param unit: (Optional) The unit of measurement for the metric value + """ + + metric: str + value: int | float + unit: str | None = None + + +# This is a short term solution to allow inference API to return metrics +# The ideal way to do this is to have a way for all response types to include metrics +# and all metric events logged to the telemetry API to be included with the response +# To do this, we will need to augment all response types with a metrics field. +# We have hit a blocker from stainless SDK that prevents us from doing this. +# The blocker is that if we were to augment the response types that have a data field +# in them like so +# class ListModelsResponse(BaseModel): +# metrics: Optional[List[MetricEvent]] = None +# data: List[Models] +# ... +# The client SDK will need to access the data by using a .data field, which is not +# ergonomic. Stainless SDK does support unwrapping the response type, but it +# requires that the response type to only have a single field. + +# We will need a way in the client SDK to signal that the metrics are needed +# and if they are needed, the client SDK has to return the full response type +# without unwrapping it. + + +class MetricResponseMixin(BaseModel): + """Mixin class for API responses that can include metrics. + :param metrics: (Optional) List of metrics associated with the API response + """ + + metrics: list[MetricInResponse] | None = None + + +@json_schema_type +class StructuredLogType(Enum): + """The type of structured log event payload. + :cvar SPAN_START: Event indicating the start of a new span + :cvar SPAN_END: Event indicating the completion of a span + """ + + SPAN_START = "span_start" + SPAN_END = "span_end" + + +@json_schema_type +class SpanStartPayload(BaseModel): + """Payload for a span start event. + :param type: Payload type identifier set to SPAN_START + :param name: Human-readable name describing the operation this span represents + :param parent_span_id: (Optional) Unique identifier for the parent span, if this is a child span + """ + + type: Literal[StructuredLogType.SPAN_START] = StructuredLogType.SPAN_START + name: str + parent_span_id: str | None = None + + +@json_schema_type +class SpanEndPayload(BaseModel): + """Payload for a span end event. + :param type: Payload type identifier set to SPAN_END + :param status: The final status of the span indicating success or failure + """ + + type: Literal[StructuredLogType.SPAN_END] = StructuredLogType.SPAN_END + status: SpanStatus + + +StructuredLogPayload = Annotated[ + SpanStartPayload | SpanEndPayload, + Field(discriminator="type"), +] +register_schema(StructuredLogPayload, name="StructuredLogPayload") + + +@json_schema_type +class StructuredLogEvent(EventCommon): + """A structured log event containing typed payload data. + :param type: Event type identifier set to STRUCTURED_LOG + :param payload: The structured payload data for the log event + """ + + type: Literal[EventType.STRUCTURED_LOG] = EventType.STRUCTURED_LOG + payload: StructuredLogPayload + + +Event = Annotated[ + UnstructuredLogEvent | MetricEvent | StructuredLogEvent, + Field(discriminator="type"), +] +register_schema(Event, name="Event") + + +@json_schema_type +class EvalTrace(BaseModel): + """A trace record for evaluation purposes. + :param session_id: Unique identifier for the evaluation session + :param step: The evaluation step or phase identifier + :param input: The input data for the evaluation + :param output: The actual output produced during evaluation + :param expected_output: The expected output for comparison during evaluation + """ + + session_id: str + step: str + input: str + output: str + expected_output: str + + +@json_schema_type +class SpanWithStatus(Span): + """A span that includes status information. + :param status: (Optional) The current status of the span + """ + + status: SpanStatus | None = None + + +@json_schema_type +class QueryConditionOp(Enum): + """Comparison operators for query conditions. + :cvar EQ: Equal to comparison + :cvar NE: Not equal to comparison + :cvar GT: Greater than comparison + :cvar LT: Less than comparison + """ + + EQ = "eq" + NE = "ne" + GT = "gt" + LT = "lt" + + +@json_schema_type +class QueryCondition(BaseModel): + """A condition for filtering query results. + :param key: The attribute key to filter on + :param op: The comparison operator to apply + :param value: The value to compare against + """ + + key: str + op: QueryConditionOp + value: Any + + +class QueryTracesResponse(BaseModel): + """Response containing a list of traces. + :param data: List of traces matching the query criteria + """ + + data: list[Trace] + + +class QuerySpansResponse(BaseModel): + """Response containing a list of spans. + :param data: List of spans matching the query criteria + """ + + data: list[Span] + + +class QuerySpanTreeResponse(BaseModel): + """Response containing a tree structure of spans. + :param data: Dictionary mapping span IDs to spans with status information + """ + + data: dict[str, SpanWithStatus] + + +class MetricQueryType(Enum): + """The type of metric query to perform. + :cvar RANGE: Query metrics over a time range + :cvar INSTANT: Query metrics at a specific point in time + """ + + RANGE = "range" + INSTANT = "instant" + + +class MetricLabelOperator(Enum): + """Operators for matching metric labels. + :cvar EQUALS: Label value must equal the specified value + :cvar NOT_EQUALS: Label value must not equal the specified value + :cvar REGEX_MATCH: Label value must match the specified regular expression + :cvar REGEX_NOT_MATCH: Label value must not match the specified regular expression + """ + + EQUALS = "=" + NOT_EQUALS = "!=" + REGEX_MATCH = "=~" + REGEX_NOT_MATCH = "!~" + + +class MetricLabelMatcher(BaseModel): + """A matcher for filtering metrics by label values. + :param name: The name of the label to match + :param value: The value to match against + :param operator: The comparison operator to use for matching + """ + + name: str + value: str + operator: MetricLabelOperator = MetricLabelOperator.EQUALS + + +@json_schema_type +class MetricLabel(BaseModel): + """A label associated with a metric. + :param name: The name of the label + :param value: The value of the label + """ + + name: str + value: str + + +@json_schema_type +class MetricDataPoint(BaseModel): + """A single data point in a metric time series. + :param timestamp: Unix timestamp when the metric value was recorded + :param value: The numeric value of the metric at this timestamp + """ + + timestamp: int + value: float + unit: str + + +@json_schema_type +class MetricSeries(BaseModel): + """A time series of metric data points. + :param metric: The name of the metric + :param labels: List of labels associated with this metric series + :param values: List of data points in chronological order + """ + + metric: str + labels: list[MetricLabel] + values: list[MetricDataPoint] + + +class QueryMetricsResponse(BaseModel): + """Response containing metric time series data. + :param data: List of metric series matching the query criteria + """ + + data: list[MetricSeries] + _GLOBAL_STORAGE: dict[str, dict[str | int, Any]] = { "active_spans": {}, @@ -49,7 +433,7 @@ def is_tracing_enabled(tracer): return span.is_recording() -class Telemetry(TelemetryBase): +class Telemetry: def __init__(self) -> None: self.meter = None diff --git a/llama_stack/core/telemetry/tracing.py b/llama_stack/core/telemetry/tracing.py index 7742ea0f4..a67cbe784 100644 --- a/llama_stack/core/telemetry/tracing.py +++ b/llama_stack/core/telemetry/tracing.py @@ -17,7 +17,8 @@ from datetime import UTC, datetime from functools import wraps from typing import Any, Self -from llama_stack.apis.telemetry import ( +from llama_stack.core.telemetry.telemetry import ( + ROOT_SPAN_MARKERS, Event, LogSeverity, Span, @@ -47,7 +48,6 @@ if not _fallback_logger.handlers: INVALID_SPAN_ID = 0x0000000000000000 INVALID_TRACE_ID = 0x00000000000000000000000000000000 -ROOT_SPAN_MARKERS = ["__root__", "__root_span__"] # The logical root span may not be visible to this process if a parent context # is passed in. The local root span is the first local span in a trace. LOCAL_ROOT_SPAN_MARKER = "__local_root_span__" diff --git a/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py b/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py index f0bafff21..093643bac 100644 --- a/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py +++ b/llama_stack/providers/inline/agents/meta_reference/responses/streaming.py @@ -217,7 +217,9 @@ class StreamingResponseOrchestrator: while True: # Text is the default response format for chat completion so don't need to pass it # (some providers don't support non-empty response_format when tools are present) - response_format = None if self.ctx.response_format.type == "text" else self.ctx.response_format + response_format = ( + None if getattr(self.ctx.response_format, "type", None) == "text" else self.ctx.response_format + ) logger.debug(f"calling openai_chat_completion with tools: {self.ctx.chat_tools}") params = OpenAIChatCompletionRequestWithExtraBody( diff --git a/llama_stack/ui/package-lock.json b/llama_stack/ui/package-lock.json index 8e93fc5ab..09285f2d4 100644 --- a/llama_stack/ui/package-lock.json +++ b/llama_stack/ui/package-lock.json @@ -36,7 +36,7 @@ "@eslint/eslintrc": "^3", "@tailwindcss/postcss": "^4", "@testing-library/dom": "^10.4.1", - 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First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-007a9180a7aa", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 414, + "total_tokens": 416, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/0275b5b0278c3188f5530957d25d7eb8ab8a9a14c0b9b31d9a70ad342b02353d.json b/tests/integration/agents/recordings/0275b5b0278c3188f5530957d25d7eb8ab8a9a14c0b9b31d9a70ad342b02353d.json new file mode 100644 index 000000000..dc4f9f6d9 --- /dev/null +++ b/tests/integration/agents/recordings/0275b5b0278c3188f5530957d25d7eb8ab8a9a14c0b9b31d9a70ad342b02353d.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to materials, such as films, television shows, video games, or\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-0275b5b0278c", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 402, + "total_tokens": 404, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/042da9b89effc00fd0b794b9ae8066633f8f6d9797f5c082a7100d9a1fea81a3.json b/tests/integration/agents/recordings/042da9b89effc00fd0b794b9ae8066633f8f6d9797f5c082a7100d9a1fea81a3.json new file mode 100644 index 000000000..558311149 --- /dev/null +++ b/tests/integration/agents/recordings/042da9b89effc00fd0b794b9ae8066633f8f6d9797f5c082a7100d9a1fea81a3.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to materials, such as films\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - 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This type of content can be sensationalized, graphic, or realistic, and may not necessarily promote or\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - First line must read 'safe' or 'unsafe'.\n - If unsafe, a second line must include a comma-separated list of violated categories." + } + ], + "stream": false, + "temperature": 0.0 + }, + "endpoint": "/v1/chat/completions", + "model": "llama-guard3:1b" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-fd553c8a8897", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "safe", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama-guard3:1b", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 2, + "prompt_tokens": 440, + "total_tokens": 442, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/agents/recordings/ff2acaf7fbb3ac4363566533fb3c19ce56234c5d1fea4aa9db7d69d47c748206.json b/tests/integration/agents/recordings/ff2acaf7fbb3ac4363566533fb3c19ce56234c5d1fea4aa9db7d69d47c748206.json new file mode 100644 index 000000000..408061e74 --- /dev/null +++ b/tests/integration/agents/recordings/ff2acaf7fbb3ac4363566533fb3c19ce56234c5d1fea4aa9db7d69d47c748206.json @@ -0,0 +1,59 @@ +{ + "test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_guardrails_unsafe_content[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama-guard3:1b", + "messages": [ + { + "role": "user", + "content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n\nS1: Violent Crimes.\nS2: Non-Violent Crimes.\nS3: Sex Crimes.\nS4: Child Exploitation.\nS5: Defamation.\nS6: Specialized Advice.\nS7: Privacy.\nS8: Intellectual Property.\nS9: Indiscriminate Weapons.\nS10: Hate.\nS11: Self-Harm.\nS12: Sexual Content.\nS13: Elections.\nS14: Code Interpreter Abuse.\n\n\n\n\nUser: Violent content refers to materials, such as films, television shows, video games, or literature, that depict\n\n\n\nProvide your safety assessment for ONLY THE LAST User message in the above conversation:\n - 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# For replay tests, only use providers that are available in ci-tests environment - if os.environ.get("LLAMA_STACK_TEST_INFERENCE_MODE") == "replay": + # For CI tests (replay/record), only use providers that are available in ci-tests environment + if os.environ.get("LLAMA_STACK_TEST_INFERENCE_MODE") in ("replay", "record"): all_providers = ["faiss", "sqlite-vec"] else: # For live tests, try all providers (they'll skip if not available) diff --git a/tests/integration/eval/recordings/0a2ea52bcc4c7e04d0b4b844ad94bed06bcbaa03d13b228f61e2b36e23093469.json b/tests/integration/eval/recordings/0a2ea52bcc4c7e04d0b4b844ad94bed06bcbaa03d13b228f61e2b36e23093469.json new file mode 100644 index 000000000..b84e2e6f2 --- /dev/null +++ b/tests/integration/eval/recordings/0a2ea52bcc4c7e04d0b4b844ad94bed06bcbaa03d13b228f61e2b36e23093469.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_benchmark[txt=ollama/llama3.2:3b-instruct-fp16-basic::subset_of]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the largest planet in our solar system?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-0a2ea52bcc4c", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "The largest planet in our solar system is Jupiter. It is a gas giant and is approximately 1,421 times the size of Earth.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 29, + "prompt_tokens": 35, + "total_tokens": 64, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/recordings/58177cd1c0d7d8de9e20515c3e8fe465b66d8436754b30ff4da28c7c03c094a4.json b/tests/integration/eval/recordings/58177cd1c0d7d8de9e20515c3e8fe465b66d8436754b30ff4da28c7c03c094a4.json new file mode 100644 index 000000000..df2f664e7 --- /dev/null +++ b/tests/integration/eval/recordings/58177cd1c0d7d8de9e20515c3e8fe465b66d8436754b30ff4da28c7c03c094a4.json @@ -0,0 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"http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the capital of France?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-752abf1ef7f7", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "The capital of France is Paris.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 8, + "prompt_tokens": 32, + "total_tokens": 40, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/recordings/94e3d8dba56da92e1014a6ee81b61fe8e95d98692c189e7308724338f918678d.json b/tests/integration/eval/recordings/94e3d8dba56da92e1014a6ee81b61fe8e95d98692c189e7308724338f918678d.json new file mode 100644 index 000000000..ae2fe160c --- /dev/null +++ b/tests/integration/eval/recordings/94e3d8dba56da92e1014a6ee81b61fe8e95d98692c189e7308724338f918678d.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_benchmark[txt=ollama/llama3.2:3b-instruct-fp16-basic::subset_of]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the capital of France?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": 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b/tests/integration/eval/recordings/bf6b37511a044df8ad1c6113d3936b1e7f4a9d4f7f8ba8bd844d50265067f417.json new file mode 100644 index 000000000..022d45dce --- /dev/null +++ b/tests/integration/eval/recordings/bf6b37511a044df8ad1c6113d3936b1e7f4a9d4f7f8ba8bd844d50265067f417.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_benchmark[txt=ollama/llama3.2:3b-instruct-fp16-basic::subset_of]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the smallest country in the world?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-bf6b37511a04", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "The smallest country in the world is the Vatican City, which has an area of approximately 0.44 km\u00b2 (0.17 sq mi). It is an independent city-state located within Rome, Italy, and is home to the Pope and the central government of the Catholic Church.\n\nTo put that size into perspective, the Vatican City is:\n\n* Smaller than a typical American football field\n* Larger than a standard tennis court\n* About 1/44th the size of the island of Gibraltar\n\nDespite its tiny size, the Vatican City has its own government, currency, postal system, and even a small army (the Pontifical Swiss Guard). It is recognized as a sovereign state by over 180 countries around the world.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 150, + "prompt_tokens": 34, + "total_tokens": 184, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/recordings/c4ef767672c890e77ceaa15b6239e9d5a9a5ad6ee7bcad0b12853979b1e43ede.json b/tests/integration/eval/recordings/c4ef767672c890e77ceaa15b6239e9d5a9a5ad6ee7bcad0b12853979b1e43ede.json new file mode 100644 index 000000000..abea3f50e --- /dev/null +++ b/tests/integration/eval/recordings/c4ef767672c890e77ceaa15b6239e9d5a9a5ad6ee7bcad0b12853979b1e43ede.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_benchmark[txt=ollama/llama3.2:3b-instruct-fp16-basic::subset_of]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the currency of Japan?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-c4ef767672c8", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "The currency of Japan is the Japanese yen (\u00a5). It is denoted by the symbol \u00a5 and its ISO code is JPY.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 28, + "prompt_tokens": 32, + "total_tokens": 60, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/recordings/cbf92825593fd79fe76e0ad0193ebe742743cd3042654efefa86714e357b86f6.json b/tests/integration/eval/recordings/cbf92825593fd79fe76e0ad0193ebe742743cd3042654efefa86714e357b86f6.json new file mode 100644 index 000000000..10434cbf4 --- /dev/null +++ b/tests/integration/eval/recordings/cbf92825593fd79fe76e0ad0193ebe742743cd3042654efefa86714e357b86f6.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_rows[txt=ollama/llama3.2:3b-instruct-fp16-basic::equality]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "What is the largest planet in our solar system?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-cbf92825593f", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "The largest planet in our solar system is Jupiter. It has a diameter of approximately 142,984 kilometers (88,846 miles) and makes up about 2.5 times the mass of all the other planets in our solar system combined.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 50, + "prompt_tokens": 35, + "total_tokens": 85, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/recordings/dcf3c9afad420e66c3cc7434a48169a1235798c2b3ad9abbb29acf1f1b2952fa.json b/tests/integration/eval/recordings/dcf3c9afad420e66c3cc7434a48169a1235798c2b3ad9abbb29acf1f1b2952fa.json new file mode 100644 index 000000000..92d07571b --- /dev/null +++ b/tests/integration/eval/recordings/dcf3c9afad420e66c3cc7434a48169a1235798c2b3ad9abbb29acf1f1b2952fa.json @@ -0,0 +1,58 @@ +{ + "test_id": "tests/integration/eval/test_eval.py::test_evaluate_rows[txt=ollama/llama3.2:3b-instruct-fp16-basic::equality]", + "request": { + "method": "POST", + "url": "http://0.0.0.0:11434/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "llama3.2:3b-instruct-fp16", + "messages": [ + { + "role": "user", + "content": "Who is the CEO of Meta?" + } + ], + "max_tokens": 512 + }, + "endpoint": "/v1/chat/completions", + "model": "llama3.2:3b-instruct-fp16" + }, + "response": { + "body": { + "__type__": "openai.types.chat.chat_completion.ChatCompletion", + "__data__": { + "id": "rec-dcf3c9afad42", + "choices": [ + { + "finish_reason": "stop", + "index": 0, + "logprobs": null, + "message": { + "content": "Mark Zuckerberg is the founder, chairman and CEO of Meta, which he originally founded as Facebook in 2004.", + "refusal": null, + "role": "assistant", + "annotations": null, + "audio": null, + "function_call": null, + "tool_calls": null + } + } + ], + "created": 0, + "model": "llama3.2:3b-instruct-fp16", + "object": "chat.completion", + "service_tier": null, + "system_fingerprint": "fp_ollama", + "usage": { + "completion_tokens": 24, + "prompt_tokens": 32, + "total_tokens": 56, + "completion_tokens_details": null, + "prompt_tokens_details": null + } + } + }, + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/integration/eval/test_eval.py b/tests/integration/eval/test_eval.py index 98b3302e0..e042008dd 100644 --- a/tests/integration/eval/test_eval.py +++ b/tests/integration/eval/test_eval.py @@ -55,6 +55,7 @@ def test_evaluate_rows(llama_stack_client, text_model_id, scoring_fn_id): "model": text_model_id, "sampling_params": { "temperature": 0.0, + "max_tokens": 512, }, }, }, @@ -88,6 +89,7 @@ def test_evaluate_benchmark(llama_stack_client, text_model_id, scoring_fn_id): "model": text_model_id, "sampling_params": { "temperature": 0.0, + "max_tokens": 512, }, }, }, diff --git a/tests/unit/providers/agents/meta_reference/test_openai_responses.py b/tests/unit/providers/agents/meta_reference/test_openai_responses.py index f31ec0c28..ba914d808 100644 --- a/tests/unit/providers/agents/meta_reference/test_openai_responses.py +++ b/tests/unit/providers/agents/meta_reference/test_openai_responses.py @@ -24,6 +24,7 @@ from llama_stack.apis.agents.openai_responses import ( OpenAIResponseInputToolWebSearch, OpenAIResponseMessage, OpenAIResponseOutputMessageContentOutputText, + OpenAIResponseOutputMessageFunctionToolCall, OpenAIResponseOutputMessageMCPCall, OpenAIResponseOutputMessageWebSearchToolCall, OpenAIResponseText, @@ -1169,3 +1170,75 @@ async def test_create_openai_response_with_invalid_text_format(openai_responses_ model=model, text=OpenAIResponseText(format={"type": "invalid"}), ) + + +async def test_create_openai_response_with_output_types_as_input( + openai_responses_impl, mock_inference_api, mock_responses_store +): + """Test that response outputs can be used as inputs in multi-turn conversations. + + Before adding OpenAIResponseOutput types to OpenAIResponseInput, + creating a _OpenAIResponseObjectWithInputAndMessages with some output types + in the input field would fail with a Pydantic ValidationError. + + This test simulates storing a response where the input contains output message + types (MCP calls, function calls), which happens in multi-turn conversations. + """ + model = "meta-llama/Llama-3.1-8B-Instruct" + + # Mock the inference response + mock_inference_api.openai_chat_completion.return_value = fake_stream() + + # Create a response with store=True to trigger the storage path + result = await openai_responses_impl.create_openai_response( + input="What's the weather?", + model=model, + stream=True, + temperature=0.1, + store=True, + ) + + # Consume the stream + _ = [chunk async for chunk in result] + + # Verify store was called + assert mock_responses_store.store_response_object.called + + # Get the stored data + store_call_args = mock_responses_store.store_response_object.call_args + stored_response = store_call_args.kwargs["response_object"] + + # Now simulate a multi-turn conversation where outputs become inputs + input_with_output_types = [ + OpenAIResponseMessage(role="user", content="What's the weather?", name=None), + # These output types need to be valid OpenAIResponseInput + OpenAIResponseOutputMessageFunctionToolCall( + call_id="call_123", + name="get_weather", + arguments='{"city": "Tokyo"}', + type="function_call", + ), + OpenAIResponseOutputMessageMCPCall( + id="mcp_456", + type="mcp_call", + server_label="weather_server", + name="get_temperature", + arguments='{"location": "Tokyo"}', + output="25°C", + ), + ] + + # This simulates storing a response in a multi-turn conversation + # where previous outputs are included in the input. + stored_with_outputs = _OpenAIResponseObjectWithInputAndMessages( + id=stored_response.id, + created_at=stored_response.created_at, + model=stored_response.model, + status=stored_response.status, + output=stored_response.output, + input=input_with_output_types, # This will trigger Pydantic validation + messages=None, + ) + + assert stored_with_outputs.input == input_with_output_types + assert len(stored_with_outputs.input) == 3