mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-12-16 22:22:37 +00:00
address comments
This commit is contained in:
Swapna Lekkala
parent
c66757ea4d
commit
0efdc46d89
25 changed files with 1251 additions and 77 deletions
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@ -34,7 +34,6 @@ from llama_stack.apis.conversations import Conversations
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from llama_stack.apis.conversations.conversations import ConversationItem
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from llama_stack.apis.conversations.conversations import ConversationItem
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from llama_stack.apis.inference import (
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from llama_stack.apis.inference import (
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Inference,
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Inference,
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Message,
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OpenAIMessageParam,
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OpenAIMessageParam,
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OpenAISystemMessageParam,
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OpenAISystemMessageParam,
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)
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)
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@ -47,7 +46,6 @@ from llama_stack.providers.utils.responses.responses_store import (
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_OpenAIResponseObjectWithInputAndMessages,
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_OpenAIResponseObjectWithInputAndMessages,
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)
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)
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from ..safety import SafetyException
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from .streaming import StreamingResponseOrchestrator
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from .streaming import StreamingResponseOrchestrator
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from .tool_executor import ToolExecutor
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from .tool_executor import ToolExecutor
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from .types import ChatCompletionContext, ToolContext
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from .types import ChatCompletionContext, ToolContext
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@ -55,7 +53,6 @@ from .utils import (
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convert_response_input_to_chat_messages,
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convert_response_input_to_chat_messages,
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convert_response_text_to_chat_response_format,
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convert_response_text_to_chat_response_format,
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extract_shield_ids,
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extract_shield_ids,
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run_multiple_shields,
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)
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)
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logger = get_logger(name=__name__, category="openai_responses")
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logger = get_logger(name=__name__, category="openai_responses")
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@ -297,18 +294,6 @@ class OpenAIResponsesImpl:
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raise ValueError("The response stream never reached a terminal state")
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raise ValueError("The response stream never reached a terminal state")
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return final_response
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return final_response
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async def _check_input_safety(
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self, messages: list[Message], shield_ids: list[str]
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) -> OpenAIResponseContentPartRefusal | None:
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"""Validate input messages against shields. Returns refusal content if violation found."""
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try:
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await run_multiple_shields(self.safety_api, messages, shield_ids)
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except SafetyException as e:
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logger.info(f"Input shield violation: {e.violation.user_message}")
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return OpenAIResponseContentPartRefusal(
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refusal=e.violation.user_message or "Content blocked by safety shields"
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)
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async def _create_refusal_response_events(
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async def _create_refusal_response_events(
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self, refusal_content: OpenAIResponseContentPartRefusal, response_id: str, created_at: int, model: str
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self, refusal_content: OpenAIResponseContentPartRefusal, response_id: str, created_at: int, model: str
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) -> AsyncIterator[OpenAIResponseObjectStream]:
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) -> AsyncIterator[OpenAIResponseObjectStream]:
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@ -49,6 +49,7 @@ from llama_stack.apis.agents.openai_responses import (
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from llama_stack.apis.inference import (
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from llama_stack.apis.inference import (
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CompletionMessage,
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CompletionMessage,
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Inference,
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Inference,
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Message,
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OpenAIAssistantMessageParam,
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OpenAIAssistantMessageParam,
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OpenAIChatCompletion,
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OpenAIChatCompletion,
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OpenAIChatCompletionChunk,
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OpenAIChatCompletionChunk,
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@ -126,7 +127,7 @@ class StreamingResponseOrchestrator:
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# Track if we've sent a refusal response
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# Track if we've sent a refusal response
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self.violation_detected = False
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self.violation_detected = False
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async def _check_input_safety(self, messages: list[OpenAIMessageParam]) -> OpenAIResponseContentPartRefusal | None:
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async def _check_input_safety(self, messages: list[Message]) -> OpenAIResponseContentPartRefusal | None:
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"""Validate input messages against shields. Returns refusal content if violation found."""
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"""Validate input messages against shields. Returns refusal content if violation found."""
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try:
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try:
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await run_multiple_shields(self.safety_api, messages, self.shield_ids)
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await run_multiple_shields(self.safety_api, messages, self.shield_ids)
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@ -141,13 +142,12 @@ class StreamingResponseOrchestrator:
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) -> AsyncIterator[OpenAIResponseObjectStream]:
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) -> AsyncIterator[OpenAIResponseObjectStream]:
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"""Create refusal response events for input safety violations."""
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"""Create refusal response events for input safety violations."""
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# Create the refusal content part explicitly with the correct structure
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# Create the refusal content part explicitly with the correct structure
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refusal_part = OpenAIResponseContentPartRefusal(refusal=refusal_content.refusal, type="refusal")
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refusal_response = OpenAIResponseObject(
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refusal_response = OpenAIResponseObject(
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id=self.response_id,
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id=self.response_id,
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created_at=self.created_at,
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created_at=self.created_at,
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model=self.ctx.model,
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model=self.ctx.model,
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status="completed",
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status="completed",
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output=[OpenAIResponseMessage(role="assistant", content=[refusal_part], type="message")],
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output=[OpenAIResponseMessage(role="assistant", content=[refusal_content], type="message")],
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)
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)
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yield OpenAIResponseObjectStreamResponseCompleted(response=refusal_response)
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yield OpenAIResponseObjectStreamResponseCompleted(response=refusal_response)
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@ -557,7 +557,7 @@ class StreamingResponseOrchestrator:
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response_tool_call.function.arguments or ""
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response_tool_call.function.arguments or ""
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) + tool_call.function.arguments
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) + tool_call.function.arguments
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# Safety check after processing all chunks
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# Safety check after processing all choices in this chunk
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if chat_response_content:
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if chat_response_content:
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accumulated_text = "".join(chat_response_content)
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accumulated_text = "".join(chat_response_content)
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violation_message = await self._check_output_stream_chunk_safety(accumulated_text)
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violation_message = await self._check_output_stream_chunk_safety(accumulated_text)
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@ -4,6 +4,7 @@
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# This source code is licensed under the terms described in the LICENSE file in
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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# the root directory of this source tree.
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import asyncio
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import re
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import re
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import uuid
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import uuid
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@ -317,12 +318,13 @@ async def run_multiple_shields(safety_api: Safety, messages: list[Message], shie
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"""Run multiple shields against messages and raise SafetyException for violations."""
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"""Run multiple shields against messages and raise SafetyException for violations."""
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if not shield_ids or not messages:
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if not shield_ids or not messages:
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return
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return
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for shield_id in shield_ids:
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shield_tasks = [
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response = await safety_api.run_shield(
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safety_api.run_shield(shield_id=shield_id, messages=messages, params={}) for shield_id in shield_ids
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shield_id=shield_id,
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]
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messages=messages,
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params={},
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responses = await asyncio.gather(*shield_tasks)
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)
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for response in responses:
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if response.violation and response.violation.violation_level.name == "ERROR":
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if response.violation and response.violation.violation_level.name == "ERROR":
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from ..safety import SafetyException
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from ..safety import SafetyException
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@ -0,0 +1,59 @@
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{
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"test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_shields[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-False]",
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"request": {
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"method": "POST",
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"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
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"headers": {},
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"body": {
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"model": "llama-guard3:1b",
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"messages": [
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{
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"role": "user",
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"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\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<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Violent content\n\n<END CONVERSATION>\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."
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}
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],
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"stream": false,
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"temperature": 0.0
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},
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"endpoint": "/v1/chat/completions",
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"model": "llama-guard3:1b"
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},
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"response": {
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"body": {
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"__type__": "openai.types.chat.chat_completion.ChatCompletion",
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"__data__": {
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"id": "rec-00f53413463a",
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"choices": [
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{
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"finish_reason": "stop",
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"index": 0,
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"logprobs": null,
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"message": {
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"content": "safe",
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"refusal": null,
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"role": "assistant",
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"annotations": null,
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"audio": null,
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"function_call": null,
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"tool_calls": null
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}
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}
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],
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"created": 0,
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"model": "llama-guard3:1b",
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"object": "chat.completion",
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"service_tier": null,
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"system_fingerprint": "fp_ollama",
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"usage": {
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|
"completion_tokens": 2,
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|
"prompt_tokens": 387,
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"total_tokens": 389,
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|
"completion_tokens_details": null,
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"prompt_tokens_details": null
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}
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}
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},
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"is_streaming": false
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},
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"id_normalization_mapping": {}
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}
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@ -0,0 +1,59 @@
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{
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"test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_shields[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]",
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"request": {
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"method": "POST",
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|
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
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"headers": {},
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"body": {
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"model": "llama-guard3:1b",
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|
"messages": [
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{
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"role": "user",
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|
"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\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<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Violent content refers to media,\n\n<END CONVERSATION>\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."
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}
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],
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"stream": false,
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|
"temperature": 0.0
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|
},
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"endpoint": "/v1/chat/completions",
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"model": "llama-guard3:1b"
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|
},
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"response": {
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"body": {
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|
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
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|
"__data__": {
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|
"id": "rec-215f48b4ebf7",
|
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|
"choices": [
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|
{
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|
"finish_reason": "stop",
|
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|
"index": 0,
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|
"logprobs": null,
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|
"message": {
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|
"content": "safe",
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|
"refusal": null,
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|
"role": "assistant",
|
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|
"annotations": null,
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|
"audio": null,
|
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|
"function_call": null,
|
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|
"tool_calls": null
|
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|
}
|
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|
}
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|
],
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|
"created": 0,
|
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|
"model": "llama-guard3:1b",
|
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|
"object": "chat.completion",
|
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|
"service_tier": null,
|
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|
"system_fingerprint": "fp_ollama",
|
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|
"usage": {
|
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|
"completion_tokens": 2,
|
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|
"prompt_tokens": 390,
|
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|
"total_tokens": 392,
|
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|
"completion_tokens_details": null,
|
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|
"prompt_tokens_details": null
|
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|
}
|
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|
}
|
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|
},
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|
"is_streaming": false
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|
},
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|
"id_normalization_mapping": {}
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|
}
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|
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@ -0,0 +1,59 @@
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|
{
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|
"test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_shields[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]",
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|
"request": {
|
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|
"method": "POST",
|
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|
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
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|
"headers": {},
|
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|
"body": {
|
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|
"model": "llama-guard3:1b",
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|
"messages": [
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|
{
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|
"role": "user",
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|
"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\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<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Violent content refers to media, such as films\n\n<END CONVERSATION>\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."
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|
}
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|
],
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|
"stream": false,
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|
"temperature": 0.0
|
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|
},
|
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|
"endpoint": "/v1/chat/completions",
|
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|
"model": "llama-guard3:1b"
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|
},
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|
"response": {
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|
"body": {
|
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|
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
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|
"__data__": {
|
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|
"id": "rec-302796e5a32b",
|
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|
"choices": [
|
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|
{
|
||||||
|
"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": 394,
|
||||||
|
"total_tokens": 396,
|
||||||
|
"completion_tokens_details": null,
|
||||||
|
"prompt_tokens_details": null
|
||||||
|
}
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||||||
|
}
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||||||
|
},
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||||||
|
"is_streaming": false
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||||||
|
},
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||||||
|
"id_normalization_mapping": {}
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||||||
|
}
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|
|
@ -0,0 +1,59 @@
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|
{
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|
"test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_shields[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]",
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|
"request": {
|
||||||
|
"method": "POST",
|
||||||
|
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||||
|
"headers": {},
|
||||||
|
"body": {
|
||||||
|
"model": "llama-guard3:1b",
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|
"messages": [
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|
{
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|
"role": "user",
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||||||
|
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|
||||||
|
"__type__": "openai.types.chat.chat_completion.ChatCompletion",
|
||||||
|
"__data__": {
|
||||||
|
"id": "rec-fabde751eb5c",
|
||||||
|
"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": 390,
|
||||||
|
"total_tokens": 392,
|
||||||
|
"completion_tokens_details": null,
|
||||||
|
"prompt_tokens_details": null
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"is_streaming": false
|
||||||
|
},
|
||||||
|
"id_normalization_mapping": {}
|
||||||
|
}
|
||||||
|
|
@ -0,0 +1,59 @@
|
||||||
|
{
|
||||||
|
"test_id": "tests/integration/agents/test_openai_responses.py::test_output_safety_shields[openai_client-txt=ollama/llama3.2:3b-instruct-fp16-True]",
|
||||||
|
"request": {
|
||||||
|
"method": "POST",
|
||||||
|
"url": "http://0.0.0.0:11434/v1/v1/chat/completions",
|
||||||
|
"headers": {},
|
||||||
|
"body": {
|
||||||
|
"model": "llama-guard3:1b",
|
||||||
|
"messages": [
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": "Task: Check if there is unsafe content in 'User' messages in conversations according our safety policy with the below categories.\n\n<BEGIN UNSAFE CONTENT CATEGORIES>\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<END UNSAFE CONTENT CATEGORIES>\n\n<BEGIN CONVERSATION>\n\nUser: Violent content refers to media, such as films,\n\n<END CONVERSATION>\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-fb536645a0e3",
|
||||||
|
"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": 394,
|
||||||
|
"total_tokens": 396,
|
||||||
|
"completion_tokens_details": null,
|
||||||
|
"prompt_tokens_details": null
|
||||||
|
}
|
||||||
|
}
|
||||||
|
},
|
||||||
|
"is_streaming": false
|
||||||
|
},
|
||||||
|
"id_normalization_mapping": {}
|
||||||
|
}
|
||||||
|
|
@ -18,7 +18,6 @@ from openai.types.chat.chat_completion_chunk import (
|
||||||
from llama_stack.apis.agents import Order
|
from llama_stack.apis.agents import Order
|
||||||
from llama_stack.apis.agents.openai_responses import (
|
from llama_stack.apis.agents.openai_responses import (
|
||||||
ListOpenAIResponseInputItem,
|
ListOpenAIResponseInputItem,
|
||||||
OpenAIResponseContentPartRefusal,
|
|
||||||
OpenAIResponseInputMessageContentText,
|
OpenAIResponseInputMessageContentText,
|
||||||
OpenAIResponseInputToolFunction,
|
OpenAIResponseInputToolFunction,
|
||||||
OpenAIResponseInputToolMCP,
|
OpenAIResponseInputToolMCP,
|
||||||
|
|
@ -39,9 +38,7 @@ from llama_stack.apis.inference import (
|
||||||
OpenAIResponseFormatJSONObject,
|
OpenAIResponseFormatJSONObject,
|
||||||
OpenAIResponseFormatJSONSchema,
|
OpenAIResponseFormatJSONSchema,
|
||||||
OpenAIUserMessageParam,
|
OpenAIUserMessageParam,
|
||||||
UserMessage,
|
|
||||||
)
|
)
|
||||||
from llama_stack.apis.safety import SafetyViolation, ViolationLevel
|
|
||||||
from llama_stack.apis.tools.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
|
from llama_stack.apis.tools.tools import ListToolDefsResponse, ToolDef, ToolGroups, ToolInvocationResult, ToolRuntime
|
||||||
from llama_stack.core.access_control.access_control import default_policy
|
from llama_stack.core.access_control.access_control import default_policy
|
||||||
from llama_stack.core.datatypes import ResponsesStoreConfig
|
from llama_stack.core.datatypes import ResponsesStoreConfig
|
||||||
|
|
@ -1093,52 +1090,3 @@ async def test_create_openai_response_with_invalid_text_format(openai_responses_
|
||||||
model=model,
|
model=model,
|
||||||
text=OpenAIResponseText(format={"type": "invalid"}),
|
text=OpenAIResponseText(format={"type": "invalid"}),
|
||||||
)
|
)
|
||||||
|
|
||||||
|
|
||||||
async def test_check_input_safety_no_violation(openai_responses_impl):
|
|
||||||
"""Test input shield validation with no violations."""
|
|
||||||
messages = [UserMessage(content="Hello world")]
|
|
||||||
shield_ids = ["llama-guard"]
|
|
||||||
|
|
||||||
# Mock successful shield validation (no violation)
|
|
||||||
mock_response = AsyncMock()
|
|
||||||
mock_response.violation = None
|
|
||||||
openai_responses_impl.safety_api.run_shield.return_value = mock_response
|
|
||||||
|
|
||||||
result = await openai_responses_impl._check_input_safety(messages, shield_ids)
|
|
||||||
|
|
||||||
assert result is None
|
|
||||||
openai_responses_impl.safety_api.run_shield.assert_called_once_with(
|
|
||||||
shield_id="llama-guard", messages=messages, params={}
|
|
||||||
)
|
|
||||||
|
|
||||||
|
|
||||||
async def test_check_input_safety_with_violation(openai_responses_impl):
|
|
||||||
"""Test input shield validation with safety violation."""
|
|
||||||
messages = [UserMessage(content="Harmful content")]
|
|
||||||
shield_ids = ["llama-guard"]
|
|
||||||
|
|
||||||
# Mock shield violation
|
|
||||||
violation = SafetyViolation(
|
|
||||||
violation_level=ViolationLevel.ERROR, user_message="Content violates safety guidelines", metadata={}
|
|
||||||
)
|
|
||||||
mock_response = AsyncMock()
|
|
||||||
mock_response.violation = violation
|
|
||||||
openai_responses_impl.safety_api.run_shield.return_value = mock_response
|
|
||||||
|
|
||||||
result = await openai_responses_impl._check_input_safety(messages, shield_ids)
|
|
||||||
|
|
||||||
assert isinstance(result, OpenAIResponseContentPartRefusal)
|
|
||||||
assert result.refusal == "Content violates safety guidelines"
|
|
||||||
assert result.type == "refusal"
|
|
||||||
|
|
||||||
|
|
||||||
async def test_check_input_safety_empty_inputs(openai_responses_impl):
|
|
||||||
"""Test input shield validation with empty inputs."""
|
|
||||||
# Test empty shield_ids
|
|
||||||
result = await openai_responses_impl._check_input_safety([UserMessage(content="test")], [])
|
|
||||||
assert result is None
|
|
||||||
|
|
||||||
# Test empty messages
|
|
||||||
result = await openai_responses_impl._check_input_safety([], ["llama-guard"])
|
|
||||||
assert result is None
|
|
||||||
|
|
|
||||||
Loading…
Add table
Add a link
Reference in a new issue