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# What does this PR do? Initial implementation for `Conversations` and `ConversationItems` using `AuthorizedSqlStore` with endpoints to: - CREATE - UPDATE - GET/RETRIEVE/LIST - DELETE Set `level=LLAMA_STACK_API_V1`. NOTE: This does not currently incorporate changes for Responses, that'll be done in a subsequent PR. Closes https://github.com/llamastack/llama-stack/issues/3235 ## Test Plan - Unit tests - Integration tests Also comparison of [OpenAPI spec for OpenAI API](https://github.com/openai/openai-openapi/tree/manual_spec) ```bash oasdiff breaking --fail-on ERR docs/static/llama-stack-spec.yaml https://raw.githubusercontent.com/openai/openai-openapi/refs/heads/manual_spec/openapi.yaml --strip-prefix-base "/v1/openai/v1" \ --match-path '(^/v1/openai/v1/conversations.*|^/conversations.*)' ``` Note I still have some uncertainty about this, I borrowed this info from @cdoern on https://github.com/llamastack/llama-stack/pull/3514 but need to spend more time to confirm it's working, at the moment it suggests it does. UPDATE on `oasdiff`, I investigated the OpenAI spec further and it looks like currently the spec does not list Conversations, so that analysis is useless. Noting for future reference. --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
132 lines
4.5 KiB
Python
132 lines
4.5 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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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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import tempfile
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from pathlib import Path
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import pytest
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from openai.types.conversations.conversation import Conversation as OpenAIConversation
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from openai.types.conversations.conversation_item import ConversationItem as OpenAIConversationItem
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from pydantic import TypeAdapter
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from llama_stack.apis.agents.openai_responses import (
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OpenAIResponseInputMessageContentText,
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OpenAIResponseMessage,
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)
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from llama_stack.core.conversations.conversations import (
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ConversationServiceConfig,
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ConversationServiceImpl,
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)
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from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
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@pytest.fixture
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async def service():
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with tempfile.TemporaryDirectory() as tmpdir:
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db_path = Path(tmpdir) / "test_conversations.db"
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config = ConversationServiceConfig(conversations_store=SqliteSqlStoreConfig(db_path=str(db_path)), policy=[])
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service = ConversationServiceImpl(config, {})
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await service.initialize()
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yield service
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async def test_conversation_lifecycle(service):
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conversation = await service.create_conversation(metadata={"test": "data"})
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assert conversation.id.startswith("conv_")
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assert conversation.metadata == {"test": "data"}
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retrieved = await service.get_conversation(conversation.id)
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assert retrieved.id == conversation.id
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deleted = await service.openai_delete_conversation(conversation.id)
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assert deleted.id == conversation.id
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async def test_conversation_items(service):
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conversation = await service.create_conversation()
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items = [
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OpenAIResponseMessage(
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type="message",
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role="user",
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content=[OpenAIResponseInputMessageContentText(type="input_text", text="Hello")],
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id="msg_test123",
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status="completed",
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)
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]
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item_list = await service.add_items(conversation.id, items)
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assert len(item_list.data) == 1
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assert item_list.data[0].id == "msg_test123"
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items = await service.list(conversation.id)
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assert len(items.data) == 1
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async def test_invalid_conversation_id(service):
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with pytest.raises(ValueError, match="Expected an ID that begins with 'conv_'"):
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await service._get_validated_conversation("invalid_id")
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async def test_empty_parameter_validation(service):
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with pytest.raises(ValueError, match="Expected a non-empty value"):
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await service.retrieve("", "item_123")
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async def test_openai_type_compatibility(service):
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conversation = await service.create_conversation(metadata={"test": "value"})
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conversation_dict = conversation.model_dump()
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openai_conversation = OpenAIConversation.model_validate(conversation_dict)
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for attr in ["id", "object", "created_at", "metadata"]:
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assert getattr(openai_conversation, attr) == getattr(conversation, attr)
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items = [
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OpenAIResponseMessage(
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type="message",
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role="user",
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content=[OpenAIResponseInputMessageContentText(type="input_text", text="Hello")],
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id="msg_test456",
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status="completed",
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)
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]
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item_list = await service.add_items(conversation.id, items)
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for attr in ["object", "data", "first_id", "last_id", "has_more"]:
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assert hasattr(item_list, attr)
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assert item_list.object == "list"
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items = await service.list(conversation.id)
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item = await service.retrieve(conversation.id, items.data[0].id)
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item_dict = item.model_dump()
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openai_item_adapter = TypeAdapter(OpenAIConversationItem)
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openai_item_adapter.validate_python(item_dict)
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async def test_policy_configuration():
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from llama_stack.core.access_control.datatypes import Action, Scope
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from llama_stack.core.datatypes import AccessRule
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with tempfile.TemporaryDirectory() as tmpdir:
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db_path = Path(tmpdir) / "test_conversations_policy.db"
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restrictive_policy = [
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AccessRule(forbid=Scope(principal="test_user", actions=[Action.CREATE, Action.READ], resource="*"))
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]
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config = ConversationServiceConfig(
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conversations_store=SqliteSqlStoreConfig(db_path=str(db_path)), policy=restrictive_policy
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)
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service = ConversationServiceImpl(config, {})
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await service.initialize()
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assert service.policy == restrictive_policy
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assert len(service.policy) == 1
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assert service.policy[0].forbid is not None
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