feat: Add OpenAI Conversations API (#3429)

# 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>

llama_stack/core/conversations/__init__.py

@@ -0,0 +1,5 @@
+# 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.

llama_stack/core/conversations/conversations.py

@@ -0,0 +1,306 @@
+# 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.
+
+import os
+import secrets
+import time
+from typing import Any
+
+from openai import NOT_GIVEN
+from pydantic import BaseModel, TypeAdapter
+
+from llama_stack.apis.conversations.conversations import (
+    Conversation,
+    ConversationDeletedResource,
+    ConversationItem,
+    ConversationItemDeletedResource,
+    ConversationItemList,
+    Conversations,
+    Metadata,
+)
+from llama_stack.core.datatypes import AccessRule
+from llama_stack.core.utils.config_dirs import DISTRIBS_BASE_DIR
+from llama_stack.log import get_logger
+from llama_stack.providers.utils.sqlstore.api import ColumnDefinition, ColumnType
+from llama_stack.providers.utils.sqlstore.authorized_sqlstore import AuthorizedSqlStore
+from llama_stack.providers.utils.sqlstore.sqlstore import (
+    SqliteSqlStoreConfig,
+    SqlStoreConfig,
+    sqlstore_impl,
+)
+
+logger = get_logger(name=__name__, category="openai::conversations")
+
+
+class ConversationServiceConfig(BaseModel):
+    """Configuration for the built-in conversation service.
+
+    :param conversations_store: SQL store configuration for conversations (defaults to SQLite)
+    :param policy: Access control rules
+    """
+
+    conversations_store: SqlStoreConfig = SqliteSqlStoreConfig(
+        db_path=(DISTRIBS_BASE_DIR / "conversations.db").as_posix()
+    )
+    policy: list[AccessRule] = []
+
+
+async def get_provider_impl(config: ConversationServiceConfig, deps: dict[Any, Any]):
+    """Get the conversation service implementation."""
+    impl = ConversationServiceImpl(config, deps)
+    await impl.initialize()
+    return impl
+
+
+class ConversationServiceImpl(Conversations):
+    """Built-in conversation service implementation using AuthorizedSqlStore."""
+
+    def __init__(self, config: ConversationServiceConfig, deps: dict[Any, Any]):
+        self.config = config
+        self.deps = deps
+        self.policy = config.policy
+
+        base_sql_store = sqlstore_impl(config.conversations_store)
+        self.sql_store = AuthorizedSqlStore(base_sql_store, self.policy)
+
+    async def initialize(self) -> None:
+        """Initialize the store and create tables."""
+        if isinstance(self.config.conversations_store, SqliteSqlStoreConfig):
+            os.makedirs(os.path.dirname(self.config.conversations_store.db_path), exist_ok=True)
+
+        await self.sql_store.create_table(
+            "openai_conversations",
+            {
+                "id": ColumnDefinition(type=ColumnType.STRING, primary_key=True),
+                "created_at": ColumnType.INTEGER,
+                "items": ColumnType.JSON,
+                "metadata": ColumnType.JSON,
+            },
+        )
+
+        await self.sql_store.create_table(
+            "conversation_items",
+            {
+                "id": ColumnDefinition(type=ColumnType.STRING, primary_key=True),
+                "conversation_id": ColumnType.STRING,
+                "created_at": ColumnType.INTEGER,
+                "item_data": ColumnType.JSON,
+            },
+        )
+
+    async def create_conversation(
+        self, items: list[ConversationItem] | None = None, metadata: Metadata | None = None
+    ) -> Conversation:
+        """Create a conversation."""
+        random_bytes = secrets.token_bytes(24)
+        conversation_id = f"conv_{random_bytes.hex()}"
+        created_at = int(time.time())
+
+        record_data = {
+            "id": conversation_id,
+            "created_at": created_at,
+            "items": [],
+            "metadata": metadata,
+        }
+
+        await self.sql_store.insert(
+            table="openai_conversations",
+            data=record_data,
+        )
+
+        if items:
+            item_records = []
+            for item in items:
+                item_dict = item.model_dump()
+                item_id = self._get_or_generate_item_id(item, item_dict)
+
+                item_record = {
+                    "id": item_id,
+                    "conversation_id": conversation_id,
+                    "created_at": created_at,
+                    "item_data": item_dict,
+                }
+
+                item_records.append(item_record)
+
+            await self.sql_store.insert(table="conversation_items", data=item_records)
+
+        conversation = Conversation(
+            id=conversation_id,
+            created_at=created_at,
+            metadata=metadata,
+            object="conversation",
+        )
+
+        logger.info(f"Created conversation {conversation_id}")
+        return conversation
+
+    async def get_conversation(self, conversation_id: str) -> Conversation:
+        """Get a conversation with the given ID."""
+        record = await self.sql_store.fetch_one(table="openai_conversations", where={"id": conversation_id})
+
+        if record is None:
+            raise ValueError(f"Conversation {conversation_id} not found")
+
+        return Conversation(
+            id=record["id"], created_at=record["created_at"], metadata=record.get("metadata"), object="conversation"
+        )
+
+    async def update_conversation(self, conversation_id: str, metadata: Metadata) -> Conversation:
+        """Update a conversation's metadata with the given ID"""
+        await self.sql_store.update(
+            table="openai_conversations", data={"metadata": metadata}, where={"id": conversation_id}
+        )
+
+        return await self.get_conversation(conversation_id)
+
+    async def openai_delete_conversation(self, conversation_id: str) -> ConversationDeletedResource:
+        """Delete a conversation with the given ID."""
+        await self.sql_store.delete(table="openai_conversations", where={"id": conversation_id})
+
+        logger.info(f"Deleted conversation {conversation_id}")
+        return ConversationDeletedResource(id=conversation_id)
+
+    def _validate_conversation_id(self, conversation_id: str) -> None:
+        """Validate conversation ID format."""
+        if not conversation_id.startswith("conv_"):
+            raise ValueError(
+                f"Invalid 'conversation_id': '{conversation_id}'. Expected an ID that begins with 'conv_'."
+            )
+
+    def _get_or_generate_item_id(self, item: ConversationItem, item_dict: dict) -> str:
+        """Get existing item ID or generate one if missing."""
+        if item.id is None:
+            random_bytes = secrets.token_bytes(24)
+            if item.type == "message":
+                item_id = f"msg_{random_bytes.hex()}"
+            else:
+                item_id = f"item_{random_bytes.hex()}"
+            item_dict["id"] = item_id
+            return item_id
+        return item.id
+
+    async def _get_validated_conversation(self, conversation_id: str) -> Conversation:
+        """Validate conversation ID and return the conversation if it exists."""
+        self._validate_conversation_id(conversation_id)
+        return await self.get_conversation(conversation_id)
+
+    async def add_items(self, conversation_id: str, items: list[ConversationItem]) -> ConversationItemList:
+        """Create (add) items to a conversation."""
+        await self._get_validated_conversation(conversation_id)
+
+        created_items = []
+        created_at = int(time.time())
+
+        for item in items:
+            item_dict = item.model_dump()
+            item_id = self._get_or_generate_item_id(item, item_dict)
+
+            item_record = {
+                "id": item_id,
+                "conversation_id": conversation_id,
+                "created_at": created_at,
+                "item_data": item_dict,
+            }
+
+            # TODO: Add support for upsert in sql_store, this will fail first if ID exists and then update
+            try:
+                await self.sql_store.insert(table="conversation_items", data=item_record)
+            except Exception:
+                # If insert fails due to ID conflict, update existing record
+                await self.sql_store.update(
+                    table="conversation_items",
+                    data={"created_at": created_at, "item_data": item_dict},
+                    where={"id": item_id},
+                )
+
+            created_items.append(item_dict)
+
+        logger.info(f"Created {len(created_items)} items in conversation {conversation_id}")
+
+        # Convert created items (dicts) to proper ConversationItem types
+        adapter: TypeAdapter[ConversationItem] = TypeAdapter(ConversationItem)
+        response_items: list[ConversationItem] = [adapter.validate_python(item_dict) for item_dict in created_items]
+
+        return ConversationItemList(
+            data=response_items,
+            first_id=created_items[0]["id"] if created_items else None,
+            last_id=created_items[-1]["id"] if created_items else None,
+            has_more=False,
+        )
+
+    async def retrieve(self, conversation_id: str, item_id: str) -> ConversationItem:
+        """Retrieve a conversation item."""
+        if not conversation_id:
+            raise ValueError(f"Expected a non-empty value for `conversation_id` but received {conversation_id!r}")
+        if not item_id:
+            raise ValueError(f"Expected a non-empty value for `item_id` but received {item_id!r}")
+
+        # Get item from conversation_items table
+        record = await self.sql_store.fetch_one(
+            table="conversation_items", where={"id": item_id, "conversation_id": conversation_id}
+        )
+
+        if record is None:
+            raise ValueError(f"Item {item_id} not found in conversation {conversation_id}")
+
+        adapter: TypeAdapter[ConversationItem] = TypeAdapter(ConversationItem)
+        return adapter.validate_python(record["item_data"])
+
+    async def list(self, conversation_id: str, after=NOT_GIVEN, include=NOT_GIVEN, limit=NOT_GIVEN, order=NOT_GIVEN):
+        """List items in the conversation."""
+        result = await self.sql_store.fetch_all(table="conversation_items", where={"conversation_id": conversation_id})
+        records = result.data
+
+        if order != NOT_GIVEN and order == "asc":
+            records.sort(key=lambda x: x["created_at"])
+        else:
+            records.sort(key=lambda x: x["created_at"], reverse=True)
+
+        actual_limit = 20
+        if limit != NOT_GIVEN and isinstance(limit, int):
+            actual_limit = limit
+
+        records = records[:actual_limit]
+        items = [record["item_data"] for record in records]
+
+        adapter: TypeAdapter[ConversationItem] = TypeAdapter(ConversationItem)
+        response_items: list[ConversationItem] = [adapter.validate_python(item) for item in items]
+
+        first_id = response_items[0].id if response_items else None
+        last_id = response_items[-1].id if response_items else None
+
+        return ConversationItemList(
+            data=response_items,
+            first_id=first_id,
+            last_id=last_id,
+            has_more=False,
+        )
+
+    async def openai_delete_conversation_item(
+        self, conversation_id: str, item_id: str
+    ) -> ConversationItemDeletedResource:
+        """Delete a conversation item."""
+        if not conversation_id:
+            raise ValueError(f"Expected a non-empty value for `conversation_id` but received {conversation_id!r}")
+        if not item_id:
+            raise ValueError(f"Expected a non-empty value for `item_id` but received {item_id!r}")
+
+        _ = await self._get_validated_conversation(conversation_id)
+
+        record = await self.sql_store.fetch_one(
+            table="conversation_items", where={"id": item_id, "conversation_id": conversation_id}
+        )
+
+        if record is None:
+            raise ValueError(f"Item {item_id} not found in conversation {conversation_id}")
+
+        await self.sql_store.delete(
+            table="conversation_items", where={"id": item_id, "conversation_id": conversation_id}
+        )
+
+        logger.info(f"Deleted item {item_id} from conversation {conversation_id}")
+        return ConversationItemDeletedResource(id=item_id)

llama_stack/core/datatypes.py

@@ -475,6 +475,13 @@ InferenceStoreConfig (with queue tuning parameters) or a SqlStoreConfig (depreca
 If not specified, a default SQLite store will be used.""",
     )
 
+    conversations_store: SqlStoreConfig | None = Field(
+        default=None,
+        description="""
+Configuration for the persistence store used by the conversations API.
+If not specified, a default SQLite store will be used.""",
+    )
+
     # registry of "resources" in the distribution
     models: list[ModelInput] = Field(default_factory=list)
     shields: list[ShieldInput] = Field(default_factory=list)

llama_stack/core/distribution.py

@@ -25,7 +25,7 @@ from llama_stack.providers.datatypes import (
 logger = get_logger(name=__name__, category="core")
 
 
-INTERNAL_APIS = {Api.inspect, Api.providers, Api.prompts}
+INTERNAL_APIS = {Api.inspect, Api.providers, Api.prompts, Api.conversations}
 
 
 def stack_apis() -> list[Api]:

llama_stack/core/resolver.py

@@ -10,6 +10,7 @@ from typing import Any
 from llama_stack.apis.agents import Agents
 from llama_stack.apis.batches import Batches
 from llama_stack.apis.benchmarks import Benchmarks
+from llama_stack.apis.conversations import Conversations
 from llama_stack.apis.datasetio import DatasetIO
 from llama_stack.apis.datasets import Datasets
 from llama_stack.apis.datatypes import ExternalApiSpec
@@ -96,6 +97,7 @@ def api_protocol_map(external_apis: dict[Api, ExternalApiSpec] | None = None) ->
         Api.tool_runtime: ToolRuntime,
         Api.files: Files,
         Api.prompts: Prompts,
+        Api.conversations: Conversations,
     }
 
     if external_apis:

llama_stack/core/server/server.py

@@ -451,6 +451,7 @@ def create_app(
     apis_to_serve.add("inspect")
     apis_to_serve.add("providers")
     apis_to_serve.add("prompts")
+    apis_to_serve.add("conversations")
     for api_str in apis_to_serve:
         api = Api(api_str)
 

llama_stack/core/stack.py

@@ -15,6 +15,7 @@ import yaml
 
 from llama_stack.apis.agents import Agents
 from llama_stack.apis.benchmarks import Benchmarks
+from llama_stack.apis.conversations import Conversations
 from llama_stack.apis.datasetio import DatasetIO
 from llama_stack.apis.datasets import Datasets
 from llama_stack.apis.eval import Eval
@@ -34,6 +35,7 @@ from llama_stack.apis.telemetry import Telemetry
 from llama_stack.apis.tools import RAGToolRuntime, ToolGroups, ToolRuntime
 from llama_stack.apis.vector_dbs import VectorDBs
 from llama_stack.apis.vector_io import VectorIO
+from llama_stack.core.conversations.conversations import ConversationServiceConfig, ConversationServiceImpl
 from llama_stack.core.datatypes import Provider, StackRunConfig
 from llama_stack.core.distribution import get_provider_registry
 from llama_stack.core.inspect import DistributionInspectConfig, DistributionInspectImpl
@@ -73,6 +75,7 @@ class LlamaStack(
     RAGToolRuntime,
     Files,
     Prompts,
+    Conversations,
 ):
     pass
 
@@ -312,6 +315,12 @@ def add_internal_implementations(impls: dict[Api, Any], run_config: StackRunConf
     )
     impls[Api.prompts] = prompts_impl
 
+    conversations_impl = ConversationServiceImpl(
+        ConversationServiceConfig(run_config=run_config),
+        deps=impls,
+    )
+    impls[Api.conversations] = conversations_impl
+
 
 class Stack:
     def __init__(self, run_config: StackRunConfig, provider_registry: ProviderRegistry | None = None):
@@ -342,6 +351,8 @@ class Stack:
 
         if Api.prompts in impls:
             await impls[Api.prompts].initialize()
+        if Api.conversations in impls:
+            await impls[Api.conversations].initialize()
 
         await register_resources(self.run_config, impls)