feat: reference implementation for files API (#2330)

# What does this PR do?
TSIA
Added Files provider to the fireworks template. Might want to add to all
templates as a follow-up.

## Test Plan
llama-stack pytest tests/unit/files/test_files.py

llama-stack llama stack build --template fireworks --image-type conda
--run
LLAMA_STACK_CONFIG=http://localhost:8321 pytest -s -v
tests/integration/files/

docs/source/distributions/self_hosted_distro/fireworks.md

@@ -18,6 +18,7 @@ The `llamastack/distribution-fireworks` distribution consists of the following p
 | agents | `inline::meta-reference` |
 | datasetio | `remote::huggingface`, `inline::localfs` |
 | eval | `inline::meta-reference` |
+| files | `inline::localfs` |
 | inference | `remote::fireworks`, `inline::sentence-transformers` |
 | safety | `inline::llama-guard` |
 | scoring | `inline::basic`, `inline::llm-as-judge`, `inline::braintrust` |

llama_stack/distribution/server/server.py

@@ -18,7 +18,7 @@ from collections.abc import Callable
 from contextlib import asynccontextmanager
 from importlib.metadata import version as parse_version
 from pathlib import Path
-from typing import Annotated, Any
+from typing import Annotated, Any, get_origin
 
 import rich.pretty
 import yaml
@@ -244,15 +244,23 @@ def create_dynamic_typed_route(func: Any, method: str, route: str) -> Callable:
 
     path_params = extract_path_params(route)
     if method == "post":
-        # Annotate parameters that are in the path with Path(...) and others with Body(...)
+        # Annotate parameters that are in the path with Path(...) and others with Body(...),
-        new_params = [new_params[0]] + [
+        # but preserve existing File() and Form() annotations for multipart form data
-            (
+        new_params = (
-                param.replace(annotation=Annotated[param.annotation, FastapiPath(..., title=param.name)])
+            [new_params[0]]
-                if param.name in path_params
+            + [
-                else param.replace(annotation=Annotated[param.annotation, Body(..., embed=True)])
+                (
-            )
+                    param.replace(annotation=Annotated[param.annotation, FastapiPath(..., title=param.name)])
-            for param in new_params[1:]
+                    if param.name in path_params
-        ]
+                    else (
+                        param  # Keep original annotation if it's already an Annotated type
+                        if get_origin(param.annotation) is Annotated
+                        else param.replace(annotation=Annotated[param.annotation, Body(..., embed=True)])
+                    )
+                )
+                for param in new_params[1:]
+            ]
+        )
 
     route_handler.__signature__ = sig.replace(parameters=new_params)
 

llama_stack/providers/inline/files/localfs/__init__.py

@@ -0,0 +1,20 @@
+# 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 typing import Any
+
+from llama_stack.distribution.datatypes import Api
+
+from .config import LocalfsFilesImplConfig
+from .files import LocalfsFilesImpl
+
+__all__ = ["LocalfsFilesImpl", "LocalfsFilesImplConfig"]
+
+
+async def get_provider_impl(config: LocalfsFilesImplConfig, deps: dict[Api, Any]):
+    impl = LocalfsFilesImpl(config)
+    await impl.initialize()
+    return impl

llama_stack/providers/inline/files/localfs/config.py

@@ -0,0 +1,31 @@
+# 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 typing import Any
+
+from pydantic import BaseModel, Field
+
+from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig, SqlStoreConfig
+
+
+class LocalfsFilesImplConfig(BaseModel):
+    storage_dir: str = Field(
+        description="Directory to store uploaded files",
+    )
+    metadata_store: SqlStoreConfig = Field(
+        description="SQL store configuration for file metadata",
+    )
+    ttl_secs: int = 365 * 24 * 60 * 60  # 1 year
+
+    @classmethod
+    def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]:
+        return {
+            "storage_dir": "${env.FILES_STORAGE_DIR:" + __distro_dir__ + "/files}",
+            "metadata_store": SqliteSqlStoreConfig.sample_run_config(
+                __distro_dir__=__distro_dir__,
+                db_name="files_metadata.db",
+            ),
+        }

llama_stack/providers/inline/files/localfs/files.py

@@ -0,0 +1,214 @@
+# 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 time
+import uuid
+from pathlib import Path
+from typing import Annotated
+
+from fastapi import File, Form, Response, UploadFile
+
+from llama_stack.apis.common.responses import Order
+from llama_stack.apis.files import (
+    Files,
+    ListOpenAIFileResponse,
+    OpenAIFileDeleteResponse,
+    OpenAIFileObject,
+    OpenAIFilePurpose,
+)
+from llama_stack.providers.utils.sqlstore.api import ColumnDefinition, ColumnType
+from llama_stack.providers.utils.sqlstore.sqlstore import SqlStore, sqlstore_impl
+
+from .config import LocalfsFilesImplConfig
+
+
+class LocalfsFilesImpl(Files):
+    def __init__(self, config: LocalfsFilesImplConfig) -> None:
+        self.config = config
+        self.sql_store: SqlStore | None = None
+
+    async def initialize(self) -> None:
+        """Initialize the files provider by setting up storage directory and metadata database."""
+        # Create storage directory if it doesn't exist
+        storage_path = Path(self.config.storage_dir)
+        storage_path.mkdir(parents=True, exist_ok=True)
+
+        # Initialize SQL store for metadata
+        self.sql_store = sqlstore_impl(self.config.metadata_store)
+        await self.sql_store.create_table(
+            "openai_files",
+            {
+                "id": ColumnDefinition(type=ColumnType.STRING, primary_key=True),
+                "filename": ColumnType.STRING,
+                "purpose": ColumnType.STRING,
+                "bytes": ColumnType.INTEGER,
+                "created_at": ColumnType.INTEGER,
+                "expires_at": ColumnType.INTEGER,
+                "file_path": ColumnType.STRING,  # Path to actual file on disk
+            },
+        )
+
+    def _generate_file_id(self) -> str:
+        """Generate a unique file ID for OpenAI API."""
+        return f"file-{uuid.uuid4().hex}"
+
+    def _get_file_path(self, file_id: str) -> Path:
+        """Get the filesystem path for a file ID."""
+        return Path(self.config.storage_dir) / file_id
+
+    # OpenAI Files API Implementation
+    async def openai_upload_file(
+        self,
+        file: Annotated[UploadFile, File()],
+        purpose: Annotated[OpenAIFilePurpose, Form()],
+    ) -> OpenAIFileObject:
+        """Upload a file that can be used across various endpoints."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        file_id = self._generate_file_id()
+        file_path = self._get_file_path(file_id)
+
+        content = await file.read()
+        file_size = len(content)
+
+        with open(file_path, "wb") as f:
+            f.write(content)
+
+        created_at = int(time.time())
+        expires_at = created_at + self.config.ttl_secs
+
+        await self.sql_store.insert(
+            "openai_files",
+            {
+                "id": file_id,
+                "filename": file.filename or "uploaded_file",
+                "purpose": purpose.value,
+                "bytes": file_size,
+                "created_at": created_at,
+                "expires_at": expires_at,
+                "file_path": file_path.as_posix(),
+            },
+        )
+
+        return OpenAIFileObject(
+            id=file_id,
+            filename=file.filename or "uploaded_file",
+            purpose=purpose,
+            bytes=file_size,
+            created_at=created_at,
+            expires_at=expires_at,
+        )
+
+    async def openai_list_files(
+        self,
+        after: str | None = None,
+        limit: int | None = 10000,
+        order: Order | None = Order.desc,
+        purpose: OpenAIFilePurpose | None = None,
+    ) -> ListOpenAIFileResponse:
+        """Returns a list of files that belong to the user's organization."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        # TODO: Implement 'after' pagination properly
+        if after:
+            raise NotImplementedError("After pagination not yet implemented")
+
+        where = None
+        if purpose:
+            where = {"purpose": purpose.value}
+
+        rows = await self.sql_store.fetch_all(
+            "openai_files",
+            where=where,
+            order_by=[("created_at", order.value if order else Order.desc.value)],
+            limit=limit,
+        )
+
+        files = [
+            OpenAIFileObject(
+                id=row["id"],
+                filename=row["filename"],
+                purpose=OpenAIFilePurpose(row["purpose"]),
+                bytes=row["bytes"],
+                created_at=row["created_at"],
+                expires_at=row["expires_at"],
+            )
+            for row in rows
+        ]
+
+        return ListOpenAIFileResponse(
+            data=files,
+            has_more=False,  # TODO: Implement proper pagination
+            first_id=files[0].id if files else "",
+            last_id=files[-1].id if files else "",
+        )
+
+    async def openai_retrieve_file(self, file_id: str) -> OpenAIFileObject:
+        """Returns information about a specific file."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        row = await self.sql_store.fetch_one("openai_files", where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
+        return OpenAIFileObject(
+            id=row["id"],
+            filename=row["filename"],
+            purpose=OpenAIFilePurpose(row["purpose"]),
+            bytes=row["bytes"],
+            created_at=row["created_at"],
+            expires_at=row["expires_at"],
+        )
+
+    async def openai_delete_file(self, file_id: str) -> OpenAIFileDeleteResponse:
+        """Delete a file."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        row = await self.sql_store.fetch_one("openai_files", where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
+        # Delete physical file
+        file_path = Path(row["file_path"])
+        if file_path.exists():
+            file_path.unlink()
+
+        # Delete metadata from database
+        await self.sql_store.delete("openai_files", where={"id": file_id})
+
+        return OpenAIFileDeleteResponse(
+            id=file_id,
+            deleted=True,
+        )
+
+    async def openai_retrieve_file_content(self, file_id: str) -> Response:
+        """Returns the contents of the specified file."""
+        if not self.sql_store:
+            raise RuntimeError("Files provider not initialized")
+
+        # Get file metadata
+        row = await self.sql_store.fetch_one("openai_files", where={"id": file_id})
+        if not row:
+            raise ValueError(f"File with id {file_id} not found")
+
+        # Read file content
+        file_path = Path(row["file_path"])
+        if not file_path.exists():
+            raise ValueError(f"File content not found on disk: {file_path}")
+
+        with open(file_path, "rb") as f:
+            content = f.read()
+
+        # Return as binary response with appropriate content type
+        return Response(
+            content=content,
+            media_type="application/octet-stream",
+            headers={"Content-Disposition": f'attachment; filename="{row["filename"]}"'},
+        )

llama_stack/providers/registry/files.py

@@ -4,8 +4,22 @@
 # This source code is licensed under the terms described in the LICENSE file in
 # the root directory of this source tree.
 
-from llama_stack.providers.datatypes import ProviderSpec
+from llama_stack.providers.datatypes import (
+    Api,
+    InlineProviderSpec,
+    ProviderSpec,
+)
+from llama_stack.providers.utils.sqlstore.sqlstore import sql_store_pip_packages
 
 
 def available_providers() -> list[ProviderSpec]:
-    return []
+    return [
+        InlineProviderSpec(
+            api=Api.files,
+            provider_type="inline::localfs",
+            # TODO: make this dynamic according to the sql store type
+            pip_packages=sql_store_pip_packages,
+            module="llama_stack.providers.inline.files.localfs",
+            config_class="llama_stack.providers.inline.files.localfs.config.LocalfsFilesImplConfig",
+        ),
+    ]

llama_stack/providers/utils/sqlstore/sqlstore.py

@@ -16,6 +16,8 @@ from llama_stack.distribution.utils.config_dirs import RUNTIME_BASE_DIR
 
 from .api import SqlStore
 
+sql_store_pip_packages = ["sqlalchemy[asyncio]", "aiosqlite", "asyncpg"]
+
 
 class SqlStoreType(Enum):
     sqlite = "sqlite"

llama_stack/templates/fireworks/build.yaml

@@ -24,6 +24,8 @@ distribution_spec:
     - inline::basic
     - inline::llm-as-judge
     - inline::braintrust
+    files:
+    - inline::localfs
     tool_runtime:
     - remote::brave-search
     - remote::tavily-search

llama_stack/templates/fireworks/fireworks.py

@@ -13,6 +13,7 @@ from llama_stack.distribution.datatypes import (
     ShieldInput,
     ToolGroupInput,
 )
+from llama_stack.providers.inline.files.localfs.config import LocalfsFilesImplConfig
 from llama_stack.providers.inline.inference.sentence_transformers import (
     SentenceTransformersInferenceConfig,
 )
@@ -36,6 +37,7 @@ def get_distribution_template() -> DistributionTemplate:
         "eval": ["inline::meta-reference"],
         "datasetio": ["remote::huggingface", "inline::localfs"],
         "scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
+        "files": ["inline::localfs"],
         "tool_runtime": [
             "remote::brave-search",
             "remote::tavily-search",
@@ -62,6 +64,11 @@ def get_distribution_template() -> DistributionTemplate:
         provider_type="inline::faiss",
         config=FaissVectorIOConfig.sample_run_config(f"~/.llama/distributions/{name}"),
     )
+    files_provider = Provider(
+        provider_id="meta-reference-files",
+        provider_type="inline::localfs",
+        config=LocalfsFilesImplConfig.sample_run_config(f"~/.llama/distributions/{name}"),
+    )
 
     available_models = {
         "fireworks": MODEL_ENTRIES,
@@ -104,6 +111,7 @@ def get_distribution_template() -> DistributionTemplate:
                 provider_overrides={
                     "inference": [inference_provider, embedding_provider],
                     "vector_io": [vector_io_provider],
+                    "files": [files_provider],
                 },
                 default_models=default_models + [embedding_model],
                 default_shields=[ShieldInput(shield_id="meta-llama/Llama-Guard-3-8B")],
@@ -116,6 +124,7 @@ def get_distribution_template() -> DistributionTemplate:
                         embedding_provider,
                     ],
                     "vector_io": [vector_io_provider],
+                    "files": [files_provider],
                     "safety": [
                         Provider(
                             provider_id="llama-guard",

llama_stack/templates/fireworks/run-with-safety.yaml

@@ -4,6 +4,7 @@ apis:
 - agents
 - datasetio
 - eval
+- files
 - inference
 - safety
 - scoring
@@ -90,6 +91,14 @@ providers:
     provider_type: inline::braintrust
     config:
       openai_api_key: ${env.OPENAI_API_KEY:}
+  files:
+  - provider_id: meta-reference-files
+    provider_type: inline::localfs
+    config:
+      storage_dir: ${env.FILES_STORAGE_DIR:~/.llama/distributions/fireworks/files}
+      metadata_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/fireworks}/files_metadata.db
   tool_runtime:
   - provider_id: brave-search
     provider_type: remote::brave-search

llama_stack/templates/fireworks/run.yaml

@@ -4,6 +4,7 @@ apis:
 - agents
 - datasetio
 - eval
+- files
 - inference
 - safety
 - scoring
@@ -85,6 +86,14 @@ providers:
     provider_type: inline::braintrust
     config:
       openai_api_key: ${env.OPENAI_API_KEY:}
+  files:
+  - provider_id: meta-reference-files
+    provider_type: inline::localfs
+    config:
+      storage_dir: ${env.FILES_STORAGE_DIR:~/.llama/distributions/fireworks/files}
+      metadata_store:
+        type: sqlite
+        db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/fireworks}/files_metadata.db
   tool_runtime:
   - provider_id: brave-search
     provider_type: remote::brave-search

pyproject.toml

@@ -41,6 +41,7 @@ dependencies = [
     "tiktoken",
     "pillow",
     "h11>=0.16.0",
+    "python-multipart>=0.0.20",
 ]
 
 [project.optional-dependencies]

requirements.txt

@@ -130,6 +130,8 @@ python-dotenv==1.0.1
     # via llama-stack
 python-jose==3.4.0
     # via llama-stack
+python-multipart==0.0.20
+    # via llama-stack
 pytz==2025.1
     # via pandas
 pyyaml==6.0.2

tests/integration/files/__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.

tests/integration/files/test_files.py

@@ -0,0 +1,51 @@
+# 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 io import BytesIO
+
+
+def test_openai_client_basic_operations(openai_client):
+    """Test basic file operations through OpenAI client."""
+    client = openai_client
+
+    test_content = b"files test content"
+
+    try:
+        # Upload file using OpenAI client
+        with BytesIO(test_content) as file_buffer:
+            file_buffer.name = "openai_test.txt"
+            uploaded_file = client.files.create(file=file_buffer, purpose="assistants")
+
+        # Verify basic response structure
+        assert uploaded_file.id.startswith("file-")
+        assert hasattr(uploaded_file, "filename")
+
+        # List files
+        files_list = client.files.list()
+        file_ids = [f.id for f in files_list.data]
+        assert uploaded_file.id in file_ids
+
+        # Retrieve file info
+        retrieved_file = client.files.retrieve(uploaded_file.id)
+        assert retrieved_file.id == uploaded_file.id
+
+        # Retrieve file content - OpenAI client returns httpx Response object
+        content_response = client.files.content(uploaded_file.id)
+        # The response is an httpx Response object with .content attribute containing bytes
+        content = content_response.content
+        assert content == test_content
+
+        # Delete file
+        delete_response = client.files.delete(uploaded_file.id)
+        assert delete_response.deleted is True
+
+    except Exception as e:
+        # Cleanup in case of failure
+        try:
+            client.files.delete(uploaded_file.id)
+        except Exception:
+            pass
+        raise e

tests/unit/files/__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.

tests/unit/files/test_files.py

@@ -0,0 +1,334 @@
+# 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 pytest
+import pytest_asyncio
+
+from llama_stack.apis.common.responses import Order
+from llama_stack.apis.files import OpenAIFilePurpose
+from llama_stack.providers.inline.files.localfs import (
+    LocalfsFilesImpl,
+    LocalfsFilesImplConfig,
+)
+from llama_stack.providers.utils.sqlstore.sqlstore import SqliteSqlStoreConfig
+
+
+class MockUploadFile:
+    """Mock UploadFile for testing file uploads."""
+
+    def __init__(self, content: bytes, filename: str, content_type: str = "text/plain"):
+        self.content = content
+        self.filename = filename
+        self.content_type = content_type
+
+    async def read(self):
+        return self.content
+
+
+@pytest_asyncio.fixture
+async def files_provider(tmp_path):
+    """Create a files provider with temporary storage for testing."""
+    storage_dir = tmp_path / "files"
+    db_path = tmp_path / "files_metadata.db"
+
+    config = LocalfsFilesImplConfig(
+        storage_dir=storage_dir.as_posix(), metadata_store=SqliteSqlStoreConfig(db_path=db_path.as_posix())
+    )
+
+    provider = LocalfsFilesImpl(config)
+    await provider.initialize()
+    yield provider
+
+
+@pytest.fixture
+def sample_text_file():
+    """Sample text file for testing."""
+    content = b"Hello, this is a test file for the OpenAI Files API!"
+    return MockUploadFile(content, "test.txt", "text/plain")
+
+
+@pytest.fixture
+def sample_json_file():
+    """Sample JSON file for testing."""
+    content = b'{"message": "Hello, World!", "type": "test"}'
+    return MockUploadFile(content, "data.json", "application/json")
+
+
+@pytest.fixture
+def large_file():
+    """Large file for testing file size handling."""
+    content = b"x" * 1024 * 1024  # 1MB file
+    return MockUploadFile(content, "large_file.bin", "application/octet-stream")
+
+
+class TestOpenAIFilesAPI:
+    """Test suite for OpenAI Files API endpoints."""
+
+    @pytest.mark.asyncio
+    async def test_upload_file_success(self, files_provider, sample_text_file):
+        """Test successful file upload."""
+        # Upload file
+        result = await files_provider.openai_upload_file(file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+
+        # Verify response
+        assert result.id.startswith("file-")
+        assert result.filename == "test.txt"
+        assert result.purpose == OpenAIFilePurpose.ASSISTANTS
+        assert result.bytes == len(sample_text_file.content)
+        assert result.created_at > 0
+        assert result.expires_at > result.created_at
+
+    @pytest.mark.asyncio
+    async def test_upload_different_purposes(self, files_provider, sample_text_file):
+        """Test uploading files with different purposes."""
+        purposes = list(OpenAIFilePurpose)
+
+        uploaded_files = []
+        for purpose in purposes:
+            result = await files_provider.openai_upload_file(file=sample_text_file, purpose=purpose)
+            uploaded_files.append(result)
+            assert result.purpose == purpose
+
+    @pytest.mark.asyncio
+    async def test_upload_different_file_types(self, files_provider, sample_text_file, sample_json_file, large_file):
+        """Test uploading different types and sizes of files."""
+        files_to_test = [
+            (sample_text_file, "test.txt"),
+            (sample_json_file, "data.json"),
+            (large_file, "large_file.bin"),
+        ]
+
+        for file_obj, expected_filename in files_to_test:
+            result = await files_provider.openai_upload_file(file=file_obj, purpose=OpenAIFilePurpose.ASSISTANTS)
+            assert result.filename == expected_filename
+            assert result.bytes == len(file_obj.content)
+
+    @pytest.mark.asyncio
+    async def test_list_files_empty(self, files_provider):
+        """Test listing files when no files exist."""
+        result = await files_provider.openai_list_files()
+
+        assert result.data == []
+        assert result.has_more is False
+        assert result.first_id == ""
+        assert result.last_id == ""
+
+    @pytest.mark.asyncio
+    async def test_list_files_with_content(self, files_provider, sample_text_file, sample_json_file):
+        """Test listing files when files exist."""
+        # Upload multiple files
+        file1 = await files_provider.openai_upload_file(file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+        file2 = await files_provider.openai_upload_file(file=sample_json_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+
+        # List files
+        result = await files_provider.openai_list_files()
+
+        assert len(result.data) == 2
+        file_ids = [f.id for f in result.data]
+        assert file1.id in file_ids
+        assert file2.id in file_ids
+
+    @pytest.mark.asyncio
+    async def test_list_files_with_purpose_filter(self, files_provider, sample_text_file):
+        """Test listing files with purpose filtering."""
+        # Upload file with specific purpose
+        uploaded_file = await files_provider.openai_upload_file(
+            file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        # List files with matching purpose
+        result = await files_provider.openai_list_files(purpose=OpenAIFilePurpose.ASSISTANTS)
+        assert len(result.data) == 1
+        assert result.data[0].id == uploaded_file.id
+        assert result.data[0].purpose == OpenAIFilePurpose.ASSISTANTS
+
+    @pytest.mark.asyncio
+    async def test_list_files_with_limit(self, files_provider, sample_text_file):
+        """Test listing files with limit parameter."""
+        # Upload multiple files
+        for _ in range(5):
+            await files_provider.openai_upload_file(file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+
+        # List with limit
+        result = await files_provider.openai_list_files(limit=3)
+        assert len(result.data) == 3
+
+    @pytest.mark.asyncio
+    async def test_list_files_with_order(self, files_provider, sample_text_file):
+        """Test listing files with different order."""
+        # Upload multiple files
+        files = []
+        for _ in range(3):
+            file = await files_provider.openai_upload_file(file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+            files.append(file)
+
+        # Test descending order (default)
+        result_desc = await files_provider.openai_list_files(order=Order.desc)
+        assert len(result_desc.data) == 3
+        # Most recent should be first
+        assert result_desc.data[0].created_at >= result_desc.data[1].created_at >= result_desc.data[2].created_at
+
+        # Test ascending order
+        result_asc = await files_provider.openai_list_files(order=Order.asc)
+        assert len(result_asc.data) == 3
+        # Oldest should be first
+        assert result_asc.data[0].created_at <= result_asc.data[1].created_at <= result_asc.data[2].created_at
+
+    @pytest.mark.asyncio
+    async def test_retrieve_file_success(self, files_provider, sample_text_file):
+        """Test successful file retrieval."""
+        # Upload file
+        uploaded_file = await files_provider.openai_upload_file(
+            file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        # Retrieve file
+        retrieved_file = await files_provider.openai_retrieve_file(uploaded_file.id)
+
+        # Verify response
+        assert retrieved_file.id == uploaded_file.id
+        assert retrieved_file.filename == uploaded_file.filename
+        assert retrieved_file.purpose == uploaded_file.purpose
+        assert retrieved_file.bytes == uploaded_file.bytes
+        assert retrieved_file.created_at == uploaded_file.created_at
+        assert retrieved_file.expires_at == uploaded_file.expires_at
+
+    @pytest.mark.asyncio
+    async def test_retrieve_file_not_found(self, files_provider):
+        """Test retrieving a non-existent file."""
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
+            await files_provider.openai_retrieve_file("file-nonexistent")
+
+    @pytest.mark.asyncio
+    async def test_retrieve_file_content_success(self, files_provider, sample_text_file):
+        """Test successful file content retrieval."""
+        # Upload file
+        uploaded_file = await files_provider.openai_upload_file(
+            file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        # Retrieve file content
+        content = await files_provider.openai_retrieve_file_content(uploaded_file.id)
+
+        # Verify content
+        assert content.body == sample_text_file.content
+
+    @pytest.mark.asyncio
+    async def test_retrieve_file_content_not_found(self, files_provider):
+        """Test retrieving content of a non-existent file."""
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
+            await files_provider.openai_retrieve_file_content("file-nonexistent")
+
+    @pytest.mark.asyncio
+    async def test_delete_file_success(self, files_provider, sample_text_file):
+        """Test successful file deletion."""
+        # Upload file
+        uploaded_file = await files_provider.openai_upload_file(
+            file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        # Verify file exists
+        await files_provider.openai_retrieve_file(uploaded_file.id)
+
+        # Delete file
+        delete_response = await files_provider.openai_delete_file(uploaded_file.id)
+
+        # Verify delete response
+        assert delete_response.id == uploaded_file.id
+        assert delete_response.deleted is True
+
+        # Verify file no longer exists
+        with pytest.raises(ValueError, match=f"File with id {uploaded_file.id} not found"):
+            await files_provider.openai_retrieve_file(uploaded_file.id)
+
+    @pytest.mark.asyncio
+    async def test_delete_file_not_found(self, files_provider):
+        """Test deleting a non-existent file."""
+        with pytest.raises(ValueError, match="File with id file-nonexistent not found"):
+            await files_provider.openai_delete_file("file-nonexistent")
+
+    @pytest.mark.asyncio
+    async def test_file_persistence_across_operations(self, files_provider, sample_text_file):
+        """Test that files persist correctly across multiple operations."""
+        # Upload file
+        uploaded_file = await files_provider.openai_upload_file(
+            file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        # Verify it appears in listing
+        files_list = await files_provider.openai_list_files()
+        assert len(files_list.data) == 1
+        assert files_list.data[0].id == uploaded_file.id
+
+        # Retrieve file info
+        retrieved_file = await files_provider.openai_retrieve_file(uploaded_file.id)
+        assert retrieved_file.id == uploaded_file.id
+
+        # Retrieve file content
+        content = await files_provider.openai_retrieve_file_content(uploaded_file.id)
+        assert content.body == sample_text_file.content
+
+        # Delete file
+        await files_provider.openai_delete_file(uploaded_file.id)
+
+        # Verify it's gone from listing
+        files_list = await files_provider.openai_list_files()
+        assert len(files_list.data) == 0
+
+    @pytest.mark.asyncio
+    async def test_multiple_files_operations(self, files_provider, sample_text_file, sample_json_file):
+        """Test operations with multiple files."""
+        # Upload multiple files
+        file1 = await files_provider.openai_upload_file(file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+        file2 = await files_provider.openai_upload_file(file=sample_json_file, purpose=OpenAIFilePurpose.ASSISTANTS)
+
+        # Verify both exist
+        files_list = await files_provider.openai_list_files()
+        assert len(files_list.data) == 2
+
+        # Delete one file
+        await files_provider.openai_delete_file(file1.id)
+
+        # Verify only one remains
+        files_list = await files_provider.openai_list_files()
+        assert len(files_list.data) == 1
+        assert files_list.data[0].id == file2.id
+
+        # Verify the remaining file is still accessible
+        content = await files_provider.openai_retrieve_file_content(file2.id)
+        assert content.body == sample_json_file.content
+
+    @pytest.mark.asyncio
+    async def test_file_id_uniqueness(self, files_provider, sample_text_file):
+        """Test that each uploaded file gets a unique ID."""
+        file_ids = set()
+
+        # Upload same file multiple times
+        for _ in range(10):
+            uploaded_file = await files_provider.openai_upload_file(
+                file=sample_text_file, purpose=OpenAIFilePurpose.ASSISTANTS
+            )
+            assert uploaded_file.id not in file_ids, f"Duplicate file ID: {uploaded_file.id}"
+            file_ids.add(uploaded_file.id)
+            assert uploaded_file.id.startswith("file-")
+
+    @pytest.mark.asyncio
+    async def test_file_no_filename_handling(self, files_provider):
+        """Test handling files with no filename."""
+        file_without_name = MockUploadFile(b"content", None)  # No filename
+
+        uploaded_file = await files_provider.openai_upload_file(
+            file=file_without_name, purpose=OpenAIFilePurpose.ASSISTANTS
+        )
+
+        assert uploaded_file.filename == "uploaded_file"  # Default filename
+
+    @pytest.mark.asyncio
+    async def test_after_pagination_not_implemented(self, files_provider):
+        """Test that 'after' pagination raises NotImplementedError."""
+        with pytest.raises(NotImplementedError, match="After pagination not yet implemented"):
+            await files_provider.openai_list_files(after="file-some-id")