From 18cc93f6c88a4f78eda09984dbb2e72589fb688f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Kacper=20=C5=81ukawski?= Date: Mon, 10 Mar 2025 09:25:02 +0100 Subject: [PATCH] Implement the server with FastMCP --- pyproject.toml | 6 +- src/mcp_server_qdrant/__init__.py | 2 +- src/mcp_server_qdrant/custom_server.py | 137 -- src/mcp_server_qdrant/embeddings/factory.py | 15 +- src/mcp_server_qdrant/embeddings/fastembed.py | 2 +- src/mcp_server_qdrant/handlers/__init__.py | 0 src/mcp_server_qdrant/handlers/decorators.py | 13 - src/mcp_server_qdrant/handlers/memory.py | 0 src/mcp_server_qdrant/helper.py | 10 - src/mcp_server_qdrant/qdrant.py | 10 +- src/mcp_server_qdrant/server.py | 266 ++-- src/mcp_server_qdrant/settings.py | 101 ++ tests/test_config.py | 61 + tests/test_custom_server.py | 100 -- tests/test_fastembed_integration.py | 63 + uv.lock | 1357 +++++++++-------- 16 files changed, 1079 insertions(+), 1064 deletions(-) delete mode 100644 src/mcp_server_qdrant/custom_server.py delete mode 100644 src/mcp_server_qdrant/handlers/__init__.py delete mode 100644 src/mcp_server_qdrant/handlers/decorators.py delete mode 100644 src/mcp_server_qdrant/handlers/memory.py delete mode 100644 src/mcp_server_qdrant/helper.py create mode 100644 src/mcp_server_qdrant/settings.py create mode 100644 tests/test_config.py delete mode 100644 tests/test_custom_server.py create mode 100644 tests/test_fastembed_integration.py diff --git a/pyproject.toml b/pyproject.toml index d796ee2..98ad061 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,8 +6,10 @@ readme = "README.md" requires-python = ">=3.10" license = "Apache-2.0" dependencies = [ - "mcp>=0.9.1", - "qdrant-client[fastembed]>=1.12.0", + "mcp[cli]>=1.3.0", + "fastembed>=0.6.0", + "qdrant-client>=1.12.0", + "typer>=0.15.2", ] [build-system] diff --git a/src/mcp_server_qdrant/__init__.py b/src/mcp_server_qdrant/__init__.py index 32ddcf8..50f6835 100644 --- a/src/mcp_server_qdrant/__init__.py +++ b/src/mcp_server_qdrant/__init__.py @@ -3,7 +3,7 @@ from . import server def main(): """Main entry point for the package.""" - server.main() + server.mcp.run() # Optionally expose other important items at package level diff --git a/src/mcp_server_qdrant/custom_server.py b/src/mcp_server_qdrant/custom_server.py deleted file mode 100644 index dcddfa2..0000000 --- a/src/mcp_server_qdrant/custom_server.py +++ /dev/null @@ -1,137 +0,0 @@ -import inspect -from typing import Any, Callable, Dict, List, Optional, get_type_hints - -from mcp import types -from mcp.server import Server - - -class QdrantMCPServer(Server): - """ - An MCP server that uses Qdrant to store and retrieve information. - """ - - def __init__(self, name: str = "Qdrant"): - super().__init__(name) - self._tool_handlers: Dict[str, Callable] = {} - self._tools: List[types.Tool] = [] - # This monkeypatching is required to make the server list the tools - # and handle tool calls. It simplifies the process of registering - # tool handlers. Please do not remove it. - self.handle_list_tool = self.list_tools()(self.handle_list_tool) - self.handle_tool_call = self.call_tool()(self.handle_tool_call) - - def register_tool( - self, - *, - description: str, - name: Optional[str] = None, - input_schema: Optional[dict[str, Any]] = None, - ): - """ - A decorator to register a tool with the server. The description is used - to generate the tool's metadata. - - Name is optional, and if not provided, the function's name will be used. - - :param description: The description of the tool. - :param name: The name of the tool. If not provided, the function's name will be used. - :param input_schema: The input schema for the tool. If not provided, it will be - automatically generated from the function's parameters. - """ - - def decorator(func: Callable): - def wrapper(fn): - nonlocal name, input_schema - - # Use function name if name not provided - if name is None: - name = fn.__name__ - - # If no input schema is provided, generate one from the function parameters - if input_schema is None: - input_schema = self.__parse_function_parameters(fn) - - # Create the tool definition - tool = types.Tool( - name=name, - description=description, - inputSchema=input_schema, - ) - - # Register in both collections - self._tool_handlers[name] = fn - self._tools.append(tool) - - return fn - - # Handle both @register_tool and @register_tool() syntax - if func is None: - return wrapper - return wrapper(func) - - return decorator - - async def handle_list_tool(self) -> List[types.Tool]: - """Expose the list of tools to the server.""" - return self._tools - - async def handle_tool_call( - self, name: str, arguments: dict | None - ) -> list[types.TextContent | types.ImageContent | types.EmbeddedResource]: - """Handle any tool call.""" - if name not in self._tool_handlers: - raise ValueError(f"Unknown tool: {name}") - return await self._tool_handlers[name](**arguments) - - @staticmethod - def __parse_function_parameters(func: Callable) -> Dict[str, Any]: - """ - Parse the parameters of a function to create an input schema. - - :param func: The function to parse. - :return: A dictionary representing the input schema. - """ - signature = inspect.signature(func) - type_hints = get_type_hints(func) - - properties = {} - required = [] - - for param_name, param in signature.parameters.items(): - # Skip self parameter for methods - if param_name == "self": - continue - - param_type = type_hints.get(param_name, Any) - param_schema = {"type": "string"} # Default to string - - # Map Python types to JSON Schema types - if param_type in (int, float): - param_schema["type"] = "number" - elif param_type is bool: - param_schema["type"] = "boolean" - elif param_type is list or getattr(param_type, "__origin__", None) is list: - param_schema["type"] = "array" - - # Get default value if any - if param.default is not inspect.Parameter.empty: - param_schema["default"] = param.default - else: - required.append(param_name) - - # Get description from docstring if available - if func.__doc__: - param_docs = [ - line.strip() - for line in func.__doc__.split("\n") - if f":param {param_name}:" in line - ] - if param_docs: - description = ( - param_docs[0].split(f":param {param_name}:")[1].strip() - ) - param_schema["description"] = description - - properties[param_name] = param_schema - - return {"type": "object", "properties": properties, "required": required} diff --git a/src/mcp_server_qdrant/embeddings/factory.py b/src/mcp_server_qdrant/embeddings/factory.py index c69a194..af73a75 100644 --- a/src/mcp_server_qdrant/embeddings/factory.py +++ b/src/mcp_server_qdrant/embeddings/factory.py @@ -1,17 +1,16 @@ from mcp_server_qdrant.embeddings import EmbeddingProvider +from mcp_server_qdrant.settings import EmbeddingProviderSettings -def create_embedding_provider(provider_type: str, model_name: str) -> EmbeddingProvider: +def create_embedding_provider(settings: EmbeddingProviderSettings) -> EmbeddingProvider: """ Create an embedding provider based on the specified type. - - :param provider_type: The type of embedding provider to create. - :param model_name: The name of the model to use for embeddings, specific to the provider type. + :param settings: The settings for the embedding provider. :return: An instance of the specified embedding provider. """ - if provider_type.lower() == "fastembed": - from .fastembed import FastEmbedProvider + if settings.provider_type.lower() == "fastembed": + from mcp_server_qdrant.embeddings.fastembed import FastEmbedProvider - return FastEmbedProvider(model_name) + return FastEmbedProvider(settings.model_name) else: - raise ValueError(f"Unsupported embedding provider: {provider_type}") + raise ValueError(f"Unsupported embedding provider: {settings.provider_type}") diff --git a/src/mcp_server_qdrant/embeddings/fastembed.py b/src/mcp_server_qdrant/embeddings/fastembed.py index acfeedf..9eb6b51 100644 --- a/src/mcp_server_qdrant/embeddings/fastembed.py +++ b/src/mcp_server_qdrant/embeddings/fastembed.py @@ -3,7 +3,7 @@ from typing import List from fastembed import TextEmbedding -from .base import EmbeddingProvider +from mcp_server_qdrant.embeddings.base import EmbeddingProvider class FastEmbedProvider(EmbeddingProvider): diff --git a/src/mcp_server_qdrant/handlers/__init__.py b/src/mcp_server_qdrant/handlers/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/mcp_server_qdrant/handlers/decorators.py b/src/mcp_server_qdrant/handlers/decorators.py deleted file mode 100644 index d04de89..0000000 --- a/src/mcp_server_qdrant/handlers/decorators.py +++ /dev/null @@ -1,13 +0,0 @@ -import functools -from typing import Callable - - -def register_task(func: Callable) -> Callable: - @functools.wraps(func) - async def wrapper(*args, **kwargs): - print(f"Starting task {func.__name__}") - result = await func(*args, **kwargs) - print(f"Finished task {func.__name__}") - return result - - return wrapper diff --git a/src/mcp_server_qdrant/handlers/memory.py b/src/mcp_server_qdrant/handlers/memory.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/mcp_server_qdrant/helper.py b/src/mcp_server_qdrant/helper.py deleted file mode 100644 index 659a81b..0000000 --- a/src/mcp_server_qdrant/helper.py +++ /dev/null @@ -1,10 +0,0 @@ -import importlib.metadata - - -def get_package_version() -> str: - """Get the package version using importlib.metadata.""" - try: - return importlib.metadata.version("mcp-server-qdrant") - except importlib.metadata.PackageNotFoundError: - # Fall back to a default version if package is not installed - return "0.0.0" diff --git a/src/mcp_server_qdrant/qdrant.py b/src/mcp_server_qdrant/qdrant.py index 4340fd0..ed6aac7 100644 --- a/src/mcp_server_qdrant/qdrant.py +++ b/src/mcp_server_qdrant/qdrant.py @@ -53,9 +53,9 @@ class QdrantConnector: }, ) - async def store_memory(self, information: str): + async def store(self, information: str): """ - Store a memory in the Qdrant collection. + Store some information in the Qdrant collection. :param information: The information to store. """ await self._ensure_collection_exists() @@ -76,11 +76,11 @@ class QdrantConnector: ], ) - async def find_memories(self, query: str) -> list[str]: + async def search(self, query: str) -> list[str]: """ - Find memories in the Qdrant collection. If there are no memories found, an empty list is returned. + Find points in the Qdrant collection. If there are no entries found, an empty list is returned. :param query: The query to use for the search. - :return: A list of memories found. + :return: A list of entries found. """ collection_exists = await self._client.collection_exists(self._collection_name) if not collection_exists: diff --git a/src/mcp_server_qdrant/server.py b/src/mcp_server_qdrant/server.py index 1725b17..fe36b80 100644 --- a/src/mcp_server_qdrant/server.py +++ b/src/mcp_server_qdrant/server.py @@ -1,170 +1,122 @@ -import asyncio -from typing import Optional +import logging +import os +from contextlib import asynccontextmanager +from typing import AsyncIterator, List -import click -import mcp -import mcp.types as types -from mcp.server import NotificationOptions, Server -from mcp.server.models import InitializationOptions +from mcp.server import Server +from mcp.server.fastmcp import Context, FastMCP -from .custom_server import QdrantMCPServer -from .embeddings.factory import create_embedding_provider -from .helper import get_package_version -from .qdrant import QdrantConnector +from mcp_server_qdrant.embeddings.factory import create_embedding_provider +from mcp_server_qdrant.qdrant import QdrantConnector +from mcp_server_qdrant.settings import ( + EmbeddingProviderSettings, + QdrantSettings, + parse_args, +) + +logger = logging.getLogger(__name__) + +# Parse command line arguments and set them as environment variables. +# This is done for backwards compatibility with the previous versions +# of the MCP server. +env_vars = parse_args() +for key, value in env_vars.items(): + os.environ[key] = value -def serve( - qdrant_connector: QdrantConnector, -) -> Server: +@asynccontextmanager +async def server_lifespan(server: Server) -> AsyncIterator[dict]: # noqa """ - Instantiate the server and configure tools to store and find memories in Qdrant. - :param qdrant_connector: An instance of QdrantConnector to use for storing and retrieving memories. + Context manager to handle the lifespan of the server. + This is used to configure the embedding provider and Qdrant connector. """ - server = QdrantMCPServer("qdrant") - - @server.register_tool( - name="qdrant-store-memory", - description=( - "Keep the memory for later use, when you are asked to remember something." - ), - ) - async def store_memory(information: str): - """ - Store a memory in Qdrant. - :param information: The information to store. - """ - nonlocal qdrant_connector - await qdrant_connector.store_memory(information) - return [types.TextContent(type="text", text=f"Remembered: {information}")] - - @server.register_tool( - name="qdrant-find-memories", - description=( - "Look up memories in Qdrant. Use this tool when you need to: \n" - " - Find memories by their content \n" - " - Access memories for further analysis \n" - " - Get some personal information about the user" - ), - ) - async def find_memories(query: str): - """ - Find memories in Qdrant. - :param query: The query to use for the search. - :return: A list of memories found. - """ - nonlocal qdrant_connector - memories = await qdrant_connector.find_memories(query) - content = [ - types.TextContent(type="text", text=f"Memories for the query '{query}'"), - ] - for memory in memories: - content.append( - types.TextContent(type="text", text=f"{memory}") - ) - return content - - return server - - -@click.command() -@click.option( - "--qdrant-url", - envvar="QDRANT_URL", - required=False, - help="Qdrant URL", -) -@click.option( - "--qdrant-api-key", - envvar="QDRANT_API_KEY", - required=False, - help="Qdrant API key", -) -@click.option( - "--collection-name", - envvar="COLLECTION_NAME", - required=True, - help="Collection name", -) -@click.option( - "--fastembed-model-name", - envvar="FASTEMBED_MODEL_NAME", - required=False, - help="FastEmbed model name", - default="sentence-transformers/all-MiniLM-L6-v2", -) -@click.option( - "--embedding-provider", - envvar="EMBEDDING_PROVIDER", - required=False, - help="Embedding provider to use", - default="fastembed", - type=click.Choice(["fastembed"], case_sensitive=False), -) -@click.option( - "--embedding-model", - envvar="EMBEDDING_MODEL", - required=False, - help="Embedding model name", - default="sentence-transformers/all-MiniLM-L6-v2", -) -@click.option( - "--qdrant-local-path", - envvar="QDRANT_LOCAL_PATH", - required=False, - help="Qdrant local path", -) -def main( - qdrant_url: Optional[str], - qdrant_api_key: str, - collection_name: Optional[str], - fastembed_model_name: Optional[str], - embedding_provider: str, - embedding_model: str, - qdrant_local_path: Optional[str], -): - # XOR of url and local path, since we accept only one of them - if not (bool(qdrant_url) ^ bool(qdrant_local_path)): - raise ValueError( - "Exactly one of qdrant-url or qdrant-local-path must be provided" + try: + # Embedding provider is created with a factory function so we can add + # some more providers in the future. Currently, only FastEmbed is supported. + embedding_provider_settings = EmbeddingProviderSettings() + embedding_provider = create_embedding_provider(embedding_provider_settings) + logger.info( + f"Using embedding provider {embedding_provider_settings.provider_type} with " + f"model {embedding_provider_settings.model_name}" ) - # Warn if fastembed_model_name is provided, as this is going to be deprecated - if fastembed_model_name: - click.echo( - "Warning: --fastembed-model-name parameter is deprecated and will be removed in a future version. " - "Please use --embedding-provider and --embedding-model instead", - err=True, + qdrant_configuration = QdrantSettings() + qdrant_connector = QdrantConnector( + qdrant_configuration.location, + qdrant_configuration.api_key, + qdrant_configuration.collection_name, + embedding_provider, + qdrant_configuration.local_path, + ) + logger.info( + f"Connecting to Qdrant at {qdrant_configuration.get_qdrant_location()}" ) - async def _run(): - async with mcp.server.stdio.stdio_server() as (read_stream, write_stream): - # Create the embedding provider - provider = create_embedding_provider( - provider_type=embedding_provider, model_name=embedding_model - ) + yield { + "embedding_provider": embedding_provider, + "qdrant_connector": qdrant_connector, + } + except Exception as e: + logger.error(e) + raise e + finally: + pass - # Create the Qdrant connector - qdrant_connector = QdrantConnector( - qdrant_url, - qdrant_api_key, - collection_name, - provider, - qdrant_local_path, - ) - # Create and run the server - server = serve(qdrant_connector) - await server.run( - read_stream, - write_stream, - InitializationOptions( - server_name="qdrant", - server_version=get_package_version(), - capabilities=server.get_capabilities( - notification_options=NotificationOptions(), - experimental_capabilities={}, - ), - ), - ) +mcp = FastMCP("Qdrant", lifespan=server_lifespan) - asyncio.run(_run()) + +@mcp.tool( + name="qdrant-store-memory", + description=( + "Keep the memory for later use, when you are asked to remember something." + ), +) +async def store(information: str, ctx: Context) -> str: + """ + Store a memory in Qdrant. + :param information: The information to store. + :param ctx: The context for the request. + :return: A message indicating that the information was stored. + """ + await ctx.debug(f"Storing information {information} in Qdrant") + qdrant_connector: QdrantConnector = ctx.request_context.lifespan_context[ + "qdrant_connector" + ] + await qdrant_connector.store(information) + return f"Remembered: {information}" + + +@mcp.tool( + name="qdrant-find-memories", + description=( + "Look up memories in Qdrant. Use this tool when you need to: \n" + " - Find memories by their content \n" + " - Access memories for further analysis \n" + " - Get some personal information about the user" + ), +) +async def find(query: str, ctx: Context) -> List[str]: + """ + Find memories in Qdrant. + :param query: The query to use for the search. + :param ctx: The context for the request. + :return: A list of entries found. + """ + await ctx.debug(f"Finding points for query {query}") + qdrant_connector: QdrantConnector = ctx.request_context.lifespan_context[ + "qdrant_connector" + ] + entries = await qdrant_connector.search(query) + if not entries: + return [f"No memories found for the query '{query}'"] + content = [ + f"Memories for the query '{query}'", + ] + for entry in entries: + content.append(f"{entry}") + return content + + +if __name__ == "__main__": + mcp.run() diff --git a/src/mcp_server_qdrant/settings.py b/src/mcp_server_qdrant/settings.py new file mode 100644 index 0000000..e0aa6d0 --- /dev/null +++ b/src/mcp_server_qdrant/settings.py @@ -0,0 +1,101 @@ +import argparse +from typing import Any, Dict, Optional + +from pydantic import Field +from pydantic_settings import BaseSettings + + +class EmbeddingProviderSettings(BaseSettings): + """ + Configuration for the embedding provider. + """ + + provider_type: str = Field( + default="fastembed", validation_alias="EMBEDDING_PROVIDER" + ) + model_name: str = Field( + default="sentence-transformers/all-MiniLM-L6-v2", + validation_alias="EMBEDDING_MODEL", + ) + + +class QdrantSettings(BaseSettings): + """ + Configuration for the Qdrant connector. + """ + + location: Optional[str] = Field(default=None, validation_alias="QDRANT_URL") + api_key: Optional[str] = Field(default=None, validation_alias="QDRANT_API_KEY") + collection_name: str = Field(validation_alias="COLLECTION_NAME") + local_path: Optional[str] = Field( + default=None, validation_alias="QDRANT_LOCAL_PATH" + ) + + def get_qdrant_location(self) -> str: + """ + Get the Qdrant location, either the URL or the local path. + """ + return self.location or self.local_path + + +def parse_args() -> Dict[str, Any]: + """ + Parse command line arguments for the MCP server. + + Returns: + Dict[str, Any]: Dictionary of parsed arguments + """ + parser = argparse.ArgumentParser(description="Qdrant MCP Server") + + # Qdrant connection options + connection_group = parser.add_mutually_exclusive_group() + connection_group.add_argument( + "--qdrant-url", + help="URL of the Qdrant server, e.g. http://localhost:6333", + ) + connection_group.add_argument( + "--qdrant-local-path", + help="Path to the local Qdrant database", + ) + + # Other Qdrant settings + parser.add_argument( + "--qdrant-api-key", + help="API key for the Qdrant server", + ) + parser.add_argument( + "--collection-name", + help="Name of the collection to use", + ) + + # Embedding settings + parser.add_argument( + "--embedding-provider", + help="Embedding provider to use (currently only 'fastembed' is supported)", + ) + parser.add_argument( + "--embedding-model", + help="Name of the embedding model to use", + ) + + args = parser.parse_args() + + # Convert to dictionary and filter out None values + args_dict = {k: v for k, v in vars(args).items() if v is not None} + + # Convert argument names to environment variable format + env_vars = {} + if "qdrant_url" in args_dict: + env_vars["QDRANT_URL"] = args_dict["qdrant_url"] + if "qdrant_api_key" in args_dict: + env_vars["QDRANT_API_KEY"] = args_dict["qdrant_api_key"] + if "collection_name" in args_dict: + env_vars["COLLECTION_NAME"] = args_dict["collection_name"] + if "embedding_model" in args_dict: + env_vars["EMBEDDING_MODEL"] = args_dict["embedding_model"] + if "embedding_provider" in args_dict: + env_vars["EMBEDDING_PROVIDER"] = args_dict["embedding_provider"] + if "qdrant_local_path" in args_dict: + env_vars["QDRANT_LOCAL_PATH"] = args_dict["qdrant_local_path"] + + return env_vars diff --git a/tests/test_config.py b/tests/test_config.py new file mode 100644 index 0000000..ab0a057 --- /dev/null +++ b/tests/test_config.py @@ -0,0 +1,61 @@ +import os +from unittest.mock import patch + +import pytest + +from mcp_server_qdrant.settings import EmbeddingProviderSettings, QdrantSettings + + +class TestQdrantSettings: + def test_default_values(self): + """Test that required fields raise errors when not provided.""" + with pytest.raises(ValueError): + # Should raise error because required fields are missing + QdrantSettings() + + @patch.dict( + os.environ, + {"QDRANT_URL": "http://localhost:6333", "COLLECTION_NAME": "test_collection"}, + ) + def test_minimal_config(self): + """Test loading minimal configuration from environment variables.""" + settings = QdrantSettings() + assert settings.location == "http://localhost:6333" + assert settings.collection_name == "test_collection" + assert settings.api_key is None + assert settings.local_path is None + + @patch.dict( + os.environ, + { + "QDRANT_URL": "http://qdrant.example.com:6333", + "QDRANT_API_KEY": "test_api_key", + "COLLECTION_NAME": "my_memories", + "QDRANT_LOCAL_PATH": "/tmp/qdrant", + }, + ) + def test_full_config(self): + """Test loading full configuration from environment variables.""" + settings = QdrantSettings() + assert settings.location == "http://qdrant.example.com:6333" + assert settings.api_key == "test_api_key" + assert settings.collection_name == "my_memories" + assert settings.local_path == "/tmp/qdrant" + + +class TestEmbeddingProviderSettings: + def test_default_values(self): + """Test default values are set correctly.""" + settings = EmbeddingProviderSettings() + assert settings.provider_type == "fastembed" + assert settings.model_name == "sentence-transformers/all-MiniLM-L6-v2" + + @patch.dict( + os.environ, + {"EMBEDDING_PROVIDER": "custom_provider", "EMBEDDING_MODEL": "custom_model"}, + ) + def test_custom_values(self): + """Test loading custom values from environment variables.""" + settings = EmbeddingProviderSettings() + assert settings.provider_type == "custom_provider" + assert settings.model_name == "custom_model" diff --git a/tests/test_custom_server.py b/tests/test_custom_server.py deleted file mode 100644 index b506c25..0000000 --- a/tests/test_custom_server.py +++ /dev/null @@ -1,100 +0,0 @@ -import pytest - -from src.mcp_server_qdrant.custom_server import QdrantMCPServer - - -def test_register_tool_decorator(): - """Test that the register_tool method works as a decorator and correctly parses parameters.""" - server = QdrantMCPServer() - - @server.register_tool(description="Test function with different parameter types") - def test_function(text_param: str, number_param: int, flag_param: bool = False): - """ - A test function with different parameter types. - - :param text_param: A string parameter - :param number_param: An integer parameter - :param flag_param: A boolean parameter with default - """ - return f"{text_param} {number_param} {flag_param}" - - # Check that the function was registered in tool_handlers - assert "test_function" in server._tool_handlers - assert server._tool_handlers["test_function"] == test_function - - # Check that the tool was added to tools list - assert len(server._tools) == 1 - tool = server._tools[0] - assert tool.name == "test_function" - assert tool.description == "Test function with different parameter types" - - # Check the generated schema - schema = tool.inputSchema - assert schema["type"] == "object" - - # Check properties - properties = schema["properties"] - assert "text_param" in properties - assert properties["text_param"]["type"] == "string" - assert "description" in properties["text_param"] - - assert "number_param" in properties - assert properties["number_param"]["type"] == "number" - - assert "flag_param" in properties - assert properties["flag_param"]["type"] == "boolean" - assert "default" in properties["flag_param"] - assert properties["flag_param"]["default"] is False - - # Check required fields - assert "required" in schema - assert "text_param" in schema["required"] - assert "number_param" in schema["required"] - assert "flag_param" not in schema["required"] # Has default value - - -@pytest.mark.asyncio -async def test_handle_list_tool(): - """Test that handle_list_tool returns all registered tools.""" - server = QdrantMCPServer() - - # Register multiple tools - @server.register_tool(description="First test tool") - def tool_one(param1: str): - """First tool.""" - return param1 - - @server.register_tool(description="Second test tool") - def tool_two(param1: int, param2: bool = True): - """Second tool.""" - return param1, param2 - - @server.register_tool(name="custom_name", description="Tool with custom name") - def tool_three(param1: str): - """Third tool with custom name.""" - return param1 - - # Get the list of tools - tools = await server.handle_list_tool() - - # Check that all tools are returned - assert len(tools) == 3 - - # Check tool names - tool_names = [tool.name for tool in tools] - assert "tool_one" in tool_names - assert "tool_two" in tool_names - assert "custom_name" in tool_names - assert "tool_three" not in tool_names # Should use custom name instead - - # Check tool descriptions - descriptions = {tool.name: tool.description for tool in tools} - assert descriptions["tool_one"] == "First test tool" - assert descriptions["tool_two"] == "Second test tool" - assert descriptions["custom_name"] == "Tool with custom name" - - # Check schemas are properly generated - for tool in tools: - assert tool.inputSchema is not None - assert tool.inputSchema["type"] == "object" - assert "properties" in tool.inputSchema diff --git a/tests/test_fastembed_integration.py b/tests/test_fastembed_integration.py new file mode 100644 index 0000000..8381dd7 --- /dev/null +++ b/tests/test_fastembed_integration.py @@ -0,0 +1,63 @@ +import numpy as np +import pytest +from fastembed import TextEmbedding + +from mcp_server_qdrant.embeddings.fastembed import FastEmbedProvider + + +@pytest.mark.asyncio +class TestFastEmbedProviderIntegration: + """Integration tests for FastEmbedProvider.""" + + async def test_initialization(self): + """Test that the provider can be initialized with a valid model.""" + provider = FastEmbedProvider("sentence-transformers/all-MiniLM-L6-v2") + assert provider.model_name == "sentence-transformers/all-MiniLM-L6-v2" + assert isinstance(provider.embedding_model, TextEmbedding) + + async def test_embed_documents(self): + """Test that documents can be embedded.""" + provider = FastEmbedProvider("sentence-transformers/all-MiniLM-L6-v2") + documents = ["This is a test document.", "This is another test document."] + + embeddings = await provider.embed_documents(documents) + + # Check that we got the right number of embeddings + assert len(embeddings) == len(documents) + + # Check that embeddings have the expected shape + # The exact dimension depends on the model, but should be consistent + assert len(embeddings[0]) > 0 + assert all(len(embedding) == len(embeddings[0]) for embedding in embeddings) + + # Check that embeddings are different for different documents + # Convert to numpy arrays for easier comparison + embedding1 = np.array(embeddings[0]) + embedding2 = np.array(embeddings[1]) + assert not np.array_equal(embedding1, embedding2) + + async def test_embed_query(self): + """Test that queries can be embedded.""" + provider = FastEmbedProvider("sentence-transformers/all-MiniLM-L6-v2") + query = "This is a test query." + + embedding = await provider.embed_query(query) + + # Check that embedding has the expected shape + assert len(embedding) > 0 + + # Embed the same query again to check consistency + embedding2 = await provider.embed_query(query) + assert len(embedding) == len(embedding2) + + # The embeddings should be identical for the same input + np.testing.assert_array_almost_equal(np.array(embedding), np.array(embedding2)) + + def test_get_vector_name(self): + """Test that the vector name is generated 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