From 63d649b0f48986ef00e032164bab619ffc8689c6 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Sebasti=C3=A1n=20Est=C3=A9vez?= Date: Thu, 2 Jan 2025 23:45:54 -0500 Subject: [PATCH] feat: add anthropic mcp endpoint (#5148) * mcp WIP * [autofix.ci] apply automated fixes * logging and flow user check * mcp stdio client component * handle disconnect better * initialization * session fix and type fix * [autofix.ci] apply automated fixes * defensive against mcp server bugs * [autofix.ci] apply automated fixes * notifications and sse component * enabled flags and resource support * remove unneeded print * extract json schema util * [autofix.ci] apply automated fixes * ruff * fix tools [] bug and db asysnc session api change * Tool instead of StructuredTool * ruff fixes * ruff * validation optimization * fix frontend test * another playwright fix * Update src/frontend/tests/extended/features/notifications.spec.ts Co-authored-by: Gabriel Luiz Freitas Almeida * mcp component descriptions * mypy fixes * fix setup_database_url test --------- Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com> Co-authored-by: Gabriel Luiz Freitas Almeida --- pyproject.toml | 4 +- src/backend/base/langflow/api/router.py | 5 + src/backend/base/langflow/api/v1/__init__.py | 2 + src/backend/base/langflow/api/v1/mcp.py | 343 ++++++ .../base/langflow/base/mcp/__init__.py | 0 src/backend/base/langflow/base/mcp/util.py | 26 + .../langflow/components/tools/__init__.py | 2 + .../base/langflow/components/tools/mcp_sse.py | 98 ++ .../langflow/components/tools/mcp_stdio.py | 122 ++ src/backend/base/langflow/helpers/flow.py | 44 + .../base/langflow/services/settings/base.py | 6 + .../tests/performance/test_server_init.py | 8 +- .../regression/generalBugs-shard-3.spec.ts | 2 +- uv.lock | 1092 +++++++++-------- 14 files changed, 1229 insertions(+), 525 deletions(-) create mode 100644 src/backend/base/langflow/api/v1/mcp.py create mode 100644 src/backend/base/langflow/base/mcp/__init__.py create mode 100644 src/backend/base/langflow/base/mcp/util.py create mode 100644 src/backend/base/langflow/components/tools/mcp_sse.py create mode 100644 src/backend/base/langflow/components/tools/mcp_stdio.py diff --git a/pyproject.toml b/pyproject.toml index 51c7909f8..a7494bb52 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -113,8 +113,10 @@ dependencies = [ "aiofile>=3.9.0,<4.0.0", "sseclient-py==1.8.0", "arize-phoenix-otel>=0.6.1", - "openinference-instrumentation-langchain==0.1.29", + "openinference-instrumentation-langchain>=0.1.29", "crewai~=0.86.0", + "mcp>=0.9.1", + "uv>=0.5.7", "ag2", "pydantic-ai>=0.0.12", ] diff --git a/src/backend/base/langflow/api/router.py b/src/backend/base/langflow/api/router.py index d2ce1905a..39339035e 100644 --- a/src/backend/base/langflow/api/router.py +++ b/src/backend/base/langflow/api/router.py @@ -9,6 +9,7 @@ from langflow.api.v1 import ( flows_router, folders_router, login_router, + mcp_router, monitor_router, starter_projects_router, store_router, @@ -16,6 +17,7 @@ from langflow.api.v1 import ( validate_router, variables_router, ) +from langflow.services.deps import get_settings_service router = APIRouter( prefix="/api/v1", @@ -33,3 +35,6 @@ router.include_router(files_router) router.include_router(monitor_router) router.include_router(folders_router) router.include_router(starter_projects_router) + +if get_settings_service().settings.mcp_server_enabled: + router.include_router(mcp_router) diff --git a/src/backend/base/langflow/api/v1/__init__.py b/src/backend/base/langflow/api/v1/__init__.py index 48383770a..567415af1 100644 --- a/src/backend/base/langflow/api/v1/__init__.py +++ b/src/backend/base/langflow/api/v1/__init__.py @@ -5,6 +5,7 @@ from langflow.api.v1.files import router as files_router from langflow.api.v1.flows import router as flows_router from langflow.api.v1.folders import router as folders_router from langflow.api.v1.login import router as login_router +from langflow.api.v1.mcp import router as mcp_router from langflow.api.v1.monitor import router as monitor_router from langflow.api.v1.starter_projects import router as starter_projects_router from langflow.api.v1.store import router as store_router @@ -20,6 +21,7 @@ __all__ = [ "flows_router", "folders_router", "login_router", + "mcp_router", "monitor_router", "starter_projects_router", "store_router", diff --git a/src/backend/base/langflow/api/v1/mcp.py b/src/backend/base/langflow/api/v1/mcp.py new file mode 100644 index 000000000..0fbf08ee4 --- /dev/null +++ b/src/backend/base/langflow/api/v1/mcp.py @@ -0,0 +1,343 @@ +import asyncio +import base64 +import json +import logging +import traceback +from contextlib import suppress +from contextvars import ContextVar +from typing import Annotated +from urllib.parse import quote, unquote, urlparse +from uuid import UUID, uuid4 + +import pydantic +from anyio import BrokenResourceError +from fastapi import APIRouter, Depends, Request +from fastapi.responses import StreamingResponse +from mcp import types +from mcp.server import NotificationOptions, Server +from mcp.server.sse import SseServerTransport +from sqlmodel import select +from starlette.background import BackgroundTasks + +from langflow.api.v1.chat import build_flow +from langflow.api.v1.schemas import InputValueRequest +from langflow.helpers.flow import json_schema_from_flow +from langflow.services.auth.utils import get_current_active_user +from langflow.services.database.models import Flow, User +from langflow.services.deps import get_db_service, get_session, get_settings_service, get_storage_service +from langflow.services.storage.utils import build_content_type_from_extension + +logger = logging.getLogger(__name__) +if False: + logger.setLevel(logging.DEBUG) + if not logger.handlers: + handler = logging.StreamHandler() + handler.setLevel(logging.DEBUG) + formatter = logging.Formatter("[%(asctime)s][%(levelname)s] %(message)s") + handler.setFormatter(formatter) + logger.addHandler(handler) + + # Enable debug logging for MCP package + mcp_logger = logging.getLogger("mcp") + mcp_logger.setLevel(logging.DEBUG) + if not mcp_logger.handlers: + mcp_logger.addHandler(handler) + + logger.debug("MCP module loaded - debug logging enabled") + +enable_progress_notifications = get_settings_service().settings.mcp_server_enable_progress_notifications + +router = APIRouter(prefix="/mcp", tags=["mcp"]) + +server = Server("langflow-mcp-server") + +# Create a context variable to store the current user +current_user_ctx: ContextVar[User] = ContextVar("current_user_ctx") + +# Define constants +MAX_RETRIES = 2 + + +@server.list_prompts() +async def handle_list_prompts(): + return [] + + +@server.list_resources() +async def handle_list_resources(): + resources = [] + try: + session = await anext(get_session()) + storage_service = get_storage_service() + settings_service = get_settings_service() + + # Build full URL from settings + host = getattr(settings_service.settings, "holst", "localhost") + port = getattr(settings_service.settings, "port", 3000) + + base_url = f"http://{host}:{port}".rstrip("/") + + flows = (await session.exec(select(Flow))).all() + + for flow in flows: + if flow.id: + try: + files = await storage_service.list_files(flow_id=str(flow.id)) + for file_name in files: + # URL encode the filename + safe_filename = quote(file_name) + resource = types.Resource( + uri=f"{base_url}/api/v1/files/{flow.id}/{safe_filename}", + name=file_name, + description=f"File in flow: {flow.name}", + mimeType=build_content_type_from_extension(file_name), + ) + resources.append(resource) + except FileNotFoundError as e: + msg = f"Error listing files for flow {flow.id}: {e}" + logger.debug(msg) + continue + except Exception as e: + msg = f"Error in listing resources: {e!s}" + logger.exception(msg) + trace = traceback.format_exc() + logger.exception(trace) + raise + return resources + + +@server.read_resource() +async def handle_read_resource(uri: str) -> bytes: + """Handle resource read requests.""" + try: + # Parse the URI properly + parsed_uri = urlparse(str(uri)) + # Path will be like /api/v1/files/{flow_id}/{filename} + path_parts = parsed_uri.path.split("/") + # Remove empty strings from split + path_parts = [p for p in path_parts if p] + + # The flow_id and filename should be the last two parts + two = 2 + if len(path_parts) < two: + msg = f"Invalid URI format: {uri}" + raise ValueError(msg) + + flow_id = path_parts[-2] + filename = unquote(path_parts[-1]) # URL decode the filename + + storage_service = get_storage_service() + + # Read the file content + content = await storage_service.get_file(flow_id=flow_id, file_name=filename) + if not content: + msg = f"File {filename} not found in flow {flow_id}" + raise ValueError(msg) + + # Ensure content is base64 encoded + if isinstance(content, str): + content = content.encode() + return base64.b64encode(content) + except Exception as e: + msg = f"Error reading resource {uri}: {e!s}" + logger.exception(msg) + trace = traceback.format_exc() + logger.exception(trace) + raise + + +@server.list_tools() +async def handle_list_tools(): + tools = [] + try: + session = await anext(get_session()) + flows = (await session.exec(select(Flow))).all() + + for flow in flows: + if flow.user_id is None: + continue + + tool = types.Tool( + name=str(flow.id), # Use flow.id instead of name + description=f"{flow.name}: {flow.description}" + if flow.description + else f"Tool generated from flow: {flow.name}", + inputSchema=json_schema_from_flow(flow), + ) + tools.append(tool) + except Exception as e: + msg = f"Error in listing tools: {e!s}" + logger.exception(msg) + trace = traceback.format_exc() + logger.exception(trace) + raise + return tools + + +@server.call_tool() +async def handle_call_tool(name: str, arguments: dict) -> list[types.TextContent]: + """Handle tool execution requests.""" + try: + session = await anext(get_session()) + background_tasks = BackgroundTasks() + + current_user = current_user_ctx.get() + flow = (await session.exec(select(Flow).where(Flow.id == UUID(name)))).first() + + if not flow: + msg = f"Flow with id '{name}' not found" + raise ValueError(msg) + + # Process inputs + processed_inputs = dict(arguments) + + # Initial progress notification + if enable_progress_notifications and (progress_token := server.request_context.meta.progressToken): + await server.request_context.session.send_progress_notification( + progress_token=progress_token, progress=0.0, total=1.0 + ) + + conversation_id = str(uuid4()) + input_request = InputValueRequest( + input_value=processed_inputs.get("input_value", ""), components=[], type="chat", session=conversation_id + ) + + async def send_progress_updates(): + if not (enable_progress_notifications and server.request_context.meta.progressToken): + return + + try: + progress = 0.0 + while True: + await server.request_context.session.send_progress_notification( + progress_token=progress_token, progress=min(0.9, progress), total=1.0 + ) + progress += 0.1 + await asyncio.sleep(1.0) + except asyncio.CancelledError: + # Send final 100% progress + if enable_progress_notifications: + await server.request_context.session.send_progress_notification( + progress_token=progress_token, progress=1.0, total=1.0 + ) + raise + + db_service = get_db_service() + collected_results = [] + async with db_service.with_session() as async_session: + try: + progress_task = asyncio.create_task(send_progress_updates()) + + try: + response = await build_flow( + flow_id=UUID(name), + inputs=input_request, + background_tasks=background_tasks, + current_user=current_user, + session=async_session, + ) + + async for line in response.body_iterator: + if not line: + continue + try: + event_data = json.loads(line) + if event_data.get("event") == "end_vertex": + message = ( + event_data.get("data", {}) + .get("build_data", {}) + .get("data", {}) + .get("results", {}) + .get("message", {}) + .get("text", "") + ) + if message: + collected_results.append(types.TextContent(type="text", text=str(message))) + except json.JSONDecodeError: + msg = f"Failed to parse event data: {line}" + logger.warning(msg) + continue + + return collected_results + finally: + progress_task.cancel() + with suppress(asyncio.CancelledError): + await progress_task + except Exception as e: + msg = f"Error in async session: {e}" + logger.exception(msg) + raise + + except Exception as e: + context = server.request_context + # Send error progress if there's an exception + if enable_progress_notifications and (progress_token := context.meta.progressToken): + await server.request_context.session.send_progress_notification( + progress_token=progress_token, progress=1.0, total=1.0 + ) + msg = f"Error executing tool {name}: {e!s}" + logger.exception(msg) + trace = traceback.format_exc() + logger.exception(trace) + raise + + +sse = SseServerTransport("/api/v1/mcp/") + + +def find_validation_error(exc): + """Searches for a pydantic.ValidationError in the exception chain.""" + while exc: + if isinstance(exc, pydantic.ValidationError): + return exc + exc = getattr(exc, "__cause__", None) or getattr(exc, "__context__", None) + return None + + +@router.get("/sse", response_class=StreamingResponse) +async def handle_sse(request: Request, current_user: Annotated[User, Depends(get_current_active_user)]): + token = current_user_ctx.set(current_user) + try: + async with sse.connect_sse(request.scope, request.receive, request._send) as streams: + try: + msg = "Starting SSE connection" + logger.debug(msg) + msg = f"Stream types: read={type(streams[0])}, write={type(streams[1])}" + logger.debug(msg) + + notification_options = NotificationOptions( + prompts_changed=True, resources_changed=True, tools_changed=True + ) + init_options = server.create_initialization_options(notification_options) + msg = f"Initialization options: {init_options}" + logger.debug(msg) + + try: + await server.run(streams[0], streams[1], init_options) + except Exception as exc: # noqa: BLE001 + validation_error = find_validation_error(exc) + if validation_error: + msg = "Validation error in MCP:" + str(validation_error) + logger.debug(msg) + else: + msg = f"Error in MCP: {exc!s}" + logger.debug(msg) + return + except BrokenResourceError: + # Handle gracefully when client disconnects + logger.info("Client disconnected from SSE connection") + except asyncio.CancelledError: + logger.info("SSE connection was cancelled") + except Exception as e: + msg = f"Error in MCP: {e!s}" + logger.exception(msg) + trace = traceback.format_exc() + logger.exception(trace) + raise + finally: + current_user_ctx.reset(token) + + +@router.post("/") +async def handle_messages(request: Request): + await sse.handle_post_message(request.scope, request.receive, request._send) diff --git a/src/backend/base/langflow/base/mcp/__init__.py b/src/backend/base/langflow/base/mcp/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/base/langflow/base/mcp/util.py b/src/backend/base/langflow/base/mcp/util.py new file mode 100644 index 000000000..e4b867b0d --- /dev/null +++ b/src/backend/base/langflow/base/mcp/util.py @@ -0,0 +1,26 @@ +import asyncio +from collections.abc import Awaitable, Callable + +from langflow.helpers.base_model import BaseModel + + +def create_tool_coroutine(tool_name: str, arg_schema: type[BaseModel], session) -> Callable[[dict], Awaitable]: + async def tool_coroutine(*args): + if len(args) == 0: + msg = f"at least one positional argument is required {args}" + raise ValueError(msg) + arg_dict = dict(zip(arg_schema.model_fields.keys(), args, strict=False)) + return await session.call_tool(tool_name, arguments=arg_dict) + + return tool_coroutine + + +def create_tool_func(tool_name: str, session) -> Callable[..., str]: + def tool_func(**kwargs): + if len(kwargs) == 0: + msg = f"at least one named argument is required {kwargs}" + raise ValueError(msg) + loop = asyncio.get_event_loop() + return loop.run_until_complete(session.call_tool(tool_name, arguments=kwargs)) + + return tool_func diff --git a/src/backend/base/langflow/components/tools/__init__.py b/src/backend/base/langflow/components/tools/__init__.py index 17b5d11c6..707ecd075 100644 --- a/src/backend/base/langflow/components/tools/__init__.py +++ b/src/backend/base/langflow/components/tools/__init__.py @@ -9,6 +9,7 @@ from .exa_search import ExaSearchToolkit from .glean_search_api import GleanSearchAPIComponent from .google_search_api import GoogleSearchAPIComponent from .google_serper_api import GoogleSerperAPIComponent +from .mcp_stdio import MCPStdio from .python_code_structured_tool import PythonCodeStructuredTool from .python_repl import PythonREPLToolComponent from .search_api import SearchAPIComponent @@ -36,6 +37,7 @@ __all__ = [ "GleanSearchAPIComponent", "GoogleSearchAPIComponent", "GoogleSerperAPIComponent", + "MCPStdio", "PythonCodeStructuredTool", "PythonREPLToolComponent", "SearXNGToolComponent", diff --git a/src/backend/base/langflow/components/tools/mcp_sse.py b/src/backend/base/langflow/components/tools/mcp_sse.py new file mode 100644 index 000000000..876c05c7d --- /dev/null +++ b/src/backend/base/langflow/components/tools/mcp_sse.py @@ -0,0 +1,98 @@ +# from langflow.field_typing import Data +import asyncio +from contextlib import AsyncExitStack + +import httpx +from mcp import ClientSession, types +from mcp.client.sse import sse_client + +from langflow.base.mcp.util import create_tool_coroutine, create_tool_func +from langflow.components.tools.mcp_stdio import create_input_schema_from_json_schema +from langflow.custom import Component +from langflow.field_typing import Tool +from langflow.io import MessageTextInput, Output + +# Define constant for status code +HTTP_TEMPORARY_REDIRECT = 307 + + +class MCPSseClient: + def __init__(self): + # Initialize session and client objects + self.write = None + self.sse = None + self.session: ClientSession | None = None + self.exit_stack = AsyncExitStack() + + async def pre_check_redirect(self, url: str): + """Check if the URL responds with a 307 Redirect.""" + async with httpx.AsyncClient(follow_redirects=False) as client: + response = await client.request("HEAD", url) + if response.status_code == HTTP_TEMPORARY_REDIRECT: + return response.headers.get("Location") # Return the redirect URL + return url # Return the original URL if no redirect + + async def connect_to_server( + self, url: str, headers: dict[str, str] | None, timeout_seconds: int = 500, sse_read_timeout_seconds: int = 500 + ): + if headers is None: + headers = {} + url = await self.pre_check_redirect(url) + + async with asyncio.timeout(timeout_seconds): + sse_transport = await self.exit_stack.enter_async_context( + sse_client(url, headers, timeout_seconds, sse_read_timeout_seconds) + ) + self.sse, self.write = sse_transport + self.session = await self.exit_stack.enter_async_context(ClientSession(self.sse, self.write)) + + await self.session.initialize() + + # List available tools + response = await self.session.list_tools() + return response.tools + + +class MCPSse(Component): + client = MCPSseClient() + tools = types.ListToolsResult + tool_names = [str] + display_name = "MCP Tools (SSE)" + description = "Connects to an MCP server over SSE and exposes it's tools as langflow tools to be used by an Agent." + documentation: str = "http://docs.langflow.org/components/custom" + icon = "code" + name = "MCPSse" + + inputs = [ + MessageTextInput( + name="url", + display_name="mcp sse url", + info="sse url", + value="http://localhost:7860/api/v1/mcp/sse", + tool_mode=True, + ), + ] + + outputs = [ + Output(display_name="Tools", name="tools", method="build_output"), + ] + + async def build_output(self) -> list[Tool]: + if self.client.session is None: + self.tools = await self.client.connect_to_server(self.url, {}) + + tool_list = [] + + for tool in self.tools: + args_schema = create_input_schema_from_json_schema(tool.inputSchema) + tool_list.append( + Tool( + name=tool.name, # maybe format this + description=tool.description, + coroutine=create_tool_coroutine(tool.name, args_schema, self.client.session), + func=create_tool_func(tool.name, self.client.session), + ) + ) + + self.tool_names = [tool.name for tool in self.tools] + return tool_list diff --git a/src/backend/base/langflow/components/tools/mcp_stdio.py b/src/backend/base/langflow/components/tools/mcp_stdio.py new file mode 100644 index 000000000..a6ca98be8 --- /dev/null +++ b/src/backend/base/langflow/components/tools/mcp_stdio.py @@ -0,0 +1,122 @@ +# from langflow.field_typing import Data +import os +from contextlib import AsyncExitStack +from typing import Any + +from mcp import ClientSession, StdioServerParameters, types +from mcp.client.stdio import stdio_client +from pydantic import BaseModel, Field, create_model + +from langflow.base.mcp.util import create_tool_coroutine, create_tool_func +from langflow.custom import Component +from langflow.field_typing import Tool +from langflow.io import MessageTextInput, Output + + +class MCPStdioClient: + def __init__(self): + # Initialize session and client objects + self.session: ClientSession | None = None + self.exit_stack = AsyncExitStack() + + async def connect_to_server(self, command_str: str): + command = command_str.split(" ") + server_params = StdioServerParameters( + command=command[0], args=command[1:], env={"DEBUG": "true", "PATH": os.environ["PATH"]} + ) + + stdio_transport = await self.exit_stack.enter_async_context(stdio_client(server_params)) + self.stdio, self.write = stdio_transport + self.session = await self.exit_stack.enter_async_context(ClientSession(self.stdio, self.write)) + + await self.session.initialize() + + # List available tools + response = await self.session.list_tools() + return response.tools + + +def create_input_schema_from_json_schema(schema: dict[str, Any]) -> type[BaseModel]: + """Converts a JSON schema into a Pydantic model dynamically. + + :param schema: The JSON schema as a dictionary. + :return: A Pydantic model class. + """ + if schema.get("type") != "object": + msg = "JSON schema must be of type 'object' at the root level." + raise ValueError(msg) + + fields = {} + properties = schema.get("properties", {}) + required_fields = set(schema.get("required", [])) + + for field_name, field_def in properties.items(): + # Extract type + field_type_str = field_def.get("type", "str") # Default to string type if not specified + field_type = { + "string": str, + "str": str, + "integer": int, + "int": int, + "number": float, + "boolean": bool, + "array": list, + "object": dict, + }.get(field_type_str, Any) + + # Extract description and default if present + field_metadata = {"description": field_def.get("description", "")} + if field_name not in required_fields: + field_metadata["default"] = field_def.get("default", None) + + # Create Pydantic field + fields[field_name] = (field_type, Field(**field_metadata)) + + # Dynamically create the model + return create_model("InputSchema", **fields) + + +class MCPStdio(Component): + client = MCPStdioClient() + tools = types.ListToolsResult + tool_names = [str] + display_name = "MCP Tools (stdio)" + description = ( + "Connects to an MCP server over stdio and exposes it's tools as langflow tools to be used by an Agent." + ) + documentation: str = "http://docs.langflow.org/components/custom" + icon = "code" + name = "MCPStdio" + + inputs = [ + MessageTextInput( + name="command", + display_name="mcp command", + info="mcp command", + value="uvx mcp-sse-shim@latest", + tool_mode=True, + ), + ] + + outputs = [ + Output(display_name="Tools", name="tools", method="build_output"), + ] + + async def build_output(self) -> list[Tool]: + if self.client.session is None: + self.tools = await self.client.connect_to_server(self.command) + + tool_list = [] + + for tool in self.tools: + args_schema = create_input_schema_from_json_schema(tool.inputSchema) + tool_list.append( + Tool( + name=tool.name, + description=tool.description, + coroutine=create_tool_coroutine(tool.name, args_schema, self.client.session), + func=create_tool_func(tool.name, args_schema), + ) + ) + self.tool_names = [tool.name for tool in self.tools] + return tool_list diff --git a/src/backend/base/langflow/helpers/flow.py b/src/backend/base/langflow/helpers/flow.py index 9fc56cbc1..c2b543769 100644 --- a/src/backend/base/langflow/helpers/flow.py +++ b/src/backend/base/langflow/helpers/flow.py @@ -4,6 +4,7 @@ from typing import TYPE_CHECKING, Any, cast from uuid import UUID from fastapi import HTTPException +from loguru import logger from pydantic.v1 import BaseModel, Field, create_model from sqlmodel import select @@ -314,3 +315,46 @@ async def generate_unique_flow_name(flow_name, user_id, session): # If a flow with the name already exists, append (n) to the name and increment n flow_name = f"{original_name} ({n})" n += 1 + + +def json_schema_from_flow(flow: Flow) -> dict: + """Generate JSON schema from flow input nodes.""" + from langflow.graph.graph.base import Graph + + # Get the flow's data which contains the nodes and their configurations + flow_data = flow.data if flow.data else {} + + graph = Graph.from_payload(flow_data) + input_nodes = [vertex for vertex in graph.vertices if vertex.is_input] + + properties = {} + required = [] + for node in input_nodes: + node_data = node.data["node"] + template = node_data["template"] + + for field_name, field_data in template.items(): + if field_data != "Component" and field_data.get("show", False) and not field_data.get("advanced", False): + field_type = field_data.get("type", "string") + properties[field_name] = { + "type": field_type, + "description": field_data.get("info", f"Input for {field_name}"), + } + # Update field_type in properties after determining the JSON Schema type + if field_type == "str": + field_type = "string" + elif field_type == "int": + field_type = "integer" + elif field_type == "float": + field_type = "number" + elif field_type == "bool": + field_type = "boolean" + else: + logger.warning(f"Unknown field type: {field_type} defaulting to string") + field_type = "string" + properties[field_name]["type"] = field_type + + if field_data.get("required", False): + required.append(field_name) + + return {"type": "object", "properties": properties, "required": required} diff --git a/src/backend/base/langflow/services/settings/base.py b/src/backend/base/langflow/services/settings/base.py index 039939913..3833b4b90 100644 --- a/src/backend/base/langflow/services/settings/base.py +++ b/src/backend/base/langflow/services/settings/base.py @@ -181,6 +181,12 @@ class Settings(BaseSettings): max_vertex_builds_to_keep: int = 3000 """The maximum number of vertex builds to keep in the database.""" + # MCP Server + mcp_server_enabled: bool = True + """If set to False, Langflow will not enable the MCP server.""" + mcp_server_enable_progress_notifications: bool = False + """If set to False, Langflow will not send progress notifications in the MCP server.""" + @field_validator("dev") @classmethod def set_dev(cls, value): diff --git a/src/backend/tests/performance/test_server_init.py b/src/backend/tests/performance/test_server_init.py index 858e9c8c6..42f7e15a3 100644 --- a/src/backend/tests/performance/test_server_init.py +++ b/src/backend/tests/performance/test_server_init.py @@ -1,3 +1,5 @@ +import os + import pytest from langflow.services.deps import get_settings_service @@ -5,14 +7,18 @@ from langflow.services.deps import get_settings_service @pytest.fixture(autouse=True) def setup_database_url(tmp_path, monkeypatch): """Setup a temporary database URL for testing.""" + settings_service = get_settings_service() db_path = tmp_path / "test_performance.db" - original_value = monkeypatch.delenv("LANGFLOW_DATABASE_URL", raising=False) + original_value = os.getenv("LANGFLOW_DATABASE_URL") + monkeypatch.delenv("LANGFLOW_DATABASE_URL", raising=False) test_db_url = f"sqlite:///{db_path}" monkeypatch.setenv("LANGFLOW_DATABASE_URL", test_db_url) + settings_service.set("database_url", test_db_url) yield # Restore original value if it existed if original_value is not None: monkeypatch.setenv("LANGFLOW_DATABASE_URL", original_value) + settings_service.set("database_url", original_value) else: monkeypatch.delenv("LANGFLOW_DATABASE_URL", raising=False) diff --git a/src/frontend/tests/extended/regression/generalBugs-shard-3.spec.ts b/src/frontend/tests/extended/regression/generalBugs-shard-3.spec.ts index 208c2d595..57b35d8f1 100644 --- a/src/frontend/tests/extended/regression/generalBugs-shard-3.spec.ts +++ b/src/frontend/tests/extended/regression/generalBugs-shard-3.spec.ts @@ -90,7 +90,7 @@ test( } await page.locator(".react-flow__pane").click(); - + await adjustScreenView(page, { numberOfZoomOut: 1 }); await visibleElementHandle.hover(); 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