diff --git a/Makefile b/Makefile index 328ac8580..0eef78999 100644 --- a/Makefile +++ b/Makefile @@ -26,8 +26,15 @@ install_frontend: run_frontend: cd src/frontend && npm start -run_backend: - poetry run uvicorn langflow.main:app --port 5003 --reload +frontend: + make install_frontend + make run_frontend + +install_backend: + poetry install + +backend: + poetry run uvicorn langflow.main:app --port 7860 --reload --log-level debug build_frontend: cd src/frontend && CI='' npm run build diff --git a/build_and_push b/build_and_push deleted file mode 100755 index e9c9edf14..000000000 --- a/build_and_push +++ /dev/null @@ -1,11 +0,0 @@ -#! /bin/bash - -cd src/frontend -docker build -t logspace/frontend_build -f build.Dockerfile . -cd ../backend -docker build -t logspace/backend_build -f build.Dockerfile . - -cd ../../ -VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) -docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . -docker push 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">=8.1.0,<9.0.0" tqdm = ">=4.48.0" [package.extras] -all = ["aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.2.6,<0.3.0)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=3,<4)", "deeplake (>=3.3.0,<4.0.0)", "duckduckgo-search (>=2.8.6,<3.0.0)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jina (>=3.14,<4.0)", "jinja2 (>=3,<4)", "lancedb (>=0.1,<0.2)", "lark (>=1.1.5,<2.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "opensearch-py (>=2.0.0,<3.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "qdrant-client (>=1.1.2,<2.0.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0.3.2,<0.4.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] +all = ["aleph-alpha-client (>=2.15.0,<3.0.0)", "anthropic (>=0.2.6,<0.3.0)", "arxiv (>=1.4,<2.0)", "atlassian-python-api (>=3.36.0,<4.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "beautifulsoup4 (>=4,<5)", "clickhouse-connect (>=0.5.14,<0.6.0)", "cohere (>=3,<4)", "deeplake (>=3.3.0,<4.0.0)", "duckduckgo-search (>=2.8.6,<3.0.0)", "elasticsearch (>=8,<9)", "faiss-cpu (>=1,<2)", "google-api-python-client (==2.70.0)", "google-search-results (>=2,<3)", "gptcache (>=0.1.7)", "html2text (>=2020.1.16,<2021.0.0)", "huggingface_hub (>=0,<1)", "jina (>=3.14,<4.0)", "jinja2 (>=3,<4)", "lancedb (>=0.1,<0.2)", "lark (>=1.1.5,<2.0.0)", "manifest-ml (>=0.0.1,<0.0.2)", "networkx (>=2.6.3,<3.0.0)", "nlpcloud (>=1,<2)", "nltk (>=3,<4)", "nomic (>=1.0.43,<2.0.0)", "openai (>=0,<1)", "opensearch-py (>=2.0.0,<3.0.0)", "pexpect (>=4.8.0,<5.0.0)", "pgvector (>=0.1.6,<0.2.0)", "pinecone-client (>=2,<3)", "pinecone-text (>=0.4.2,<0.5.0)", "psycopg2-binary (>=2.9.5,<3.0.0)", "pyowm (>=3.3.0,<4.0.0)", "pypdf (>=3.4.0,<4.0.0)", "pytesseract (>=0.3.10,<0.4.0)", "qdrant-client (>=1.1.2,<2.0.0)", "redis (>=4,<5)", "sentence-transformers (>=2,<3)", "spacy (>=3,<4)", "tensorflow-text (>=2.11.0,<3.0.0)", "tiktoken (>=0.3.2,<0.4.0)", "torch (>=1,<3)", "transformers (>=4,<5)", "weaviate-client (>=3,<4)", "wikipedia (>=1,<2)", "wolframalpha (==5.0.0)"] azure = ["azure-core (>=1.26.4,<2.0.0)", "azure-cosmos (>=4.4.0b1,<5.0.0)", "azure-identity (>=1.12.0,<2.0.0)", "openai (>=0,<1)"] cohere = ["cohere (>=3,<4)"] embeddings = ["sentence-transformers (>=2,<3)"] @@ -2698,6 +2698,21 @@ pytz = ">=2020.1" [package.extras] test = ["hypothesis (>=5.5.3)", "pytest (>=6.0)", "pytest-xdist (>=1.31)"] +[[package]] +name = "pandas-stubs" +version = "2.0.0.230412" +description = "Type annotations for pandas" +category = "dev" +optional = false +python-versions = ">=3.8" +files = [ + {file = "pandas_stubs-2.0.0.230412-py3-none-any.whl", hash = "sha256:311ab8b42ee574d9fea5061d1f63aeca297e472de6073ba84bf2a017c6cb1b6b"}, + {file = "pandas_stubs-2.0.0.230412.tar.gz", hash = "sha256:016f567cb9947edd0067ea2665ab00b77fa47e73a65ce1a097de4f499b3485c0"}, +] + +[package.dependencies] +types-pytz = ">=2022.1.1" + [[package]] name = "parso" version = "0.8.3" @@ -4428,6 +4443,30 @@ dev = ["autoflake (>=1.3.1,<2.0.0)", "flake8 (>=3.8.3,<4.0.0)", "pre-commit (>=2 doc = ["cairosvg (>=2.5.2,<3.0.0)", "mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-material (>=8.1.4,<9.0.0)", "pillow (>=9.3.0,<10.0.0)"] test = ["black (>=22.3.0,<23.0.0)", "coverage (>=6.2,<7.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.910)", "pytest (>=4.4.0,<8.0.0)", "pytest-cov (>=2.10.0,<5.0.0)", "pytest-sugar (>=0.9.4,<0.10.0)", "pytest-xdist (>=1.32.0,<4.0.0)", "rich (>=10.11.0,<13.0.0)", "shellingham (>=1.3.0,<2.0.0)"] +[[package]] +name = "types-pillow" +version = "9.5.0.2" +description = "Typing stubs for Pillow" +category = "dev" +optional = false +python-versions = "*" +files = [ + {file = "types-Pillow-9.5.0.2.tar.gz", hash = "sha256:b3f9f621f259566c19c1deca21901017c8b1e3e200ed2e49e0a2d83c0a5175db"}, + {file = "types_Pillow-9.5.0.2-py3-none-any.whl", hash = "sha256:58fdebd0ffa2353ecccdd622adde23bce89da5c0c8b96c34f2d1eca7b7e42d0e"}, +] + +[[package]] +name = "types-pytz" +version = "2023.3.0.0" +description = "Typing stubs for pytz" +category = "dev" +optional = false +python-versions = "*" +files = [ + {file = "types-pytz-2023.3.0.0.tar.gz", hash = "sha256:ecdc70d543aaf3616a7e48631543a884f74205f284cefd6649ddf44c6a820aac"}, + {file = "types_pytz-2023.3.0.0-py3-none-any.whl", hash = "sha256:4fc2a7fbbc315f0b6630e0b899fd6c743705abe1094d007b0e612d10da15e0f3"}, +] + [[package]] name = "types-pyyaml" version = "6.0.12.9" @@ -4442,14 +4481,14 @@ files = [ [[package]] name = "types-requests" -version = "2.28.11.17" +version = "2.29.0.0" description = "Typing stubs for requests" category = "dev" optional = false python-versions = "*" files = [ - {file = "types-requests-2.28.11.17.tar.gz", hash = "sha256:0d580652ce903f643f8c3b494dd01d29367ea57cea0c7ad7f65cf3169092edb0"}, - {file = "types_requests-2.28.11.17-py3-none-any.whl", hash = "sha256:cc1aba862575019306b2ed134eb1ea994cab1c887a22e18d3383e6dd42e9789b"}, + {file = "types-requests-2.29.0.0.tar.gz", hash = "sha256:c86f4a955d943d2457120dbe719df24ef0924e11177164d10a0373cf311d7b4d"}, + {file = "types_requests-2.29.0.0-py3-none-any.whl", hash = "sha256:4cf6e323e856c779fbe8815bb977a5bf5d6c5034713e4c17ff2a9a20610f5b27"}, ] [package.dependencies] @@ -4955,4 +4994,4 @@ cffi = ["cffi (>=1.11)"] [metadata] lock-version = "2.0" python-versions = "^3.9" -content-hash = "49fd166dc3811d79f8344946ee40a62c28215db9fdd41f5f051ab109657d9a62" +content-hash = "c8ba5d9e0208fc55dc2f00efffed26d7a2c7d325568dfd697cc6499d210304d9" diff --git a/pyproject.toml b/pyproject.toml index 372ddcc6c..7ea498898 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,6 +47,7 @@ fake-useragent = "^1.1.3" docstring-parser = "^0.15" psycopg2-binary = "^2.9.6" pyarrow = "^11.0.0" +websockets = "^11.0.2" [tool.poetry.group.dev.dependencies] black = "^23.1.0" @@ -58,6 +59,8 @@ pytest = "^7.2.2" types-requests = "^2.28.11" requests = "^2.28.0" pytest-cov = "^4.0.0" +pandas-stubs = "^2.0.0.230412" +types-pillow = "^9.5.0.2" [tool.ruff] diff --git a/src/backend/build.Dockerfile b/src/backend/build.Dockerfile deleted file mode 100644 index 42452c691..000000000 --- a/src/backend/build.Dockerfile +++ /dev/null @@ -1,52 +0,0 @@ -# `python-base` sets up all our shared environment variables -FROM python:3.10-slim - -# python -ENV PYTHONUNBUFFERED=1 \ - # prevents python creating .pyc files - PYTHONDONTWRITEBYTECODE=1 \ - \ - # pip - PIP_NO_CACHE_DIR=off \ - PIP_DISABLE_PIP_VERSION_CHECK=on \ - PIP_DEFAULT_TIMEOUT=100 \ - \ - # poetry - # https://python-poetry.org/docs/configuration/#using-environment-variables - POETRY_VERSION=1.4.0 \ - # make poetry install to this location - POETRY_HOME="/opt/poetry" \ - # make poetry create the virtual environment in the project's root - # it gets named `.venv` - POETRY_VIRTUALENVS_IN_PROJECT=true \ - # do not ask any interactive question - POETRY_NO_INTERACTION=1 \ - \ - # paths - # this is where our requirements + virtual environment will live - PYSETUP_PATH="/opt/pysetup" \ - VENV_PATH="/opt/pysetup/.venv" - -# prepend poetry and venv to path -ENV PATH="$POETRY_HOME/bin:$VENV_PATH/bin:$PATH" - -RUN apt-get update \ - && apt-get install --no-install-recommends -y \ - # deps for installing poetry - curl \ - # deps for building python deps - build-essential libpq-dev - -# install poetry - respects $POETRY_VERSION & $POETRY_HOME -RUN curl -sSL https://install.python-poetry.org | python3 - - -# copy project requirement files here to ensure they will be cached. -WORKDIR /app -COPY poetry.lock pyproject.toml ./ -COPY langflow/ ./langflow - -# poetry install -RUN poetry install --without dev - -# build wheel -RUN poetry build -f wheel diff --git a/src/backend/build_and_push b/src/backend/build_and_push deleted file mode 100755 index d70366d72..000000000 --- a/src/backend/build_and_push +++ /dev/null @@ -1,6 +0,0 @@ -#! /bin/bash - -docker build -t logspace/backend_build -f build.Dockerfile . -VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) -docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . -docker push ibiscp/langflow:$VERSION diff --git a/src/backend/langflow/__init__.py b/src/backend/langflow/__init__.py index 1be5464c2..fb06fe1a7 100644 --- a/src/backend/langflow/__init__.py +++ b/src/backend/langflow/__init__.py @@ -1 +1,4 @@ -from langflow.interface.loading import load_flow_from_json # noqa +from langflow.interface.loading import load_flow_from_json +from langflow.cache import cache_manager + +__all__ = ["load_flow_from_json", "cache_manager"] diff --git a/src/backend/langflow/api/base.py b/src/backend/langflow/api/base.py index 084e04d65..8cddc52e4 100644 --- a/src/backend/langflow/api/base.py +++ b/src/backend/langflow/api/base.py @@ -3,6 +3,10 @@ from pydantic import BaseModel, validator from langflow.graph.utils import extract_input_variables_from_prompt +class CacheResponse(BaseModel): + data: dict + + class Code(BaseModel): code: str diff --git a/src/backend/langflow/api/callback.py b/src/backend/langflow/api/callback.py new file mode 100644 index 000000000..cad4b1416 --- /dev/null +++ b/src/backend/langflow/api/callback.py @@ -0,0 +1,16 @@ +from typing import Any +from langchain.callbacks.base import AsyncCallbackHandler + +from langflow.api.schemas import ChatResponse + + +# https://github.com/hwchase17/chat-langchain/blob/master/callback.py +class StreamingLLMCallbackHandler(AsyncCallbackHandler): + """Callback handler for streaming LLM responses.""" + + def __init__(self, websocket): + self.websocket = websocket + + async def on_llm_new_token(self, token: str, **kwargs: Any) -> None: + resp = ChatResponse(message=token, type="stream", intermediate_steps="") + await self.websocket.send_json(resp.dict()) diff --git a/src/backend/langflow/api/chat.py b/src/backend/langflow/api/chat.py new file mode 100644 index 000000000..e25d0d2f1 --- /dev/null +++ b/src/backend/langflow/api/chat.py @@ -0,0 +1,18 @@ +from fastapi import APIRouter, WebSocket + +from langflow.api.chat_manager import ChatManager +from langflow.utils.logger import logger + +router = APIRouter() +chat_manager = ChatManager() + + +@router.websocket("/chat/{client_id}") +async def websocket_endpoint(client_id: str, websocket: WebSocket): + """Websocket endpoint for chat.""" + try: + await chat_manager.handle_websocket(client_id, websocket) + except Exception as e: + # Log stack trace + logger.exception(e) + raise e diff --git a/src/backend/langflow/api/chat_manager.py b/src/backend/langflow/api/chat_manager.py new file mode 100644 index 000000000..5c490c43c --- /dev/null +++ b/src/backend/langflow/api/chat_manager.py @@ -0,0 +1,212 @@ +import asyncio +from typing import Dict, List +from collections import defaultdict +from fastapi import WebSocket +import json +from langflow.api.schemas import ChatMessage, ChatResponse, FileResponse +from langflow.cache.manager import Subject +from langflow.interface.run import ( + get_result_and_steps, + load_or_build_langchain_object, +) +from langflow.interface.utils import pil_to_base64, try_setting_streaming_options +from langflow.utils.logger import logger +from langflow.cache import cache_manager + + +class ChatHistory(Subject): + def __init__(self): + super().__init__() + self.history: Dict[str, List[ChatMessage]] = defaultdict(list) + + def add_message(self, client_id: str, message: ChatMessage): + """Add a message to the chat history.""" + + self.history[client_id].append(message) + + if not isinstance(message, FileResponse): + self.notify() + + def get_history(self, client_id: str, filter=True) -> List[ChatMessage]: + """Get the chat history for a client.""" + if history := self.history.get(client_id, []): + if filter: + return [msg for msg in history if msg.type not in ["start", "stream"]] + return history + else: + return [] + + def empty_history(self, client_id: str): + """Empty the chat history for a client.""" + self.history[client_id] = [] + + +class ChatManager: + def __init__(self): + self.active_connections: Dict[str, WebSocket] = {} + self.chat_history = ChatHistory() + self.chat_history.attach(self.on_chat_history_update) + self.cache_manager = cache_manager + self.cache_manager.attach(self.update) + + def on_chat_history_update(self): + """Send the last chat message to the client.""" + client_id = self.cache_manager.current_client_id + if client_id in self.active_connections: + chat_response = self.chat_history.get_history(client_id, filter=False)[-1] + if chat_response.is_bot: + # Process FileResponse + if isinstance(chat_response, FileResponse): + # If data_type is pandas, convert to csv + if chat_response.data_type == "pandas": + chat_response.data = chat_response.data.to_csv() + elif chat_response.data_type == "image": + # Base64 encode the image + chat_response.data = pil_to_base64(chat_response.data) + # get event loop + loop = asyncio.get_event_loop() + + coroutine = self.send_json(client_id, chat_response) + asyncio.run_coroutine_threadsafe(coroutine, loop) + + def update(self): + if self.cache_manager.current_client_id in self.active_connections: + self.last_cached_object_dict = self.cache_manager.get_last() + # Add a new ChatResponse with the data + chat_response = FileResponse( + message=None, + type="file", + data=self.last_cached_object_dict["obj"], + data_type=self.last_cached_object_dict["type"], + ) + + self.chat_history.add_message( + self.cache_manager.current_client_id, chat_response + ) + + async def connect(self, client_id: str, websocket: WebSocket): + await websocket.accept() + self.active_connections[client_id] = websocket + + def disconnect(self, client_id: str): + del self.active_connections[client_id] + + async def send_message(self, client_id: str, message: str): + websocket = self.active_connections[client_id] + await websocket.send_text(message) + + async def send_json(self, client_id: str, message: ChatMessage): + websocket = self.active_connections[client_id] + await websocket.send_json(message.dict()) + + async def process_message(self, client_id: str, payload: Dict): + # Process the graph data and chat message + chat_message = payload.pop("message", "") + chat_message = ChatMessage(message=chat_message) + self.chat_history.add_message(client_id, chat_message) + + graph_data = payload + start_resp = ChatResponse(message=None, type="start", intermediate_steps="") + self.chat_history.add_message(client_id, start_resp) + + is_first_message = len(self.chat_history.get_history(client_id=client_id)) == 0 + # Generate result and thought + try: + logger.debug("Generating result and thought") + + result, intermediate_steps = await process_graph( + graph_data=graph_data, + is_first_message=is_first_message, + chat_message=chat_message, + websocket=self.active_connections[client_id], + ) + except Exception as e: + # Log stack trace + logger.exception(e) + self.chat_history.empty_history(client_id) + raise e + # Send a response back to the frontend, if needed + intermediate_steps = intermediate_steps or "" + history = self.chat_history.get_history(client_id, filter=False) + file_responses = [] + if history: + # Iterate backwards through the history + for msg in reversed(history): + if isinstance(msg, FileResponse): + if msg.data_type == "image": + # Base64 encode the image + msg.data = pil_to_base64(msg.data) + file_responses.append(msg) + if msg.type == "start": + break + + response = ChatResponse( + message=result or "", + intermediate_steps=intermediate_steps.strip(), + type="end", + files=file_responses, + ) + self.chat_history.add_message(client_id, response) + + async def handle_websocket(self, client_id: str, websocket: WebSocket): + await self.connect(client_id, websocket) + + try: + chat_history = self.chat_history.get_history(client_id) + # iterate and make BaseModel into dict + chat_history = [chat.dict() for chat in chat_history] + await websocket.send_json(chat_history) + + while True: + json_payload = await websocket.receive_json() + try: + payload = json.loads(json_payload) + except TypeError: + payload = json_payload + if "clear_history" in payload: + self.chat_history.history[client_id] = [] + continue + + with self.cache_manager.set_client_id(client_id): + await self.process_message(client_id, payload) + except Exception as e: + # Handle any exceptions that might occur + logger.exception(e) + # send a message to the client + await self.send_message(client_id, str(e)) + raise e + finally: + await self.active_connections[client_id].close( + code=1000, reason="Client disconnected" + ) + self.disconnect(client_id) + + +async def process_graph( + graph_data: Dict, + is_first_message: bool, + chat_message: ChatMessage, + websocket: WebSocket, +): + langchain_object = load_or_build_langchain_object(graph_data, is_first_message) + langchain_object = try_setting_streaming_options(langchain_object, websocket) + logger.debug("Loaded langchain object") + + if langchain_object is None: + # Raise user facing error + raise ValueError( + "There was an error loading the langchain_object. Please, check all the nodes and try again." + ) + + # Generate result and thought + try: + logger.debug("Generating result and thought") + result, intermediate_steps = get_result_and_steps( + langchain_object, chat_message.message or "" + ) + logger.debug("Generated result and intermediate_steps") + return result, intermediate_steps + except Exception as e: + # Log stack trace + logger.exception(e) + raise e diff --git a/src/backend/langflow/api/schemas.py b/src/backend/langflow/api/schemas.py new file mode 100644 index 000000000..e4adacf9e --- /dev/null +++ b/src/backend/langflow/api/schemas.py @@ -0,0 +1,40 @@ +from typing import Any, Union +from pydantic import BaseModel, validator + + +class ChatMessage(BaseModel): + """Chat message schema.""" + + is_bot: bool = False + message: Union[str, None] = None + type: str = "human" + + +class ChatResponse(ChatMessage): + """Chat response schema.""" + + intermediate_steps: str + type: str + is_bot: bool = True + files: list = [] + + @validator("type") + def validate_message_type(cls, v): + if v not in ["start", "stream", "end", "error", "info", "file"]: + raise ValueError("type must be start, stream, end, error, info, or file") + return v + + +class FileResponse(ChatMessage): + """File response schema.""" + + data: Any + data_type: str + type: str = "file" + is_bot: bool = True + + @validator("data_type") + def validate_data_type(cls, v): + if v not in ["image", "csv"]: + raise ValueError("data_type must be image or csv") + return v diff --git a/src/backend/langflow/api/validate.py b/src/backend/langflow/api/validate.py index a60bcc506..e1b5a3a1a 100644 --- a/src/backend/langflow/api/validate.py +++ b/src/backend/langflow/api/validate.py @@ -7,6 +7,7 @@ from langflow.api.base import ( PromptValidationResponse, validate_prompt, ) +from langflow.interface.run import build_graph from langflow.utils.logger import logger from langflow.utils.validate import validate_code @@ -33,3 +34,20 @@ def post_validate_prompt(prompt: Prompt): except Exception as e: logger.exception(e) raise HTTPException(status_code=500, detail=str(e)) from e + + +# validate node +@router.post("/node/{node_id}", status_code=200) +def post_validate_node(node_id: str, data: dict): + try: + # build graph + graph = build_graph(data) + # validate node + node = graph.get_node(node_id) + if node is not None: + _ = node.build() + return str(node.params) + raise Exception(f"Node {node_id} not found") + except Exception as e: + logger.exception(e) + raise HTTPException(status_code=500, detail=str(e)) from e diff --git a/src/backend/langflow/cache/__init__.py b/src/backend/langflow/cache/__init__.py index e69de29bb..583d5ac6d 100644 --- a/src/backend/langflow/cache/__init__.py +++ b/src/backend/langflow/cache/__init__.py @@ -0,0 +1 @@ +from langflow.cache.manager import cache_manager # noqa diff --git a/src/backend/langflow/cache/utils.py b/src/backend/langflow/cache/base.py similarity index 98% rename from src/backend/langflow/cache/utils.py rename to src/backend/langflow/cache/base.py index 310f3be80..ede0fb06e 100644 --- a/src/backend/langflow/cache/utils.py +++ b/src/backend/langflow/cache/base.py @@ -2,14 +2,17 @@ import base64 import contextlib import functools import hashlib + import json import os import tempfile from collections import OrderedDict from pathlib import Path - +from typing import Any, Dict import dill # type: ignore +CACHE: Dict[str, Any] = {} + def create_cache_folder(func): def wrapper(*args, **kwargs): diff --git a/src/backend/langflow/cache/manager.py b/src/backend/langflow/cache/manager.py new file mode 100644 index 000000000..971519230 --- /dev/null +++ b/src/backend/langflow/cache/manager.py @@ -0,0 +1,149 @@ +from contextlib import contextmanager +from typing import Any, Awaitable, Callable, List, Optional +from PIL import Image +import pandas as pd + + +class Subject: + """Base class for implementing the observer pattern.""" + + def __init__(self): + self.observers: List[Callable[[], None]] = [] + + def attach(self, observer: Callable[[], None]): + """Attach an observer to the subject.""" + self.observers.append(observer) + + def detach(self, observer: Callable[[], None]): + """Detach an observer from the subject.""" + self.observers.remove(observer) + + def notify(self): + """Notify all observers about an event.""" + for observer in self.observers: + if observer is None: + continue + observer() + + +class AsyncSubject: + """Base class for implementing the async observer pattern.""" + + def __init__(self): + self.observers: List[Callable[[], Awaitable]] = [] + + def attach(self, observer: Callable[[], Awaitable]): + """Attach an observer to the subject.""" + self.observers.append(observer) + + def detach(self, observer: Callable[[], Awaitable]): + """Detach an observer from the subject.""" + self.observers.remove(observer) + + async def notify(self): + """Notify all observers about an event.""" + for observer in self.observers: + if observer is None: + continue + await observer() + + +class CacheManager(Subject): + """Manages cache for different clients and notifies observers on changes.""" + + def __init__(self): + super().__init__() + self.CACHE = {} + self.current_client_id = None + self.current_cache = {} + + @contextmanager + def set_client_id(self, client_id: str): + """ + Context manager to set the current client_id and associated cache. + + Args: + client_id (str): The client identifier. + """ + previous_client_id = self.current_client_id + self.current_client_id = client_id + self.current_cache = self.CACHE.setdefault(client_id, {}) + try: + yield + finally: + self.current_client_id = previous_client_id + self.current_cache = self.CACHE.get(self.current_client_id, {}) + + def add(self, name: str, obj: Any, obj_type: str, extension: Optional[str] = None): + """ + Add an object to the current client's cache. + + Args: + name (str): The cache key. + obj (Any): The object to cache. + obj_type (str): The type of the object. + """ + object_extensions = { + "image": "png", + "pandas": "csv", + } + if obj_type in object_extensions: + _extension = object_extensions[obj_type] + else: + _extension = type(obj).__name__.lower() + self.current_cache[name] = { + "obj": obj, + "type": obj_type, + "extension": extension or _extension, + } + self.notify() + + def add_pandas(self, name: str, obj: Any): + """ + Add a pandas DataFrame or Series to the current client's cache. + + Args: + name (str): The cache key. + obj (Any): The pandas DataFrame or Series object. + """ + if isinstance(obj, (pd.DataFrame, pd.Series)): + self.add(name, obj.to_csv(), "pandas", extension="csv") + else: + raise ValueError("Object is not a pandas DataFrame or Series") + + def add_image(self, name: str, obj: Any, extension: str = "png"): + """ + Add a PIL Image to the current client's cache. + + Args: + name (str): The cache key. + obj (Any): The PIL Image object. + """ + if isinstance(obj, Image.Image): + self.add(name, obj, "image", extension=extension) + else: + raise ValueError("Object is not a PIL Image") + + def get(self, name: str): + """ + Get an object from the current client's cache. + + Args: + name (str): The cache key. + + Returns: + The cached object associated with the given cache key. + """ + return self.current_cache[name] + + def get_last(self): + """ + Get the last added item in the current client's cache. + + Returns: + The last added item in the cache. + """ + return list(self.current_cache.values())[-1] + + +cache_manager = CacheManager() diff --git a/src/backend/langflow/graph/base.py b/src/backend/langflow/graph/base.py index 6d998eed6..e661fec69 100644 --- a/src/backend/langflow/graph/base.py +++ b/src/backend/langflow/graph/base.py @@ -4,16 +4,18 @@ # - Build each inner agent first, then build the outer agent import contextlib +import inspect import types import warnings from copy import deepcopy from typing import Any, Dict, List, Optional -from langflow.cache import utils as cache_utils +from langflow.cache import base as cache_utils from langflow.graph.constants import DIRECT_TYPES from langflow.interface import loading from langflow.interface.listing import ALL_TYPES_DICT from langflow.utils.logger import logger +from langflow.utils.util import sync_to_async class Node: @@ -158,13 +160,21 @@ class Node: continue result = value.build() # If the key is "func", then we need to use the run method - if key == "func" and not isinstance(result, types.FunctionType): - # func can be PythonFunction(code='\ndef upper_case(text: str) -> str:\n return text.upper()\n') - # so we need to check if there is an attribute called run - if hasattr(result, "run"): - result = result.run # type: ignore - elif hasattr(result, "get_function"): - result = result.get_function() # type: ignore + if key == "func": + if not isinstance(result, types.FunctionType): + # func can be + # PythonFunction(code='\ndef upper_case(text: str) -> str:\n return text.upper()\n') + # so we need to check if there is an attribute called run + if hasattr(result, "run"): + result = result.run # type: ignore + elif hasattr(result, "get_function"): + result = result.get_function() # type: ignore + elif inspect.iscoroutinefunction(result): + self.params["coroutine"] = result + else: + # turn result which is a function into a coroutine + # so that it can be awaited + self.params["coroutine"] = sync_to_async(result) self.params[key] = result elif isinstance(value, list) and all( diff --git a/src/backend/langflow/interface/chains/base.py b/src/backend/langflow/interface/chains/base.py index 9dc8ded3f..7b8da370b 100644 --- a/src/backend/langflow/interface/chains/base.py +++ b/src/backend/langflow/interface/chains/base.py @@ -37,7 +37,9 @@ class ChainCreator(LangChainTypeCreator): try: if name in get_custom_nodes(self.type_name).keys(): return get_custom_nodes(self.type_name)[name] - return build_template_from_class(name, self.type_to_loader_dict) + return build_template_from_class( + name, self.type_to_loader_dict, add_function=True + ) except ValueError as exc: raise ValueError("Chain not found") from exc except AttributeError as exc: diff --git a/src/backend/langflow/interface/loading.py b/src/backend/langflow/interface/loading.py index e08b7fdda..cab23c7e4 100644 --- a/src/backend/langflow/interface/loading.py +++ b/src/backend/langflow/interface/loading.py @@ -20,6 +20,7 @@ from langchain.llms.loading import load_llm_from_config from langflow.interface.agents.custom import CUSTOM_AGENTS from langflow.interface.importing.utils import import_by_type +from langflow.interface.run import fix_memory_inputs from langflow.interface.toolkits.base import toolkits_creator from langflow.interface.types import get_type_list from langflow.interface.utils import load_file_into_dict @@ -33,6 +34,12 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any: return custom_agent.initialize(**params) # type: ignore class_object = import_by_type(_type=base_type, name=node_type) + # check if it is a class before using issubclass + + # if isinstance(class_object, type) and issubclass(class_object, BaseModel): + # # validate params + # fields = class_object.__fields__ + # params = {key: value for key, value in params.items() if key in fields} if base_type == "agents": # We need to initialize it differently @@ -65,6 +72,7 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any: return load_toolkits_executor(node_type, loaded_toolkit, params) return loaded_toolkit elif base_type == "embeddings": + # ? Why remove model from params? params.pop("model") return class_object(**params) elif base_type == "vectorstores": @@ -106,7 +114,19 @@ def load_flow_from_json(path: str, build=True): # Nodes, edges and root node edges = data_graph["edges"] graph = Graph(nodes, edges) - return graph.build() if build else graph + if build: + langchain_object = graph.build() + if hasattr(langchain_object, "verbose"): + langchain_object.verbose = True + + if hasattr(langchain_object, "return_intermediate_steps"): + # https://github.com/hwchase17/langchain/issues/2068 + # Deactivating until we have a frontend solution + # to display intermediate steps + langchain_object.return_intermediate_steps = False + fix_memory_inputs(langchain_object) + return langchain_object + return graph def replace_zero_shot_prompt_with_prompt_template(nodes): diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py index 047ba733e..89f26944e 100644 --- a/src/backend/langflow/interface/run.py +++ b/src/backend/langflow/interface/run.py @@ -3,7 +3,7 @@ import io from typing import Any, Dict from chromadb.errors import NotEnoughElementsException # type: ignore -from langflow.cache.utils import compute_dict_hash, load_cache, memoize_dict +from langflow.cache.base import compute_dict_hash, load_cache, memoize_dict from langflow.graph.graph import Graph from langflow.interface import loading from langflow.utils.logger import logger @@ -32,23 +32,23 @@ def load_or_build_langchain_object(data_graph, is_first_message=False): return build_langchain_object_with_caching(data_graph) -@memoize_dict(maxsize=1) +@memoize_dict(maxsize=10) def build_langchain_object_with_caching(data_graph): """ Build langchain object from data_graph. """ logger.debug("Building langchain object") - nodes = data_graph["nodes"] - # Add input variables - # nodes = payload.extract_input_variables(nodes) - # Nodes, edges and root node - edges = data_graph["edges"] - graph = Graph(nodes, edges) - + graph = build_graph(data_graph) return graph.build() +def build_graph(data_graph): + nodes = data_graph["nodes"] + edges = data_graph["edges"] + return Graph(nodes, edges) + + def build_langchain_object(data_graph): """ Build langchain object from data_graph. @@ -87,7 +87,7 @@ def process_graph(data_graph: Dict[str, Any]): # Generate result and thought logger.debug("Generating result and thought") - result, thought = get_result_and_thought_using_graph(langchain_object, message) + result, thought = get_result_and_steps(langchain_object, message) logger.debug("Generated result and thought") # Save langchain_object to cache @@ -118,7 +118,7 @@ def process_graph_cached(data_graph: Dict[str, Any]): # Generate result and thought logger.debug("Generating result and thought") - result, thought = get_result_and_thought_using_graph(langchain_object, message) + result, thought = get_result_and_steps(langchain_object, message) logger.debug("Generated result and thought") return {"result": str(result), "thought": thought.strip()} @@ -184,7 +184,7 @@ def fix_memory_inputs(langchain_object): update_memory_keys(langchain_object, possible_new_mem_key) -def get_result_and_thought_using_graph(langchain_object, message: str): +def get_result_and_steps(langchain_object, message: str): """Get result and thought from extracted json""" try: if hasattr(langchain_object, "verbose"): @@ -240,6 +240,61 @@ def get_result_and_thought_using_graph(langchain_object, message: str): return result, thought +def async_get_result_and_steps(langchain_object, message: str): + """Get result and thought from extracted json""" + try: + if hasattr(langchain_object, "verbose"): + langchain_object.verbose = True + chat_input = None + memory_key = "" + if hasattr(langchain_object, "memory") and langchain_object.memory is not None: + memory_key = langchain_object.memory.memory_key + + if hasattr(langchain_object, "input_keys"): + for key in langchain_object.input_keys: + if key not in [memory_key, "chat_history"]: + chat_input = {key: message} + else: + chat_input = message # type: ignore + + if hasattr(langchain_object, "return_intermediate_steps"): + # https://github.com/hwchase17/langchain/issues/2068 + # Deactivating until we have a frontend solution + # to display intermediate steps + langchain_object.return_intermediate_steps = False + + fix_memory_inputs(langchain_object) + + with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer): + try: + # if hasattr(langchain_object, "acall"): + # output = await langchain_object.acall(chat_input) + # else: + output = langchain_object(chat_input) + except ValueError as exc: + # make the error message more informative + logger.debug(f"Error: {str(exc)}") + output = langchain_object.run(chat_input) + + intermediate_steps = ( + output.get("intermediate_steps", []) if isinstance(output, dict) else [] + ) + + result = ( + output.get(langchain_object.output_keys[0]) + if isinstance(output, dict) + else output + ) + if intermediate_steps: + thought = format_intermediate_steps(intermediate_steps) + else: + thought = output_buffer.getvalue() + + except Exception as exc: + raise ValueError(f"Error: {str(exc)}") from exc + return result, thought + + def get_result_and_thought(extracted_json: Dict[str, Any], message: str): """Get result and thought from extracted json""" try: diff --git a/src/backend/langflow/interface/utils.py b/src/backend/langflow/interface/utils.py index b3b154790..604df6f28 100644 --- a/src/backend/langflow/interface/utils.py +++ b/src/backend/langflow/interface/utils.py @@ -1,5 +1,12 @@ +import base64 +from io import BytesIO import json import os +from PIL.Image import Image +from langchain.callbacks.base import AsyncCallbackManager +from langchain.chat_models import AzureChatOpenAI, ChatOpenAI +from langchain.llms import AzureOpenAI, OpenAI +from langflow.api.callback import StreamingLLMCallbackHandler import yaml @@ -20,3 +27,30 @@ def load_file_into_dict(file_path: str) -> dict: raise ValueError("Unsupported file type. Please provide a JSON or YAML file.") return data + + +def pil_to_base64(image: Image) -> str: + buffered = BytesIO() + image.save(buffered, format="PNG") + img_str = base64.b64encode(buffered.getvalue()) + return img_str.decode("utf-8") + + +def try_setting_streaming_options(langchain_object, websocket): + # If the LLM type is OpenAI or ChatOpenAI, + # set streaming to True + # First we need to find the LLM + llm = None + if hasattr(langchain_object, "llm"): + llm = langchain_object.llm + elif hasattr(langchain_object, "llm_chain") and hasattr( + langchain_object.llm_chain, "llm" + ): + llm = langchain_object.llm_chain.llm + if isinstance(llm, (OpenAI, ChatOpenAI, AzureOpenAI, AzureChatOpenAI)): + llm.streaming = bool(hasattr(llm, "streaming")) + stream_handler = StreamingLLMCallbackHandler(websocket) + stream_manager = AsyncCallbackManager([stream_handler]) + llm.callback_manager = stream_manager + + return langchain_object diff --git a/src/backend/langflow/main.py b/src/backend/langflow/main.py index 176e46236..c1f2decd5 100644 --- a/src/backend/langflow/main.py +++ b/src/backend/langflow/main.py @@ -3,6 +3,7 @@ from fastapi.middleware.cors import CORSMiddleware from langflow.api.endpoints import router as endpoints_router from langflow.api.validate import router as validate_router +from langflow.api.chat import router as chat_router def create_app(): @@ -23,6 +24,7 @@ def create_app(): app.include_router(endpoints_router) app.include_router(validate_router) + app.include_router(chat_router) return app diff --git a/src/backend/langflow/template/base.py b/src/backend/langflow/template/base.py index 860d2ac1e..bab3a7b2d 100644 --- a/src/backend/langflow/template/base.py +++ b/src/backend/langflow/template/base.py @@ -229,10 +229,6 @@ class FrontendNode(BaseModel): field.required = False if field.value is None: field.value = "" - # If the field.name contains api or api and key, then it might be an api key - # other conditions are to make sure that it is not an input or output variable - if "api" in key.lower() and "key" in key.lower(): - field.required = False if "kwargs" in field.name.lower(): field.advanced = True diff --git a/src/backend/langflow/template/nodes.py b/src/backend/langflow/template/nodes.py index 9e33e2a79..7b5ac6d3f 100644 --- a/src/backend/langflow/template/nodes.py +++ b/src/backend/langflow/template/nodes.py @@ -199,6 +199,7 @@ class SeriesCharacterChainNode(FrontendNode): "Chain", "ConversationChain", "SeriesCharacterChain", + "function", ] @@ -317,7 +318,7 @@ class InitializeAgentNode(FrontendNode): ], ) description: str = """Construct a json agent from an LLM and tools.""" - base_classes: list[str] = ["AgentExecutor"] + base_classes: list[str] = ["AgentExecutor", "function"] def to_dict(self): return super().to_dict() @@ -529,7 +530,7 @@ class ChainFrontendNode(FrontendNode): field.advanced = True # Separated for possible future changes - if field.name == "prompt": + if field.name == "prompt" and field.value is None: # if no prompt is provided, use the default prompt field.required = False field.show = True diff --git a/src/backend/langflow/utils/util.py b/src/backend/langflow/utils/util.py index b31a3bed1..874debd8d 100644 --- a/src/backend/langflow/utils/util.py +++ b/src/backend/langflow/utils/util.py @@ -1,3 +1,4 @@ +from functools import wraps import importlib import inspect import re @@ -301,3 +302,15 @@ def update_verbose(d: dict, new_value: bool) -> dict: elif k == "verbose": d[k] = new_value return d + + +def sync_to_async(func): + """ + Decorator to convert a sync function to an async function. + """ + + @wraps(func) + async def async_wrapper(*args, **kwargs): + return func(*args, **kwargs) + + return async_wrapper diff --git a/src/backend/run b/src/backend/run deleted file mode 100755 index c9ba24768..000000000 --- a/src/backend/run +++ /dev/null @@ -1,8 +0,0 @@ -#! /bin/bash - -poetry remove langchain -docker build -t logspace/backend_build -f build.Dockerfile . -VERSION=$(toml get --toml-path pyproject.toml tool.poetry.version) -docker build --build-arg VERSION=$VERSION -t ibiscp/langflow:$VERSION . -docker run -p 5003:80 -d ibiscp/langflow:$VERSION -poetry add --editable ../../../langchain diff --git a/src/frontend/build.Dockerfile b/src/frontend/build.Dockerfile deleted file mode 100644 index af2335b5c..000000000 --- a/src/frontend/build.Dockerfile +++ /dev/null @@ -1,5 +0,0 @@ -FROM node:14-alpine -WORKDIR /app -COPY . /app -RUN npm install -RUN npm run build \ No newline at end of file diff --git a/src/frontend/build_and_push b/src/frontend/build_and_push deleted file mode 100755 index f223dd343..000000000 --- a/src/frontend/build_and_push +++ /dev/null @@ -1,11 +0,0 @@ -#! /bin/bash - -# Read the contents of the JSON file -json=$(cat package.json) - -# Extract the value of the "version" field using jq -VERSION=$(echo "$json" | jq -r '.version') - -docker build -t logspace/frontend_build -f build.Dockerfile . -docker build --build-arg VERSION=$VERSION -t ibiscp/langflow_frontend:$VERSION . -docker push ibiscp/langflow_frontend:$VERSION diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index 35d27c5f4..9b90b435e 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -25,13 +25,14 @@ "ace-builds": "^1.16.0", "ansi-to-html": "^0.7.2", "axios": "^1.3.2", + "base64-js": "^1.5.1", "lodash": "^4.17.21", "react": "^18.2.0", "react-ace": "^10.1.0", "react-cookie": "^4.1.1", "react-dom": "^18.2.0", "react-error-boundary": "^4.0.2", - "react-icons": "^4.7.1", + "react-icons": "^4.8.0", "react-laag": "^2.0.5", "react-router-dom": "^6.8.1", "react-scripts": "5.0.1", @@ -5862,6 +5863,25 @@ "resolved": "https://registry.npmjs.org/balanced-match/-/balanced-match-1.0.2.tgz", "integrity": "sha512-3oSeUO0TMV67hN1AmbXsK4yaqU7tjiHlbxRDZOpH0KW9+CeX4bRAaX0Anxt0tx2MrpRpWwQaPwIlISEJhYU5Pw==" }, + "node_modules/base64-js": { + "version": "1.5.1", + "resolved": "https://registry.npmjs.org/base64-js/-/base64-js-1.5.1.tgz", + "integrity": "sha512-AKpaYlHn8t4SVbOHCy+b5+KKgvR4vrsD8vbvrbiQJps7fKDTkjkDry6ji0rUJjC0kzbNePLwzxq8iypo41qeWA==", + "funding": [ + { + "type": "github", + "url": "https://github.com/sponsors/feross" + }, + { + "type": "patreon", + "url": "https://www.patreon.com/feross" + }, + { + "type": "consulting", + "url": "https://feross.org/support" + } + ] + }, "node_modules/batch": { "version": "0.6.1", "resolved": "https://registry.npmjs.org/batch/-/batch-0.6.1.tgz", @@ -15040,9 +15060,9 @@ "integrity": "sha512-/6UZ2qgEyH2aqzYZgQPxEnz33NJ2gNsnHA2o5+o4wW9bLM/JYQitNP9xPhsXwC08hMMovfGe/8retsdDsczPRg==" }, "node_modules/react-icons": { - "version": "4.7.1", - "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-4.7.1.tgz", - "integrity": "sha512-yHd3oKGMgm7zxo3EA7H2n7vxSoiGmHk5t6Ou4bXsfcgWyhfDKMpyKfhHR6Bjnn63c+YXBLBPUql9H4wPJM6sXw==", + "version": "4.8.0", + "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-4.8.0.tgz", + "integrity": "sha512-N6+kOLcihDiAnj5Czu637waJqSnwlMNROzVZMhfX68V/9bu9qHaMIJC4UdozWoOk57gahFCNHwVvWzm0MTzRjg==", "peerDependencies": { "react": "*" } diff --git a/src/frontend/package.json b/src/frontend/package.json index 6eba117fc..388f8c9f7 100644 --- a/src/frontend/package.json +++ b/src/frontend/package.json @@ -20,13 +20,14 @@ "ace-builds": "^1.16.0", "ansi-to-html": "^0.7.2", "axios": "^1.3.2", + "base64-js": "^1.5.1", "lodash": "^4.17.21", "react": "^18.2.0", "react-ace": "^10.1.0", "react-cookie": "^4.1.1", "react-dom": "^18.2.0", "react-error-boundary": "^4.0.2", - "react-icons": "^4.7.1", + "react-icons": "^4.8.0", "react-laag": "^2.0.5", "react-router-dom": "^6.8.1", "react-scripts": "5.0.1", @@ -37,7 +38,7 @@ "web-vitals": "^2.1.4" }, "scripts": { - "start": "react-scripts start", + "start": "NODE_ENV=development react-scripts start", "build": "react-scripts build", "test": "react-scripts test", "eject": "react-scripts eject" @@ -60,5 +61,5 @@ "last 1 safari version" ] }, - "proxy": "http://backend:7860" -} + "proxy": "http://127.0.0.1:7860" +} \ No newline at end of file diff --git a/src/frontend/src/CustomNodes/GenericNode/index.tsx b/src/frontend/src/CustomNodes/GenericNode/index.tsx index bfaa2ba24..fb9771be8 100644 --- a/src/frontend/src/CustomNodes/GenericNode/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/index.tsx @@ -7,12 +7,13 @@ import { } from "../../utils"; import ParameterComponent from "./components/parameterComponent"; import { typesContext } from "../../contexts/typesContext"; -import { useContext, useRef } from "react"; +import { useContext, useState, useEffect, useRef } from "react"; import { NodeDataType } from "../../types/flow"; import { alertContext } from "../../contexts/alertContext"; import { PopUpContext } from "../../contexts/popUpContext"; import NodeModal from "../../modals/NodeModal"; - +import { useCallback } from "react"; +import { TabsContext } from "../../contexts/tabsContext"; export default function GenericNode({ data, selected, @@ -25,6 +26,52 @@ export default function GenericNode({ const { types, deleteNode } = useContext(typesContext); const { openPopUp } = useContext(PopUpContext); const Icon = nodeIcons[types[data.type]]; + const [validationStatus, setValidationStatus] = useState("idle"); + // State for outline color + const [isValid, setIsValid] = useState(false); + const {save} = useContext(TabsContext) + const { reactFlowInstance } = useContext(typesContext); + const [params, setParams] = useState([]); + + console.log(); + + useEffect(() => { + if (reactFlowInstance) { + setParams(Object.values(reactFlowInstance.toObject())); + } + }, [save]); + + useEffect(() => { + try { + fetch(`/validate/node/${data.id}`, { + method: "POST", + headers: { + "Content-Type": "application/json", + }, + body: JSON.stringify(reactFlowInstance.toObject()), + }).then((response) => { + console.log(response.status, response.body); + + if (response.status === 200) { + setValidationStatus("success"); + } else if (response.status === 500) { + setValidationStatus("error"); + } + }); + } catch (error) { + console.error("Error validating node:", error); + setValidationStatus("error"); + } + }, [params]); + + useEffect(() => { + if (validationStatus === "success") { + setIsValid(true); + } else { + setIsValid(false); + } + }, [validationStatus]); + if (!Icon) { if (showError.current) { setErrorData({ @@ -37,9 +84,11 @@ export default function GenericNode({ deleteNode(data.id); return; } + return (
{dropItem.title}
++ {dropItem.link ? ( + + Details + ) : ( <>> )} -
{dropItem.title}
-- {dropItem.link ? ( - - Details - - ) : ( - <>> - )} -
-+ {dropItem.title} +
+- {dropItem.title} -
-