diff --git a/src/backend/langflow/api/callback.py b/src/backend/langflow/api/callback.py index baab596a4..d63e107c4 100644 --- a/src/backend/langflow/api/callback.py +++ b/src/backend/langflow/api/callback.py @@ -1,12 +1,13 @@ +import asyncio from typing import Any -from langchain.callbacks.base import AsyncCallbackHandler +from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler from langflow.api.schemas import ChatResponse # https://github.com/hwchase17/chat-langchain/blob/master/callback.py -class StreamingLLMCallbackHandler(AsyncCallbackHandler): +class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler): """Callback handler for streaming LLM responses.""" def __init__(self, websocket): @@ -15,3 +16,17 @@ class StreamingLLMCallbackHandler(AsyncCallbackHandler): 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()) + + +class StreamingLLMCallbackHandler(BaseCallbackHandler): + """Callback handler for streaming LLM responses.""" + + def __init__(self, websocket): + self.websocket = websocket + + def on_llm_new_token(self, token: str, **kwargs: Any) -> None: + resp = ChatResponse(message=token, type="stream", intermediate_steps="") + + loop = asyncio.get_event_loop() + coroutine = self.websocket.send_json(resp.dict()) + asyncio.run_coroutine_threadsafe(coroutine, loop) diff --git a/src/backend/langflow/api/chat.py b/src/backend/langflow/api/chat.py index e25d0d2f1..4afa6c22f 100644 --- a/src/backend/langflow/api/chat.py +++ b/src/backend/langflow/api/chat.py @@ -1,4 +1,10 @@ -from fastapi import APIRouter, WebSocket +from fastapi import ( + APIRouter, + WebSocket, + WebSocketDisconnect, + WebSocketException, + status, +) from langflow.api.chat_manager import ChatManager from langflow.utils.logger import logger @@ -12,7 +18,9 @@ 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 + except WebSocketException as exc: + logger.error(exc) + await websocket.close(code=status.WS_1011_INTERNAL_ERROR, reason=str(exc)) + except WebSocketDisconnect as exc: + logger.error(exc) + await websocket.close(code=status.WS_1000_NORMAL_CLOSURE, reason=str(exc)) diff --git a/src/backend/langflow/api/chat_manager.py b/src/backend/langflow/api/chat_manager.py index 2dab12e34..3636a94f3 100644 --- a/src/backend/langflow/api/chat_manager.py +++ b/src/backend/langflow/api/chat_manager.py @@ -3,7 +3,7 @@ import json from collections import defaultdict from typing import Dict, List -from fastapi import WebSocket +from fastapi import WebSocket, status from langflow.api.schemas import ChatMessage, ChatResponse, FileResponse from langflow.cache import cache_manager @@ -47,7 +47,6 @@ 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) @@ -91,7 +90,7 @@ class ChatManager: self.active_connections[client_id] = websocket def disconnect(self, client_id: str): - del self.active_connections[client_id] + self.active_connections.pop(client_id, None) async def send_message(self, client_id: str, message: str): websocket = self.active_connections[client_id] @@ -109,7 +108,7 @@ class ChatManager: graph_data = payload start_resp = ChatResponse(message=None, type="start", intermediate_steps="") - self.chat_history.add_message(client_id, start_resp) + await self.send_json(client_id, start_resp) is_first_message = len(self.chat_history.get_history(client_id=client_id)) == 0 # Generate result and thought @@ -143,11 +142,12 @@ class ChatManager: break response = ChatResponse( - message=result or "", + message=result, intermediate_steps=intermediate_steps.strip(), type="end", files=file_responses, ) + await self.send_json(client_id, response) self.chat_history.add_message(client_id, response) async def handle_websocket(self, client_id: str, websocket: WebSocket): @@ -171,17 +171,24 @@ class ChatManager: 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" + code=status.WS_1011_INTERNAL_ERROR, reason=str(e)[:120] ) self.disconnect(client_id) + finally: + try: + connection = self.active_connections.get(client_id) + if connection: + await connection.close(code=1000, reason="Client disconnected") + self.disconnect(client_id) + except Exception as e: + logger.exception(e) + self.disconnect(client_id) async def process_graph( @@ -203,8 +210,8 @@ async def process_graph( # Generate result and thought try: logger.debug("Generating result and thought") - result, intermediate_steps = get_result_and_steps( - langchain_object, chat_message.message or "" + result, intermediate_steps = await get_result_and_steps( + langchain_object, chat_message.message or "", websocket=websocket ) logger.debug("Generated result and intermediate_steps") return result, intermediate_steps diff --git a/src/backend/langflow/api/endpoints.py b/src/backend/langflow/api/endpoints.py index b8290e691..eae0e9f60 100644 --- a/src/backend/langflow/api/endpoints.py +++ b/src/backend/langflow/api/endpoints.py @@ -1,8 +1,13 @@ import logging -from typing import Any, Dict from fastapi import APIRouter, HTTPException +from langflow.api.schemas import ( + ExportedFlow, + GraphData, + PredictRequest, + PredictResponse, +) from langflow.interface.run import process_graph_cached from langflow.interface.types import build_langchain_types_dict @@ -16,10 +21,14 @@ def get_all(): return build_langchain_types_dict() -@router.post("/predict") -def get_load(data: Dict[str, Any]): +@router.post("/predict", response_model=PredictResponse) +async def get_load(predict_request: PredictRequest): try: - return process_graph_cached(data) + exported_flow: ExportedFlow = predict_request.exported_flow + graph_data: GraphData = exported_flow.data + data = graph_data.dict() + response = process_graph_cached(data, predict_request.message) + return PredictResponse(result=response.get("result", "")) except Exception as e: # Log stack trace logger.exception(e) diff --git a/src/backend/langflow/api/schemas.py b/src/backend/langflow/api/schemas.py index dd157d85f..f73b0642d 100644 --- a/src/backend/langflow/api/schemas.py +++ b/src/backend/langflow/api/schemas.py @@ -1,8 +1,37 @@ -from typing import Any, Union +from typing import Any, Dict, List, Union from pydantic import BaseModel, validator +class GraphData(BaseModel): + """Data inside the exported flow.""" + + nodes: List[Dict[str, Any]] + edges: List[Dict[str, Any]] + + +class ExportedFlow(BaseModel): + """Exported flow from LangFlow.""" + + description: str + name: str + id: str + data: GraphData + + +class PredictRequest(BaseModel): + """Predict request schema.""" + + message: str + exported_flow: ExportedFlow + + +class PredictResponse(BaseModel): + """Predict response schema.""" + + result: str + + class ChatMessage(BaseModel): """Chat message schema.""" diff --git a/src/backend/langflow/interface/agents/custom.py b/src/backend/langflow/interface/agents/custom.py index 6d2efed68..d85ba8a56 100644 --- a/src/backend/langflow/interface/agents/custom.py +++ b/src/backend/langflow/interface/agents/custom.py @@ -1,3 +1,4 @@ +from abc import ABC from typing import Any, List, Optional from langchain import LLMChain @@ -27,14 +28,31 @@ from langchain.agents.agent_toolkits.vectorstore.prompt import ( from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS as SQL_FORMAT_INSTRUCTIONS from langchain.base_language import BaseLanguageModel - from langchain.memory.chat_memory import BaseChatMemory from langchain.sql_database import SQLDatabase from langchain.tools.python.tool import PythonAstREPLTool from langchain.tools.sql_database.prompt import QUERY_CHECKER -class JsonAgent(AgentExecutor): +class CustomAgentExecutor(AgentExecutor, ABC): + """Custom agent executor""" + + @staticmethod + def function_name(): + return "CustomAgentExecutor" + + @classmethod + def initialize(cls, *args, **kwargs): + pass + + def __init__(self, *args, **kwargs): + super().__init__(*args, **kwargs) + + def run(self, *args, **kwargs): + return super().run(*args, **kwargs) + + +class JsonAgent(CustomAgentExecutor): """Json agent""" @staticmethod @@ -70,7 +88,7 @@ class JsonAgent(AgentExecutor): return super().run(*args, **kwargs) -class CSVAgent(AgentExecutor): +class CSVAgent(CustomAgentExecutor): """CSV agent""" @staticmethod @@ -118,7 +136,7 @@ class CSVAgent(AgentExecutor): return super().run(*args, **kwargs) -class VectorStoreAgent(AgentExecutor): +class VectorStoreAgent(CustomAgentExecutor): """Vector Store agent""" @staticmethod @@ -156,7 +174,7 @@ class VectorStoreAgent(AgentExecutor): return super().run(*args, **kwargs) -class SQLAgent(AgentExecutor): +class SQLAgent(CustomAgentExecutor): """SQL agent""" @staticmethod @@ -228,7 +246,7 @@ class SQLAgent(AgentExecutor): return super().run(*args, **kwargs) -class VectorStoreRouterAgent(AgentExecutor): +class VectorStoreRouterAgent(CustomAgentExecutor): """Vector Store Router Agent""" @staticmethod @@ -267,7 +285,7 @@ class VectorStoreRouterAgent(AgentExecutor): return super().run(*args, **kwargs) -class InitializeAgent(AgentExecutor): +class InitializeAgent(CustomAgentExecutor): """Implementation of initialize_agent function""" @staticmethod diff --git a/src/backend/langflow/interface/importing/utils.py b/src/backend/langflow/interface/importing/utils.py index 0d14249cb..8c65bf60e 100644 --- a/src/backend/langflow/interface/importing/utils.py +++ b/src/backend/langflow/interface/importing/utils.py @@ -5,9 +5,9 @@ from typing import Any, Type from langchain import PromptTemplate from langchain.agents import Agent +from langchain.base_language import BaseLanguageModel from langchain.chains.base import Chain from langchain.chat_models.base import BaseChatModel -from langchain.base_language import BaseLanguageModel from langchain.tools import BaseTool diff --git a/src/backend/langflow/interface/loading.py b/src/backend/langflow/interface/loading.py index a2d9a799c..0e23c2b45 100644 --- a/src/backend/langflow/interface/loading.py +++ b/src/backend/langflow/interface/loading.py @@ -13,9 +13,9 @@ from langchain.agents.load_tools import ( ) from langchain.agents.loading import load_agent_from_config from langchain.agents.tools import Tool +from langchain.base_language import BaseLanguageModel from langchain.callbacks.base import BaseCallbackManager from langchain.chains.loading import load_chain_from_config -from langchain.base_language import BaseLanguageModel from langchain.llms.loading import load_llm_from_config from pydantic import ValidationError @@ -30,88 +30,19 @@ from langflow.utils import util, validate def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any: """Instantiate class from module type and key, and params""" + params = convert_params_to_sets(params) + if node_type in CUSTOM_AGENTS: - if custom_agent := CUSTOM_AGENTS.get(node_type): - return custom_agent.initialize(**params) # type: ignore - params = process_params(params) + custom_agent = CUSTOM_AGENTS.get(node_type) + if custom_agent: + return custom_agent.initialize(**params) + 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 - return load_agent_executor(class_object, params) - elif base_type == "prompts": - if node_type == "ZeroShotPrompt": - if "tools" not in params: - params["tools"] = [] - return ZeroShotAgent.create_prompt(**params) - elif base_type == "tools": - if node_type == "JsonSpec": - params["dict_"] = load_file_into_dict(params.pop("path")) - return class_object(**params) - elif node_type == "PythonFunction": - # If the node_type is "PythonFunction" - # we need to get the function from the params - # which will be a str containing a python function - # and then we need to compile it and return the function - # as the instance - function_string = params["code"] - if isinstance(function_string, str): - return validate.eval_function(function_string) - raise ValueError("Function should be a string") - elif node_type.lower() == "tool": - return class_object(**params) - elif base_type == "toolkits": - loaded_toolkit = class_object(**params) - # Check if node_type has a loader - if toolkits_creator.has_create_function(node_type): - return load_toolkits_executor(node_type, loaded_toolkit, params) - return loaded_toolkit - elif base_type == "embeddings": - # ? Why remove model from params? - try: - params.pop("model") - except KeyError: - pass - # remove all params that are not in class_object.__fields__ - try: - return class_object(**params) - except ValidationError: - params = { - key: value - for key, value in params.items() - if key in class_object.__fields__ - } - return class_object(**params) - elif base_type == "vectorstores": - if len(params.get("documents", [])) == 0: - # Error when the pdf or other source was not correctly - # loaded. - raise ValueError( - "The source you provided did not load correctly or was empty." - "This may cause an error in the vectorstore." - ) - return class_object.from_documents(**params) - elif base_type == "documentloaders": - return class_object(**params).load() - elif base_type == "textsplitters": - documents = params.pop("documents") - text_splitter = class_object(**params) - return text_splitter.split_documents(documents) - elif base_type == "utilities": - if node_type == "SQLDatabase": - return class_object.from_uri(params.pop("uri")) - - return class_object(**params) + return instantiate_based_on_type(class_object, base_type, node_type, params) -def process_params(params): - """Process params""" +def convert_params_to_sets(params): + """Convert certain params to sets""" if "allowed_special" in params: params["allowed_special"] = set(params["allowed_special"]) if "disallowed_special" in params: @@ -119,6 +50,100 @@ def process_params(params): return params +def instantiate_based_on_type(class_object, base_type, node_type, params): + if base_type == "agents": + return instantiate_agent(class_object, params) + elif base_type == "prompts": + return instantiate_prompt(node_type, params) + elif base_type == "tools": + return instantiate_tool(node_type, class_object, params) + elif base_type == "toolkits": + return instantiate_toolkit(node_type, class_object, params) + elif base_type == "embeddings": + return instantiate_embedding(class_object, params) + elif base_type == "vectorstores": + return instantiate_vectorstore(class_object, params) + elif base_type == "documentloaders": + return instantiate_documentloader(class_object, params) + elif base_type == "textsplitters": + return instantiate_textsplitter(class_object, params) + elif base_type == "utilities": + return instantiate_utility(node_type, class_object, params) + else: + return class_object(**params) + + +def instantiate_agent(class_object, params): + return load_agent_executor(class_object, params) + + +def instantiate_prompt(node_type, params): + if node_type == "ZeroShotPrompt": + if "tools" not in params: + params["tools"] = [] + return ZeroShotAgent.create_prompt(**params) + return None # Or some other default action + + +def instantiate_tool(node_type, class_object, params): + if node_type == "JsonSpec": + params["dict_"] = load_file_into_dict(params.pop("path")) + return class_object(**params) + elif node_type == "PythonFunction": + function_string = params["code"] + if isinstance(function_string, str): + return validate.eval_function(function_string) + raise ValueError("Function should be a string") + elif node_type.lower() == "tool": + return class_object(**params) + return None # Or some other default action + + +def instantiate_toolkit(node_type, class_object, params): + loaded_toolkit = class_object(**params) + if toolkits_creator.has_create_function(node_type): + return load_toolkits_executor(node_type, loaded_toolkit, params) + return loaded_toolkit + + +def instantiate_embedding(class_object, params): + params.pop("model", None) + try: + return class_object(**params) + except ValidationError: + params = { + key: value + for key, value in params.items() + if key in class_object.__fields__ + } + return class_object(**params) + + +def instantiate_vectorstore(class_object, params): + if len(params.get("documents", [])) == 0: + raise ValueError( + "The source you provided did not load correctly or was empty." + "This may cause an error in the vectorstore." + ) + return class_object.from_documents(**params) + + +def instantiate_documentloader(class_object, params): + return class_object(**params).load() + + +def instantiate_textsplitter(class_object, params): + documents = params.pop("documents") + text_splitter = class_object(**params) + return text_splitter.split_documents(documents) + + +def instantiate_utility(node_type, class_object, params): + if node_type == "SQLDatabase": + return class_object.from_uri(params.pop("uri")) + return class_object(**params) + + def load_flow_from_json(path: str, build=True): # This is done to avoid circular imports from langflow.graph import Graph diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py index 68639785c..af80b7acd 100644 --- a/src/backend/langflow/interface/run.py +++ b/src/backend/langflow/interface/run.py @@ -4,9 +4,9 @@ from typing import Any, Dict from chromadb.errors import NotEnoughElementsException # type: ignore +from langflow.api.callback import AsyncStreamingLLMCallbackHandler, StreamingLLMCallbackHandler # type: ignore 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 @@ -66,47 +66,12 @@ def build_langchain_object(data_graph): return graph.build() -def process_graph(data_graph: Dict[str, Any]): +def process_graph_cached(data_graph: Dict[str, Any], message: str): """ Process graph by extracting input variables and replacing ZeroShotPrompt with PromptTemplate,then run the graph and return the result and thought. """ # Load langchain object - logger.debug("Loading langchain object") - message = data_graph.pop("message", "") - is_first_message = len(data_graph.get("chatHistory", [])) == 0 - computed_hash, langchain_object = load_langchain_object( - data_graph, is_first_message - ) - 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 - logger.debug("Generating result and thought") - result, thought = get_result_and_steps(langchain_object, message) - logger.debug("Generated result and thought") - - # Save langchain_object to cache - # We have to save it here because if the - # memory is updated we need to keep the new values - logger.debug("Saving langchain object to cache") - # save_cache(computed_hash, langchain_object, is_first_message) - logger.debug("Saved langchain object to cache") - return {"result": str(result), "thought": thought.strip()} - - -def process_graph_cached(data_graph: Dict[str, Any]): - """ - Process graph by extracting input variables and replacing ZeroShotPrompt - with PromptTemplate,then run the graph and return the result and thought. - """ - # Load langchain object - message = data_graph.pop("message", "") is_first_message = len(data_graph.get("chatHistory", [])) == 0 langchain_object = load_or_build_langchain_object(data_graph, is_first_message) logger.debug("Loaded langchain object") @@ -119,7 +84,7 @@ def process_graph_cached(data_graph: Dict[str, Any]): # Generate result and thought logger.debug("Generating result and thought") - result, thought = get_result_and_steps(langchain_object, message) + result, thought = get_result_and_thought(langchain_object, message) logger.debug("Generated result and thought") return {"result": str(result), "thought": thought.strip()} @@ -185,8 +150,9 @@ def fix_memory_inputs(langchain_object): update_memory_keys(langchain_object, possible_new_mem_key) -def get_result_and_steps(langchain_object, message: str): +async def get_result_and_steps(langchain_object, message: str, **kwargs): """Get result and thought from extracted json""" + try: if hasattr(langchain_object, "verbose"): langchain_object.verbose = True @@ -206,17 +172,21 @@ def get_result_and_steps(langchain_object, message: str): # https://github.com/hwchase17/langchain/issues/2068 # Deactivating until we have a frontend solution # to display intermediate steps - langchain_object.return_intermediate_steps = False + langchain_object.return_intermediate_steps = True fix_memory_inputs(langchain_object) with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer): try: - output = langchain_object(chat_input) - except ValueError as exc: + async_callbacks = [AsyncStreamingLLMCallbackHandler(**kwargs)] + output = await langchain_object.acall( + chat_input, callbacks=async_callbacks + ) + except Exception as exc: # make the error message more informative logger.debug(f"Error: {str(exc)}") - output = langchain_object.run(chat_input) + sync_callbacks = [StreamingLLMCallbackHandler(**kwargs)] + output = langchain_object(chat_input, callbacks=sync_callbacks) intermediate_steps = ( output.get("intermediate_steps", []) if isinstance(output, dict) else [] @@ -241,7 +211,7 @@ def get_result_and_steps(langchain_object, message: str): return result, thought -def async_get_result_and_steps(langchain_object, message: str): +def get_result_and_thought(langchain_object, message: str): """Get result and thought from extracted json""" try: if hasattr(langchain_object, "verbose"): @@ -296,34 +266,6 @@ def async_get_result_and_steps(langchain_object, message: str): return result, thought -def get_result_and_thought(extracted_json: Dict[str, Any], message: str): - """Get result and thought from extracted json""" - try: - langchain_object = loading.load_langchain_type_from_config( - config=extracted_json - ) - with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer): - output = langchain_object(message) - 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 e: - result = f"Error: {str(e)}" - thought = "" - return result, thought - - def format_intermediate_steps(intermediate_steps): formatted_chain = "> Entering new AgentExecutor chain...\n" for step in intermediate_steps: diff --git a/src/backend/langflow/interface/utils.py b/src/backend/langflow/interface/utils.py index e8b3e417e..7368fda3e 100644 --- a/src/backend/langflow/interface/utils.py +++ b/src/backend/langflow/interface/utils.py @@ -4,13 +4,9 @@ import os from io import BytesIO import yaml -from langchain.callbacks.manager import AsyncCallbackManager -from langchain.chat_models import AzureChatOpenAI, ChatOpenAI -from langchain.llms import AzureOpenAI, OpenAI +from langchain.base_language import BaseLanguageModel from PIL.Image import Image -from langflow.api.callback import StreamingLLMCallbackHandler - def load_file_into_dict(file_path: str) -> dict: if not os.path.exists(file_path): @@ -48,10 +44,7 @@ def try_setting_streaming_options(langchain_object, websocket): langchain_object.llm_chain, "llm" ): llm = langchain_object.llm_chain.llm - if isinstance(llm, (OpenAI, ChatOpenAI, AzureOpenAI, AzureChatOpenAI)): + if isinstance(llm, BaseLanguageModel): 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/template/nodes.py b/src/backend/langflow/template/nodes.py index 61a41589b..6ce08e57b 100644 --- a/src/backend/langflow/template/nodes.py +++ b/src/backend/langflow/template/nodes.py @@ -123,6 +123,13 @@ class MidJourneyPromptChainNode(FrontendNode): multiline=False, name="llm", ), + TemplateField( + field_type="BaseChatMemory", + required=False, + show=True, + name="memory", + advanced=False, + ), ], ) description: str = "MidJourneyPromptChain is a chain you can use to generate new MidJourney prompts." diff --git a/src/frontend/dev.Dockerfile b/src/frontend/dev.Dockerfile index df5f7f5dc..4773fc2b9 100644 --- a/src/frontend/dev.Dockerfile +++ b/src/frontend/dev.Dockerfile @@ -15,7 +15,10 @@ WORKDIR /home/node/app COPY --chown=node:node . ./ COPY ./set_proxy.sh . -RUN chmod +x set_proxy.sh && ./set_proxy.sh +RUN chmod +x set_proxy.sh && \ + cat set_proxy.sh | tr -d '\r' > set_proxy_unix.sh && \ + chmod +x set_proxy_unix.sh && \ + ./set_proxy_unix.sh USER node diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index bbb60b863..1722f2514 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -35,14 +35,21 @@ "react-error-boundary": "^4.0.2", "react-icons": "^4.8.0", "react-laag": "^2.0.5", + "react-markdown": "^8.0.7", "react-router-dom": "^6.8.1", "react-scripts": "5.0.1", "react-syntax-highlighter": "^15.5.0", "react-tabs": "^6.0.0", "reactflow": "^11.5.5", + "rehype-mathjax": "^4.0.2", + "remark-gfm": "^3.0.1", + "remark-math": "^5.1.1", "tailwindcss": "^3.2.6", "typescript": "^4.9.5", "web-vitals": "^2.1.4" + }, + "devDependencies": { + "@tailwindcss/typography": "^0.5.9" } }, "node_modules/@adobe/css-tools": { @@ -3923,31 +3930,6 @@ "url": "https://github.com/sponsors/gregberge" } }, - "node_modules/@tabler/icons": { - "version": "2.18.0", - "resolved": "https://registry.npmjs.org/@tabler/icons/-/icons-2.18.0.tgz", - "integrity": "sha512-N7a20mwbhrFXNqvd8Rxa0Btwu1Li5rQbqdIi3mzt5HRjP25PbyYuTU2BXbu8yMEnUk018Gi13gpS/jlMgXFuOw==", - "funding": { - "type": "github", - "url": "https://github.com/sponsors/codecalm" - } - }, - "node_modules/@tabler/icons-react": { - "version": "2.18.0", - "resolved": "https://registry.npmjs.org/@tabler/icons-react/-/icons-react-2.18.0.tgz", - "integrity": "sha512-F4HyBIoC3DvIPmjP9ienurvSWhQOajDuTc3C5F7UfjhBkom3cAuJfDWH2tqGAfNrhjvG4X3ERR2dxOWLpegsiA==", - "dependencies": { - "@tabler/icons": 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"is-buffer": "^2.0.0", + "is-plain-obj": "^4.0.0", + "trough": "^2.0.0", + "vfile": "^5.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unified/node_modules/is-plain-obj": { + "version": "4.1.0", + "resolved": "https://registry.npmjs.org/is-plain-obj/-/is-plain-obj-4.1.0.tgz", + "integrity": "sha512-+Pgi+vMuUNkJyExiMBt5IlFoMyKnr5zhJ4Uspz58WOhBF5QoIZkFyNHIbBAtHwzVAgk5RtndVNsDRN61/mmDqg==", + "engines": { + "node": ">=12" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" + } + }, "node_modules/unique-string": { "version": "2.0.0", "resolved": "https://registry.npmjs.org/unique-string/-/unique-string-2.0.0.tgz", @@ -17220,6 +18498,91 @@ "node": ">=8" } }, + "node_modules/unist-util-find-after": { + "version": "4.0.1", + "resolved": "https://registry.npmjs.org/unist-util-find-after/-/unist-util-find-after-4.0.1.tgz", + "integrity": "sha512-QO/PuPMm2ERxC6vFXEPtmAutOopy5PknD+Oq64gGwxKtk4xwo9Z97t9Av1obPmGU0IyTa6EKYUfTrK2QJS3Ozw==", + "dependencies": { + "@types/unist": "^2.0.0", + "unist-util-is": "^5.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-generated": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/unist-util-generated/-/unist-util-generated-2.0.1.tgz", + "integrity": "sha512-qF72kLmPxAw0oN2fwpWIqbXAVyEqUzDHMsbtPvOudIlUzXYFIeQIuxXQCRCFh22B7cixvU0MG7m3MW8FTq/S+A==", + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-is": { + "version": "5.2.1", + "resolved": "https://registry.npmjs.org/unist-util-is/-/unist-util-is-5.2.1.tgz", + "integrity": "sha512-u9njyyfEh43npf1M+yGKDGVPbY/JWEemg5nH05ncKPfi+kBbKBJoTdsogMu33uhytuLlv9y0O7GH7fEdwLdLQw==", + "dependencies": { + "@types/unist": "^2.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-position": { + "version": "4.0.4", + "resolved": "https://registry.npmjs.org/unist-util-position/-/unist-util-position-4.0.4.tgz", + "integrity": "sha512-kUBE91efOWfIVBo8xzh/uZQ7p9ffYRtUbMRZBNFYwf0RK8koUMx6dGUfwylLOKmaT2cs4wSW96QoYUSXAyEtpg==", + "dependencies": { + "@types/unist": "^2.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-stringify-position": { + "version": "3.0.3", + "resolved": "https://registry.npmjs.org/unist-util-stringify-position/-/unist-util-stringify-position-3.0.3.tgz", + "integrity": "sha512-k5GzIBZ/QatR8N5X2y+drfpWG8IDBzdnVj6OInRNWm1oXrzydiaAT2OQiA8DPRRZyAKb9b6I2a6PxYklZD0gKg==", + "dependencies": { + "@types/unist": "^2.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-visit": { + "version": "4.1.2", + "resolved": "https://registry.npmjs.org/unist-util-visit/-/unist-util-visit-4.1.2.tgz", + "integrity": "sha512-MSd8OUGISqHdVvfY9TPhyK2VdUrPgxkUtWSuMHF6XAAFuL4LokseigBnZtPnJMu+FbynTkFNnFlyjxpVKujMRg==", + "dependencies": { + "@types/unist": "^2.0.0", + "unist-util-is": "^5.0.0", + "unist-util-visit-parents": "^5.1.1" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/unist-util-visit-parents": { + "version": "5.1.3", + "resolved": "https://registry.npmjs.org/unist-util-visit-parents/-/unist-util-visit-parents-5.1.3.tgz", + "integrity": "sha512-x6+y8g7wWMyQhL1iZfhIPhDAs7Xwbn9nRosDXl7qoPTSCy0yNxnKc+hWokFifWQIDGi154rdUqKvbCa4+1kLhg==", + "dependencies": { + "@types/unist": "^2.0.0", + "unist-util-is": "^5.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, "node_modules/universal-cookie": { "version": "4.0.4", "resolved": "https://registry.npmjs.org/universal-cookie/-/universal-cookie-4.0.4.tgz", @@ -17357,6 +18720,31 @@ "uuid": "dist/bin/uuid" } }, + "node_modules/uvu": { + "version": "0.5.6", + "resolved": "https://registry.npmjs.org/uvu/-/uvu-0.5.6.tgz", + "integrity": "sha512-+g8ENReyr8YsOc6fv/NVJs2vFdHBnBNdfE49rshrTzDWOlUx4Gq7KOS2GD8eqhy2j+Ejq29+SbKH8yjkAqXqoA==", + "dependencies": { + "dequal": "^2.0.0", + "diff": "^5.0.0", + "kleur": "^4.0.3", + "sade": "^1.7.3" + }, + "bin": { + "uvu": "bin.js" + }, + "engines": { + "node": ">=8" + } + }, + "node_modules/uvu/node_modules/kleur": { + "version": "4.1.5", + "resolved": "https://registry.npmjs.org/kleur/-/kleur-4.1.5.tgz", + "integrity": "sha512-o+NO+8WrRiQEE4/7nwRJhN1HWpVmJm511pBHUxPLtp0BUISzlBplORYSmTclCnJvQq2tKu/sgl3xVpkc7ZWuQQ==", + "engines": { + "node": ">=6" + } + }, "node_modules/v8-to-istanbul": { "version": "8.1.1", "resolved": "https://registry.npmjs.org/v8-to-istanbul/-/v8-to-istanbul-8.1.1.tgz", @@ -17378,6 +18766,34 @@ "node": ">= 0.8" } }, + "node_modules/vfile": { + "version": "5.3.7", + "resolved": "https://registry.npmjs.org/vfile/-/vfile-5.3.7.tgz", + "integrity": "sha512-r7qlzkgErKjobAmyNIkkSpizsFPYiUPuJb5pNW1RB4JcYVZhs4lIbVqk8XPk033CV/1z8ss5pkax8SuhGpcG8g==", + "dependencies": { + "@types/unist": "^2.0.0", + "is-buffer": "^2.0.0", + "unist-util-stringify-position": "^3.0.0", + "vfile-message": "^3.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, + "node_modules/vfile-message": { + "version": "3.1.4", + "resolved": "https://registry.npmjs.org/vfile-message/-/vfile-message-3.1.4.tgz", + "integrity": "sha512-fa0Z6P8HUrQN4BZaX05SIVXic+7kE3b05PWAtPuYP9QLHsLKYR7/AlLW3NtOrpXRLeawpDLMsVkmk5DG0NXgWw==", + "dependencies": { + "@types/unist": "^2.0.0", + "unist-util-stringify-position": "^3.0.0" + }, + "funding": { + "type": "opencollective", + "url": "https://opencollective.com/unified" + } + }, "node_modules/w3c-hr-time": { "version": "1.0.2", "resolved": "https://registry.npmjs.org/w3c-hr-time/-/w3c-hr-time-1.0.2.tgz", @@ -17426,6 +18842,15 @@ "minimalistic-assert": "^1.0.0" } }, + "node_modules/web-namespaces": { + "version": "2.0.1", + "resolved": "https://registry.npmjs.org/web-namespaces/-/web-namespaces-2.0.1.tgz", + "integrity": "sha512-bKr1DkiNa2krS7qxNtdrtHAmzuYGFQLiQ13TsorsdT6ULTkPLKuu5+GsFpDlg6JFjUTwX2DyhMPG2be8uPrqsQ==", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } + }, "node_modules/web-vitals": { "version": "2.1.4", "resolved": "https://registry.npmjs.org/web-vitals/-/web-vitals-2.1.4.tgz", @@ -17872,6 +19297,11 @@ "url": "https://github.com/sponsors/ljharb" } }, + "node_modules/wicked-good-xpath": { + "version": "1.3.0", + "resolved": "https://registry.npmjs.org/wicked-good-xpath/-/wicked-good-xpath-1.3.0.tgz", + "integrity": "sha512-Gd9+TUn5nXdwj/hFsPVx5cuHHiF5Bwuc30jZ4+ronF1qHK5O7HD0sgmXWSEgwKquT3ClLoKPVbO6qGwVwLzvAw==" + }, "node_modules/word-wrap": { "version": "1.2.3", "resolved": "https://registry.npmjs.org/word-wrap/-/word-wrap-1.2.3.tgz", @@ -18266,6 +19696,14 @@ "resolved": "https://registry.npmjs.org/xmlchars/-/xmlchars-2.2.0.tgz", "integrity": "sha512-JZnDKK8B0RCDw84FNdDAIpZK+JuJw+s7Lz8nksI7SIuU3UXJJslUthsi+uWBUYOwPFwW7W7PRLRfUKpxjtjFCw==" }, + "node_modules/xmldom-sre": { + "version": "0.1.31", + "resolved": "https://registry.npmjs.org/xmldom-sre/-/xmldom-sre-0.1.31.tgz", + "integrity": "sha512-f9s+fUkX04BxQf+7mMWAp5zk61pciie+fFLC9hX9UVvCeJQfNHRHXpeo5MPcR0EUf57PYLdt+ZO4f3Ipk2oZUw==", + "engines": { + "node": ">=0.1" + } + }, "node_modules/xtend": { "version": "4.0.2", "resolved": "https://registry.npmjs.org/xtend/-/xtend-4.0.2.tgz", @@ -18353,6 +19791,15 @@ "optional": true } } + }, + "node_modules/zwitch": { + "version": "2.0.4", + "resolved": "https://registry.npmjs.org/zwitch/-/zwitch-2.0.4.tgz", + "integrity": "sha512-bXE4cR/kVZhKZX/RjPEflHaKVhUVl85noU3v6b8apfQEc1x4A+zBxjZ4lN8LqGd6WZ3dl98pY4o717VFmoPp+A==", + "funding": { + "type": "github", + "url": "https://github.com/sponsors/wooorm" + } } } } diff --git a/src/frontend/package.json b/src/frontend/package.json index 4467156ec..9a035a0ea 100644 --- a/src/frontend/package.json +++ b/src/frontend/package.json @@ -30,11 +30,16 @@ "react-error-boundary": "^4.0.2", "react-icons": "^4.8.0", "react-laag": "^2.0.5", + "react-markdown": "^8.0.7", "react-router-dom": "^6.8.1", "react-scripts": "5.0.1", "react-syntax-highlighter": "^15.5.0", + "react-syntax-highlighter": "^15.5.0", "react-tabs": "^6.0.0", "reactflow": "^11.5.5", + "rehype-mathjax": "^4.0.2", + "remark-gfm": "^3.0.1", + "remark-math": "^5.1.1", "tailwindcss": "^3.2.6", "typescript": "^4.9.5", "web-vitals": "^2.1.4" @@ -63,5 +68,8 @@ "last 1 safari version" ] }, - "proxy": "http://127.0.0.1:7860" + "proxy": "http://127.0.0.1:7860", + "devDependencies": { + "@tailwindcss/typography": "^0.5.9" + } } diff --git a/src/frontend/set_proxy.sh b/src/frontend/set_proxy.sh index e9ad9f109..0330c2915 100755 --- a/src/frontend/set_proxy.sh +++ b/src/frontend/set_proxy.sh @@ -7,4 +7,4 @@ packagejson=$(cat package.json) packagejson=$(echo "$packagejson" | jq ".proxy = \"$backend_url\"") -echo "$packagejson" > package.json +echo "$packagejson" > package.json \ No newline at end of file diff --git a/src/frontend/src/App.css b/src/frontend/src/App.css index 319e2ba39..be7173d7f 100644 --- a/src/frontend/src/App.css +++ b/src/frontend/src/App.css @@ -3,45 +3,45 @@ @tailwind utilities; .App { - text-align: center; + text-align: center; } .App-logo { - height: 40vmin; - pointer-events: none; + height: 40vmin; + pointer-events: none; } @media (prefers-reduced-motion: no-preference) { - .App-logo { - animation: App-logo-spin infinite 20s linear; - } + .App-logo { + animation: App-logo-spin infinite 20s linear; + } } .App-header { - background-color: #282c34; - min-height: 100vh; - display: flex; - flex-direction: column; - align-items: center; - justify-content: center; - font-size: calc(10px + 2vmin); - color: white; + background-color: #282c34; + min-height: 100vh; + display: flex; + flex-direction: column; + align-items: center; + justify-content: center; + font-size: calc(10px + 2vmin); + color: white; } .App-link { - color: #61dafb; + color: #61dafb; } @keyframes App-logo-spin { - from { - transform: rotate(0deg); - } - to { - transform: rotate(360deg); - } + from { + transform: rotate(0deg); + } + to { + transform: rotate(360deg); + } } -@font-face{ - font-family: text-security-disc; - src: url("assets/text-security-disc.woff") format("woff"); -} \ No newline at end of file +@font-face { + font-family: text-security-disc; + src: url("assets/text-security-disc.woff") format("woff"); +} diff --git a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx index 1a2eeb9e6..c79904661 100644 --- a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx @@ -198,7 +198,9 @@ export default function ParameterComponent({ save(); }} /> - ):(<>>)} + ) : ( + <>> + )} > ); diff --git a/src/frontend/src/CustomNodes/GenericNode/index.tsx b/src/frontend/src/CustomNodes/GenericNode/index.tsx index da55e690c..85e7810a1 100644 --- a/src/frontend/src/CustomNodes/GenericNode/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/index.tsx @@ -1,10 +1,5 @@ import { BugAntIcon, Cog6ToothIcon, ExclamationCircleIcon, InformationCircleIcon, TrashIcon } from "@heroicons/react/24/outline"; -import { - classNames, - nodeColors, - nodeIcons, - toNormalCase, -} from "../../utils"; +import { classNames, nodeColors, nodeIcons, toNormalCase } from "../../utils"; import ParameterComponent from "./components/parameterComponent"; import { typesContext } from "../../contexts/typesContext"; import { useContext, useState, useEffect, useRef, Fragment } from "react"; @@ -17,11 +12,11 @@ import { TabsContext } from "../../contexts/tabsContext"; import { debounce } from "../../utils"; import Tooltip from "../../components/TooltipComponent"; export default function GenericNode({ - data, - selected, + data, + selected, }: { - data: NodeDataType; - selected: boolean; + data: NodeDataType; + selected: boolean; }) { const { setErrorData } = useContext(alertContext); const showError = useRef(true); @@ -35,23 +30,22 @@ export default function GenericNode({ const { reactFlowInstance } = useContext(typesContext); const [params, setParams] = useState([]); + useEffect(() => { + if (reactFlowInstance) { + setParams(Object.values(reactFlowInstance.toObject())); + } + }, [save]); - useEffect(() => { - if (reactFlowInstance) { - setParams(Object.values(reactFlowInstance.toObject())); - } - }, [save]); - - const validateNode = useCallback( - debounce(async () => { - try { - const response = await fetch(`/validate/node/${data.id}`, { - method: "POST", - headers: { - "Content-Type": "application/json", - }, - body: JSON.stringify(reactFlowInstance.toObject()), - }); + const validateNode = useCallback( + debounce(async () => { + try { + const response = await fetch(`/validate/node/${data.id}`, { + method: "POST", + headers: { + "Content-Type": "application/json", + }, + body: JSON.stringify(reactFlowInstance.toObject()), + }); if (response.status === 200) { let jsonResponse = await response.json(); @@ -84,18 +78,18 @@ export default function GenericNode({ } }, [validationStatus]); - if (!Icon) { - if (showError.current) { - setErrorData({ - title: data.type - ? `The ${data.type} node could not be rendered, please review your json file` - : "There was a node that can't be rendered, please review your json file", - }); - showError.current = false; - } - deleteNode(data.id); - return; - } + if (!Icon) { + if (showError.current) { + setErrorData({ + title: data.type + ? `The ${data.type} node could not be rendered, please review your json file` + : "There was a node that can't be rendered, please review your json file", + }); + showError.current = false; + } + deleteNode(data.id); + return; + } return (
{dropItem.title}
-- {dropItem.link ? ( - - Details - - ) : ( - <>> - )} -
-- {dropItem.title} -
-{dropItem.title}
++ {dropItem.link ? ( + + Details + + ) : ( + <>> + )} +
++ {dropItem.title} +
+- Please click the 'Reset Application' button - to restore the application's state. If the error persists, please - create an issue on our GitHub page. We apologize for any inconvenience - this may have caused. + Please click the 'Reset Application' button to restore the + application's state. If the error persists, please create an issue on + our GitHub page. We apologize for any inconvenience this may have + caused.
+ {children}
+
+ );
+ },
+ }}
+ >
+ {message}
+