diff --git a/.githooks/pre-commit b/.githooks/pre-commit old mode 100644 new mode 100755 diff --git a/.gitignore b/.gitignore index b730d67bc..ee7c1a707 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,5 @@ +# This is to avoid Opencommit hook from getting pushed +prepare-commit-msg # Logs logs *.log @@ -242,4 +244,5 @@ dmypy.json # Poetry .testenv/* langflow.db +.githooks/prepare-commit-msg langchain.db \ No newline at end of file diff --git a/Makefile b/Makefile index bfed91f37..79e27833e 100644 --- a/Makefile +++ b/Makefile @@ -5,6 +5,8 @@ all: help init: @echo 'Installing pre-commit hooks' git config core.hooksPath .githooks + @echo 'Making pre-commit hook executable' + chmod +x .githooks/pre-commit @echo 'Installing backend dependencies' make install_backend @echo 'Installing frontend dependencies' diff --git a/README.md b/README.md index 647210d38..b07ec482d 100644 --- a/README.md +++ b/README.md @@ -31,12 +31,13 @@ - [Table of Contents](#table-of-contents) - [📦 Installation](#-installation) - [Locally](#locally) + - [HuggingFace Spaces](#huggingface-spaces) - [🖥️ Command Line Interface (CLI)](#️-command-line-interface-cli) - [Usage](#usage) - [Environment Variables](#environment-variables) - [Deployment](#deployment) - - [Deploy Langflow on Google Cloud Platform](#deploy-langflow-on-google-cloud-platform) - - [Deploy Langflow on Jina AI Cloud](#deploy-langflow-on-jina-ai-cloud) + - [Deploy Langflow on Google Cloud Platform](#deploy-langflow-on-google-cloud-platform) + - [Deploy Langflow on Jina AI Cloud](#deploy-langflow-on-jina-ai-cloud) - [API Usage](#api-usage) - [🎨 Creating Flows](#-creating-flows) - [👋 Contributing](#-contributing) @@ -61,6 +62,8 @@ or langflow # or langflow --help ``` +### HuggingFace Spaces +You can also check it out on [HuggingFace Spaces](https://huggingface.co/spaces/Logspace/Langflow) and run it in your browser! You can even clone it and have your own copy of Langflow to play with. # 🖥️ Command Line Interface (CLI) @@ -103,7 +106,7 @@ A sample `.env` file named `.env.example` is included with the project. Copy thi # Deployment -### Deploy Langflow on Google Cloud Platform +## Deploy Langflow on Google Cloud Platform Follow our step-by-step guide to deploy Langflow on Google Cloud Platform (GCP) using Google Cloud Shell. The guide is available in the [**Langflow in Google Cloud Platform**](GCP_DEPLOYMENT.md) document. @@ -112,7 +115,7 @@ Alternatively, click the **"Open in Cloud Shell"** button below to launch Google [![Open in Cloud Shell](https://gstatic.com/cloudssh/images/open-btn.svg)](https://console.cloud.google.com/cloudshell/open?git_repo=https://github.com/logspace-ai/langflow&working_dir=scripts&shellonly=true&tutorial=walkthroughtutorial_spot.md) -### Deploy Langflow on [Jina AI Cloud](https://github.com/jina-ai/langchain-serve) +## Deploy Langflow on [Jina AI Cloud](https://github.com/jina-ai/langchain-serve) Langflow integrates with langchain-serve to provide a one-command deployment to Jina AI Cloud. @@ -219,6 +222,13 @@ print(run_flow("Your message", flow_id=FLOW_ID, tweaks=TWEAKS)) > Read more about resource customization, cost, and management of Langflow apps on Jina AI Cloud in the **[langchain-serve](https://github.com/jina-ai/langchain-serve)** repository. +## Deploy on Railway +[![Deploy on Railway](https://railway.app/button.svg)](https://railway.app/template/Emy2sU?referralCode=MnPSdg) + +## Deploy on Render + +Deploy to Render + # 🎨 Creating Flows diff --git a/poetry.lock b/poetry.lock index dd4e1116e..2da880491 100644 --- a/poetry.lock +++ b/poetry.lock @@ -150,23 +150,23 @@ files = [ [[package]] name = "anthropic" -version = "0.3.2" +version = "0.3.4" description = "Client library for the anthropic API" category = "main" optional = false python-versions = ">=3.7,<4.0" files = [ - 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"sha256:21e674f39831ae3f8acde238afd9a27a37d0d2fb5a28ea094f0ce25d2cbf2091"}, ] [package.extras] @@ -5223,14 +5236,14 @@ diagrams = ["jinja2", "railroad-diagrams"] [[package]] name = "pypdf" -version = "3.12.0" +version = "3.12.1" description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files" category = "main" optional = false python-versions = ">=3.6" files = [ - {file = "pypdf-3.12.0-py3-none-any.whl", hash = "sha256:826ad4681660394d7a5742fe8380168cf13058e27b826b7f5b798e994cb77b38"}, - {file = "pypdf-3.12.0.tar.gz", hash = "sha256:cebac920db0698369f49c389018858a5436862bf3c45b64b10c55c008878db95"}, + {file = "pypdf-3.12.1-py3-none-any.whl", hash = "sha256:74aa287c83e9aad2ce4a3627458dad729e39b5deae52175fe9f97bfffdde41bc"}, + {file = "pypdf-3.12.1.tar.gz", hash = "sha256:68bf9e089caaab356518410168df9ed90f0a6109e29adac168449d4054fa0094"}, ] [package.dependencies] @@ -6417,14 +6430,14 @@ sqlcipher = ["sqlcipher3-binary"] [[package]] name = "sqlalchemy2-stubs" -version = "0.0.2a34" +version = "0.0.2a35" description = "Typing Stubs for SQLAlchemy 1.4" category = "main" optional = false python-versions = ">=3.6" files = [ - {file = "sqlalchemy2-stubs-0.0.2a34.tar.gz", hash = "sha256:2432137ab2fde1a608df4544f6712427b0b7ff25990cfbbc5a9d1db6c8c6f489"}, - {file = "sqlalchemy2_stubs-0.0.2a34-py3-none-any.whl", hash = "sha256:a313220ac793404349899faf1272e821a62dbe1d3a029bd444faa8d3e966cd07"}, + {file = "sqlalchemy2-stubs-0.0.2a35.tar.gz", hash = "sha256:bd5d530697d7e8c8504c7fe792ef334538392a5fb7aa7e4f670bfacdd668a19d"}, + {file = "sqlalchemy2_stubs-0.0.2a35-py3-none-any.whl", hash = "sha256:593784ff9fc0dc2ded1895e3322591689db3be06f3ca006e3ef47640baf2d38a"}, ] [package.dependencies] @@ -7377,14 +7390,14 @@ files = [ [[package]] name = "weaviate-client" -version = "3.21.0" +version = "3.22.1" description = "A python native Weaviate client" category = "main" optional = false python-versions = ">=3.8" files = [ - {file = "weaviate-client-3.21.0.tar.gz", hash = "sha256:ec94ac554883c765e94da8b2947c4f0fa4a0378ed3bbe9f3653df3a5b1745a6d"}, - {file = "weaviate_client-3.21.0-py3-none-any.whl", hash = "sha256:420444ded7106fb000f4f8b2321b5f5fa2387825aa7a303d702accf61026f9d2"}, + {file = "weaviate-client-3.22.1.tar.gz", hash = "sha256:aff61bd3f5d74df20a62328443e3aa9c860d5330fdfb19c4d8ddc44cb604032f"}, + {file = "weaviate_client-3.22.1-py3-none-any.whl", hash = "sha256:01843a4899a227300e570409e77628e9d1b28476313f94943c37aee3f75112e1"}, ] [package.dependencies] @@ -7753,19 +7766,19 @@ multidict = ">=4.0" [[package]] name = "zipp" -version = "3.15.0" +version = "3.16.0" description = "Backport of pathlib-compatible object wrapper for zip files" category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"}, - {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"}, + {file = "zipp-3.16.0-py3-none-any.whl", hash = "sha256:5dadc3ad0a1f825fe42ce1bce0f2fc5a13af2e6b2d386af5b0ff295bc0a287d3"}, + {file = "zipp-3.16.0.tar.gz", hash = "sha256:1876cb065531855bbe83b6c489dcf69ecc28f1068d8e95959fe8bbc77774c941"}, ] [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] -testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-ruff"] [[package]] name = "zstandard" @@ -7832,4 +7845,4 @@ deploy = ["langchain-serve"] [metadata] lock-version = "2.0" python-versions = ">=3.9,<3.11" -content-hash = "e25e43fde8f96f57beab702ac4c51cb3e569b81f85c540a7b4b5fb7b6388d04e" +content-hash = "3ef18bc73e595f6aa8c3ee4b4c9666f3328c601933aef1bf225b865f39504e3c" diff --git a/pyproject.toml b/pyproject.toml index 08bdaad65..c82e532f8 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -23,14 +23,14 @@ langflow = "langflow.__main__:main" [tool.poetry.dependencies] python = ">=3.9,<3.11" -fastapi = "^0.99.0" +fastapi = "^0.100.0" uvicorn = "^0.22.0" beautifulsoup4 = "^4.12.2" google-search-results = "^2.4.1" google-api-python-client = "^2.79.0" typer = "^0.9.0" gunicorn = "^20.1.0" -langchain = "^0.0.219" +langchain = "^0.0.229" openai = "^0.27.8" pandas = "^2.0.0" chromadb = "^0.3.21" @@ -78,7 +78,7 @@ black = "^23.1.0" ipykernel = "^6.21.2" mypy = "^1.1.1" ruff = "^0.0.254" -httpx = "^0.23.3" +httpx = "*" pytest = "^7.2.2" types-requests = "^2.28.11" requests = "^2.28.0" diff --git a/render.yaml b/render.yaml new file mode 100644 index 000000000..e67da9334 --- /dev/null +++ b/render.yaml @@ -0,0 +1,11 @@ +services: + # A Docker web service + - type: web + name: langflow + runtime: docker + plan: free + dockerfilePath: ./Dockerfile + repo: https://github.com/logspace-ai/langflow + branch: main + healthCheckPath: /health + autoDeploy: false diff --git a/src/backend/langflow/api/utils.py b/src/backend/langflow/api/utils.py index bfd9e3da5..2384a4089 100644 --- a/src/backend/langflow/api/utils.py +++ b/src/backend/langflow/api/utils.py @@ -22,3 +22,38 @@ def remove_api_keys(flow: dict): value["value"] = None return flow + + +def build_input_keys_response(langchain_object, artifacts): + """Build the input keys response.""" + + input_keys_response = { + "input_keys": {key: "" for key in langchain_object.input_keys}, + "memory_keys": [], + "handle_keys": artifacts.get("handle_keys", []), + } + + # Set the input keys values from artifacts + for key, value in artifacts.items(): + if key in input_keys_response["input_keys"]: + input_keys_response["input_keys"][key] = value + # If the object has memory, that memory will have a memory_variables attribute + # memory variables should be removed from the input keys + if hasattr(langchain_object, "memory") and hasattr( + langchain_object.memory, "memory_variables" + ): + # Remove memory variables from input keys + input_keys_response["input_keys"] = { + key: value + for key, value in input_keys_response["input_keys"].items() + if key not in langchain_object.memory.memory_variables + } + # Add memory variables to memory_keys + input_keys_response["memory_keys"] = langchain_object.memory.memory_variables + + if hasattr(langchain_object, "prompt") and hasattr( + langchain_object.prompt, "template" + ): + input_keys_response["template"] = langchain_object.prompt.template + + return input_keys_response diff --git a/src/backend/langflow/api/v1/base.py b/src/backend/langflow/api/v1/base.py index 6941bedf3..71cac5412 100644 --- a/src/backend/langflow/api/v1/base.py +++ b/src/backend/langflow/api/v1/base.py @@ -1,6 +1,8 @@ +from langflow.template.frontend_node.base import FrontendNode from pydantic import BaseModel, validator from langflow.interface.utils import extract_input_variables_from_prompt +from langchain.prompts import PromptTemplate class CacheResponse(BaseModel): @@ -11,8 +13,14 @@ class Code(BaseModel): code: str -class Prompt(BaseModel): +class FrontendNodeRequest(FrontendNode): + template: dict # type: ignore + + +class ValidatePromptRequest(BaseModel): + name: str template: str + frontend_node: FrontendNodeRequest # Build ValidationResponse class for {"imports": {"errors": []}, "function": {"errors": []}} @@ -31,6 +39,7 @@ class CodeValidationResponse(BaseModel): class PromptValidationResponse(BaseModel): input_variables: list + frontend_node: FrontendNodeRequest INVALID_CHARACTERS = { @@ -51,34 +60,93 @@ INVALID_CHARACTERS = { "}", } +INVALID_NAMES = { + "input_variables", + "output_parser", + "partial_variables", + "template", + "template_format", + "validate_template", +} + def validate_prompt(template: str): input_variables = extract_input_variables_from_prompt(template) # Check if there are invalid characters in the input_variables input_variables = check_input_variables(input_variables) + if any(var in INVALID_NAMES for var in input_variables): + raise ValueError( + f"Invalid input variables. None of the variables can be named {', '.join(input_variables)}. " + ) - return PromptValidationResponse(input_variables=input_variables) + try: + PromptTemplate(template=template, input_variables=input_variables) + except Exception as exc: + raise ValueError(str(exc)) from exc + + return input_variables def check_input_variables(input_variables: list): invalid_chars = [] fixed_variables = [] + wrong_variables = [] + empty_variables = [] for variable in input_variables: new_var = variable - for char in INVALID_CHARACTERS: - if char in variable: - invalid_chars.append(char) - new_var = new_var.replace(char, "") + + # if variable is empty, then we should add that to the wrong variables + if not variable: + empty_variables.append(variable) + continue + + # if variable starts with a number we should add that to the invalid chars + # and wrong variables + if variable[0].isdigit(): + invalid_chars.append(variable[0]) + new_var = new_var.replace(variable[0], "") + wrong_variables.append(variable) + else: + for char in INVALID_CHARACTERS: + if char in variable: + invalid_chars.append(char) + new_var = new_var.replace(char, "") + wrong_variables.append(variable) fixed_variables.append(new_var) - if new_var != variable: - input_variables.remove(variable) - input_variables.append(new_var) # If any of the input_variables is not in the fixed_variables, then it means that # there are invalid characters in the input_variables - if any(var not in fixed_variables for var in input_variables): - raise ValueError( - f"Invalid input variables: {input_variables}. Please, use something like {fixed_variables} instead." - ) + if any(var not in fixed_variables for var in input_variables): + error_message = build_error_message( + input_variables, + invalid_chars, + wrong_variables, + fixed_variables, + empty_variables, + ) + raise ValueError(error_message) return input_variables + + +def build_error_message( + input_variables, invalid_chars, wrong_variables, fixed_variables, empty_variables +): + input_variables_str = ", ".join([f"'{var}'" for var in input_variables]) + error_string = f"Invalid input variables: {input_variables_str}. " + + if wrong_variables and invalid_chars: + # fix the wrong variables replacing invalid chars and find them in the fixed variables + error_string_vars = "You can fix them by replacing the invalid characters: " + wvars = wrong_variables.copy() + for i, wrong_var in enumerate(wvars): + for char in invalid_chars: + wrong_var = wrong_var.replace(char, "") + if wrong_var in fixed_variables: + error_string_vars += f"'{wrong_variables[i]}' -> '{wrong_var}'" + error_string += error_string_vars + elif empty_variables: + error_string += f" There are {len(empty_variables)} empty variable{'s' if len(empty_variables) > 1 else ''}." + elif len(set(fixed_variables)) != len(fixed_variables): + error_string += "There are duplicate variables." + return error_string diff --git a/src/backend/langflow/api/v1/callback.py b/src/backend/langflow/api/v1/callback.py index b58393d7b..deddde47f 100644 --- a/src/backend/langflow/api/v1/callback.py +++ b/src/backend/langflow/api/v1/callback.py @@ -1,22 +1,132 @@ import asyncio -from typing import Any from langchain.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler from langflow.api.v1.schemas import ChatResponse +from typing import Any, Dict, List, Union +from fastapi import WebSocket + + +from langchain.schema import AgentAction, LLMResult, AgentFinish +from langflow.utils.logger import logger + + # https://github.com/hwchase17/chat-langchain/blob/master/callback.py class AsyncStreamingLLMCallbackHandler(AsyncCallbackHandler): """Callback handler for streaming LLM responses.""" - def __init__(self, websocket): + def __init__(self, websocket: 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()) + async def on_llm_start( + self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any + ) -> Any: + """Run when LLM starts running.""" + + async def on_llm_end(self, response: LLMResult, **kwargs: Any) -> Any: + """Run when LLM ends running.""" + + async def on_llm_error( + self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any + ) -> Any: + """Run when LLM errors.""" + + async def on_chain_start( + self, serialized: Dict[str, Any], inputs: Dict[str, Any], **kwargs: Any + ) -> Any: + """Run when chain starts running.""" + + async def on_chain_end(self, outputs: Dict[str, Any], **kwargs: Any) -> Any: + """Run when chain ends running.""" + + async def on_chain_error( + self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any + ) -> Any: + """Run when chain errors.""" + + async def on_tool_start( + self, serialized: Dict[str, Any], input_str: str, **kwargs: Any + ) -> Any: + """Run when tool starts running.""" + resp = ChatResponse( + message="", + type="stream", + intermediate_steps=f"Tool input: {input_str}", + ) + await self.websocket.send_json(resp.dict()) + + async def on_tool_end(self, output: str, **kwargs: Any) -> Any: + """Run when tool ends running.""" + observation_prefix = kwargs.get("observation_prefix", "Tool output: ") + split_output = output.split() + first_word = split_output[0] + rest_of_output = split_output[1:] + # Create a formatted message. + intermediate_steps = f"{observation_prefix}{first_word}" + + # Create a ChatResponse instance. + resp = ChatResponse( + message="", + type="stream", + intermediate_steps=intermediate_steps, + ) + rest_of_resps = [ + ChatResponse( + message="", + type="stream", + intermediate_steps=f"{word}", + ) + for word in rest_of_output + ] + resps = [resp] + rest_of_resps + # Try to send the response, handle potential errors. + + try: + # This is to emulate the stream of tokens + for resp in resps: + await self.websocket.send_json(resp.dict()) + except Exception as e: + logger.error(e) + + async def on_tool_error( + self, error: Union[Exception, KeyboardInterrupt], **kwargs: Any + ) -> Any: + """Run when tool errors.""" + + async def on_text(self, text: str, **kwargs: Any) -> Any: + """Run on arbitrary text.""" + # This runs when first sending the prompt + # to the LLM, adding it will send the final prompt + # to the frontend + + async def on_agent_action(self, action: AgentAction, **kwargs: Any): + log = f"Thought: {action.log}" + # if there are line breaks, split them and send them + # as separate messages + if "\n" in log: + logs = log.split("\n") + for log in logs: + resp = ChatResponse(message="", type="stream", intermediate_steps=log) + await self.websocket.send_json(resp.dict()) + else: + resp = ChatResponse(message="", type="stream", intermediate_steps=log) + await self.websocket.send_json(resp.dict()) + + async def on_agent_finish(self, finish: AgentFinish, **kwargs: Any) -> Any: + """Run on agent end.""" + resp = ChatResponse( + message="", + type="stream", + intermediate_steps=finish.log, + ) + await self.websocket.send_json(resp.dict()) + class StreamingLLMCallbackHandler(BaseCallbackHandler): """Callback handler for streaming LLM responses.""" diff --git a/src/backend/langflow/api/v1/chat.py b/src/backend/langflow/api/v1/chat.py index e47c31694..937eb2cf6 100644 --- a/src/backend/langflow/api/v1/chat.py +++ b/src/backend/langflow/api/v1/chat.py @@ -1,5 +1,6 @@ from fastapi import APIRouter, HTTPException, WebSocket, WebSocketException, status from fastapi.responses import StreamingResponse +from langflow.api.utils import build_input_keys_response from langflow.api.v1.schemas import BuildStatus, BuiltResponse, InitResponse, StreamData from langflow.chat.manager import ChatManager @@ -83,6 +84,7 @@ async def stream_build(flow_id: str): async def event_stream(flow_id): final_response = {"end_of_stream": True} + artifacts = {} try: if flow_id not in flow_data_store: error_message = "Invalid session ID" @@ -113,13 +115,6 @@ async def stream_build(flow_id: str): number_of_nodes = len(graph.nodes) flow_data_store[flow_id]["status"] = BuildStatus.IN_PROGRESS - # To deal with the ZeroShotAgent case - # we need to build the root node first - # and then the rest of the graph - # This is a big problem because certain nodes require - # params that are not connected to it. - # We should consider connecting the tools to the ZeroShotPrompt - graph.build() for i, vertex in enumerate(graph.generator_build(), 1): try: @@ -131,8 +126,13 @@ async def stream_build(flow_id: str): params = vertex._built_object_repr() valid = True logger.debug( - f"Building node {params[:50]}{'...' if len(params) > 50 else ''}" + f"Building node {str(params)[:50]}{'...' if len(str(params)) > 50 else ''}" ) + if vertex.artifacts: + # The artifacts will be prompt variables + # passed to build_input_keys_response + # to set the input_keys values + artifacts.update(vertex.artifacts) except Exception as exc: params = str(exc) valid = False @@ -147,9 +147,26 @@ async def stream_build(flow_id: str): yield str(StreamData(event="message", data=response)) - chat_manager.set_cache(flow_id, graph.build()) + langchain_object = graph.build() + # Now we need to check the input_keys to send them to the client + if hasattr(langchain_object, "input_keys"): + input_keys_response = build_input_keys_response( + langchain_object, artifacts + ) + else: + input_keys_response = { + "input_keys": {}, + "memory_keys": [], + "handle_keys": [], + } + yield str(StreamData(event="message", data=input_keys_response)) + + chat_manager.set_cache(flow_id, langchain_object) + # We need to reset the chat history + chat_manager.chat_history.empty_history(flow_id) flow_data_store[flow_id]["status"] = BuildStatus.SUCCESS except Exception as exc: + logger.exception(exc) logger.error("Error while building the flow: %s", exc) flow_data_store[flow_id]["status"] = BuildStatus.FAILURE yield str(StreamData(event="error", data={"error": str(exc)})) diff --git a/src/backend/langflow/api/v1/schemas.py b/src/backend/langflow/api/v1/schemas.py index 22df4a977..e4b9a6e84 100644 --- a/src/backend/langflow/api/v1/schemas.py +++ b/src/backend/langflow/api/v1/schemas.py @@ -53,7 +53,7 @@ class ChatMessage(BaseModel): """Chat message schema.""" is_bot: bool = False - message: Union[str, None] = None + message: Union[str, None, dict] = None type: str = "human" diff --git a/src/backend/langflow/api/v1/validate.py b/src/backend/langflow/api/v1/validate.py index 959273a00..2a5bdd673 100644 --- a/src/backend/langflow/api/v1/validate.py +++ b/src/backend/langflow/api/v1/validate.py @@ -3,10 +3,11 @@ from fastapi import APIRouter, HTTPException from langflow.api.v1.base import ( Code, CodeValidationResponse, - Prompt, + ValidatePromptRequest, PromptValidationResponse, validate_prompt, ) +from langflow.template.field.base import TemplateField from langflow.utils.logger import logger from langflow.utils.validate import validate_code @@ -27,9 +28,100 @@ def post_validate_code(code: Code): @router.post("/prompt", status_code=200, response_model=PromptValidationResponse) -def post_validate_prompt(prompt: Prompt): +def post_validate_prompt(prompt_request: ValidatePromptRequest): try: - return validate_prompt(prompt.template) + input_variables = validate_prompt(prompt_request.template) + + old_custom_fields = get_old_custom_fields(prompt_request) + + add_new_variables_to_template(input_variables, prompt_request) + + remove_old_variables_from_template( + old_custom_fields, input_variables, prompt_request + ) + + update_input_variables_field(input_variables, prompt_request) + + return PromptValidationResponse( + input_variables=input_variables, + frontend_node=prompt_request.frontend_node, + ) except Exception as e: logger.exception(e) raise HTTPException(status_code=500, detail=str(e)) from e + + +def get_old_custom_fields(prompt_request): + try: + old_custom_fields = prompt_request.frontend_node.custom_fields[ + prompt_request.name + ].copy() + except KeyError: + old_custom_fields = [] + prompt_request.frontend_node.custom_fields[prompt_request.name] = [] + return old_custom_fields + + +def add_new_variables_to_template(input_variables, prompt_request): + for variable in input_variables: + try: + template_field = TemplateField( + name=variable, + display_name=variable, + field_type="str", + show=True, + advanced=False, + multiline=True, + input_types=["Document", "BaseOutputParser"], + value="", # Set the value to empty string + ) + if variable in prompt_request.frontend_node.template: + # Set the new field with the old value + template_field.value = prompt_request.frontend_node.template[variable][ + "value" + ] + + prompt_request.frontend_node.template[variable] = template_field.to_dict() + + # Check if variable is not already in the list before appending + if ( + variable + not in prompt_request.frontend_node.custom_fields[prompt_request.name] + ): + prompt_request.frontend_node.custom_fields[prompt_request.name].append( + variable + ) + + except Exception as exc: + logger.exception(exc) + raise HTTPException(status_code=500, detail=str(exc)) from exc + + +def remove_old_variables_from_template( + old_custom_fields, input_variables, prompt_request +): + for variable in old_custom_fields: + if variable not in input_variables: + try: + # Remove the variable from custom_fields associated with the given name + if ( + variable + in prompt_request.frontend_node.custom_fields[prompt_request.name] + ): + prompt_request.frontend_node.custom_fields[ + prompt_request.name + ].remove(variable) + + # Remove the variable from the template + prompt_request.frontend_node.template.pop(variable, None) + + except Exception as exc: + logger.exception(exc) + raise HTTPException(status_code=500, detail=str(exc)) from exc + + +def update_input_variables_field(input_variables, prompt_request): + if "input_variables" in prompt_request.frontend_node.template: + prompt_request.frontend_node.template["input_variables"][ + "value" + ] = input_variables diff --git a/src/backend/langflow/chat/manager.py b/src/backend/langflow/chat/manager.py index 4a1b8e77c..33de784b5 100644 --- a/src/backend/langflow/chat/manager.py +++ b/src/backend/langflow/chat/manager.py @@ -104,16 +104,22 @@ class ChatManager: async def close_connection(self, client_id: str, code: int, reason: str): if websocket := self.active_connections[client_id]: - await websocket.close(code=code, reason=reason) - self.disconnect(client_id) + try: + await websocket.close(code=code, reason=reason) + self.disconnect(client_id) + except RuntimeError as exc: + # This is to catch the following error: + # Unexpected ASGI message 'websocket.close', after sending 'websocket.close' + if "after sending" in str(exc): + logger.error(exc) async def process_message( self, client_id: str, payload: Dict, langchain_object: Any ): # 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) + chat_inputs = payload.pop("inputs", "") + chat_inputs = ChatMessage(message=chat_inputs) + self.chat_history.add_message(client_id, chat_inputs) # graph_data = payload start_resp = ChatResponse(message=None, type="start", intermediate_steps="") @@ -126,7 +132,7 @@ class ChatManager: result, intermediate_steps = await process_graph( langchain_object=langchain_object, - chat_message=chat_message, + chat_inputs=chat_inputs, websocket=self.active_connections[client_id], ) except Exception as e: diff --git a/src/backend/langflow/chat/utils.py b/src/backend/langflow/chat/utils.py index 2e2ee367f..7db65b8e3 100644 --- a/src/backend/langflow/chat/utils.py +++ b/src/backend/langflow/chat/utils.py @@ -7,7 +7,7 @@ from langflow.utils.logger import logger async def process_graph( langchain_object, - chat_message: ChatMessage, + chat_inputs: ChatMessage, websocket: WebSocket, ): langchain_object = try_setting_streaming_options(langchain_object, websocket) @@ -21,9 +21,13 @@ async def process_graph( # Generate result and thought try: + if not chat_inputs.message: + logger.debug("No message provided") + raise ValueError("No message provided") + logger.debug("Generating result and thought") result, intermediate_steps = await get_result_and_steps( - langchain_object, chat_message.message or "", websocket=websocket + langchain_object, chat_inputs.message, websocket=websocket ) logger.debug("Generated result and intermediate_steps") return result, intermediate_steps diff --git a/src/backend/langflow/config.yaml b/src/backend/langflow/config.yaml index 3745b9e22..3116e74c7 100644 --- a/src/backend/langflow/config.yaml +++ b/src/backend/langflow/config.yaml @@ -151,12 +151,19 @@ memories: documentation: "https://python.langchain.com/docs/modules/memory/how_to/buffer_window" VectorStoreRetrieverMemory: documentation: "https://python.langchain.com/docs/modules/memory/how_to/vectorstore_retriever_memory" - + MongoDBChatMessageHistory: + documentation: "https://python.langchain.com/docs/modules/memory/integrations/mongodb_chat_message_history" prompts: + ChatMessagePromptTemplate: + documentation: "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/msg_prompt_templates" + HumanMessagePromptTemplate: + documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts" + SystemMessagePromptTemplate: + documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts" + ChatPromptTemplate: + documentation: "https://python.langchain.com/docs/modules/model_io/models/chat/how_to/prompts" PromptTemplate: documentation: "https://python.langchain.com/docs/modules/model_io/prompts/prompt_templates/" - ZeroShotPrompt: - documentation: "https://python.langchain.com/docs/modules/agents/how_to/custom_mrkl_agent" textsplitters: CharacterTextSplitter: documentation: "https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/character_text_splitter" @@ -269,7 +276,17 @@ vectorstores: SupabaseVectorStore: documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/supabase" MongoDBAtlasVectorSearch: - documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/mongodb_atlas_vector_search" + documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/mongodb_atlas" + # Requires docarray >=0.32.0 but langchain-serve requires jina 3.15.2 which doesn't support docarray >=0.32.0 + # DocArrayInMemorySearch: + # documentation: "https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/docarray_in_memory" wrappers: RequestsWrapper: documentation: "" + SQLDatabase: + documentation: "" +output_parsers: + StructuredOutputParser: + documentation: "https://python.langchain.com/docs/modules/model_io/output_parsers/structured" + ResponseSchema: + documentation: "https://python.langchain.com/docs/modules/model_io/output_parsers/structured" diff --git a/src/backend/langflow/custom/customs.py b/src/backend/langflow/custom/customs.py index 0f1e44308..58ef1b508 100644 --- a/src/backend/langflow/custom/customs.py +++ b/src/backend/langflow/custom/customs.py @@ -2,9 +2,9 @@ from langflow.template import frontend_node # These should always be instantiated CUSTOM_NODES = { - "prompts": { - "ZeroShotPrompt": frontend_node.prompts.ZeroShotPromptNode(), - }, + # "prompts": { + # "ZeroShotPrompt": frontend_node.prompts.ZeroShotPromptNode(), + # }, "tools": { "PythonFunctionTool": frontend_node.tools.PythonFunctionToolNode(), "PythonFunction": frontend_node.tools.PythonFunctionNode(), @@ -23,6 +23,7 @@ CUSTOM_NODES = { }, "memories": { "PostgresChatMessageHistory": frontend_node.memories.PostgresChatMessageHistoryFrontendNode(), + "MongoDBChatMessageHistory": frontend_node.memories.MongoDBChatMessageHistoryFrontendNode(), }, "chains": { "SeriesCharacterChain": frontend_node.chains.SeriesCharacterChainNode(), diff --git a/src/backend/langflow/graph/edge/base.py b/src/backend/langflow/graph/edge/base.py index 88a177e40..569d33ec0 100644 --- a/src/backend/langflow/graph/edge/base.py +++ b/src/backend/langflow/graph/edge/base.py @@ -6,9 +6,15 @@ if TYPE_CHECKING: class Edge: - def __init__(self, source: "Vertex", target: "Vertex"): + def __init__(self, source: "Vertex", target: "Vertex", edge: dict): self.source: "Vertex" = source self.target: "Vertex" = target + self.source_handle = edge.get("sourceHandle", "") + self.target_handle = edge.get("targetHandle", "") + # 'BaseLoader;BaseOutputParser|documents|PromptTemplate-zmTlD' + # target_param is documents + self.target_param = self.target_handle.split("|")[1] + self.validate_edge() def validate_edge(self) -> None: @@ -42,6 +48,16 @@ class Edge: def __repr__(self) -> str: return ( - f"Edge(source={self.source.id}, target={self.target.id}, valid={self.valid}" + f"Edge(source={self.source.id}, target={self.target.id}, target_param={self.target_param}" f", matched_type={self.matched_type})" ) + + def __hash__(self) -> int: + return hash(self.__repr__()) + + def __eq__(self, __value: object) -> bool: + return ( + self.__repr__() == __value.__repr__() + if isinstance(__value, Edge) + else False + ) diff --git a/src/backend/langflow/graph/graph/base.py b/src/backend/langflow/graph/graph/base.py index 46425ddf6..86a2f98a9 100644 --- a/src/backend/langflow/graph/graph/base.py +++ b/src/backend/langflow/graph/graph/base.py @@ -179,7 +179,7 @@ class Graph: raise ValueError(f"Source node {edge['source']} not found") if target is None: raise ValueError(f"Target node {edge['target']} not found") - edges.append(Edge(source, target)) + edges.append(Edge(source, target, edge)) return edges def _get_vertex_class(self, node_type: str, node_lc_type: str) -> Type[Vertex]: @@ -214,3 +214,10 @@ class Graph: if node_type in node_types: children.append(node) return children + + def __repr__(self): + node_ids = [node.id for node in self.nodes] + edges_repr = "\n".join( + [f"{edge.source.id} --> {edge.target.id}" for edge in self.edges] + ) + return f"Graph:\nNodes: {node_ids}\nConnections:\n{edges_repr}" diff --git a/src/backend/langflow/graph/graph/constants.py b/src/backend/langflow/graph/graph/constants.py index 9474e311e..a2fd287eb 100644 --- a/src/backend/langflow/graph/graph/constants.py +++ b/src/backend/langflow/graph/graph/constants.py @@ -12,6 +12,7 @@ from langflow.interface.toolkits.base import toolkits_creator from langflow.interface.tools.base import tool_creator from langflow.interface.vector_store.base import vectorstore_creator from langflow.interface.wrappers.base import wrapper_creator +from langflow.interface.output_parsers.base import output_parser_creator from langflow.interface.retrievers.base import retriever_creator from typing import Dict, Type @@ -30,5 +31,6 @@ VERTEX_TYPE_MAP: Dict[str, Type[Vertex]] = { **{t: types.VectorStoreVertex for t in vectorstore_creator.to_list()}, **{t: types.DocumentLoaderVertex for t in documentloader_creator.to_list()}, **{t: types.TextSplitterVertex for t in textsplitter_creator.to_list()}, + **{t: types.OutputParserVertex for t in output_parser_creator.to_list()}, **{t: types.RetrieverVertex for t in retriever_creator.to_list()}, } diff --git a/src/backend/langflow/graph/vertex/base.py b/src/backend/langflow/graph/vertex/base.py index 275a9e080..4eb39e8e8 100644 --- a/src/backend/langflow/graph/vertex/base.py +++ b/src/backend/langflow/graph/vertex/base.py @@ -1,14 +1,12 @@ -from langflow.utils.constants import DIRECT_TYPES from langflow.interface.initialize import loading from langflow.interface.listing import ALL_TYPES_DICT +from langflow.utils.constants import DIRECT_TYPES from langflow.utils.logger import logger from langflow.utils.util import sync_to_async -import contextlib import inspect import types -import warnings from typing import Any, Dict, List, Optional from typing import TYPE_CHECKING @@ -25,6 +23,7 @@ class Vertex: self._parse_data() self._built_object = None self._built = False + self.artifacts: Dict[str, Any] = {} def _parse_data(self) -> None: self.data = self._data["data"] @@ -45,6 +44,14 @@ class Vertex: for key, value in template_dicts.items() if not value["required"] ] + # Add the template_dicts[key]["input_types"] to the optional_inputs + self.optional_inputs.extend( + [ + input_type + for value in template_dicts.values() + for input_type in value.get("input_types", []) + ] + ) template_dict = self.data["node"]["template"] self.vertex_type = ( @@ -60,6 +67,7 @@ class Vertex: break def _build_params(self): + # sourcery skip: merge-list-append, remove-redundant-if # Some params are required, some are optional # but most importantly, some params are python base classes # like str and others are LangChain objects like LLMChain, BasePromptTemplate @@ -80,8 +88,19 @@ class Vertex: if isinstance(value, dict) } params = {} + + for edge in self.edges: + param_key = edge.target_param + if param_key in template_dict: + if template_dict[param_key]["list"]: + if param_key not in params: + params[param_key] = [] + params[param_key].append(edge.source) + elif edge.target.id == self.id: + params[param_key] = edge.source + for key, value in template_dict.items(): - if key == "_type": + if key == "_type" or not value.get("show"): continue # If the type is not transformable to a python base class # then we need to get the edge that connects to this node @@ -92,124 +111,131 @@ class Vertex: file_path = value.get("file_path") params[key] = file_path + elif value.get("type") in DIRECT_TYPES and params.get(key) is None: + params[key] = value.get("value") - elif value.get("type") not in DIRECT_TYPES: - # Get the edge that connects to this node - edges = [ - edge - for edge in self.edges - if edge.target == self and edge.matched_type in value["type"] - ] - - # Get the output of the node that the edge connects to - # if the value['list'] is True, then there will be more - # than one time setting to params[key] - # so we need to append to a list if it exists - # or create a new list if it doesn't - - if value["required"] and not edges: - # If a required parameter is not found, raise an error - raise ValueError( - f"Required input {key} for module {self.vertex_type} not found" - ) - elif value["list"]: - # If this is a list parameter, append all sources to a list - params[key] = [edge.source for edge in edges] - elif edges: - # If a single parameter is found, use its source - params[key] = edges[0].source - - elif value["required"] or value.get("value"): - # If value does not have value this still passes - # but then gives a keyError - # so we need to check if value has value - new_value = value.get("value") - if new_value is None: - warnings.warn(f"Value for {key} in {self.vertex_type} is None. ") - if value.get("type") == "int": - with contextlib.suppress(TypeError, ValueError): - new_value = int(new_value) # type: ignore - params[key] = new_value - + if not value.get("required") and params.get(key) is None: + if value.get("default"): + params[key] = value.get("default") + else: + params.pop(key, None) # Add _type to params self.params = params def _build(self): - # The params dict is used to build the module - # it contains values and keys that point to nodes which - # have their own params dict - # When build is called, we iterate through the params dict - # and if the value is a node, we call build on that node - # and use the output of that build as the value for the param - # if the value is not a node, then we use the value as the param - # and continue - # Another aspect is that the node_type is the class that we need to import - # and instantiate with these built params + """ + Initiate the build process. + """ logger.debug(f"Building {self.vertex_type}") - # Build each node in the params dict + self._build_each_node_in_params_dict() + self._get_and_instantiate_class() + self._validate_built_object() + + self._built = True + + def _build_each_node_in_params_dict(self): + """ + Iterates over each node in the params dictionary and builds it. + """ for key, value in self.params.copy().items(): - # Check if Node or list of Nodes and not self - # to avoid recursion - if isinstance(value, Vertex): + if self._is_node(value): if value == self: del self.params[key] continue - result = value.build() - # If the key is "func", then we need to use the run method - 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) - if isinstance(result, list): - # If the result is a list, then we need to extend the list - # with the result but first check if the key exists - # if it doesn't, then we need to create a new list - if isinstance(self.params[key], list): - self.params[key].extend(result) + self._build_node_and_update_params(key, value) + elif isinstance(value, list) and self._is_list_of_nodes(value): + self._build_list_of_nodes_and_update_params(key, value) - self.params[key] = result - elif isinstance(value, list) and all( - isinstance(node, Vertex) for node in value - ): - self.params[key] = [] - for node in value: - built = node.build() - if isinstance(built, list): - self.params[key].extend(built) - else: - self.params[key].append(built) + def _is_node(self, value): + """ + Checks if the provided value is an instance of Vertex. + """ + return isinstance(value, Vertex) - # Get the class from LANGCHAIN_TYPES_DICT - # and instantiate it with the params - # and return the instance + def _is_list_of_nodes(self, value): + """ + Checks if the provided value is a list of Vertex instances. + """ + return all(self._is_node(node) for node in value) + def _build_node_and_update_params(self, key, node): + """ + Builds a given node and updates the params dictionary accordingly. + """ + result = node.build() + self._handle_func(key, result) + if isinstance(result, list): + self._extend_params_list_with_result(key, result) + self.params[key] = result + + def _build_list_of_nodes_and_update_params(self, key, nodes): + """ + Iterates over a list of nodes, builds each and updates the params dictionary. + """ + self.params[key] = [] + for node in nodes: + built = node.build() + if isinstance(built, list): + self.params[key].extend(built) + else: + self.params[key].append(built) + + def _handle_func(self, key, result): + """ + Handles 'func' key by checking if the result is a function and setting it as coroutine. + """ + if key == "func": + if not isinstance(result, types.FunctionType): + 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: + self.params["coroutine"] = sync_to_async(result) + + def _extend_params_list_with_result(self, key, result): + """ + Extends a list in the params dictionary with the given result if it exists. + """ + if isinstance(self.params[key], list): + self.params[key].extend(result) + + def _get_and_instantiate_class(self): + """ + Gets the class from a dictionary and instantiates it with the params. + """ + if self.base_type is None: + raise ValueError(f"Base type for node {self.vertex_type} not found") try: - self._built_object = loading.instantiate_class( + result = loading.instantiate_class( node_type=self.vertex_type, base_type=self.base_type, params=self.params, ) + self._update_built_object_and_artifacts(result) except Exception as exc: raise ValueError( f"Error building node {self.vertex_type}: {str(exc)}" ) from exc + def _update_built_object_and_artifacts(self, result): + """ + Updates the built object and its artifacts. + """ + if isinstance(result, tuple): + self._built_object, self.artifacts = result + else: + self._built_object = result + + def _validate_built_object(self): + """ + Checks if the built object is None and raises a ValueError if so. + """ if self._built_object is None: raise ValueError(f"Node type {self.vertex_type} not found") - self._built = True - def build(self, force: bool = False) -> Any: if not self._built or force: self._build() @@ -217,7 +243,8 @@ class Vertex: return self._built_object def add_edge(self, edge: "Edge") -> None: - self.edges.append(edge) + if edge not in self.edges: + self.edges.append(edge) def __repr__(self) -> str: return f"Vertex(id={self.id}, data={self.data})" @@ -229,4 +256,5 @@ class Vertex: return id(self) def _built_object_repr(self): - return repr(self._built_object) + # Add a message with an emoji, stars for sucess, + return "Built sucessfully ✨" if self._built_object else "Failed to build 😵‍💫" diff --git a/src/backend/langflow/graph/vertex/types.py b/src/backend/langflow/graph/vertex/types.py index 846b79bc0..effd00071 100644 --- a/src/backend/langflow/graph/vertex/types.py +++ b/src/backend/langflow/graph/vertex/types.py @@ -1,3 +1,4 @@ +import ast from typing import Any, Dict, List, Optional, Union from langflow.graph.vertex.base import Vertex @@ -79,7 +80,7 @@ class WrapperVertex(Vertex): def build(self, force: bool = False) -> Any: if not self._built or force: if "headers" in self.params: - self.params["headers"] = eval(self.params["headers"]) + self.params["headers"] = ast.literal_eval(self.params["headers"]) self._build() return self._built_object @@ -91,8 +92,13 @@ class DocumentLoaderVertex(Vertex): def _built_object_repr(self): # This built_object is a list of documents. Maybe we should # show how many documents are in the list? + if self._built_object: + avg_length = sum(len(doc.page_content) for doc in self._built_object) / len( + self._built_object + ) return f"""{self.vertex_type}({len(self._built_object)} documents) + \nAvg. Document Length (characters): {avg_length} Documents: {self._built_object[:3]}...""" return f"{self.vertex_type}()" @@ -124,8 +130,13 @@ class TextSplitterVertex(Vertex): def _built_object_repr(self): # This built_object is a list of documents. Maybe we should # show how many documents are in the list? + if self._built_object: + avg_length = sum(len(doc.page_content) for doc in self._built_object) / len( + self._built_object + ) return f"""{self.vertex_type}({len(self._built_object)} documents) + \nAvg. Document Length (characters): {avg_length} \nDocuments: {self._built_object[:3]}...""" return f"{self.vertex_type}()" @@ -185,11 +196,46 @@ class PromptVertex(Vertex): ] else: prompt_params = ["template"] - for param in prompt_params: - prompt_text = self.params[param] - variables = extract_input_variables_from_prompt(prompt_text) - self.params["input_variables"].extend(variables) - self.params["input_variables"] = list(set(self.params["input_variables"])) + + if "prompt" not in self.params and "messages" not in self.params: + for param in prompt_params: + prompt_text = self.params[param] + variables = extract_input_variables_from_prompt(prompt_text) + self.params["input_variables"].extend(variables) + self.params["input_variables"] = list( + set(self.params["input_variables"]) + ) + else: + self.params.pop("input_variables", None) self._build() return self._built_object + + def _built_object_repr(self): + if ( + not self.artifacts + or self._built_object is None + or not hasattr(self._built_object, "format") + ): + return super()._built_object_repr() + # We'll build the prompt with the artifacts + # to show the user what the prompt looks like + # with the variables filled in + artifacts = self.artifacts.copy() + # Remove the handle_keys from the artifacts + # so the prompt format doesn't break + artifacts.pop("handle_keys", None) + try: + template = self._built_object.format(**artifacts) + return ( + template + if isinstance(template, str) + else f"{self.vertex_type}({template})" + ) + except KeyError: + return str(self._built_object) + + +class OutputParserVertex(Vertex): + def __init__(self, data: Dict): + super().__init__(data, base_type="output_parsers") diff --git a/src/backend/langflow/interface/agents/base.py b/src/backend/langflow/interface/agents/base.py index d404f845d..b272144bc 100644 --- a/src/backend/langflow/interface/agents/base.py +++ b/src/backend/langflow/interface/agents/base.py @@ -6,13 +6,20 @@ from langflow.custom.customs import get_custom_nodes from langflow.interface.agents.custom import CUSTOM_AGENTS from langflow.interface.base import LangChainTypeCreator from langflow.settings import settings +from langflow.template.frontend_node.agents import AgentFrontendNode from langflow.utils.logger import logger -from langflow.utils.util import build_template_from_class +from langflow.utils.util import build_template_from_class, build_template_from_method class AgentCreator(LangChainTypeCreator): type_name: str = "agents" + from_method_nodes = {"ZeroShotAgent": "from_llm_and_tools"} + + @property + def frontend_node_class(self) -> type[AgentFrontendNode]: + return AgentFrontendNode + @property def type_to_loader_dict(self) -> Dict: if self.type_dict is None: @@ -27,6 +34,13 @@ class AgentCreator(LangChainTypeCreator): try: if name in get_custom_nodes(self.type_name).keys(): return get_custom_nodes(self.type_name)[name] + elif name in self.from_method_nodes: + return build_template_from_method( + name, + type_to_cls_dict=self.type_to_loader_dict, + add_function=True, + method_name=self.from_method_nodes[name], + ) return build_template_from_class( name, self.type_to_loader_dict, add_function=True ) diff --git a/src/backend/langflow/interface/agents/custom.py b/src/backend/langflow/interface/agents/custom.py index aa0cfb5db..b4e2b9bac 100644 --- a/src/backend/langflow/interface/agents/custom.py +++ b/src/backend/langflow/interface/agents/custom.py @@ -157,7 +157,7 @@ class VectorStoreAgent(CustomAgentExecutor): llm_chain=llm_chain, allowed_tools=tool_names, **kwargs # type: ignore ) return AgentExecutor.from_agent_and_tools( - agent=agent, tools=tools, verbose=True + agent=agent, tools=tools, verbose=True, handle_parsing_errors=True ) def run(self, *args, **kwargs): @@ -232,6 +232,7 @@ class SQLAgent(CustomAgentExecutor): verbose=True, max_iterations=15, early_stopping_method="force", + handle_parsing_errors=True, ) def run(self, *args, **kwargs): @@ -276,7 +277,7 @@ class VectorStoreRouterAgent(CustomAgentExecutor): llm_chain=llm_chain, allowed_tools=tool_names, **kwargs # type: ignore ) return AgentExecutor.from_agent_and_tools( - agent=agent, tools=tools, verbose=True + agent=agent, tools=tools, verbose=True, handle_parsing_errors=True ) def run(self, *args, **kwargs): @@ -308,6 +309,7 @@ class InitializeAgent(CustomAgentExecutor): agent=agent, # type: ignore memory=memory, return_intermediate_steps=True, + handle_parsing_errors=True, ) def __init__(self, *args, **kwargs): diff --git a/src/backend/langflow/interface/chains/base.py b/src/backend/langflow/interface/chains/base.py index ff7e1ee33..67d31308f 100644 --- a/src/backend/langflow/interface/chains/base.py +++ b/src/backend/langflow/interface/chains/base.py @@ -23,6 +23,7 @@ class ChainCreator(LangChainTypeCreator): from_method_nodes = { "ConversationalRetrievalChain": "from_llm", "LLMCheckerChain": "from_llm", + "SQLDatabaseChain": "from_llm", } @property diff --git a/src/backend/langflow/interface/importing/utils.py b/src/backend/langflow/interface/importing/utils.py index 7ef916ca9..ccfd8d5dd 100644 --- a/src/backend/langflow/interface/importing/utils.py +++ b/src/backend/langflow/interface/importing/utils.py @@ -10,6 +10,7 @@ from langchain.chains.base import Chain from langchain.chat_models.base import BaseChatModel from langchain.tools import BaseTool from langflow.utils import validate +from langflow.interface.wrappers.base import wrapper_creator def import_module(module_path: str) -> Any: @@ -44,6 +45,7 @@ def import_by_type(_type: str, name: str) -> Any: "documentloaders": import_documentloader, "textsplitters": import_textsplitter, "utilities": import_utility, + "output_parsers": import_output_parser, "retrievers": import_retriever, } if _type == "llms": @@ -55,6 +57,11 @@ def import_by_type(_type: str, name: str) -> Any: return loaded_func(name) +def import_output_parser(output_parser: str) -> Any: + """Import output parser from output parser name""" + return import_module(f"from langchain.output_parsers import {output_parser}") + + def import_chat_llm(llm: str) -> BaseChatModel: """Import chat llm from llm name""" return import_class(f"langchain.chat_models.{llm}") @@ -90,7 +97,11 @@ def import_prompt(prompt: str) -> Type[PromptTemplate]: def import_wrapper(wrapper: str) -> Any: """Import wrapper from wrapper name""" - return import_module(f"from langchain.requests import {wrapper}") + if ( + isinstance(wrapper_creator.type_dict, dict) + and wrapper in wrapper_creator.type_dict + ): + return wrapper_creator.type_dict.get(wrapper) def import_toolkit(toolkit: str) -> Any: diff --git a/src/backend/langflow/interface/initialize/loading.py b/src/backend/langflow/interface/initialize/loading.py index 9c618b1cd..b232d089c 100644 --- a/src/backend/langflow/interface/initialize/loading.py +++ b/src/backend/langflow/interface/initialize/loading.py @@ -1,5 +1,6 @@ +import contextlib import json -from typing import Any, Callable, Dict, Sequence, Type +from typing import Any, Callable, Dict, List, Sequence, Type from langchain.agents import ZeroShotAgent from langchain.agents import agent as agent_module @@ -10,19 +11,22 @@ from langflow.interface.initialize.llm import initialize_vertexai from langflow.interface.initialize.vector_store import vecstore_initializer +from langchain.schema import Document, BaseOutputParser from pydantic import ValidationError from langflow.interface.custom_lists import CUSTOM_NODES from langflow.interface.importing.utils import get_function, import_by_type +from langflow.interface.agents.base import agent_creator from langflow.interface.toolkits.base import toolkits_creator from langflow.interface.chains.base import chain_creator +from langflow.interface.output_parsers.base import output_parser_creator from langflow.interface.retrievers.base import retriever_creator +from langflow.interface.wrappers.base import wrapper_creator from langflow.interface.utils import load_file_into_dict from langflow.utils import validate from langchain.chains.base import Chain from langchain.vectorstores.base import VectorStore from langchain.document_loaders.base import BaseLoader -from langchain.prompts.base import BasePromptTemplate def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any: @@ -60,11 +64,15 @@ def convert_kwargs(params): def instantiate_based_on_type(class_object, base_type, node_type, params): if base_type == "agents": - return instantiate_agent(class_object, params) + return instantiate_agent(node_type, class_object, params) elif base_type == "prompts": return instantiate_prompt(node_type, class_object, params) elif base_type == "tools": - return instantiate_tool(node_type, class_object, params) + tool = instantiate_tool(node_type, class_object, params) + if hasattr(tool, "name") and isinstance(tool, BaseTool): + # tool name shouldn't contain spaces + tool.name = tool.name.replace(" ", "_") + return tool elif base_type == "toolkits": return instantiate_toolkit(node_type, class_object, params) elif base_type == "embeddings": @@ -79,26 +87,63 @@ def instantiate_based_on_type(class_object, base_type, node_type, params): return instantiate_utility(node_type, class_object, params) elif base_type == "chains": return instantiate_chains(node_type, class_object, params) + elif base_type == "output_parsers": + return instantiate_output_parser(node_type, class_object, params) elif base_type == "llms": return instantiate_llm(node_type, class_object, params) elif base_type == "retrievers": return instantiate_retriever(node_type, class_object, params) elif base_type == "memory": return instantiate_memory(node_type, class_object, params) + elif base_type == "wrappers": + return instantiate_wrapper(node_type, class_object, params) else: return class_object(**params) +def instantiate_wrapper(node_type, class_object, params): + if node_type in wrapper_creator.from_method_nodes: + method = wrapper_creator.from_method_nodes[node_type] + if class_method := getattr(class_object, method, None): + return class_method(**params) + raise ValueError(f"Method {method} not found in {class_object}") + return class_object(**params) + + +def instantiate_output_parser(node_type, class_object, params): + if node_type in output_parser_creator.from_method_nodes: + method = output_parser_creator.from_method_nodes[node_type] + if class_method := getattr(class_object, method, None): + return class_method(**params) + raise ValueError(f"Method {method} not found in {class_object}") + return class_object(**params) + + def instantiate_llm(node_type, class_object, params: Dict): # This is a workaround so JinaChat works until streaming is implemented # if "openai_api_base" in params and "jina" in params["openai_api_base"]: # False if condition is True if node_type == "VertexAI": return initialize_vertexai(class_object=class_object, params=params) + # max_tokens sometimes is a string and should be an int + if "max_tokens" in params: + if isinstance(params["max_tokens"], str) and params["max_tokens"].isdigit(): + params["max_tokens"] = int(params["max_tokens"]) + elif not isinstance(params.get("max_tokens"), int): + params.pop("max_tokens", None) return class_object(**params) def instantiate_memory(node_type, class_object, params): + # process input_key and output_key to remove them if + # they are empty strings + if node_type == "ConversationEntityMemory": + params.pop("memory_key", None) + + for key in ["input_key", "output_key"]: + if key in params and (params[key] == "" or not params[key]): + params.pop(key) + try: if "retriever" in params and hasattr(params["retriever"], "as_retriever"): params["retriever"] = params["retriever"].as_retriever() @@ -141,26 +186,94 @@ def instantiate_chains(node_type, class_object: Type[Chain], params: Dict): return class_object(**params) -def instantiate_agent(class_object: Type[agent_module.Agent], params: Dict): +def instantiate_agent(node_type, class_object: Type[agent_module.Agent], params: Dict): + if node_type in agent_creator.from_method_nodes: + method = agent_creator.from_method_nodes[node_type] + if class_method := getattr(class_object, method, None): + agent = class_method(**params) + tools = params.get("tools", []) + return AgentExecutor.from_agent_and_tools( + agent=agent, tools=tools, handle_parsing_errors=True + ) return load_agent_executor(class_object, params) -def instantiate_prompt(node_type, class_object: Type[BasePromptTemplate], params: Dict): +def instantiate_prompt(node_type, class_object, params: Dict): if node_type == "ZeroShotPrompt": if "tools" not in params: params["tools"] = [] return ZeroShotAgent.create_prompt(**params) - return class_object(**params) + elif "MessagePromptTemplate" in node_type: + # Then we only need the template + from_template_params = { + "template": params.pop("prompt", params.pop("template", "")) + } + + if not from_template_params.get("template"): + raise ValueError("Prompt template is required") + prompt = class_object.from_template(**from_template_params) + + elif node_type == "ChatPromptTemplate": + prompt = class_object.from_messages(**params) + else: + prompt = class_object(**params) + + format_kwargs: Dict[str, Any] = {} + for input_variable in prompt.input_variables: + if input_variable in params: + variable = params[input_variable] + if isinstance(variable, str): + format_kwargs[input_variable] = variable + elif isinstance(variable, BaseOutputParser) and hasattr( + variable, "get_format_instructions" + ): + format_kwargs[input_variable] = variable.get_format_instructions() + elif isinstance(variable, List) and all( + isinstance(item, Document) for item in variable + ): + # Format document to contain page_content and metadata + # as one string separated by a newline + if len(variable) > 1: + content = "\n".join( + [item.page_content for item in variable if item.page_content] + ) + else: + content = variable[0].page_content + # content could be a json list of strings + with contextlib.suppress(json.JSONDecodeError): + content = json.loads(content) + if isinstance(content, list): + content = ",".join([str(item) for item in content]) + format_kwargs[input_variable] = content + # handle_keys will be a list but it does not exist yet + # so we need to create it + + if ( + isinstance(variable, List) + and all(isinstance(item, Document) for item in variable) + ) or ( + isinstance(variable, BaseOutputParser) + and hasattr(variable, "get_format_instructions") + ): + if "handle_keys" not in format_kwargs: + format_kwargs["handle_keys"] = [] + + # Add the handle_keys to the list + format_kwargs["handle_keys"].append(input_variable) + + return prompt, format_kwargs def instantiate_tool(node_type, class_object: Type[BaseTool], params: Dict): if node_type == "JsonSpec": - params["dict_"] = load_file_into_dict(params.pop("path")) + if file_dict := load_file_into_dict(params.pop("path")): + params["dict_"] = file_dict + else: + raise ValueError("Invalid file") return class_object(**params) elif node_type == "PythonFunctionTool": params["func"] = get_function(params.get("code")) return class_object(**params) - # For backward compatibility elif node_type == "PythonFunction": function_string = params["code"] if isinstance(function_string, str): @@ -218,7 +331,7 @@ def instantiate_documentloader(class_object: Type[BaseLoader], params: Dict): # like lambda x: x.endswith(".txt") but as we don't know # anything besides the string, we will simply check if the string is # in x and if it is, we will return True - file_filter = params.pop("file_filter", None) + file_filter = params.pop("file_filter") extensions = file_filter.split(",") params["file_filter"] = lambda x: any( extension.strip() in x for extension in extensions @@ -260,6 +373,12 @@ def instantiate_textsplitter( "separator_type" in params and params["separator_type"] == "Text" ) or "separator_type" not in params: params.pop("separator_type", None) + # separators might come in as an escaped string like \\n + # so we need to convert it to a string + if "separators" in params: + params["separators"] = ( + params["separators"].encode().decode("unicode-escape") + ) text_splitter = class_object(**params) else: from langchain.text_splitter import Language @@ -312,6 +431,7 @@ def load_agent_executor(agent_class: type[agent_module.Agent], params, **kwargs) return AgentExecutor.from_agent_and_tools( agent=agent, tools=allowed_tools, + handle_parsing_errors=True, # memory=memory, **kwargs, ) diff --git a/src/backend/langflow/interface/listing.py b/src/backend/langflow/interface/listing.py index 1e1421d32..0893f855a 100644 --- a/src/backend/langflow/interface/listing.py +++ b/src/backend/langflow/interface/listing.py @@ -11,6 +11,7 @@ from langflow.interface.tools.base import tool_creator from langflow.interface.utilities.base import utility_creator from langflow.interface.vector_store.base import vectorstore_creator from langflow.interface.wrappers.base import wrapper_creator +from langflow.interface.output_parsers.base import output_parser_creator from langflow.interface.retrievers.base import retriever_creator @@ -29,6 +30,7 @@ def get_type_dict(): "embeddings": embedding_creator.to_list(), "textSplitters": textsplitter_creator.to_list(), "utilities": utility_creator.to_list(), + "outputParsers": output_parser_creator.to_list(), "retrievers": retriever_creator.to_list(), } diff --git a/src/backend/langflow/interface/output_parsers/__init__.py b/src/backend/langflow/interface/output_parsers/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/src/backend/langflow/interface/output_parsers/base.py b/src/backend/langflow/interface/output_parsers/base.py new file mode 100644 index 000000000..79cbdd98c --- /dev/null +++ b/src/backend/langflow/interface/output_parsers/base.py @@ -0,0 +1,64 @@ +from typing import Dict, List, Optional, Type + +from langchain import output_parsers + +from langflow.interface.base import LangChainTypeCreator +from langflow.interface.importing.utils import import_class +from langflow.settings import settings +from langflow.template.frontend_node.output_parsers import OutputParserFrontendNode +from langflow.utils.logger import logger +from langflow.utils.util import build_template_from_class, build_template_from_method + + +class OutputParserCreator(LangChainTypeCreator): + type_name: str = "output_parsers" + from_method_nodes = { + "StructuredOutputParser": "from_response_schemas", + } + + @property + def frontend_node_class(self) -> Type[OutputParserFrontendNode]: + return OutputParserFrontendNode + + @property + def type_to_loader_dict(self) -> Dict: + if self.type_dict is None: + self.type_dict = { + output_parser_name: import_class( + f"langchain.output_parsers.{output_parser_name}" + ) + # if output_parser_name is not lower case it is a class + for output_parser_name in output_parsers.__all__ + } + self.type_dict = { + name: output_parser + for name, output_parser in self.type_dict.items() + if name in settings.output_parsers or settings.dev + } + return self.type_dict + + def get_signature(self, name: str) -> Optional[Dict]: + try: + if name in self.from_method_nodes: + return build_template_from_method( + name, + type_to_cls_dict=self.type_to_loader_dict, + method_name=self.from_method_nodes[name], + ) + else: + return build_template_from_class( + name, + type_to_cls_dict=self.type_to_loader_dict, + ) + except ValueError as exc: + # raise ValueError("OutputParser not found") from exc + logger.error(f"OutputParser {name} not found: {exc}") + except AttributeError as exc: + logger.error(f"OutputParser {name} not loaded: {exc}") + return None + + def to_list(self) -> List[str]: + return list(self.type_to_loader_dict.keys()) + + +output_parser_creator = OutputParserCreator() diff --git a/src/backend/langflow/interface/run.py b/src/backend/langflow/interface/run.py index ff888487f..97f47334e 100644 --- a/src/backend/langflow/interface/run.py +++ b/src/backend/langflow/interface/run.py @@ -14,6 +14,23 @@ def build_langchain_object_with_caching(data_graph): return graph.build() +@memoize_dict(maxsize=10) +def build_sorted_vertices_with_caching(data_graph): + """ + Build langchain object from data_graph. + """ + + logger.debug("Building langchain object") + graph = Graph.from_payload(data_graph) + sorted_vertices = graph.topological_sort() + artifacts = {} + for vertex in sorted_vertices: + vertex.build() + if vertex.artifacts: + artifacts.update(vertex.artifacts) + return graph.build(), artifacts + + def build_langchain_object(data_graph): """ Build langchain object from data_graph. diff --git a/src/backend/langflow/interface/tools/base.py b/src/backend/langflow/interface/tools/base.py index d6b114e4c..027224a3a 100644 --- a/src/backend/langflow/interface/tools/base.py +++ b/src/backend/langflow/interface/tools/base.py @@ -90,7 +90,7 @@ class ToolCreator(LangChainTypeCreator): def get_signature(self, name: str) -> Optional[Dict]: """Get the signature of a tool.""" - base_classes = ["Tool"] + base_classes = ["Tool", "BaseTool"] fields = [] params = [] tool_params = {} diff --git a/src/backend/langflow/interface/types.py b/src/backend/langflow/interface/types.py index 6b1ecb3e2..72ecb6775 100644 --- a/src/backend/langflow/interface/types.py +++ b/src/backend/langflow/interface/types.py @@ -11,6 +11,7 @@ from langflow.interface.tools.base import tool_creator from langflow.interface.utilities.base import utility_creator from langflow.interface.vector_store.base import vectorstore_creator from langflow.interface.wrappers.base import wrapper_creator +from langflow.interface.output_parsers.base import output_parser_creator from langflow.interface.retrievers.base import retriever_creator @@ -45,6 +46,7 @@ def build_langchain_types_dict(): # sourcery skip: dict-assign-update-to-union documentloader_creator, textsplitter_creator, utility_creator, + output_parser_creator, retriever_creator, ] diff --git a/src/backend/langflow/interface/utils.py b/src/backend/langflow/interface/utils.py index 1ab2b4ce5..9203915cf 100644 --- a/src/backend/langflow/interface/utils.py +++ b/src/backend/langflow/interface/utils.py @@ -16,17 +16,15 @@ def load_file_into_dict(file_path: str) -> dict: if not os.path.exists(file_path): raise FileNotFoundError(f"File not found: {file_path}") - file_extension = os.path.splitext(file_path)[1].lower() - - if file_extension == ".json": - with open(file_path, "r") as json_file: - data = json.load(json_file) - elif file_extension in [".yaml", ".yml"]: - with open(file_path, "r") as yaml_file: - data = yaml.safe_load(yaml_file) - else: - raise ValueError("Unsupported file type. Please provide a JSON or YAML file.") - + # Files names are UUID, so we can't find the extension + with open(file_path, "r") as file: + try: + data = json.load(file) + except json.JSONDecodeError: + file.seek(0) + data = yaml.safe_load(file) + except ValueError as exc: + raise ValueError("Invalid file type. Expected .json or .yaml.") from exc return data diff --git a/src/backend/langflow/interface/wrappers/base.py b/src/backend/langflow/interface/wrappers/base.py index f5773d07a..77e38f921 100644 --- a/src/backend/langflow/interface/wrappers/base.py +++ b/src/backend/langflow/interface/wrappers/base.py @@ -1,25 +1,36 @@ from typing import Dict, List, Optional -from langchain import requests +from langchain import requests, sql_database from langflow.interface.base import LangChainTypeCreator from langflow.utils.logger import logger -from langflow.utils.util import build_template_from_class +from langflow.utils.util import build_template_from_class, build_template_from_method class WrapperCreator(LangChainTypeCreator): type_name: str = "wrappers" + from_method_nodes = {"SQLDatabase": "from_uri"} + @property def type_to_loader_dict(self) -> Dict: if self.type_dict is None: self.type_dict = { - wrapper.__name__: wrapper for wrapper in [requests.TextRequestsWrapper] + wrapper.__name__: wrapper + for wrapper in [requests.TextRequestsWrapper, sql_database.SQLDatabase] } return self.type_dict def get_signature(self, name: str) -> Optional[Dict]: try: + if name in self.from_method_nodes: + return build_template_from_method( + name, + type_to_cls_dict=self.type_to_loader_dict, + add_function=True, + method_name=self.from_method_nodes[name], + ) + return build_template_from_class(name, self.type_to_loader_dict) except ValueError as exc: raise ValueError("Wrapper not found") from exc diff --git a/src/backend/langflow/lcserve.py b/src/backend/langflow/lcserve.py index affc0ff79..87f69e014 100644 --- a/src/backend/langflow/lcserve.py +++ b/src/backend/langflow/lcserve.py @@ -3,9 +3,9 @@ import os # Use the JCLOUD_WORKSPACE for db URL if it's provided by JCloud. -if 'JCLOUD_WORKSPACE' in os.environ: +if "JCLOUD_WORKSPACE" in os.environ: os.environ[ - 'LANGFLOW_DATABASE_URL' + "LANGFLOW_DATABASE_URL" ] = f"sqlite:///{os.environ['JCLOUD_WORKSPACE']}/langflow.db" from langflow.main import setup_app diff --git a/src/backend/langflow/processing/base.py b/src/backend/langflow/processing/base.py index b332eac7c..f8690bbdf 100644 --- a/src/backend/langflow/processing/base.py +++ b/src/backend/langflow/processing/base.py @@ -1,3 +1,4 @@ +from typing import Union from langflow.api.v1.callback import ( AsyncStreamingLLMCallbackHandler, StreamingLLMCallbackHandler, @@ -6,39 +7,31 @@ from langflow.processing.process import fix_memory_inputs, format_actions from langflow.utils.logger import logger -async def get_result_and_steps(langchain_object, message: str, **kwargs): +async def get_result_and_steps(langchain_object, inputs: Union[dict, str], **kwargs): """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 = True + try: + fix_memory_inputs(langchain_object) + except Exception as exc: + logger.error(exc) - fix_memory_inputs(langchain_object) try: async_callbacks = [AsyncStreamingLLMCallbackHandler(**kwargs)] - output = await langchain_object.acall(chat_input, callbacks=async_callbacks) + output = await langchain_object.acall(inputs, callbacks=async_callbacks) except Exception as exc: # make the error message more informative logger.debug(f"Error: {str(exc)}") sync_callbacks = [StreamingLLMCallbackHandler(**kwargs)] - output = langchain_object(chat_input, callbacks=sync_callbacks) + output = langchain_object(inputs, callbacks=sync_callbacks) intermediate_steps = ( output.get("intermediate_steps", []) if isinstance(output, dict) else [] @@ -49,7 +42,11 @@ async def get_result_and_steps(langchain_object, message: str, **kwargs): if isinstance(output, dict) else output ) - thought = format_actions(intermediate_steps) if intermediate_steps else "" + try: + thought = format_actions(intermediate_steps) if intermediate_steps else "" + except Exception as exc: + logger.exception(exc) + thought = "" except Exception as exc: logger.exception(exc) raise ValueError(f"Error: {str(exc)}") from exc diff --git a/src/backend/langflow/processing/process.py b/src/backend/langflow/processing/process.py index e36cbfd8b..03e6e4c35 100644 --- a/src/backend/langflow/processing/process.py +++ b/src/backend/langflow/processing/process.py @@ -2,7 +2,7 @@ from pathlib import Path from langchain.schema import AgentAction import json from langflow.interface.run import ( - build_langchain_object_with_caching, + build_sorted_vertices_with_caching, get_memory_key, update_memory_keys, ) @@ -22,7 +22,10 @@ def fix_memory_inputs(langchain_object): if not hasattr(langchain_object, "memory") or langchain_object.memory is None: return try: - if langchain_object.memory.memory_key in langchain_object.input_variables: + if ( + hasattr(langchain_object.memory, "memory_key") + and langchain_object.memory.memory_key in langchain_object.input_variables + ): return except AttributeError: input_variables = ( @@ -88,8 +91,20 @@ def process_graph_cached(data_graph: Dict[str, Any], inputs: Optional[dict] = No with PromptTemplate,then run the graph and return the result and thought. """ # Load langchain object - langchain_object = build_langchain_object_with_caching(data_graph) + langchain_object, artifacts = build_sorted_vertices_with_caching(data_graph) logger.debug("Loaded LangChain object") + if inputs is None: + inputs = {} + + # Add artifacts to inputs + # artifacts can be documents loaded when building + # the flow + for ( + key, + value, + ) in artifacts.items(): + if key not in inputs or not inputs[key]: + inputs[key] = value if langchain_object is None: # Raise user facing error @@ -105,8 +120,7 @@ def process_graph_cached(data_graph: Dict[str, Any], inputs: Optional[dict] = No result = get_result_and_thought(langchain_object, inputs) logger.debug("Generated result and thought") elif isinstance(langchain_object, VectorStore): - class_name = langchain_object.__class__.__name__ - result = {"message": f"Processed {class_name} successfully"} + result = langchain_object.search(**inputs) else: raise ValueError( f"Unknown langchain_object type: {type(langchain_object).__name__}" @@ -115,23 +129,23 @@ def process_graph_cached(data_graph: Dict[str, Any], inputs: Optional[dict] = No def load_flow_from_json( - input: Union[Path, str, dict], tweaks: Optional[dict] = None, build=True + flow: Union[Path, str, dict], tweaks: Optional[dict] = None, build=True ): """ Load flow from a JSON file or a JSON object. - :param input: JSON file path or JSON object + :param flow: JSON file path or JSON object :param tweaks: Optional tweaks to be processed :param build: If True, build the graph, otherwise return the graph object :return: Langchain object or Graph object depending on the build parameter """ # If input is a file path, load JSON from the file - if isinstance(input, (str, Path)): - with open(input, "r", encoding="utf-8") as f: + if isinstance(flow, (str, Path)): + with open(flow, "r", encoding="utf-8") as f: flow_graph = json.load(f) # If input is a dictionary, assume it's a JSON object - elif isinstance(input, dict): - flow_graph = input + elif isinstance(flow, dict): + flow_graph = flow else: raise TypeError( "Input must be either a file path (str) or a JSON object (dict)" diff --git a/src/backend/langflow/settings.py b/src/backend/langflow/settings.py index df00a2c27..9e6c60082 100644 --- a/src/backend/langflow/settings.py +++ b/src/backend/langflow/settings.py @@ -21,6 +21,7 @@ class Settings(BaseSettings): toolkits: dict = {} textsplitters: dict = {} utilities: dict = {} + output_parsers: dict = {} dev: bool = False database_url: Optional[str] = None cache: str = "InMemoryCache" @@ -66,7 +67,7 @@ class Settings(BaseSettings): self.vectorstores = new_settings.vectorstores or {} self.documentloaders = new_settings.documentloaders or {} self.retrievers = new_settings.retrievers or {} - + self.output_parsers = new_settings.output_parsers or {} self.dev = dev def update_settings(self, **kwargs): diff --git a/src/backend/langflow/template/field/base.py b/src/backend/langflow/template/field/base.py index fdfdca562..a747ad322 100644 --- a/src/backend/langflow/template/field/base.py +++ b/src/backend/langflow/template/field/base.py @@ -21,6 +21,7 @@ class TemplateFieldCreator(BaseModel, ABC): name: str = "" display_name: Optional[str] = None advanced: bool = False + input_types: list[str] = [] info: Optional[str] = "" def to_dict(self): diff --git a/src/backend/langflow/template/frontend_node/agents.py b/src/backend/langflow/template/frontend_node/agents.py index f692a7d6c..02aea78b9 100644 --- a/src/backend/langflow/template/frontend_node/agents.py +++ b/src/backend/langflow/template/frontend_node/agents.py @@ -13,6 +13,16 @@ NON_CHAT_AGENTS = { } +class AgentFrontendNode(FrontendNode): + @staticmethod + def format_field(field: TemplateField, name: Optional[str] = None) -> None: + if field.name in ["suffix", "prefix"]: + field.show = True + if field.name == "Tools" and name == "ZeroShotAgent": + field.field_type = "BaseTool" + field.is_list = True + + class SQLAgentNode(FrontendNode): name: str = "SQLAgent" template: Template = Template( diff --git a/src/backend/langflow/template/frontend_node/base.py b/src/backend/langflow/template/frontend_node/base.py index de8c78112..7dae45463 100644 --- a/src/backend/langflow/template/frontend_node/base.py +++ b/src/backend/langflow/template/frontend_node/base.py @@ -1,15 +1,16 @@ +from collections import defaultdict import re from typing import List, Optional from pydantic import BaseModel, Field +from langflow.template.frontend_node.formatter import field_formatters from langflow.template.frontend_node.constants import FORCE_SHOW_FIELDS from langflow.template.field.base import TemplateField from langflow.template.template.base import Template from langflow.utils import constants -from langflow.template.frontend_node.formatter import field_formatters -CLASSES_TO_REMOVE = ["Serializable", "BaseModel"] +CLASSES_TO_REMOVE = ["Serializable", "BaseModel", "object"] class FieldFormatters(BaseModel): @@ -47,6 +48,8 @@ class FrontendNode(BaseModel): name: str = "" display_name: str = "" documentation: str = "" + custom_fields: defaultdict = defaultdict(list) + output_types: List[str] = [] field_formatters: FieldFormatters = Field(default_factory=FieldFormatters) def process_base_classes(self) -> None: @@ -76,6 +79,8 @@ class FrontendNode(BaseModel): "description": self.description, "base_classes": self.base_classes, "display_name": self.display_name or self.name, + "custom_fields": self.custom_fields, + "output_types": self.output_types, "documentation": self.documentation, }, } diff --git a/src/backend/langflow/template/frontend_node/chains.py b/src/backend/langflow/template/frontend_node/chains.py index ce8c1c62c..b678dec3b 100644 --- a/src/backend/langflow/template/frontend_node/chains.py +++ b/src/backend/langflow/template/frontend_node/chains.py @@ -81,7 +81,7 @@ class ChainFrontendNode(FrontendNode): field.advanced = False if field.name == "verbose": field.required = False - field.show = True + field.show = False field.advanced = True if field.name == "llm": field.required = True diff --git a/src/backend/langflow/template/frontend_node/constants.py b/src/backend/langflow/template/frontend_node/constants.py index 90cdbf280..295995586 100644 --- a/src/backend/langflow/template/frontend_node/constants.py +++ b/src/backend/langflow/template/frontend_node/constants.py @@ -58,3 +58,7 @@ The base URL of the OpenAI API. Defaults to https://api.openai.com/v1. You can change this to use other APIs like JinaChat, LocalAI and Prem. """ + + +INPUT_KEY_INFO = """The variable to be used as Chat Input when more than one variable is available.""" +OUTPUT_KEY_INFO = """The variable to be used as Chat Output (e.g. answer in a ConversationalRetrievalChain)""" diff --git a/src/backend/langflow/template/frontend_node/documentloaders.py b/src/backend/langflow/template/frontend_node/documentloaders.py index 35a727870..d775d8736 100644 --- a/src/backend/langflow/template/frontend_node/documentloaders.py +++ b/src/backend/langflow/template/frontend_node/documentloaders.py @@ -19,6 +19,10 @@ def build_file_field( class DocumentLoaderFrontNode(FrontendNode): + def add_extra_base_classes(self) -> None: + self.base_classes = ["Document"] + self.output_types = ["Document"] + file_path_templates = { "AirbyteJSONLoader": build_file_field(suffixes=[".json"], fileTypes=["json"]), "CoNLLULoader": build_file_field(suffixes=[".csv"], fileTypes=["csv"]), diff --git a/src/backend/langflow/template/frontend_node/formatter/base.py b/src/backend/langflow/template/frontend_node/formatter/base.py index 67e906593..f582bc298 100644 --- a/src/backend/langflow/template/frontend_node/formatter/base.py +++ b/src/backend/langflow/template/frontend_node/formatter/base.py @@ -2,9 +2,10 @@ from abc import ABC, abstractmethod from typing import Optional from langflow.template.field.base import TemplateField +from pydantic import BaseModel -class FieldFormatter(ABC): +class FieldFormatter(BaseModel, ABC): @abstractmethod def format(self, field: TemplateField, name: Optional[str]) -> None: pass diff --git a/src/backend/langflow/template/frontend_node/memories.py b/src/backend/langflow/template/frontend_node/memories.py index 6d490212f..374d36ff0 100644 --- a/src/backend/langflow/template/frontend_node/memories.py +++ b/src/backend/langflow/template/frontend_node/memories.py @@ -2,8 +2,13 @@ from typing import Optional from langflow.template.field.base import TemplateField from langflow.template.frontend_node.base import FrontendNode +from langflow.template.frontend_node.constants import INPUT_KEY_INFO, OUTPUT_KEY_INFO from langflow.template.template.base import Template from langchain.memory.chat_message_histories.postgres import DEFAULT_CONNECTION_STRING +from langchain.memory.chat_message_histories.mongodb import ( + DEFAULT_COLLECTION_NAME, + DEFAULT_DBNAME, +) class MemoryFrontendNode(FrontendNode): @@ -66,11 +71,15 @@ class MemoryFrontendNode(FrontendNode): field.required = False field.show = True field.advanced = False - if field.name in ["input_key", "output_key"]: + if field.name in {"input_key", "output_key"}: field.required = False field.show = True field.advanced = False field.value = "" + field.info = ( + INPUT_KEY_INFO if field.name == "input_key" else OUTPUT_KEY_INFO + ) + if field.name == "memory_key": field.value = "chat_history" if field.name == "chat_memory": @@ -80,9 +89,10 @@ class MemoryFrontendNode(FrontendNode): if field.name == "url": field.show = True if field.name == "entity_store": - field.show = True - if name == "SQLiteEntityStore": - field.show = True + field.show = False + if name == "ConversationEntityMemory" and field.name == "memory_key": + field.show = False + field.required = False class PostgresChatMessageHistoryFrontendNode(MemoryFrontendNode): @@ -120,3 +130,56 @@ class PostgresChatMessageHistoryFrontendNode(MemoryFrontendNode): ) description: str = "Memory store with Postgres" base_classes: list[str] = ["PostgresChatMessageHistory", "BaseChatMessageHistory"] + + +class MongoDBChatMessageHistoryFrontendNode(MemoryFrontendNode): + name: str = "MongoDBChatMessageHistory" + template: Template = Template( + # langchain/memory/chat_message_histories/mongodb.py + # connection_string: str, + # session_id: str, + # database_name: str = DEFAULT_DBNAME, + # collection_name: str = DEFAULT_COLLECTION_NAME, + type_name="MongoDBChatMessageHistory", + fields=[ + TemplateField( + field_type="str", + required=True, + placeholder="", + is_list=False, + show=True, + multiline=False, + name="session_id", + ), + TemplateField( + field_type="str", + required=True, + show=True, + name="connection_string", + value="", + info="MongoDB connection string (e.g mongodb://mongo_user:password123@mongo:27017)", + ), + TemplateField( + field_type="str", + required=True, + placeholder="", + is_list=False, + show=True, + multiline=False, + value=DEFAULT_DBNAME, + name="database_name", + ), + TemplateField( + field_type="str", + required=True, + placeholder="", + is_list=False, + show=True, + multiline=False, + value=DEFAULT_COLLECTION_NAME, + name="collection_name", + ), + ], + ) + description: str = "Memory store with MongoDB" + base_classes: list[str] = ["MongoDBChatMessageHistory", "BaseChatMessageHistory"] diff --git a/src/backend/langflow/template/frontend_node/output_parsers.py b/src/backend/langflow/template/frontend_node/output_parsers.py new file mode 100644 index 000000000..e9b4d3706 --- /dev/null +++ b/src/backend/langflow/template/frontend_node/output_parsers.py @@ -0,0 +1,10 @@ +from typing import Optional +from langflow.template.field.base import TemplateField +from langflow.template.frontend_node.base import FrontendNode + + +class OutputParserFrontendNode(FrontendNode): + @staticmethod + def format_field(field: TemplateField, name: Optional[str] = None) -> None: + FrontendNode.format_field(field, name) + field.show = True diff --git a/src/backend/langflow/template/frontend_node/textsplitters.py b/src/backend/langflow/template/frontend_node/textsplitters.py index 65a2be6f6..1d5549042 100644 --- a/src/backend/langflow/template/frontend_node/textsplitters.py +++ b/src/backend/langflow/template/frontend_node/textsplitters.py @@ -4,10 +4,14 @@ from langchain.text_splitter import Language class TextSplittersFrontendNode(FrontendNode): + def add_extra_base_classes(self) -> None: + self.base_classes = ["Document"] + self.output_types = ["Document"] + def add_extra_fields(self) -> None: self.template.add_field( TemplateField( - field_type="BaseLoader", + field_type="Document", required=True, show=True, name="documents", @@ -41,7 +45,7 @@ class TextSplittersFrontendNode(FrontendNode): field_type="str", required=True, show=True, - value=".", + value="\\n", name=name, display_name="Separator", ) diff --git a/src/backend/langflow/template/frontend_node/tools.py b/src/backend/langflow/template/frontend_node/tools.py index fa3942bd2..ece765ed7 100644 --- a/src/backend/langflow/template/frontend_node/tools.py +++ b/src/backend/langflow/template/frontend_node/tools.py @@ -53,7 +53,7 @@ class ToolNode(FrontendNode): ], ) description: str = "Converts a chain, agent or function into a tool." - base_classes: list[str] = ["Tool"] + base_classes: list[str] = ["Tool", "BaseTool"] def to_dict(self): return super().to_dict() @@ -109,7 +109,7 @@ class PythonFunctionToolNode(FrontendNode): ], ) description: str = "Python function to be executed." - base_classes: list[str] = ["Tool"] + base_classes: list[str] = ["BaseTool", "Tool"] def to_dict(self): return super().to_dict() diff --git a/src/backend/langflow/template/frontend_node/vectorstores.py b/src/backend/langflow/template/frontend_node/vectorstores.py index 89eedc596..4daf56bd2 100644 --- a/src/backend/langflow/template/frontend_node/vectorstores.py +++ b/src/backend/langflow/template/frontend_node/vectorstores.py @@ -254,7 +254,7 @@ class VectorStoreFrontendNode(FrontendNode): # when instantiating the vectorstores field.name = "documents" - field.field_type = "TextSplitter" + field.field_type = "Document" field.display_name = "Documents" field.required = False field.show = True diff --git a/src/backend/langflow/utils/util.py b/src/backend/langflow/utils/util.py index 4769563bd..c5db6052e 100644 --- a/src/backend/langflow/utils/util.py +++ b/src/backend/langflow/utils/util.py @@ -243,7 +243,11 @@ def format_dict(d, name: Optional[str] = None): # Check for list type if "List" in _type or "Sequence" in _type or "Set" in _type: - _type = _type.replace("List[", "")[:-1] + _type = ( + _type.replace("List[", "") + .replace("Sequence[", "") + .replace("Set[", "")[:-1] + ) value["list"] = True else: value["list"] = False diff --git a/src/frontend/index.html b/src/frontend/index.html index 50bdae647..8c21f0124 100644 --- a/src/frontend/index.html +++ b/src/frontend/index.html @@ -5,6 +5,7 @@ + Langflow diff --git a/src/frontend/package-lock.json b/src/frontend/package-lock.json index acf9a1865..6ac6b625c 100644 --- a/src/frontend/package-lock.json +++ b/src/frontend/package-lock.json @@ -37,7 +37,7 @@ "base64-js": "^1.5.1", "class-variance-authority": "^0.6.0", "clsx": "^1.2.1", - "dompurify": "^3.0.3", + "dompurify": "^3.0.4", "esbuild": "^0.17.18", "lodash": "^4.17.21", "lucide-react": "^0.233.0", @@ -85,6 +85,7 @@ "daisyui": "^3.1.1", "postcss": "^8.4.23", "prettier": "^2.8.8", + "prettier-plugin-organize-imports": "^3.2.2", "prettier-plugin-tailwindcss": "^0.3.0", "tailwindcss": "^3.3.2", "typescript": "^5.0.2", @@ -146,33 +147,33 @@ } }, "node_modules/@babel/compat-data": { - "version": "7.22.5", - "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.22.5.tgz", - "integrity": "sha512-4Jc/YuIaYqKnDDz892kPIledykKg12Aw1PYX5i/TY28anJtacvM1Rrr8wbieB9GfEJwlzqT0hUEao0CxEebiDA==", + "version": "7.22.6", + "resolved": "https://registry.npmjs.org/@babel/compat-data/-/compat-data-7.22.6.tgz", + "integrity": "sha512-29tfsWTq2Ftu7MXmimyC0C5FDZv5DYxOZkh3XD3+QW4V/BYuv/LyEsjj3c0hqedEaDt6DBfDvexMKU8YevdqFg==", "engines": { "node": ">=6.9.0" } }, "node_modules/@babel/core": { - "version": "7.22.5", - "resolved": "https://registry.npmjs.org/@babel/core/-/core-7.22.5.tgz", - 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"version": "4.21.5", - "resolved": "https://registry.npmjs.org/browserslist/-/browserslist-4.21.5.tgz", - "integrity": "sha512-tUkiguQGW7S3IhB7N+c2MV/HZPSCPAAiYBZXLsBhFB/PCy6ZKKsZrmBayHV9fdGV/ARIfJ14NkxKzRDjvp7L6w==", + "version": "4.21.9", + "resolved": "https://registry.npmjs.org/browserslist/-/browserslist-4.21.9.tgz", + "integrity": "sha512-M0MFoZzbUrRU4KNfCrDLnvyE7gub+peetoTid3TBIqtunaDJyXlwhakT+/VkvSXcfIzFfK/nkCs4nmyTmxdNSg==", "funding": [ { "type": "opencollective", @@ -4317,13 +4260,17 @@ { "type": "tidelift", "url": "https://tidelift.com/funding/github/npm/browserslist" + }, + { + "type": "github", + "url": "https://github.com/sponsors/ai" } ], "dependencies": { - "caniuse-lite": "^1.0.30001449", - "electron-to-chromium": "^1.4.284", - "node-releases": "^2.0.8", - "update-browserslist-db": "^1.0.10" + "caniuse-lite": "^1.0.30001503", + "electron-to-chromium": "^1.4.431", + "node-releases": "^2.0.12", + "update-browserslist-db": "^1.0.11" }, "bin": { "browserslist": "cli.js" @@ -4438,9 +4385,9 @@ } }, "node_modules/caniuse-lite": { - "version": "1.0.30001486", - "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001486.tgz", - "integrity": "sha512-uv7/gXuHi10Whlj0pp5q/tsK/32J2QSqVRKQhs2j8VsDCjgyruAh/eEXHF822VqO9yT6iZKw3nRwZRSPBE9OQg==", + "version": "1.0.30001513", + "resolved": "https://registry.npmjs.org/caniuse-lite/-/caniuse-lite-1.0.30001513.tgz", + "integrity": "sha512-pnjGJo7SOOjAGytZZ203Em95MRM8Cr6jhCXNF/FAXTpCTRTECnqQWLpiTRqrFtdYcth8hf4WECUpkezuYsMVww==", "funding": [ { "type": "opencollective", @@ -5142,9 +5089,9 @@ } }, "node_modules/dompurify": { - "version": "3.0.3", - "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.0.3.tgz", - "integrity": "sha512-axQ9zieHLnAnHh0sfAamKYiqXMJAVwu+LM/alQ7WDagoWessyWvMSFyW65CqF3owufNu8HBcE4cM2Vflu7YWcQ==" + "version": "3.0.4", + "resolved": "https://registry.npmjs.org/dompurify/-/dompurify-3.0.4.tgz", + "integrity": "sha512-ae0mA+Qiqp6C29pqZX3fQgK+F91+F7wobM/v8DRzDqJdZJELXiFUx4PP4pK/mzUS0xkiSEx3Ncd9gr69jg3YsQ==" }, "node_modules/electron-to-chromium": { "version": "1.4.440", @@ -8616,6 +8563,26 @@ "url": "https://github.com/prettier/prettier?sponsor=1" } }, + "node_modules/prettier-plugin-organize-imports": { + "version": "3.2.2", + "resolved": "https://registry.npmjs.org/prettier-plugin-organize-imports/-/prettier-plugin-organize-imports-3.2.2.tgz", + "integrity": "sha512-e97lE6odGSiHonHJMTYC0q0iLXQyw0u5z/PJpvP/3vRy6/Zi9kLBwFAbEGjDzIowpjQv8b+J04PDamoUSQbzGA==", + "dev": true, + "peerDependencies": { + "@volar/vue-language-plugin-pug": "^1.0.4", + "@volar/vue-typescript": "^1.0.4", + "prettier": ">=2.0", + "typescript": ">=2.9" + }, + "peerDependenciesMeta": { + "@volar/vue-language-plugin-pug": { + "optional": true + }, + "@volar/vue-typescript": { + "optional": true + } + } + }, "node_modules/prettier-plugin-tailwindcss": { "version": "0.3.0", "resolved": "https://registry.npmjs.org/prettier-plugin-tailwindcss/-/prettier-plugin-tailwindcss-0.3.0.tgz", @@ -9507,11 +9474,18 @@ } }, "node_modules/semver": { - "version": "6.3.0", - "resolved": "https://registry.npmjs.org/semver/-/semver-6.3.0.tgz", - "integrity": "sha512-b39TBaTSfV6yBrapU89p5fKekE2m/NwnDocOVruQFS1/veMgdzuPcnOM34M6CwxW8jH/lxEa5rBoDeUwu5HHTw==", + "version": "7.5.3", + "resolved": "https://registry.npmjs.org/semver/-/semver-7.5.3.tgz", + "integrity": "sha512-QBlUtyVk/5EeHbi7X0fw6liDZc7BBmEaSYn01fMU1OUYbf6GPsbTtd8WmnqbI20SeycoHSeiybkE/q1Q+qlThQ==", + "dev": true, + "dependencies": { + "lru-cache": "^6.0.0" + }, "bin": { "semver": "bin/semver.js" + }, + "engines": { + "node": ">=10" } }, "node_modules/semver-regex": { @@ -9527,17 +9501,38 @@ } }, "node_modules/semver-truncate": { - "version": "2.0.0", - "resolved": "https://registry.npmjs.org/semver-truncate/-/semver-truncate-2.0.0.tgz", - "integrity": "sha512-Rh266MLDYNeML5h90ttdMwfXe1+Nc4LAWd9X1KdJe8pPHP4kFmvLZALtsMNHNdvTyQygbEC0D59sIz47DIaq8w==", + "version": "3.0.0", + "resolved": "https://registry.npmjs.org/semver-truncate/-/semver-truncate-3.0.0.tgz", + "integrity": "sha512-LJWA9kSvMolR51oDE6PN3kALBNaUdkxzAGcexw8gjMA8xr5zUqK0JiR3CgARSqanYF3Z1YHvsErb1KDgh+v7Rg==", "dev": true, "dependencies": { - "semver": "^6.0.0" + "semver": "^7.3.5" }, "engines": { - "node": ">=8" + "node": ">=12" + }, + "funding": { + "url": "https://github.com/sponsors/sindresorhus" } }, + "node_modules/semver/node_modules/lru-cache": { + "version": "6.0.0", + "resolved": "https://registry.npmjs.org/lru-cache/-/lru-cache-6.0.0.tgz", + "integrity": "sha512-Jo6dJ04CmSjuznwJSS3pUeWmd/H0ffTlkXXgwZi+eq1UCmqQwCh+eLsYOYCwY991i2Fah4h1BEMCx4qThGbsiA==", + "dev": true, + "dependencies": { + "yallist": "^4.0.0" + }, + "engines": { + "node": ">=10" + } + }, + "node_modules/semver/node_modules/yallist": { + "version": "4.0.0", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-4.0.0.tgz", + "integrity": "sha512-3wdGidZyq5PB084XLES5TpOSRA3wjXAlIWMhum2kRcv/41Sn2emQ0dycQW4uZXLejwKvg6EsvbdlVL+FYEct7A==", + "dev": true + }, "node_modules/shadcn-ui": { "version": "0.2.2", "resolved": "https://registry.npmjs.org/shadcn-ui/-/shadcn-ui-0.2.2.tgz", diff --git a/src/frontend/package.json b/src/frontend/package.json index b856cd5b6..323a9a7be 100644 --- a/src/frontend/package.json +++ b/src/frontend/package.json @@ -32,7 +32,7 @@ "base64-js": "^1.5.1", "class-variance-authority": "^0.6.0", "clsx": "^1.2.1", - "dompurify": "^3.0.3", + "dompurify": "^3.0.4", "esbuild": "^0.17.18", "lodash": "^4.17.21", "lucide-react": "^0.233.0", @@ -106,6 +106,7 @@ "daisyui": "^3.1.1", "postcss": "^8.4.23", "prettier": "^2.8.8", + "prettier-plugin-organize-imports": "^3.2.2", "prettier-plugin-tailwindcss": "^0.3.0", "tailwindcss": "^3.3.2", "typescript": "^5.0.2", diff --git a/src/frontend/src/App.tsx b/src/frontend/src/App.tsx index 4f2e390c6..0088081ae 100644 --- a/src/frontend/src/App.tsx +++ b/src/frontend/src/App.tsx @@ -1,20 +1,19 @@ -import "reactflow/dist/style.css"; -import { useState, useEffect, useContext } from "react"; -import "./App.css"; -import { useLocation } from "react-router-dom"; import _ from "lodash"; +import { useContext, useEffect, useState } from "react"; +import { useLocation } from "react-router-dom"; +import "reactflow/dist/style.css"; +import "./App.css"; +import { ErrorBoundary } from "react-error-boundary"; import ErrorAlert from "./alerts/error"; import NoticeAlert from "./alerts/notice"; import SuccessAlert from "./alerts/success"; +import CrashErrorComponent from "./components/CrashErrorComponent"; +import Header from "./components/headerComponent"; import { alertContext } from "./contexts/alertContext"; import { locationContext } from "./contexts/locationContext"; -import { ErrorBoundary } from "react-error-boundary"; -import CrashErrorComponent from "./components/CrashErrorComponent"; import { TabsContext } from "./contexts/tabsContext"; -import { getVersion } from "./controllers/API"; import Router from "./routes"; -import Header from "./components/headerComponent"; export default function App() { let { setCurrent, setShowSideBar, setIsStackedOpen } = @@ -118,7 +117,7 @@ export default function App() { const removeAlert = (id: string) => { setAlertsList((prevAlertsList) => - prevAlertsList.filter((alert) => alert.id !== id), + prevAlertsList.filter((alert) => alert.id !== id) ); }; @@ -138,10 +137,7 @@ export default function App() {
-
+
{alertsList.map((alert) => (
{alert.type === "error" ? ( diff --git a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx index f9c432fc1..a3e3e6357 100644 --- a/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/components/parameterComponent/index.tsx @@ -1,31 +1,32 @@ +import { Info } from "lucide-react"; +import React, { useContext, useEffect, useRef, useState } from "react"; import { Handle, Position, useUpdateNodeInternals } from "reactflow"; +import ShadTooltip from "../../../../components/ShadTooltipComponent"; +import CodeAreaComponent from "../../../../components/codeAreaComponent"; +import Dropdown from "../../../../components/dropdownComponent"; +import FloatComponent from "../../../../components/floatComponent"; +import InputComponent from "../../../../components/inputComponent"; +import InputFileComponent from "../../../../components/inputFileComponent"; +import InputListComponent from "../../../../components/inputListComponent"; +import IntComponent from "../../../../components/intComponent"; +import PromptAreaComponent from "../../../../components/promptComponent"; +import TextAreaComponent from "../../../../components/textAreaComponent"; +import ToggleShadComponent from "../../../../components/toggleShadComponent"; +import { MAX_LENGTH_TO_SCROLL_TOOLTIP } from "../../../../constants"; +import { PopUpContext } from "../../../../contexts/popUpContext"; +import { TabsContext } from "../../../../contexts/tabsContext"; +import { typesContext } from "../../../../contexts/typesContext"; +import { ParameterComponentType } from "../../../../types/components"; +import { cleanEdges } from "../../../../util/reactflowUtils"; import { classNames, getRandomKeyByssmm, groupByFamily, isValidConnection, + nodeColors, nodeIconsLucide, + nodeNames, } from "../../../../utils"; -import { useContext, useEffect, useRef, useState } from "react"; -import InputComponent from "../../../../components/inputComponent"; -import InputListComponent from "../../../../components/inputListComponent"; -import TextAreaComponent from "../../../../components/textAreaComponent"; -import { typesContext } from "../../../../contexts/typesContext"; -import { ParameterComponentType } from "../../../../types/components"; -import FloatComponent from "../../../../components/floatComponent"; -import Dropdown from "../../../../components/dropdownComponent"; -import CodeAreaComponent from "../../../../components/codeAreaComponent"; -import InputFileComponent from "../../../../components/inputFileComponent"; -import { TabsContext } from "../../../../contexts/tabsContext"; -import IntComponent from "../../../../components/intComponent"; -import PromptAreaComponent from "../../../../components/promptComponent"; -import { nodeNames } from "../../../../utils"; -import React from "react"; -import { nodeColors } from "../../../../utils"; -import ShadTooltip from "../../../../components/ShadTooltipComponent"; -import { PopUpContext } from "../../../../contexts/popUpContext"; -import ToggleShadComponent from "../../../../components/toggleShadComponent"; -import { Info } from "lucide-react"; export default function ParameterComponent({ left, @@ -37,10 +38,12 @@ export default function ParameterComponent({ type, name = "", required = false, + optionalHandle = null, info = "", }: ParameterComponentType) { const ref = useRef(null); const refHtml = useRef(null); + const refNumberComponents = useRef(0); const infoHtml = useRef(null); const updateNodeInternals = useUpdateNodeInternals(); const [position, setPosition] = useState(0); @@ -58,10 +61,6 @@ export default function ParameterComponent({ updateNodeInternals(data.id); }, [data.id, position, updateNodeInternals]); - const [enabled, setEnabled] = useState( - data.node.template[name]?.value ?? false - ); - useEffect(() => {}, [closePopUp, data.node.template]); const { reactFlowInstance } = useContext(typesContext); @@ -76,6 +75,7 @@ export default function ParameterComponent({ return { ...prev, [tabId]: { + ...prev[tabId], isPending: true, }, }; @@ -95,44 +95,55 @@ export default function ParameterComponent({ }, [info]); useEffect(() => { - const groupedObj = groupByFamily(myData, tooltipTitle); + const groupedObj = groupByFamily(myData, tooltipTitle, left, data.type); - refHtml.current = groupedObj.map((item, i) => ( - 0 ? "mt-3 flex items-center" : "flex items-center" - )} - > -
{ + const Icon: any = nodeIconsLucide[item.family]; + + return ( + 0 ? "mt-2 flex items-center" : "flex items-center" + )} > - {React.createElement(nodeIconsLucide[item.family])} -
- - {nodeNames[item.family] ?? ""}{" "} - - {" "} - -  - {item.type.split(", ").length > 2 - ? item.type.split(", ").map((el, i) => ( - - - {i === item.type.split(", ").length - 1 - ? el - : (el += `, `)} - - {i % 2 === 0 && i > 0 &&
} - - )) - : item.type} +
+ +
+ + {nodeNames[item.family] ?? ""}{" "} + + {" "} + {item.type === "" ? "" : " - "} + {item.type.split(", ").length > 2 + ? item.type.split(", ").map((el, i) => ( + + + {i === item.type.split(", ").length - 1 + ? el + : (el += `, `)} + + + )) + : item.type} + - - )); + ); + }); }, [tooltipTitle]); return ( @@ -149,7 +160,7 @@ export default function ParameterComponent({ } > {title} - {required ? " *" : ""} + {required ? " *" : ""}
{info !== "" && ( @@ -165,10 +176,16 @@ export default function ParameterComponent({ type === "code" || type === "prompt" || type === "file" || - type === "int") ? ( + type === "int") && + !optionalHandle ? ( <> ) : ( MAX_LENGTH_TO_SCROLL_TOOLTIP + ? "tooltip-fixed-width custom-scroll overflow-y-scroll nowheel" + : "tooltip-fixed-width" + } delayDuration={0} content={refHtml.current} side={left ? "left" : "right"} @@ -227,10 +244,9 @@ export default function ParameterComponent({
{ handleOnNewValue(t); - setEnabled(t); }} size="large" /> @@ -257,6 +273,10 @@ export default function ParameterComponent({ ) : left === true && type === "code" ? (
{ + data.node = nodeClass; + }} + nodeClass={data.node} disabled={disabled} value={data.node.template[name].value ?? ""} onChange={handleOnNewValue} @@ -288,6 +308,20 @@ export default function ParameterComponent({ ) : left === true && type === "prompt" ? (
{ + data.node = nodeClass; + if (reactFlowInstance) { + cleanEdges({ + flow: { + edges: reactFlowInstance.getEdges(), + nodes: reactFlowInstance.getNodes(), + }, + updateEdge: (edge) => reactFlowInstance.setEdges(edge), + }); + } + }} + nodeClass={data.node} disabled={disabled} value={data.node.template[name].value ?? ""} onChange={handleOnNewValue} diff --git a/src/frontend/src/CustomNodes/GenericNode/index.tsx b/src/frontend/src/CustomNodes/GenericNode/index.tsx index f177ab1c0..ee62461bd 100644 --- a/src/frontend/src/CustomNodes/GenericNode/index.tsx +++ b/src/frontend/src/CustomNodes/GenericNode/index.tsx @@ -1,3 +1,15 @@ +import { Zap } from "lucide-react"; +import { useContext, useEffect, useRef, useState } from "react"; +import { NodeToolbar } from "reactflow"; +import ShadTooltip from "../../components/ShadTooltipComponent"; +import Tooltip from "../../components/TooltipComponent"; +import { useSSE } from "../../contexts/SSEContext"; +import { alertContext } from "../../contexts/alertContext"; +import { PopUpContext } from "../../contexts/popUpContext"; +import { typesContext } from "../../contexts/typesContext"; +import NodeModal from "../../modals/NodeModal"; +import NodeToolbarComponent from "../../pages/FlowPage/components/nodeToolbarComponent"; +import { NodeDataType } from "../../types/flow"; import { classNames, nodeColors, @@ -5,17 +17,6 @@ import { toTitleCase, } from "../../utils"; import ParameterComponent from "./components/parameterComponent"; -import { typesContext } from "../../contexts/typesContext"; -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 Tooltip from "../../components/TooltipComponent"; -import { NodeToolbar } from "reactflow"; -import NodeToolbarComponent from "../../pages/FlowPage/components/nodeToolbarComponent"; -import ShadTooltip from "../../components/ShadTooltipComponent"; -import { useSSE } from "../../contexts/SSEContext"; export default function GenericNode({ data, @@ -66,9 +67,7 @@ export default function GenericNode({ deleteNode(data.id); return; } - useEffect(() => {}, [closePopUp, data.node.template]); - return ( <> @@ -95,10 +94,7 @@ export default function GenericNode({ }} />
- +
{data.node.display_name}
@@ -118,14 +114,24 @@ export default function GenericNode({
Building... + ) : !validationStatus ? ( + + Build{" "} + {" "} + flow to validate status. + ) : ( -
- {validationStatus.params || - "" - .split("\n") - .map((line, index) =>
{line}
)} +
+ {validationStatus.params + ? validationStatus.params + .split("\n") + .map((line, index) =>
{line}
) + : ""}
) } @@ -162,9 +168,7 @@ export default function GenericNode({
-
- {data.node.description} -
+
{data.node.description}
<> {Object.keys(data.node.template) @@ -196,6 +200,7 @@ export default function GenericNode({ data={data} color={ nodeColors[types[data.node.template[t].type]] ?? + nodeColors[data.node.template[t].type] ?? nodeColors.unknown } title={ @@ -207,11 +212,22 @@ export default function GenericNode({ } info={data.node.template[t].info} name={t} - tooltipTitle={data.node.template[t].type} + tooltipTitle={ + data.node.template[t].input_types?.join("\n") ?? + data.node.template[t].type + } required={data.node.template[t].required} - id={data.node.template[t].type + "|" + t + "|" + data.id} + id={ + (data.node.template[t].input_types?.join(";") ?? + data.node.template[t].type) + + "|" + + t + + "|" + + data.id + } left={true} type={data.node.template[t].type} + optionalHandle={data.node.template[t].input_types} /> ) : ( <> @@ -232,8 +248,12 @@ export default function GenericNode({ 0 + ? data.node.output_types.join("|") + : data.type + } + tooltipTitle={data.node.base_classes.join("\n")} id={[data.type, data.id, ...data.node.base_classes].join("|")} type={data.node.base_classes.join("|")} left={false} diff --git a/src/frontend/src/alerts/alertDropDown/components/singleAlertComponent/index.tsx b/src/frontend/src/alerts/alertDropDown/components/singleAlertComponent/index.tsx index 857bf0fb4..18475b039 100644 --- a/src/frontend/src/alerts/alertDropDown/components/singleAlertComponent/index.tsx +++ b/src/frontend/src/alerts/alertDropDown/components/singleAlertComponent/index.tsx @@ -1,8 +1,8 @@ -import { Link } from "react-router-dom"; import { Transition } from "@headlessui/react"; +import { CheckCircle2, Info, X, XCircle } from "lucide-react"; import { useState } from "react"; +import { Link } from "react-router-dom"; import { SingleAlertComponentType } from "../../../../types/alerts"; -import { X, CheckCircle2, Info, XCircle } from "lucide-react"; export default function SingleAlert({ dropItem, diff --git a/src/frontend/src/alerts/alertDropDown/index.tsx b/src/frontend/src/alerts/alertDropDown/index.tsx index ef703f624..cd1ed9137 100644 --- a/src/frontend/src/alerts/alertDropDown/index.tsx +++ b/src/frontend/src/alerts/alertDropDown/index.tsx @@ -1,10 +1,10 @@ -import { useContext, useEffect, useRef } from "react"; +import { Trash2, X } from "lucide-react"; +import { useContext, useRef } from "react"; import { alertContext } from "../../contexts/alertContext"; -import SingleAlert from "./components/singleAlertComponent"; -import { AlertDropdownType } from "../../types/alerts"; import { PopUpContext } from "../../contexts/popUpContext"; +import { AlertDropdownType } from "../../types/alerts"; import { useOnClickOutside } from "../hooks/useOnClickOutside"; -import { X, Trash2 } from "lucide-react"; +import SingleAlert from "./components/singleAlertComponent"; export default function AlertDropdown({}: AlertDropdownType) { const { closePopUp } = useContext(PopUpContext); diff --git a/src/frontend/src/alerts/error/index.tsx b/src/frontend/src/alerts/error/index.tsx index 93f30484b..3824c3e87 100644 --- a/src/frontend/src/alerts/error/index.tsx +++ b/src/frontend/src/alerts/error/index.tsx @@ -1,7 +1,7 @@ import { Transition } from "@headlessui/react"; +import { XCircle } from "lucide-react"; import { useEffect, useState } from "react"; import { ErrorAlertType } from "../../types/alerts"; -import { XCircle } from "lucide-react"; export default function ErrorAlert({ title, @@ -20,6 +20,7 @@ export default function ErrorAlert({ }, 5000); } }, [id, removeAlert, show]); + return (
-
-

- {title} -

- {list.length !== 0 ? ( +

{title}

+ {list?.length !== 0 && + list?.some((item) => item !== null && item !== undefined) ? (
    {list.map((item, index) => ( diff --git a/src/frontend/src/alerts/notice/index.tsx b/src/frontend/src/alerts/notice/index.tsx index eeb00cd42..c77a4bcd6 100644 --- a/src/frontend/src/alerts/notice/index.tsx +++ b/src/frontend/src/alerts/notice/index.tsx @@ -1,8 +1,8 @@ import { Transition } from "@headlessui/react"; +import { Info } from "lucide-react"; import { useEffect, useState } from "react"; import { Link } from "react-router-dom"; import { NoticeAlertType } from "../../types/alerts"; -import { Info } from "lucide-react"; export default function NoticeAlert({ title, diff --git a/src/frontend/src/alerts/success/index.tsx b/src/frontend/src/alerts/success/index.tsx index e943feb8c..60dba1e93 100644 --- a/src/frontend/src/alerts/success/index.tsx +++ b/src/frontend/src/alerts/success/index.tsx @@ -1,7 +1,7 @@ import { Transition } from "@headlessui/react"; +import { CheckCircle2 } from "lucide-react"; import { useEffect, useState } from "react"; import { SuccessAlertType } from "../../types/alerts"; -import { CheckCircle2 } from "lucide-react"; export default function SuccessAlert({ title, @@ -38,15 +38,10 @@ export default function SuccessAlert({ >
    -
    -

    - {title} -

    +

    {title}

diff --git a/src/frontend/src/assets/male-technologist.png b/src/frontend/src/assets/male-technologist.png new file mode 100644 index 000000000..3b5281237 Binary files /dev/null and b/src/frontend/src/assets/male-technologist.png differ diff --git a/src/frontend/src/assets/robot.png b/src/frontend/src/assets/robot.png new file mode 100644 index 000000000..81de3118d Binary files /dev/null and b/src/frontend/src/assets/robot.png differ diff --git a/src/frontend/src/components/AccordionComponent/index.tsx b/src/frontend/src/components/AccordionComponent/index.tsx index 8990da245..3b0ddd596 100644 --- a/src/frontend/src/components/AccordionComponent/index.tsx +++ b/src/frontend/src/components/AccordionComponent/index.tsx @@ -1,16 +1,11 @@ -import { ReactElement, useContext, useEffect, useRef, useState } from "react"; -import { - AccordionComponentType, - ProgressBarType, -} from "../../types/components"; -import { Progress } from "../../components/ui/progress"; -import { setInterval } from "timers/promises"; +import { useState } from "react"; import { Accordion, AccordionContent, AccordionItem, AccordionTrigger, } from "../../components/ui/accordion"; +import { AccordionComponentType } from "../../types/components"; export default function AccordionComponent({ trigger, @@ -18,7 +13,7 @@ export default function AccordionComponent({ open = [], }: AccordionComponentType) { const [value, setValue] = useState( - open.length == 0 ? "" : getOpenAccordion(), + open.length === 0 ? "" : getOpenAccordion() ); function getOpenAccordion() { diff --git a/src/frontend/src/components/EditFlowSettingsComponent/index.tsx b/src/frontend/src/components/EditFlowSettingsComponent/index.tsx index 4c1d18b75..a0beb11f3 100644 --- a/src/frontend/src/components/EditFlowSettingsComponent/index.tsx +++ b/src/frontend/src/components/EditFlowSettingsComponent/index.tsx @@ -1,7 +1,7 @@ -import React, { useState, ChangeEvent } from "react"; -import { Textarea } from "../../components/ui/textarea"; -import { Label } from "../../components/ui/label"; +import React, { ChangeEvent, useState } from "react"; import { Input } from "../../components/ui/input"; +import { Label } from "../../components/ui/label"; +import { Textarea } from "../../components/ui/textarea"; type InputProps = { name: string | null; @@ -47,9 +47,7 @@ export const EditFlowSettings: React.FC = ({
Name{" "} {isMaxLength && ( - - Character limit reached - + Character limit reached )}