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remove dead code and unused dependencies (#1488)

Browse source 
* added esLint to frontend project

* Remove formModalPropsType from index.ts

* Remove chat input component

* Delete codeBlock and fileComponent components

* Remove unused code for BuildTrigger component

* Refactor Chat component and remove unused code

* Delete chatTrigger component

* Delete unused SVG and PNG files

* Remove LightTooltipComponent

* Remove LoadingSpinner component

* Delete RadialProgressComponent

* Delete ReactTooltipComponent

* Remove TooltipComponent

* Delete ElementStack component

* Remove ToggleComponent

* Remove unused dependencies from package.json

* Update package json

* add accordion

* change accordion sidebar to shadcn

* added million lint

* Remove MillionCompiler plugin from Vite config

* Refactor authContext autoLogin dependency

* Add console.log statements for debugging

* Refactored position of elements in IO branch

* fix assets imports

* fix re-render on pageComponent

* Add StrictMode to root render and update key in ExtraSidebarComponent

* Add showCanvas state and useEffect to update it to improve performance

* Refactor FlowPage component and remove ExtraSidebar from main area

* Refactor FlowToolbar to prevent Unnecessary re-render

* get node position with zustand in NodeToolbarComponent

* Fix ShareModal rendering issue

* Remove ExtraSidebar component and fix CodeAreaComponent bug

* Refactor: Use useMemo to avoid unnecessary render

* merge zustandIo

* Remove console.log statements

* Update package-lock.json and refactor extraSidebarComponent

* update package json

* Remove unused msgpack wheel file and add new nvidia_nvjitlink_cu12 wheel file

* Fix import formatting in loading.py

* Imported missing module and removed unused import

---------

Co-authored-by: cristhianzl <cristhian.lousa@gmail.com>
Co-authored-by: Lucas Oliveira <lucas.edu.oli@hotmail.com>
Co-authored-by: igorrCarvalho <igorsilvabhz6@gmail.com>
Co-authored-by: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
This commit is contained in:
anovazzi1 2024-03-30 17:09:51 -03:00 • committed by GitHub
commit e61896bc1f
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71 changed files with 3496 additions and 3399 deletions
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4
src/backend/base/langflow/components/data/File.py
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@ -13,8 +13,8 @@ class FileComponent(CustomComponent):
def build_config(self) -> Dict[str, Any]:
return {
"path": {
"display_name": "Path",
"paths": {
"display_name": "Paths",
"field_type": "file",
"file_types": TEXT_FILE_TYPES,
"info": f"Supported file types: {', '.join(TEXT_FILE_TYPES)}",

0
src/backend/base/langflow/components/helpers/SearchApi.py Normal file
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30
src/backend/base/langflow/components/inputs/JSONInput.py Normal file
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@ -0,0 +1,30 @@
import ast
import json
from langflow import CustomComponent
from langflow.schema import Record
class JSONInputComponent(CustomComponent):
display_name = "JSON Input"
description = "Load a JSON object as input."
def build_config(self):
return {
"json_str": {
"display_name": "JSON String",
"multiline": True,
"info": "The JSON string to load.",
}
}
def build(self, json_str: str) -> Record:
try:
data = json.loads(json_str)
except json.JSONDecodeError:
try:
data = ast.literal_eval(json_str)
except (SyntaxError, ValueError):
raise ValueError("Invalid JSON string.")
record = Record(data=data)
return record

1
src/backend/base/langflow/graph/vertex/types.py
View file

@ -1,7 +1,6 @@
import ast
import json
from typing import AsyncIterator, Callable, Dict, Iterator, List, Optional, Union
import yaml
from langchain_core.messages import AIMessage
from loguru import logger

22
src/backend/base/langflow/helpers/flow.py
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@ -1,4 +1,4 @@
from typing import TYPE_CHECKING, Any, Awaitable, Callable, List, Optional, Tuple, Type, Union, cast
from typing import TYPE_CHECKING, Any, Callable, Coroutine, List, Optional, Tuple, Union
from pydantic.v1 import BaseModel, Field, create_model
from sqlmodel import select
@ -63,30 +63,28 @@ def find_flow(flow_name: str, user_id: str) -> Optional[str]:
async def run_flow(
inputs: Optional[Union[dict, List[dict]]] = None,
inputs: Union[dict, List[dict]] = None,
tweaks: Optional[dict] = None,
flow_id: Optional[str] = None,
flow_name: Optional[str] = None,
user_id: Optional[str] = None,
) -> Any:
if not user_id:
raise ValueError("Session is invalid")
graph = await load_flow(user_id, flow_id, flow_name, tweaks)
if inputs is None:
inputs = []
inputs_list: list[dict[str, str]] = []
inputs_list = []
inputs_components = []
types = []
for input_dict in inputs:
inputs_list.append({INPUT_FIELD_NAME: cast(str, input_dict.get("input_value", ""))})
inputs_list.append({INPUT_FIELD_NAME: input_dict.get("input_value")})
inputs_components.append(input_dict.get("components", []))
types.append(input_dict.get("type", []))
return await graph.arun(inputs_list, inputs_components=inputs_components, types=types)
def generate_function_for_flow(inputs: List["Vertex"], flow_id: str) -> Callable[..., Awaitable[Any]]:
def generate_function_for_flow(inputs: List["Vertex"], flow_id: str) -> Coroutine:
"""
Generate a dynamic flow function based on the given inputs and flow ID.
@ -140,14 +138,12 @@ async def flow_function({func_args}):
"""
compiled_func = compile(func_body, "<string>", "exec")
local_scope: dict = {}
local_scope = {}
exec(compiled_func, globals(), local_scope)
return local_scope["flow_function"]
def build_function_and_schema(
flow_record: Record, graph: "Graph"
) -> Tuple[Callable[..., Awaitable[Any]], Type[BaseModel]]:
def build_function_and_schema(flow_record: Record, graph: "Graph") -> Tuple[Callable, BaseModel]:
"""
Builds a dynamic function and schema for a given flow.
@ -182,7 +178,7 @@ def get_flow_inputs(graph: "Graph") -> List["Vertex"]:
return inputs
def build_schema_from_inputs(name: str, inputs: List["Vertex"]) -> Type[BaseModel]:
def build_schema_from_inputs(name: str, inputs: List[tuple[str, str, str]]) -> BaseModel:
"""
Builds a schema from the given inputs.
@ -200,4 +196,4 @@ def build_schema_from_inputs(name: str, inputs: List["Vertex"]) -> Type[BaseMode
field_name = input_.display_name.lower().replace(" ", "_")
description = input_.description
fields[field_name] = (str, Field(default="", description=description))
return create_model(name, **fields) # type: ignore
return create_model(name, **fields)

4
src/backend/base/langflow/initial_setup/starter_projects/Langflow Basic Prompting.json
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@ -193,7 +193,7 @@
"list": false,
"show": true,
"multiline": true,
"value": "from langchain_core.prompts import PromptTemplate\n\nfrom langflow.custom import CustomComponent\nfrom langflow.field_typing import Prompt, TemplateField, Text\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"A component for creating prompts using templates\"\n icon = \"terminal-square\"\n\n def build_config(self):\n return {\n \"template\": TemplateField(display_name=\"Template\"),\n \"code\": TemplateField(advanced=True),\n }\n\n def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Text:\n from langflow.base.prompts.utils import dict_values_to_string\n\n prompt_template = PromptTemplate.from_template(Text(template))\n kwargs = dict_values_to_string(kwargs)\n kwargs = {k: \"\\n\".join(v) if isinstance(v, list) else v for k, v in kwargs.items()}\n try:\n formated_prompt = prompt_template.format(**kwargs)\n except Exception as exc:\n raise ValueError(f\"Error formatting prompt: {exc}\") from exc\n self.status = f'Prompt:\\n\"{formated_prompt}\"'\n return formated_prompt\n",
"value": "from langchain_core.prompts import PromptTemplate\n\nfrom langflow import CustomComponent\nfrom langflow.field_typing import Prompt, TemplateField, Text\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"A component for creating prompts using templates\"\n icon = \"terminal-square\"\n\n def build_config(self):\n return {\n \"template\": TemplateField(display_name=\"Template\"),\n \"code\": TemplateField(advanced=True),\n }\n\n def build(\n self,\n template: Prompt,\n **kwargs,\n ) -> Text:\n from langflow.base.prompts.utils import dict_values_to_string\n\n prompt_template = PromptTemplate.from_template(Text(template))\n kwargs = dict_values_to_string(kwargs)\n kwargs = {k: \"\\n\".join(v) if isinstance(v, list) else v for k, v in kwargs.items()}\n try:\n formated_prompt = prompt_template.format(**kwargs)\n except Exception as exc:\n raise ValueError(f\"Error formatting prompt: {exc}\") from exc\n self.status = f'Prompt:\\n\"{formated_prompt}\"'\n return formated_prompt\n",
"fileTypes": [],
"file_path": "",
"password": false,
@ -797,7 +797,7 @@
"list": false,
"show": true,
"multiline": true,
"value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.models.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI's models.\"\n icon = \"OpenAI\"\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": False,\n \"required\": False,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n \"required\": False,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"required\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": False,\n \"required\": False,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"openai_api_key\": {\n \"display_name\": \"OpenAI API Key\",\n \"advanced\": False,\n \"required\": False,\n \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"required\": False,\n \"value\": 0.7,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": \"Stream the response from the model.\",\n },\n }\n\n def build(\n self,\n input_value: Text,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n model_name: str = \"gpt-4-1106-preview\",\n openai_api_base: Optional[str] = None,\n openai_api_key: Optional[str] = None,\n temperature: float = 0.7,\n stream: bool = False,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=openai_api_key,\n temperature=temperature,\n )\n\n return self.get_result(output=output, stream=stream, input_value=input_value)\n",
"value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.components.models.base.model import LCModelComponent\nfrom langflow.field_typing import NestedDict, Text\n\n\nclass OpenAIModelComponent(LCModelComponent):\n display_name = \"OpenAI\"\n description = \"Generates text using OpenAI's models.\"\n icon = \"OpenAI\"\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": False,\n \"required\": False,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n \"required\": False,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"required\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-4-0125-preview\",\n \"gpt-4-1106-preview\",\n \"gpt-4-vision-preview\",\n \"gpt-3.5-turbo-0125\",\n \"gpt-3.5-turbo-1106\",\n ],\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": False,\n \"required\": False,\n \"info\": (\n \"The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\\n\\n\"\n \"You can change this to use other APIs like JinaChat, LocalAI and Prem.\"\n ),\n },\n \"openai_api_key\": {\n \"display_name\": \"OpenAI API Key\",\n \"advanced\": False,\n \"required\": False,\n \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"required\": False,\n \"value\": 0.7,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": \"Stream the response from the model.\",\n },\n }\n\n def build(\n self,\n input_value: Text,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n model_name: str = \"gpt-4-1106-preview\",\n openai_api_base: Optional[str] = None,\n openai_api_key: Optional[str] = None,\n temperature: float = 0.7,\n stream: bool = False,\n ) -> Text:\n if not openai_api_base:\n openai_api_base = \"https://api.openai.com/v1\"\n output = ChatOpenAI(\n max_tokens=max_tokens,\n model_kwargs=model_kwargs,\n model=model_name,\n base_url=openai_api_base,\n api_key=openai_api_key,\n temperature=temperature,\n )\n\n return self.get_result(output=output, stream=stream, input_value=input_value)\n",
"fileTypes": [],
"file_path": "",
"password": false,

1
src/backend/base/langflow/interface/initialize/loading.py
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@ -2,6 +2,7 @@ import inspect
import json
from typing import TYPE_CHECKING, Any, Callable, Dict, Sequence, Type
import orjson
from langchain.agents import agent as agent_module
from langchain.agents.agent import AgentExecutor