Merge branch 'zustand/io/migration' into cz/new-tests
This commit is contained in:
cristhianzl
commit
06fcb61d0f
82 changed files with 5936 additions and 2270 deletions
|
|
@ -246,9 +246,17 @@ def get_free_port(port):
|
|||
|
||||
|
||||
def print_banner(host, port):
|
||||
from langflow.version import __version__
|
||||
try:
|
||||
from langflow.version import __version__
|
||||
|
||||
version = __version__
|
||||
word = "Langflow"
|
||||
except ImportError:
|
||||
from importlib import metadata
|
||||
|
||||
version = metadata.version("langflow-base")
|
||||
word = "Langflow Base"
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||||
|
||||
word = "Langflow"
|
||||
colors = ["#6e42f5"]
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||||
|
||||
styled_word = ""
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||||
|
|
@ -259,7 +267,7 @@ def print_banner(host, port):
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|||
|
||||
# Title with emojis and gradient text
|
||||
title = (
|
||||
f"[bold]Welcome to :chains: {styled_word} v{__version__}[/bold]\n"
|
||||
f"[bold]Welcome to :chains: {styled_word} v{version}[/bold]\n"
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||||
f"Access [link=http://{host}:{port}]http://{host}:{port}[/link]"
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||||
)
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info_text = (
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||||
|
|
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|||
|
|
@ -372,9 +372,17 @@ async def create_upload_file(
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|||
# get endpoint to return version of langflow
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||||
@router.get("/version")
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||||
def get_version():
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||||
from langflow.version import __version__ # type: ignore
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||||
try:
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||||
from langflow.version import __version__
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||||
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||||
return {"version": __version__}
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||||
version = __version__
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package = "Langflow"
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||||
except ImportError:
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from importlib import metadata
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|
||||
version = metadata.version("langflow-base")
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||||
package = "Langflow Base"
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||||
return {"version": version, "package": package}
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||||
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||||
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@router.post("/custom_component", status_code=HTTPStatus.OK)
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||||
|
|
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|||
|
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@ -94,10 +94,10 @@ class OpenAIEmbeddingsComponent(CustomComponent):
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disallowed_special: List[str] = ["all"],
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chunk_size: int = 1000,
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client: Optional[Any] = None,
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deployment: str = "text-embedding-3-small",
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deployment: str = "text-embedding-ada-002",
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embedding_ctx_length: int = 8191,
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max_retries: int = 6,
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model: str = "text-embedding-3-small",
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model: str = "text-embedding-ada-002",
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model_kwargs: NestedDict = {},
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openai_api_base: Optional[str] = None,
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||||
openai_api_type: Optional[str] = None,
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||||
|
|
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|||
|
|
@ -1,14 +1,11 @@
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from typing import Optional
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from langchain.text_splitter import (
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RecursiveCharacterTextSplitter,
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CharacterTextSplitter,
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||||
)
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from langchain.text_splitter import CharacterTextSplitter, RecursiveCharacterTextSplitter
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from langchain_core.documents import Document
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from langflow.field_typing import Text
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from langflow.interface.custom.custom_component import CustomComponent
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from langflow.schema import Record
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from langflow.field_typing import Text
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from langflow.utils.util import unescape_string
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|
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|
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@ -18,10 +15,10 @@ class SplitTextComponent(CustomComponent):
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def build_config(self):
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return {
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"texts": {
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"display_name": "Texts",
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"inputs": {
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"display_name": "Inputs",
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"info": "Texts to split.",
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"input_types": ["Text"],
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"input_types": ["Record", "Text"],
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},
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"separators": {
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"display_name": "Separators",
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|
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@ -48,7 +45,7 @@ class SplitTextComponent(CustomComponent):
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|
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def build(
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self,
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texts: list[Text],
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inputs: list[Text],
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separators: Optional[list[str]] = [" "],
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chunk_size: Optional[int] = 1000,
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chunk_overlap: Optional[int] = 200,
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|
|
@ -77,9 +74,11 @@ class SplitTextComponent(CustomComponent):
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)
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|
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documents = []
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for _text in texts:
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# documents.append(_input.to_lc_document())
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documents.append(Document(page_content=_text))
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||||
for _input in inputs:
|
||||
if isinstance(_input, Record):
|
||||
documents.append(_input.to_lc_document())
|
||||
else:
|
||||
documents.append(Document(page_content=_input))
|
||||
|
||||
records = self.to_records(splitter.split_documents(documents))
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self.status = records
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|
|
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|
|
@ -118,7 +118,7 @@ class ChatLiteLLMComponent(CustomComponent):
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max_tokens: int = 256,
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max_retries: int = 6,
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verbose: bool = False,
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||||
) -> Union[BaseLanguageModel, Callable]:
|
||||
) -> BaseLanguageModel:
|
||||
try:
|
||||
import litellm # type: ignore
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||||
|
||||
|
|
|
|||
191
src/backend/base/langflow/components/models/ChatLiteLLMModel.py
Normal file
191
src/backend/base/langflow/components/models/ChatLiteLLMModel.py
Normal file
|
|
@ -0,0 +1,191 @@
|
|||
from typing import Any, Dict, Optional
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||||
|
||||
from langchain_community.chat_models.litellm import ChatLiteLLM, ChatLiteLLMException
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||||
|
||||
from langflow.base.constants import STREAM_INFO_TEXT
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from langflow.base.models.model import LCModelComponent
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||||
from langflow.field_typing import BaseLanguageModel, Text
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||||
|
||||
|
||||
class ChatLiteLLMModelComponent(LCModelComponent):
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display_name = "LiteLLM"
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description = "`LiteLLM` collection of large language models."
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documentation = "https://python.langchain.com/docs/integrations/chat/litellm"
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field_order = [
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"model",
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"api_key",
|
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"provider",
|
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"temperature",
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||||
"model_kwargs",
|
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"top_p",
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"top_k",
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||||
"n",
|
||||
"max_tokens",
|
||||
"max_retries",
|
||||
"verbose",
|
||||
"stream",
|
||||
"input_value",
|
||||
"system_message",
|
||||
]
|
||||
|
||||
def build_config(self):
|
||||
return {
|
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"model": {
|
||||
"display_name": "Model name",
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"field_type": "str",
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||||
"advanced": False,
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||||
"required": True,
|
||||
"info": "The name of the model to use. For example, `gpt-3.5-turbo`.",
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},
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"api_key": {
|
||||
"display_name": "API key",
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||||
"field_type": "str",
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||||
"advanced": False,
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||||
"required": False,
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||||
"password": True,
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||||
},
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"provider": {
|
||||
"display_name": "Provider",
|
||||
"info": "The provider of the API key.",
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"options": [
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"OpenAI",
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||||
"Azure",
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"Anthropic",
|
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"Replicate",
|
||||
"Cohere",
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||||
"OpenRouter",
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||||
],
|
||||
},
|
||||
"temperature": {
|
||||
"display_name": "Temperature",
|
||||
"field_type": "float",
|
||||
"advanced": False,
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||||
"required": False,
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||||
"default": 0.7,
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||||
},
|
||||
"model_kwargs": {
|
||||
"display_name": "Model kwargs",
|
||||
"field_type": "dict",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
"default": {},
|
||||
},
|
||||
"top_p": {
|
||||
"display_name": "Top p",
|
||||
"field_type": "float",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
},
|
||||
"top_k": {
|
||||
"display_name": "Top k",
|
||||
"field_type": "int",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
},
|
||||
"n": {
|
||||
"display_name": "N",
|
||||
"field_type": "int",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
"info": "Number of chat completions to generate for each prompt. "
|
||||
"Note that the API may not return the full n completions if duplicates are generated.",
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||||
"default": 1,
|
||||
},
|
||||
"max_tokens": {
|
||||
"display_name": "Max tokens",
|
||||
"field_type": "int",
|
||||
"advanced": False,
|
||||
"required": False,
|
||||
"default": 256,
|
||||
"info": "The maximum number of tokens to generate for each chat completion.",
|
||||
},
|
||||
"max_retries": {
|
||||
"display_name": "Max retries",
|
||||
"field_type": "int",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
"default": 6,
|
||||
},
|
||||
"verbose": {
|
||||
"display_name": "Verbose",
|
||||
"field_type": "bool",
|
||||
"advanced": True,
|
||||
"required": False,
|
||||
"default": False,
|
||||
},
|
||||
"input_value": {"display_name": "Input"},
|
||||
"stream": {
|
||||
"display_name": "Stream",
|
||||
"info": STREAM_INFO_TEXT,
|
||||
"advanced": True,
|
||||
},
|
||||
"system_message": {
|
||||
"display_name": "System Message",
|
||||
"info": "System message to pass to the model.",
|
||||
"advanced": True,
|
||||
},
|
||||
}
|
||||
|
||||
def build(
|
||||
self,
|
||||
input_value: Text,
|
||||
model: str,
|
||||
provider: str,
|
||||
api_key: Optional[str] = None,
|
||||
stream: bool = False,
|
||||
temperature: Optional[float] = 0.7,
|
||||
model_kwargs: Optional[Dict[str, Any]] = {},
|
||||
top_p: Optional[float] = None,
|
||||
top_k: Optional[int] = None,
|
||||
n: int = 1,
|
||||
max_tokens: int = 256,
|
||||
max_retries: int = 6,
|
||||
verbose: bool = False,
|
||||
system_message: Optional[str] = None,
|
||||
) -> BaseLanguageModel:
|
||||
try:
|
||||
import litellm # type: ignore
|
||||
|
||||
litellm.drop_params = True
|
||||
litellm.set_verbose = verbose
|
||||
except ImportError:
|
||||
raise ChatLiteLLMException(
|
||||
"Could not import litellm python package. " "Please install it with `pip install litellm`"
|
||||
)
|
||||
provider_map = {
|
||||
"OpenAI": "openai_api_key",
|
||||
"Azure": "azure_api_key",
|
||||
"Anthropic": "anthropic_api_key",
|
||||
"Replicate": "replicate_api_key",
|
||||
"Cohere": "cohere_api_key",
|
||||
"OpenRouter": "openrouter_api_key",
|
||||
}
|
||||
# Set the API key based on the provider
|
||||
api_keys: dict[str, Optional[str]] = {v: None for v in provider_map.values()}
|
||||
|
||||
if variable_name := provider_map.get(provider):
|
||||
api_keys[variable_name] = api_key
|
||||
else:
|
||||
raise ChatLiteLLMException(
|
||||
f"Provider {provider} is not supported. Supported providers are: {', '.join(provider_map.keys())}"
|
||||
)
|
||||
|
||||
output = ChatLiteLLM(
|
||||
model=model,
|
||||
client=None,
|
||||
streaming=stream,
|
||||
temperature=temperature,
|
||||
model_kwargs=model_kwargs if model_kwargs is not None else {},
|
||||
top_p=top_p,
|
||||
top_k=top_k,
|
||||
n=n,
|
||||
max_tokens=max_tokens,
|
||||
max_retries=max_retries,
|
||||
openai_api_key=api_keys["openai_api_key"],
|
||||
azure_api_key=api_keys["azure_api_key"],
|
||||
anthropic_api_key=api_keys["anthropic_api_key"],
|
||||
replicate_api_key=api_keys["replicate_api_key"],
|
||||
cohere_api_key=api_keys["cohere_api_key"],
|
||||
openrouter_api_key=api_keys["openrouter_api_key"],
|
||||
)
|
||||
return self.get_chat_result(output, stream, input_value, system_message)
|
||||
|
|
@ -2,6 +2,7 @@ from .AmazonBedrockModel import AmazonBedrockComponent
|
|||
from .AnthropicModel import AnthropicLLM
|
||||
from .AzureOpenAIModel import AzureChatOpenAIComponent
|
||||
from .BaiduQianfanChatModel import QianfanChatEndpointComponent
|
||||
from .ChatLiteLLMModel import ChatLiteLLMModelComponent
|
||||
from .CohereModel import CohereComponent
|
||||
from .GoogleGenerativeAIModel import GoogleGenerativeAIComponent
|
||||
from .HuggingFaceModel import HuggingFaceEndpointsComponent
|
||||
|
|
@ -10,6 +11,7 @@ from .OpenAIModel import OpenAIModelComponent
|
|||
from .VertexAiModel import ChatVertexAIComponent
|
||||
|
||||
__all__ = [
|
||||
"ChatLiteLLMModelComponent",
|
||||
"AmazonBedrockComponent",
|
||||
"AnthropicLLM",
|
||||
"AzureChatOpenAIComponent",
|
||||
|
|
|
|||
|
|
@ -7,8 +7,8 @@ from langflow.schema import Record
|
|||
|
||||
|
||||
class AstraDBSearchComponent(LCVectorStoreComponent):
|
||||
display_name = "AstraDB Search"
|
||||
description = "Searches an existing AstraDB Vector Store."
|
||||
display_name = "Astra DB Search"
|
||||
description = "Searches an existing Astra DB Vector Store."
|
||||
icon = "AstraDB"
|
||||
field_order = ["token", "api_endpoint", "collection_name", "input_value", "embedding"]
|
||||
|
||||
|
|
@ -25,20 +25,20 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
|
|||
"embedding": {"display_name": "Embedding", "info": "Embedding to use"},
|
||||
"collection_name": {
|
||||
"display_name": "Collection Name",
|
||||
"info": "The name of the collection within AstraDB where the vectors will be stored.",
|
||||
"info": "The name of the collection within Astra DB where the vectors will be stored.",
|
||||
},
|
||||
"token": {
|
||||
"display_name": "Token",
|
||||
"info": "Authentication token for accessing AstraDB.",
|
||||
"info": "Authentication token for accessing Astra DB.",
|
||||
"password": True,
|
||||
},
|
||||
"api_endpoint": {
|
||||
"display_name": "API Endpoint",
|
||||
"info": "API endpoint URL for the AstraDB service.",
|
||||
"info": "API endpoint URL for the Astra DB service.",
|
||||
},
|
||||
"namespace": {
|
||||
"display_name": "Namespace",
|
||||
"info": "Optional namespace within AstraDB to use for the collection.",
|
||||
"info": "Optional namespace within Astra DB to use for the collection.",
|
||||
"advanced": True,
|
||||
},
|
||||
"metric": {
|
||||
|
|
|
|||
|
|
@ -9,8 +9,8 @@ from langflow.schema import Record
|
|||
|
||||
|
||||
class AstraDBVectorStoreComponent(CustomComponent):
|
||||
display_name = "AstraDB"
|
||||
description = "Builds or loads an AstraDB Vector Store."
|
||||
display_name = "Astra DB"
|
||||
description = "Builds or loads an Astra DB Vector Store."
|
||||
icon = "AstraDB"
|
||||
field_order = ["token", "api_endpoint", "collection_name", "inputs", "embedding"]
|
||||
|
||||
|
|
@ -23,20 +23,20 @@ class AstraDBVectorStoreComponent(CustomComponent):
|
|||
"embedding": {"display_name": "Embedding", "info": "Embedding to use"},
|
||||
"collection_name": {
|
||||
"display_name": "Collection Name",
|
||||
"info": "The name of the collection within AstraDB where the vectors will be stored.",
|
||||
"info": "The name of the collection within Astra DB where the vectors will be stored.",
|
||||
},
|
||||
"token": {
|
||||
"display_name": "Token",
|
||||
"info": "Authentication token for accessing AstraDB.",
|
||||
"info": "Authentication token for accessing Astra DB.",
|
||||
"password": True,
|
||||
},
|
||||
"api_endpoint": {
|
||||
"display_name": "API Endpoint",
|
||||
"info": "API endpoint URL for the AstraDB service.",
|
||||
"info": "API endpoint URL for the Astra DB service.",
|
||||
},
|
||||
"namespace": {
|
||||
"display_name": "Namespace",
|
||||
"info": "Optional namespace within AstraDB to use for the collection.",
|
||||
"info": "Optional namespace within Astra DB to use for the collection.",
|
||||
"advanced": True,
|
||||
},
|
||||
"metric": {
|
||||
|
|
|
|||
|
|
@ -88,7 +88,7 @@ def load_starter_projects():
|
|||
starter_projects = []
|
||||
folder = Path(__file__).parent / "starter_projects"
|
||||
for file in folder.glob("*.json"):
|
||||
project = orjson.loads(file.read_text())
|
||||
project = orjson.loads(file.read_text(encoding="utf-8"))
|
||||
starter_projects.append((file, project))
|
||||
logger.info(f"Loaded starter project {file}")
|
||||
return starter_projects
|
||||
|
|
@ -124,7 +124,7 @@ def get_project_data(project):
|
|||
|
||||
def update_project_file(project_path, project, updated_project_data):
|
||||
project["data"] = updated_project_data
|
||||
with open(project_path, "w") as f:
|
||||
with open(project_path, "w", encoding="utf-8") as f:
|
||||
f.write(orjson.dumps(project, option=orjson.OPT_INDENT_2).decode())
|
||||
logger.info(f"Updated starter project {project['name']} file")
|
||||
|
||||
|
|
@ -197,7 +197,11 @@ def delete_start_projects(session):
|
|||
|
||||
def create_or_update_starter_projects():
|
||||
components_paths = get_settings_service().settings.COMPONENTS_PATH
|
||||
all_types_dict = get_all_components(components_paths, as_dict=True)
|
||||
try:
|
||||
all_types_dict = get_all_components(components_paths, as_dict=True)
|
||||
except Exception as e:
|
||||
logger.exception(f"Error loading components: {e}")
|
||||
raise e
|
||||
with session_scope() as session:
|
||||
starter_projects = load_starter_projects()
|
||||
delete_start_projects(session)
|
||||
|
|
|
|||
|
|
@ -0,0 +1,888 @@
|
|||
{
|
||||
"id": "c091a57f-43a7-4a5e-b352-035ae8d8379c",
|
||||
"data": {
|
||||
"nodes": [
|
||||
{
|
||||
"id": "Prompt-uxBqP",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": 53.588791333410654,
|
||||
"y": -107.07318910019967
|
||||
},
|
||||
"data": {
|
||||
"type": "Prompt",
|
||||
"node": {
|
||||
"template": {
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from langchain_core.prompts import PromptTemplate\n\nfrom langflow.field_typing import Prompt, TemplateField, Text\nfrom langflow.interface.custom.custom_component import CustomComponent\n\n\nclass PromptComponent(CustomComponent):\n display_name: str = \"Prompt\"\n description: str = \"Create a prompt template with dynamic variables.\"\n icon = \"prompts\"\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,
|
||||
"name": "code",
|
||||
"advanced": true,
|
||||
"dynamic": true,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"template": {
|
||||
"type": "prompt",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: ",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "template",
|
||||
"display_name": "Template",
|
||||
"advanced": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"_type": "CustomComponent",
|
||||
"user_input": {
|
||||
"field_type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "user_input",
|
||||
"display_name": "user_input",
|
||||
"advanced": false,
|
||||
"input_types": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"type": "str"
|
||||
}
|
||||
},
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"icon": "prompts",
|
||||
"is_input": null,
|
||||
"is_output": null,
|
||||
"is_composition": null,
|
||||
"base_classes": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"name": "",
|
||||
"display_name": "Prompt",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"template": [
|
||||
"user_input"
|
||||
]
|
||||
},
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"full_path": null,
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
"beta": false,
|
||||
"error": null
|
||||
},
|
||||
"id": "Prompt-uxBqP",
|
||||
"description": "Create a prompt template with dynamic variables.",
|
||||
"display_name": "Prompt"
|
||||
},
|
||||
"selected": true,
|
||||
"width": 384,
|
||||
"height": 383,
|
||||
"dragging": false,
|
||||
"positionAbsolute": {
|
||||
"x": 53.588791333410654,
|
||||
"y": -107.07318910019967
|
||||
}
|
||||
},
|
||||
{
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": 634.8148772766217,
|
||||
"y": 27.035057029045305
|
||||
},
|
||||
"data": {
|
||||
"type": "OpenAIModel",
|
||||
"node": {
|
||||
"template": {
|
||||
"input_value": {
|
||||
"type": "str",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "input_value",
|
||||
"display_name": "Input",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional\n\nfrom langchain_openai import ChatOpenAI\n\nfrom langflow.base.constants import STREAM_INFO_TEXT\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 LLMs.\"\n icon = \"OpenAI\"\n\n field_order = [\n \"max_tokens\",\n \"model_kwargs\",\n \"model_name\",\n \"openai_api_base\",\n \"openai_api_key\",\n \"temperature\",\n \"input_value\",\n \"system_message\",\n \"stream\",\n ]\n\n def build_config(self):\n return {\n \"input_value\": {\"display_name\": \"Input\"},\n \"max_tokens\": {\n \"display_name\": \"Max Tokens\",\n \"advanced\": True,\n },\n \"model_kwargs\": {\n \"display_name\": \"Model Kwargs\",\n \"advanced\": True,\n },\n \"model_name\": {\n \"display_name\": \"Model Name\",\n \"advanced\": False,\n \"options\": [\n \"gpt-4-turbo-preview\",\n \"gpt-3.5-turbo\",\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 \"value\": \"gpt-4-turbo-preview\",\n },\n \"openai_api_base\": {\n \"display_name\": \"OpenAI API Base\",\n \"advanced\": True,\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 \"info\": \"The OpenAI API Key to use for the OpenAI model.\",\n \"advanced\": False,\n \"password\": True,\n },\n \"temperature\": {\n \"display_name\": \"Temperature\",\n \"advanced\": False,\n \"value\": 0.1,\n },\n \"stream\": {\n \"display_name\": \"Stream\",\n \"info\": STREAM_INFO_TEXT,\n \"advanced\": True,\n },\n \"system_message\": {\n \"display_name\": \"System Message\",\n \"info\": \"System message to pass to the model.\",\n \"advanced\": True,\n },\n }\n\n def build(\n self,\n input_value: Text,\n openai_api_key: str,\n temperature: float,\n model_name: str,\n max_tokens: Optional[int] = 256,\n model_kwargs: NestedDict = {},\n openai_api_base: Optional[str] = None,\n stream: bool = False,\n system_message: Optional[str] = None,\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_chat_result(output, stream, input_value, system_message)\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "code",
|
||||
"advanced": true,
|
||||
"dynamic": true,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"max_tokens": {
|
||||
"type": "int",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": 256,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "max_tokens",
|
||||
"display_name": "Max Tokens",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"model_kwargs": {
|
||||
"type": "NestedDict",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": {},
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "model_kwargs",
|
||||
"display_name": "Model Kwargs",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"model_name": {
|
||||
"type": "str",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "gpt-3.5-turbo",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": [
|
||||
"gpt-4-turbo-preview",
|
||||
"gpt-3.5-turbo",
|
||||
"gpt-4-0125-preview",
|
||||
"gpt-4-1106-preview",
|
||||
"gpt-4-vision-preview",
|
||||
"gpt-3.5-turbo-0125",
|
||||
"gpt-3.5-turbo-1106"
|
||||
],
|
||||
"name": "model_name",
|
||||
"display_name": "Model Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"openai_api_base": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "openai_api_base",
|
||||
"display_name": "OpenAI API Base",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "The base URL of the OpenAI API. Defaults to https://api.openai.com/v1.\n\nYou can change this to use other APIs like JinaChat, LocalAI and Prem.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"openai_api_key": {
|
||||
"type": "str",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": true,
|
||||
"name": "openai_api_key",
|
||||
"display_name": "OpenAI API Key",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "The OpenAI API Key to use for the OpenAI model.",
|
||||
"load_from_db": true,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"value": ""
|
||||
},
|
||||
"stream": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": true,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "stream",
|
||||
"display_name": "Stream",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Stream the response from the model. Streaming works only in Chat.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"system_message": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "system_message",
|
||||
"display_name": "System Message",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "System message to pass to the model.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"temperature": {
|
||||
"type": "float",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": 0.1,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "temperature",
|
||||
"display_name": "Temperature",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"rangeSpec": {
|
||||
"step_type": "float",
|
||||
"min": -1,
|
||||
"max": 1,
|
||||
"step": 0.1
|
||||
},
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Generates text using OpenAI LLMs.",
|
||||
"icon": "OpenAI",
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"display_name": "OpenAI",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"input_value": null,
|
||||
"openai_api_key": null,
|
||||
"temperature": null,
|
||||
"model_name": null,
|
||||
"max_tokens": null,
|
||||
"model_kwargs": null,
|
||||
"openai_api_base": null,
|
||||
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|
||||
"system_message": null
|
||||
},
|
||||
"output_types": [
|
||||
"Text"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [
|
||||
"max_tokens",
|
||||
"model_kwargs",
|
||||
"model_name",
|
||||
"openai_api_base",
|
||||
"openai_api_key",
|
||||
"temperature",
|
||||
"input_value",
|
||||
"system_message",
|
||||
"stream"
|
||||
],
|
||||
"beta": false
|
||||
},
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"description": "Generates text using OpenAI LLMs.",
|
||||
"display_name": "OpenAI"
|
||||
},
|
||||
"selected": false,
|
||||
"width": 384,
|
||||
"height": 563,
|
||||
"positionAbsolute": {
|
||||
"x": 634.8148772766217,
|
||||
"y": 27.035057029045305
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"id": "ChatOutput-njtka",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": 1193.250417197867,
|
||||
"y": 71.88476890163852
|
||||
},
|
||||
"data": {
|
||||
"type": "ChatOutput",
|
||||
"node": {
|
||||
"template": {
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n display_name = \"Chat Output\"\n description = \"Display a chat message in the Interaction Panel.\"\n icon = \"ChatOutput\"\n\n def build(\n self,\n sender: Optional[str] = \"Machine\",\n sender_name: Optional[str] = \"AI\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n record_template: Optional[str] = \"{text}\",\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n record_template=record_template,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "code",
|
||||
"advanced": true,
|
||||
"dynamic": true,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"input_value": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "input_value",
|
||||
"display_name": "Message",
|
||||
"advanced": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"record_template": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "{text}",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "record_template",
|
||||
"display_name": "Record Template",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "In case of Message being a Record, this template will be used to convert it to text.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"return_record": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "return_record",
|
||||
"display_name": "Return Record",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Return the message as a record containing the sender, sender_name, and session_id.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"sender": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "Machine",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"name": "sender",
|
||||
"display_name": "Sender Type",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"sender_name": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "AI",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "sender_name",
|
||||
"display_name": "Sender Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"session_id": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "session_id",
|
||||
"display_name": "Session ID",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "If provided, the message will be stored in the memory.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Display a chat message in the Interaction Panel.",
|
||||
"icon": "ChatOutput",
|
||||
"base_classes": [
|
||||
"Record",
|
||||
"Text",
|
||||
"str",
|
||||
"object"
|
||||
],
|
||||
"display_name": "Chat Output",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"sender": null,
|
||||
"sender_name": null,
|
||||
"input_value": null,
|
||||
"session_id": null,
|
||||
"return_record": null,
|
||||
"record_template": null
|
||||
},
|
||||
"output_types": [
|
||||
"Text",
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
"beta": false
|
||||
},
|
||||
"id": "ChatOutput-njtka"
|
||||
},
|
||||
"selected": false,
|
||||
"width": 384,
|
||||
"height": 383,
|
||||
"positionAbsolute": {
|
||||
"x": 1193.250417197867,
|
||||
"y": 71.88476890163852
|
||||
},
|
||||
"dragging": false
|
||||
},
|
||||
{
|
||||
"id": "ChatInput-P3fgL",
|
||||
"type": "genericNode",
|
||||
"position": {
|
||||
"x": -495.2223093083827,
|
||||
"y": -232.56998443685862
|
||||
},
|
||||
"data": {
|
||||
"type": "ChatInput",
|
||||
"node": {
|
||||
"template": {
|
||||
"code": {
|
||||
"type": "code",
|
||||
"required": true,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n display_name = \"Chat Input\"\n description = \"Get chat inputs from the Interaction Panel.\"\n icon = \"ChatInput\"\n\n def build_config(self):\n build_config = super().build_config()\n build_config[\"input_value\"] = {\n \"input_types\": [],\n \"display_name\": \"Message\",\n \"multiline\": True,\n }\n\n return build_config\n\n def build(\n self,\n sender: Optional[str] = \"User\",\n sender_name: Optional[str] = \"User\",\n input_value: Optional[str] = None,\n session_id: Optional[str] = None,\n return_record: Optional[bool] = False,\n ) -> Union[Text, Record]:\n return super().build(\n sender=sender,\n sender_name=sender_name,\n input_value=input_value,\n session_id=session_id,\n return_record=return_record,\n )\n",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "code",
|
||||
"advanced": true,
|
||||
"dynamic": true,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"input_value": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": true,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "input_value",
|
||||
"display_name": "Message",
|
||||
"advanced": false,
|
||||
"input_types": [],
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"value": "hi"
|
||||
},
|
||||
"return_record": {
|
||||
"type": "bool",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "return_record",
|
||||
"display_name": "Return Record",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "Return the message as a record containing the sender, sender_name, and session_id.",
|
||||
"load_from_db": false,
|
||||
"title_case": false
|
||||
},
|
||||
"sender": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": true,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "User",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"options": [
|
||||
"Machine",
|
||||
"User"
|
||||
],
|
||||
"name": "sender",
|
||||
"display_name": "Sender Type",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"sender_name": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"value": "User",
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "sender_name",
|
||||
"display_name": "Sender Name",
|
||||
"advanced": false,
|
||||
"dynamic": false,
|
||||
"info": "",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"session_id": {
|
||||
"type": "str",
|
||||
"required": false,
|
||||
"placeholder": "",
|
||||
"list": false,
|
||||
"show": true,
|
||||
"multiline": false,
|
||||
"fileTypes": [],
|
||||
"file_path": "",
|
||||
"password": false,
|
||||
"name": "session_id",
|
||||
"display_name": "Session ID",
|
||||
"advanced": true,
|
||||
"dynamic": false,
|
||||
"info": "If provided, the message will be stored in the memory.",
|
||||
"load_from_db": false,
|
||||
"title_case": false,
|
||||
"input_types": [
|
||||
"Text"
|
||||
]
|
||||
},
|
||||
"_type": "CustomComponent"
|
||||
},
|
||||
"description": "Get chat inputs from the Interaction Panel.",
|
||||
"icon": "ChatInput",
|
||||
"base_classes": [
|
||||
"object",
|
||||
"Record",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"display_name": "Chat Input",
|
||||
"documentation": "",
|
||||
"custom_fields": {
|
||||
"sender": null,
|
||||
"sender_name": null,
|
||||
"input_value": null,
|
||||
"session_id": null,
|
||||
"return_record": null
|
||||
},
|
||||
"output_types": [
|
||||
"Text",
|
||||
"Record"
|
||||
],
|
||||
"field_formatters": {},
|
||||
"frozen": false,
|
||||
"field_order": [],
|
||||
"beta": false
|
||||
},
|
||||
"id": "ChatInput-P3fgL"
|
||||
},
|
||||
"selected": false,
|
||||
"width": 384,
|
||||
"height": 375,
|
||||
"positionAbsolute": {
|
||||
"x": -495.2223093083827,
|
||||
"y": -232.56998443685862
|
||||
},
|
||||
"dragging": false
|
||||
}
|
||||
],
|
||||
"edges": [
|
||||
{
|
||||
"source": "OpenAIModel-k39HS",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}",
|
||||
"target": "ChatOutput-njtka",
|
||||
"targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "ChatOutput-njtka",
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Text",
|
||||
"str"
|
||||
],
|
||||
"dataType": "OpenAIModel",
|
||||
"id": "OpenAIModel-k39HS"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-OpenAIModel-k39HS{œbaseClassesœ:[œobjectœ,œTextœ,œstrœ],œdataTypeœ:œOpenAIModelœ,œidœ:œOpenAIModel-k39HSœ}-ChatOutput-njtka{œfieldNameœ:œinput_valueœ,œidœ:œChatOutput-njtkaœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
|
||||
},
|
||||
{
|
||||
"source": "Prompt-uxBqP",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}",
|
||||
"target": "OpenAIModel-k39HS",
|
||||
"targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "input_value",
|
||||
"id": "OpenAIModel-k39HS",
|
||||
"inputTypes": [
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"dataType": "Prompt",
|
||||
"id": "Prompt-uxBqP"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-Prompt-uxBqP{œbaseClassesœ:[œobjectœ,œstrœ,œTextœ],œdataTypeœ:œPromptœ,œidœ:œPrompt-uxBqPœ}-OpenAIModel-k39HS{œfieldNameœ:œinput_valueœ,œidœ:œOpenAIModel-k39HSœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
|
||||
},
|
||||
{
|
||||
"source": "ChatInput-P3fgL",
|
||||
"sourceHandle": "{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}",
|
||||
"target": "Prompt-uxBqP",
|
||||
"targetHandle": "{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}",
|
||||
"data": {
|
||||
"targetHandle": {
|
||||
"fieldName": "user_input",
|
||||
"id": "Prompt-uxBqP",
|
||||
"inputTypes": [
|
||||
"Document",
|
||||
"BaseOutputParser",
|
||||
"Record",
|
||||
"Text"
|
||||
],
|
||||
"type": "str"
|
||||
},
|
||||
"sourceHandle": {
|
||||
"baseClasses": [
|
||||
"object",
|
||||
"Record",
|
||||
"str",
|
||||
"Text"
|
||||
],
|
||||
"dataType": "ChatInput",
|
||||
"id": "ChatInput-P3fgL"
|
||||
}
|
||||
},
|
||||
"style": {
|
||||
"stroke": "#555"
|
||||
},
|
||||
"className": "stroke-gray-900 stroke-connection",
|
||||
"id": "reactflow__edge-ChatInput-P3fgL{œbaseClassesœ:[œobjectœ,œRecordœ,œstrœ,œTextœ],œdataTypeœ:œChatInputœ,œidœ:œChatInput-P3fgLœ}-Prompt-uxBqP{œfieldNameœ:œuser_inputœ,œidœ:œPrompt-uxBqPœ,œinputTypesœ:[œDocumentœ,œBaseOutputParserœ,œRecordœ,œTextœ],œtypeœ:œstrœ}"
|
||||
}
|
||||
],
|
||||
"viewport": {
|
||||
"x": 260.58251815500563,
|
||||
"y": 318.2261172111936,
|
||||
"zoom": 0.43514115784696294
|
||||
}
|
||||
},
|
||||
"description": "This flow will get you experimenting with the basics of the UI, the Chat and the Prompt component. \n\nTry changing the Template in it to see how the model behaves. \nYou can change it to this and a Text Input into the `type_of_person` variable : \"Answer the user as if you were a pirate.\n\nUser: {user_input}\n\nAnswer: \" ",
|
||||
"name": "Basic Prompting (Ahoy World!)",
|
||||
"last_tested_version": "1.0.0a4",
|
||||
"is_component": false
|
||||
}
|
||||
File diff suppressed because it is too large
Load diff
File diff suppressed because one or more lines are too long
|
|
@ -3,9 +3,10 @@ import os
|
|||
import zlib
|
||||
from pathlib import Path
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
from loguru import logger
|
||||
|
||||
from langflow.interface.custom.custom_component import CustomComponent
|
||||
|
||||
|
||||
class CustomComponentPathValueError(ValueError):
|
||||
pass
|
||||
|
|
@ -106,8 +107,15 @@ class DirectoryReader:
|
|||
"""
|
||||
if not os.path.isfile(file_path):
|
||||
return None
|
||||
with open(file_path, "r") as file:
|
||||
return file.read()
|
||||
with open(file_path, "r", encoding="utf-8") as file:
|
||||
# UnicodeDecodeError: 'charmap' codec can't decode byte 0x9d in position 3069: character maps to <undefined>
|
||||
try:
|
||||
return file.read()
|
||||
except UnicodeDecodeError:
|
||||
# This is happening in Windows, so we need to open the file in binary mode
|
||||
# The file is always just a python file, so we can safely read it as utf-8
|
||||
with open(file_path, "rb") as file:
|
||||
return file.read().decode("utf-8")
|
||||
|
||||
def get_files(self):
|
||||
"""
|
||||
|
|
@ -198,7 +206,12 @@ class DirectoryReader:
|
|||
Process a file by validating its content and
|
||||
returning the result and content/error message.
|
||||
"""
|
||||
file_content = self.read_file_content(file_path)
|
||||
try:
|
||||
file_content = self.read_file_content(file_path)
|
||||
except Exception as exc:
|
||||
logger.exception(exc)
|
||||
logger.error(f"Error while reading file {file_path}: {str(exc)}")
|
||||
return False, f"Could not read {file_path}"
|
||||
|
||||
if file_content is None:
|
||||
return False, f"Could not read {file_path}"
|
||||
|
|
@ -233,7 +246,7 @@ class DirectoryReader:
|
|||
filename = os.path.basename(file_path)
|
||||
validation_result, result_content = self.process_file(file_path)
|
||||
if not validation_result:
|
||||
logger.error(f"Error while processing file {file_path}: {result_content}")
|
||||
logger.error(f"Error while processing file {file_path}")
|
||||
|
||||
menu_result = self.find_menu(response, menu_name) or {
|
||||
"name": menu_name,
|
||||
|
|
|
|||
|
|
@ -203,10 +203,8 @@ def prepare_global_scope(code, module):
|
|||
imported_module = importlib.import_module(node.module)
|
||||
for alias in node.names:
|
||||
exec_globals[alias.name] = getattr(imported_module, alias.name)
|
||||
except ModuleNotFoundError as e:
|
||||
raise ModuleNotFoundError(
|
||||
f"Module {node.module} not found. Please install it and try again. Error: {repr(e)}"
|
||||
)
|
||||
except ModuleNotFoundError:
|
||||
raise ModuleNotFoundError(f"Module {node.module} not found. Please install it and try again")
|
||||
return exec_globals
|
||||
|
||||
|
||||
|
|
|
|||
546
src/backend/base/poetry.lock
generated
546
src/backend/base/poetry.lock
generated
|
|
@ -1186,6 +1186,20 @@ six = ">=1.9.0"
|
|||
gmpy = ["gmpy"]
|
||||
gmpy2 = ["gmpy2"]
|
||||
|
||||
[[package]]
|
||||
name = "emoji"
|
||||
version = "2.11.0"
|
||||
description = "Emoji for Python"
|
||||
optional = false
|
||||
python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,>=2.7"
|
||||
files = [
|
||||
{file = "emoji-2.11.0-py2.py3-none-any.whl", hash = "sha256:63fc9107f06c6c2e48e5078ce9575cef98518f5ac09474f6148a43e989989582"},
|
||||
{file = "emoji-2.11.0.tar.gz", hash = "sha256:772eaa30f4e0b1ce95148a092df4c7dc97644532c03225326b0fd05e8a9f72a3"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
dev = ["coverage", "coveralls", "pytest"]
|
||||
|
||||
[[package]]
|
||||
name = "exceptiongroup"
|
||||
version = "1.2.0"
|
||||
|
|
@ -2487,13 +2501,13 @@ extended-testing = ["aiosqlite (>=0.19.0,<0.20.0)", "aleph-alpha-client (>=2.15.
|
|||
|
||||
[[package]]
|
||||
name = "langchain-core"
|
||||
version = "0.1.38"
|
||||
version = "0.1.40"
|
||||
description = "Building applications with LLMs through composability"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_core-0.1.38-py3-none-any.whl", hash = "sha256:d881b2754254cb4bdb0d5bb56e5c138d032b6e75e5cb21f151b01224b322e02b"},
|
||||
{file = "langchain_core-0.1.38.tar.gz", hash = "sha256:ee8da6d061c06cce7dc22fec224b6ecbc3a8de106d6dd9f409c7fe448ea41861"},
|
||||
{file = "langchain_core-0.1.40-py3-none-any.whl", hash = "sha256:618dbb7ab44d8b263b91e384db1ff07d0db256ae5bdafa0123a115b6a75a13f1"},
|
||||
{file = "langchain_core-0.1.40.tar.gz", hash = "sha256:34c06fc0e6d3534b738c63f85403446b4be71161665b7e091f9bb19c914ec100"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2502,7 +2516,6 @@ langsmith = ">=0.1.0,<0.2.0"
|
|||
packaging = ">=23.2,<24.0"
|
||||
pydantic = ">=1,<3"
|
||||
PyYAML = ">=5.3"
|
||||
requests = ">=2,<3"
|
||||
tenacity = ">=8.1.0,<9.0.0"
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -2526,6 +2539,22 @@ langchain-core = ">=0.1.37,<0.2.0"
|
|||
[package.extras]
|
||||
extended-testing = ["faker (>=19.3.1,<20.0.0)", "jinja2 (>=3,<4)", "pandas (>=2.0.1,<3.0.0)", "presidio-analyzer (>=2.2.352,<3.0.0)", "presidio-anonymizer (>=2.2.352,<3.0.0)", "sentence-transformers (>=2,<3)", "tabulate (>=0.9.0,<0.10.0)", "vowpal-wabbit-next (==0.6.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "langchain-openai"
|
||||
version = "0.1.1"
|
||||
description = "An integration package connecting OpenAI and LangChain"
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langchain_openai-0.1.1-py3-none-any.whl", hash = "sha256:5cf4df5d2550af673337eafedaeec014ba52f9a25aeb8451206ca254bed01e5c"},
|
||||
{file = "langchain_openai-0.1.1.tar.gz", hash = "sha256:d10e9a9fc4c8ea99ca98f23808ce44c7dcdd65354ac07ad10afe874ecf3401ca"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
langchain-core = ">=0.1.33,<0.2.0"
|
||||
openai = ">=1.10.0,<2.0.0"
|
||||
tiktoken = ">=0.5.2,<1"
|
||||
|
||||
[[package]]
|
||||
name = "langchain-text-splitters"
|
||||
version = "0.0.1"
|
||||
|
|
@ -2545,13 +2574,13 @@ extended-testing = ["lxml (>=5.1.0,<6.0.0)"]
|
|||
|
||||
[[package]]
|
||||
name = "langsmith"
|
||||
version = "0.1.38"
|
||||
version = "0.1.39"
|
||||
description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
|
||||
optional = false
|
||||
python-versions = "<4.0,>=3.8.1"
|
||||
files = [
|
||||
{file = "langsmith-0.1.38-py3-none-any.whl", hash = "sha256:f36479f82cf537cf40d129ac2e485e72a3981360c7b6cf2549dad77d98eafd8f"},
|
||||
{file = "langsmith-0.1.38.tar.gz", hash = "sha256:2c1f98ac0a8c02e43b625650a6e13c65b09523551bfc21a59d20963f46f7d265"},
|
||||
{file = "langsmith-0.1.39-py3-none-any.whl", hash = "sha256:85c19177162585728001cb7ae91ab48ca4abe39b7bc1ff783212ac426ded222b"},
|
||||
{file = "langsmith-0.1.39.tar.gz", hash = "sha256:2aec9d2f9cc664042d2121b13da569b0902aff842c86b17b440245d57da84ec5"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -2606,124 +2635,165 @@ dev = ["Sphinx (==7.2.5)", "colorama (==0.4.5)", "colorama (==0.4.6)", "exceptio
|
|||
|
||||
[[package]]
|
||||
name = "lxml"
|
||||
version = "5.2.0"
|
||||
version = "5.2.1"
|
||||
description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
|
||||
optional = false
|
||||
python-versions = ">=3.6"
|
||||
files = [
|
||||
{file = "lxml-5.2.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:c54f8d6160080831a76780d850302fdeb0e8d0806f661777b0714dfb55d9a08a"},
|
||||
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||||
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||||
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||||
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|
||||
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||||
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||||
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||||
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||||
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||||
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|
||||
]
|
||||
|
||||
[package.extras]
|
||||
|
|
@ -3369,6 +3439,29 @@ packaging = "*"
|
|||
protobuf = "*"
|
||||
sympy = "*"
|
||||
|
||||
[[package]]
|
||||
name = "openai"
|
||||
version = "1.16.1"
|
||||
description = "The official Python library for the openai API"
|
||||
optional = false
|
||||
python-versions = ">=3.7.1"
|
||||
files = [
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||||
{file = "openai-1.16.1-py3-none-any.whl", hash = "sha256:77ef3db6110071f7154859e234250fb945a36554207a30a4491092eadb73fcb5"},
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|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
anyio = ">=3.5.0,<5"
|
||||
distro = ">=1.7.0,<2"
|
||||
httpx = ">=0.23.0,<1"
|
||||
pydantic = ">=1.9.0,<3"
|
||||
sniffio = "*"
|
||||
tqdm = ">4"
|
||||
typing-extensions = ">=4.7,<5"
|
||||
|
||||
[package.extras]
|
||||
datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
|
||||
|
||||
[[package]]
|
||||
name = "opentelemetry-api"
|
||||
version = "1.24.0"
|
||||
|
|
@ -3830,41 +3923,6 @@ tests = ["check-manifest", "coverage", "defusedxml", "markdown2", "olefile", "pa
|
|||
typing = ["typing-extensions"]
|
||||
xmp = ["defusedxml"]
|
||||
|
||||
[[package]]
|
||||
name = "pip"
|
||||
version = "24.0"
|
||||
description = "The PyPA recommended tool for installing Python packages."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
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||||
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||||
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|
||||
|
||||
[[package]]
|
||||
name = "pip-tools"
|
||||
version = "7.4.1"
|
||||
description = "pip-tools keeps your pinned dependencies fresh."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
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||||
files = [
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||||
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|
||||
|
||||
[package.dependencies]
|
||||
build = ">=1.0.0"
|
||||
click = ">=8"
|
||||
pip = ">=22.2"
|
||||
pyproject_hooks = "*"
|
||||
setuptools = "*"
|
||||
tomli = {version = "*", markers = "python_version < \"3.11\""}
|
||||
wheel = "*"
|
||||
|
||||
[package.extras]
|
||||
coverage = ["covdefaults", "pytest-cov"]
|
||||
testing = ["flit_core (>=2,<4)", "poetry_core (>=1.0.0)", "pytest (>=7.2.0)", "pytest-rerunfailures", "pytest-xdist", "tomli-w"]
|
||||
|
||||
[[package]]
|
||||
name = "platformdirs"
|
||||
version = "4.2.0"
|
||||
|
|
@ -4715,6 +4773,108 @@ files = [
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|||
[package.dependencies]
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||||
cffi = {version = "*", markers = "implementation_name == \"pypy\""}
|
||||
|
||||
[[package]]
|
||||
name = "regex"
|
||||
version = "2023.12.25"
|
||||
description = "Alternative regular expression module, to replace re."
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||||
optional = false
|
||||
python-versions = ">=3.7"
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||||
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||||
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||||
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||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
|
|
@ -5057,6 +5217,58 @@ files = [
|
|||
[package.extras]
|
||||
tests = ["pytest", "pytest-cov"]
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||||
|
||||
[[package]]
|
||||
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|
||||
version = "0.6.0"
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||||
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||||
optional = false
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||||
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|
||||
{file = "tiktoken-0.6.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:b2048e1086b48e3c8c6e2ceeac866561374cd57a84622fa49a6b245ffecb7744"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:07f229a5eb250b6403a61200199cecf0aac4aa23c3ecc1c11c1ca002cbb8f159"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:432aa3be8436177b0db5a2b3e7cc28fd6c693f783b2f8722539ba16a867d0c6a"},
|
||||
{file = "tiktoken-0.6.0-cp39-cp39-win_amd64.whl", hash = "sha256:8bfe8a19c8b5c40d121ee7938cd9c6a278e5b97dc035fd61714b4f0399d2f7a1"},
|
||||
{file = "tiktoken-0.6.0.tar.gz", hash = "sha256:ace62a4ede83c75b0374a2ddfa4b76903cf483e9cb06247f566be3bf14e6beed"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
regex = ">=2022.1.18"
|
||||
requests = ">=2.26.0"
|
||||
|
||||
[package.extras]
|
||||
blobfile = ["blobfile (>=2)"]
|
||||
|
||||
[[package]]
|
||||
name = "tokenizers"
|
||||
version = "0.15.2"
|
||||
|
|
@ -5404,13 +5616,13 @@ types-pyOpenSSL = "*"
|
|||
|
||||
[[package]]
|
||||
name = "types-requests"
|
||||
version = "2.31.0.20240402"
|
||||
version = "2.31.0.20240403"
|
||||
description = "Typing stubs for requests"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "types-requests-2.31.0.20240402.tar.gz", hash = "sha256:e5c09a202f8ae79cd6ffbbba2203b6c3775a83126283bb2a6abbc129abc02a12"},
|
||||
{file = "types_requests-2.31.0.20240402-py3-none-any.whl", hash = "sha256:bd7eb7102168d4b5b489f15cdd9842b63ab7fe56aa82a0589fa595b94195acf4"},
|
||||
{file = "types-requests-2.31.0.20240403.tar.gz", hash = "sha256:e1e0cd0b655334f39d9f872b68a1310f0e343647688bf2cee932ec4c2b04de59"},
|
||||
{file = "types_requests-2.31.0.20240403-py3-none-any.whl", hash = "sha256:06abf6a68f5c4f2a62f6bb006672dfb26ed50ccbfddb281e1ee6f09a65707d5d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
|
|
@ -5752,20 +5964,6 @@ MarkupSafe = ">=2.1.1"
|
|||
[package.extras]
|
||||
watchdog = ["watchdog (>=2.3)"]
|
||||
|
||||
[[package]]
|
||||
name = "wheel"
|
||||
version = "0.43.0"
|
||||
description = "A built-package format for Python"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "wheel-0.43.0-py3-none-any.whl", hash = "sha256:55c570405f142630c6b9f72fe09d9b67cf1477fcf543ae5b8dcb1f5b7377da81"},
|
||||
{file = "wheel-0.43.0.tar.gz", hash = "sha256:465ef92c69fa5c5da2d1cf8ac40559a8c940886afcef87dcf14b9470862f1d85"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
test = ["pytest (>=6.0.0)", "setuptools (>=65)"]
|
||||
|
||||
[[package]]
|
||||
name = "win32-setctime"
|
||||
version = "1.1.0"
|
||||
|
|
@ -6070,4 +6268,4 @@ local = []
|
|||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.10,<3.12"
|
||||
content-hash = "455e5f44f2e5dcbc3e0359658d7c4ef9f93e40c99841c9de99311a0ecad483c2"
|
||||
content-hash = "27adc9d6515d9e92ee01a6aae0c9a8162aa403456134ab25a8dd98909ecbe5f2"
|
||||
|
|
|
|||
|
|
@ -1,6 +1,6 @@
|
|||
[tool.poetry]
|
||||
name = "langflow-base"
|
||||
version = "0.0.16"
|
||||
version = "0.0.18"
|
||||
description = "A Python package with a built-in web application"
|
||||
authors = ["Logspace <contact@logspace.ai>"]
|
||||
maintainers = [
|
||||
|
|
@ -60,6 +60,10 @@ pypdf = "^4.1.0"
|
|||
chromadb = "^0.4.24"
|
||||
langchain-anthropic = "^0.1.4"
|
||||
langchain-astradb = "^0.1.0"
|
||||
nest-asyncio = "^1.6.0"
|
||||
emoji = "^2.11.0"
|
||||
cryptography = "^42.0.5"
|
||||
langchain-openai = "^0.1.1"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
|
|
|||
|
|
@ -130,7 +130,7 @@ export default function CollectionCardComponent({
|
|||
return (
|
||||
<Card
|
||||
className={cn(
|
||||
"group relative flex flex-col justify-between overflow-hidden transition-all hover:shadow-md",
|
||||
"group relative flex min-h-[11rem] flex-col justify-between overflow-hidden transition-all hover:shadow-md",
|
||||
disabled ? "pointer-events-none opacity-50" : ""
|
||||
)}
|
||||
>
|
||||
|
|
|
|||
|
|
@ -43,7 +43,7 @@ export default function UndrawCardComponent({
|
|||
}}
|
||||
/>
|
||||
);
|
||||
case "Basic Prompting":
|
||||
case "Basic Prompting (Ahoy World!)":
|
||||
return (
|
||||
<BasicPrompt
|
||||
style={{
|
||||
|
|
@ -83,7 +83,7 @@ export default function UndrawCardComponent({
|
|||
}}
|
||||
/>
|
||||
);
|
||||
case "Prompt Chaining":
|
||||
case "Vector Store RAG":
|
||||
return (
|
||||
<PromptChaining
|
||||
style={{
|
||||
|
|
|
|||
|
|
@ -34,10 +34,12 @@ export default function NewFlowModal({
|
|||
{/* {examples.map((example, idx) => {
|
||||
return <UndrawCardComponent key={idx} flow={example} />;
|
||||
})} */}
|
||||
{examples.find((e) => e.name == "Basic Prompting") && (
|
||||
{examples.find((e) => e.name == "Basic Prompting (Ahoy World!)") && (
|
||||
<UndrawCardComponent
|
||||
key={1}
|
||||
flow={examples.find((e) => e.name == "Basic Prompting")!}
|
||||
flow={
|
||||
examples.find((e) => e.name == "Basic Prompting (Ahoy World!)")!
|
||||
}
|
||||
/>
|
||||
)}
|
||||
{examples.find((e) => e.name == "Memory Chatbot") && (
|
||||
|
|
@ -52,18 +54,18 @@ export default function NewFlowModal({
|
|||
flow={examples.find((e) => e.name == "Document QA")!}
|
||||
/>
|
||||
)}
|
||||
{examples.find((e) => e.name == "Prompt Chaining") && (
|
||||
<UndrawCardComponent
|
||||
key={1}
|
||||
flow={examples.find((e) => e.name == "Prompt Chaining")!}
|
||||
/>
|
||||
)}
|
||||
{examples.find((e) => e.name == "Blog Writer") && (
|
||||
<UndrawCardComponent
|
||||
key={1}
|
||||
flow={examples.find((e) => e.name == "Blog Writer")!}
|
||||
/>
|
||||
)}
|
||||
{examples.find((e) => e.name == "Vector Store RAG") && (
|
||||
<UndrawCardComponent
|
||||
key={1}
|
||||
flow={examples.find((e) => e.name == "Vector Store RAG")!}
|
||||
/>
|
||||
)}
|
||||
</div>
|
||||
</BaseModal.Content>
|
||||
</BaseModal>
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue