apply ruff
This commit is contained in:
Gabriel Luiz Freitas Almeida
parent
954c703cd8
commit
c811e5f045
23 changed files with 10 additions and 119 deletions
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@ -1,9 +1,7 @@
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from typing import Optional
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from langchain_community.embeddings import BedrockEmbeddings
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import Embeddings
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from langflow.io import DropdownInput, Output, SecretStrInput, TextInput
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from langflow.io import DropdownInput, Output, TextInput
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class AmazonBedrockEmbeddingsComponent(LCModelComponent):
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@ -1,4 +1,3 @@
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from typing import Optional
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from langchain_openai import AzureOpenAIEmbeddings
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from pydantic.v1 import SecretStr
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@ -2,7 +2,7 @@ from langchain_community.embeddings.cohere import CohereEmbeddings
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import Embeddings
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from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, Output, SecretStrInput, TextInput
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from langflow.io import DropdownInput, FloatInput, IntInput, Output, SecretStrInput, TextInput
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class CohereEmbeddingsComponent(LCModelComponent):
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@ -1,5 +1,3 @@
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from typing import Dict, Optional
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from langchain_community.embeddings.huggingface import HuggingFaceEmbeddings
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from langflow.base.models.model import LCModelComponent
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@ -1,11 +1,9 @@
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from typing import Dict, Optional
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from langchain_community.embeddings.huggingface import HuggingFaceInferenceAPIEmbeddings
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from pydantic.v1.types import SecretStr
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import Embeddings
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from langflow.io import BoolInput, DictInput, FloatInput, Output, SecretStrInput, TextInput
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from langflow.io import BoolInput, DictInput, Output, SecretStrInput, TextInput
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class HuggingFaceInferenceAPIEmbeddingsComponent(LCModelComponent):
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@ -1,5 +1,3 @@
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from typing import Optional
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from langchain_community.embeddings import OllamaEmbeddings
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import Embeddings
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@ -1,5 +1,3 @@
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from typing import List, Optional
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from langflow.base.models.model import LCModelComponent
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from langflow.field_typing import Embeddings
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from langflow.io import BoolInput, DictInput, FileInput, FloatInput, IntInput, Output, TextInput
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@ -1,86 +0,0 @@
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from typing import Optional
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from langchain_anthropic import ChatAnthropic
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from pydantic.v1.types import SecretStr
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from langflow.field_typing import LanguageModel
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class AnthropicLLM(CustomComponent):
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display_name: str = "Anthropic"
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description: str = "Generate text using Anthropic Chat&Completion LLMs."
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icon = "Anthropic"
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field_order = [
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"model",
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"anthropic_api_key",
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"max_tokens",
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"temperature",
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"anthropic_api_url",
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]
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def build_config(self):
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return {
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"model": {
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"display_name": "Model Name",
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"options": [
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"claude-3-opus-20240229",
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"claude-3-sonnet-20240229",
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"claude-3-haiku-20240307",
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"claude-2.1",
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"claude-2.0",
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"claude-instant-1.2",
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"claude-instant-1",
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],
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"info": "Name of the model to use.",
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"required": True,
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"value": "claude-3-opus-20240229",
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},
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"anthropic_api_key": {
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"display_name": "Anthropic API Key",
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"required": True,
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"password": True,
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"info": "Your Anthropic API key.",
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},
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"max_tokens": {
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"display_name": "Max Tokens",
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"advanced": True,
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"info": "The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
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},
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"temperature": {
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"display_name": "Temperature",
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"field_type": "float",
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"value": 0.1,
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},
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"anthropic_api_url": {
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"display_name": "Anthropic API URL",
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"advanced": True,
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"info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
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},
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"code": {"show": False},
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}
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def build(
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self,
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model: str,
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anthropic_api_key: Optional[str] = None,
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max_tokens: Optional[int] = 1000,
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temperature: Optional[float] = None,
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anthropic_api_url: Optional[str] = None,
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) -> LanguageModel:
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# Set default API endpoint if not provided
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if not anthropic_api_url:
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anthropic_api_url = "https://api.anthropic.com"
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try:
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output = ChatAnthropic(
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model_name=model,
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anthropic_api_key=(SecretStr(anthropic_api_key) if anthropic_api_key else None),
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max_tokens_to_sample=max_tokens, # type: ignore
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temperature=temperature,
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anthropic_api_url=anthropic_api_url,
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)
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except Exception as e:
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raise ValueError("Could not connect to Anthropic API.") from e
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return output
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@ -2,7 +2,7 @@ from langchain_aws import ChatBedrock
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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 LanguageModel, Text
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from langflow.field_typing import LanguageModel
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from langflow.io import BoolInput, DictInput, DropdownInput, MessageInput, Output, StrInput
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@ -3,7 +3,7 @@ from pydantic.v1 import SecretStr
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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 LanguageModel, Text
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from langflow.field_typing import LanguageModel
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from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, Output, SecretStrInput, StrInput
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@ -2,7 +2,7 @@ from pydantic.v1 import SecretStr
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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 LanguageModel, Text
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from langflow.field_typing import LanguageModel
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from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, Output, SecretStrInput, StrInput
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@ -47,7 +47,7 @@ class RecursiveCharacterTextSplitterComponent(Component):
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Split text into chunks of a specified length.
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Args:
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separators (list[str]): The characters to split on.
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separators (list[str] | None): The characters to split on.
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chunk_size (int): The maximum length of each chunk.
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chunk_overlap (int): The amount of overlap between chunks.
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@ -63,9 +63,9 @@ class RecursiveCharacterTextSplitterComponent(Component):
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self.separators = [unescape_string(x) for x in self.separators]
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# Make sure chunk_size and chunk_overlap are ints
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if isinstance(self.chunk_size, str):
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if self.chunk_size:
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self.chunk_size = int(self.chunk_size)
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if isinstance(self.chunk_overlap, str):
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if self.chunk_overlap:
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self.chunk_overlap = int(self.chunk_overlap)
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splitter = RecursiveCharacterTextSplitter(
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separators=self.separators,
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@ -7,7 +7,6 @@ from langflow.custom import Component
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from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, Output, SecretStrInput, StrInput
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from langflow.schema import Data
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from langflow.field_typing import Retriever
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class CassandraVectorStoreComponent(Component):
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@ -1,5 +1,5 @@
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from copy import deepcopy
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from typing import TYPE_CHECKING, List
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from typing import TYPE_CHECKING
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from chromadb.config import Settings
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from langchain_chroma.vectorstores import Chroma
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@ -8,7 +8,6 @@ from langflow.custom import Component
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from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, HandleInput, IntInput, Output, SecretStrInput, StrInput
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from langflow.schema import Data
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from langflow.field_typing import Retriever
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class CouchbaseVectorStoreComponent(Component):
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@ -8,8 +8,6 @@ from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, HandleInput, IntInput, Output, StrInput
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from langflow.schema import Data
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from langflow.field_typing import Retriever
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class MongoVectorStoreComponent(Component):
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display_name = "MongoDB Atlas"
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@ -4,7 +4,6 @@ from langchain_community.vectorstores import Qdrant
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from langchain_core.retrievers import BaseRetriever
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from langflow.custom import Component
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from langflow.field_typing import Retriever
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from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, DropdownInput, HandleInput, IntInput, Output, SecretStrInput, StrInput
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from langflow.schema import Data
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@ -5,7 +5,6 @@ from langchain_core.retrievers import BaseRetriever
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from supabase.client import Client, create_client
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from langflow.custom import Component
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from langflow.field_typing import Retriever
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from langflow.helpers.data import docs_to_data
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from langflow.io import HandleInput, IntInput, Output, StrInput
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from langflow.schema import Data
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@ -4,7 +4,6 @@ from langchain_community.vectorstores import UpstashVectorStore
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from langchain_core.retrievers import BaseRetriever
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from langflow.custom import Component
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from langflow.field_typing import Retriever
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from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, HandleInput, IntInput, Output, StrInput
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from langflow.schema import Data
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@ -5,7 +5,6 @@ from langchain_community.vectorstores import Weaviate
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from langchain_core.retrievers import BaseRetriever
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from langflow.custom import Component
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from langflow.field_typing import Retriever
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from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, HandleInput, IntInput, Output, SecretStrInput, StrInput
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from langflow.schema import Data
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@ -8,8 +8,6 @@ from langflow.helpers.data import docs_to_data
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from langflow.io import BoolInput, HandleInput, IntInput, Output, StrInput
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from langflow.schema import Data
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from langflow.field_typing import Retriever
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class PGVectorStoreComponent(Component):
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display_name = "PGVector"
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@ -6,7 +6,6 @@ from itertools import chain
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from typing import TYPE_CHECKING, Dict, Generator, List, Optional, Tuple, Type, Union
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from loguru import logger
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from langflow.exceptions.component import ComponentBuildException
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from langflow.exceptions.component import ComponentBuildException
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from langflow.graph.edge.base import ContractEdge
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from langflow.graph.graph.constants import lazy_load_vertex_dict
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@ -11,7 +11,6 @@ class Template(BaseModel):
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type_name: str = Field(serialization_alias="_type")
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fields: list[Union[Input, InputTypes]]
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def process_fields(
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self,
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format_field_func: Union[Callable, None] = None,
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