Update import statements in GitbookLoader, JsonToolkit, CSVAgent, UnstructuredHTMLLoader, IMSDbLoader, IFixitLoader, BSHTMLLoader, ReadTheDocsLoader, OpenAPIToolkit, Qdrant, EverNoteLoader, CoNLLULoader, and AirbyteJSONLoader components
This commit is contained in:
Gabriel Luiz Freitas Almeida
parent
6ffb7cc233
commit
15dd9e3ee1
20 changed files with 61 additions and 69 deletions
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@ -1,6 +1,6 @@
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from langflow import CustomComponent
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from langchain.field_typing import BaseLanguageModel, AgentExecutor
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from langflow.field_typing import BaseLanguageModel, AgentExecutor
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class CSVAgentComponent(CustomComponent):
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display_name = "CSVAgent"
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class AZLyricsLoaderComponent(CustomComponent):
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display_name = "AZLyricsLoader"
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description = "Load `AZLyrics` webpages."
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@ -10,18 +10,8 @@ class AZLyricsLoaderComponent(CustomComponent):
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def build_config(self):
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return {
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"metadata": {
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"display_name": "Metadata",
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"type": "dict",
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"default": {},
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"show": True
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},
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"web_path": {
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"display_name": "Web Page",
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"type": "str",
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"required": True,
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"show": True
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},
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"metadata": {"display_name": "Metadata", "type": "dict", "default": {}, "show": True},
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"web_path": {"display_name": "Web Page", "type": "str", "required": True, "show": True},
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}
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def build(self, metadata: Optional[Dict] = None, web_path: str = "") -> Document:
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@ -1,13 +1,14 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class AirbyteJSONLoaderComponent(CustomComponent):
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display_name = "AirbyteJSONLoader"
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description = "Load local `Airbyte` json files."
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documentation = "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/airbyte_json"
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documentation = (
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"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/airbyte_json"
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)
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def build_config(self):
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return {
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class BSHTMLLoaderComponent(CustomComponent):
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display_name = "BSHTMLLoader"
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description = "Load `HTML` files and parse them with `beautiful soup`."
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@ -1,8 +1,7 @@
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from langflow import CustomComponent
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from langchain.documents import Document
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from typing import Optional, Dict
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from langchain.field_typing import TemplateField
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from langflow.field_typing import TemplateField
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class CoNLLULoaderComponent(CustomComponent):
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@ -17,7 +16,7 @@ class CoNLLULoaderComponent(CustomComponent):
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required=True,
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type="file",
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file_types=["conllu"],
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suffixes=['.conllu'],
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suffixes=[".conllu"],
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),
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"metadata": TemplateField(
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display_name="Metadata",
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@ -1,13 +1,13 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class EverNoteLoaderComponent(CustomComponent):
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display_name = "EverNoteLoader"
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description = "Load from `EverNote`."
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documentation = "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/evernote"
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def build_config(self):
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return {
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"file_path": {
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@ -1,6 +1,5 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class IFixitLoaderComponent(CustomComponent):
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display_name = "IFixitLoader"
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description = "Load `iFixit` repair guides, device wikis and answers."
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Dict, Optional
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class IMSDbLoaderComponent(CustomComponent):
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display_name = "IMSDbLoader"
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description = "Load `IMSDb` webpages."
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Dict, Optional
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class ReadTheDocsLoaderComponent(CustomComponent):
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display_name = "ReadTheDocsLoader"
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description = "Load `ReadTheDocs` documentation directory."
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@ -1,6 +1,5 @@
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from langchain import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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@ -1,13 +1,14 @@
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from langchain import CustomComponent
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from langchain.field_typing import Document
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from langflow.field_typing import Document
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from typing import Optional, Dict
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class UnstructuredWordDocumentLoaderComponent(CustomComponent):
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display_name = "UnstructuredWordDocumentLoader"
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description = "Load `Microsoft Word` file using `Unstructured`."
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documentation = "https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_word"
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documentation = (
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"https://python.langchain.com/docs/modules/data_connection/document_loaders/integrations/microsoft_word"
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)
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def build_config(self):
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return {
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@ -17,11 +18,7 @@ class UnstructuredWordDocumentLoaderComponent(CustomComponent):
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"type": "file",
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"suffixes": [".docx", ".doc"],
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},
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"metadata": {
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"display_name": "Metadata",
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"required": False,
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"type": "dict"
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},
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"metadata": {"display_name": "Metadata", "required": False, "type": "dict"},
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}
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def build(self, file_path: str, metadata: Optional[Dict] = None) -> Document:
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@ -1,12 +1,14 @@
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from langflow import CustomComponent
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from typing import Optional, Any, Dict
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from langchain.field_typing import Embeddings
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from langflow.field_typing import Embeddings
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class HuggingFaceEmbeddingsComponent(CustomComponent):
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display_name = "HuggingFaceEmbeddings"
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description = "HuggingFace sentence_transformers embedding models."
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documentation = "https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
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documentation = (
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"https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/sentence_transformers"
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)
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def build_config(self):
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return {
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from pydantic import SecretStr
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from typing import Optional, Dict, Any
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from langchain.field_typing import BaseLanguageModel
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from langflow.field_typing import BaseLanguageModel
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class AnthropicComponent(CustomComponent):
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display_name = "Anthropic"
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@ -40,7 +40,13 @@ class AnthropicComponent(CustomComponent):
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# Here we are returning a placeholder class as the Anthropic class is not defined
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# This is to comply with the type hints required by the CustomComponent
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class Anthropic(BaseLanguageModel):
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def __init__(self, api_key: Optional[SecretStr], api_url: Optional[str], model_kwargs: Optional[Dict[str, Any]] = None, temperature: Optional[float] = None):
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def __init__(
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self,
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api_key: Optional[SecretStr],
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api_url: Optional[str],
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model_kwargs: Optional[Dict[str, Any]] = None,
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temperature: Optional[float] = None,
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):
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# Initialize Anthropic model with the provided arguments
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super().__init__()
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self.api_key = api_key
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.llms import BaseLLM
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from typing import Optional, Dict, Union, Any
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from langchain.field_typing import BaseLanguageModel
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from langflow.field_typing import BaseLanguageModel
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class ChatOpenAIComponent(CustomComponent):
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display_name = "ChatOpenAI"
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@ -69,7 +69,6 @@ class ChatOpenAIComponent(CustomComponent):
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openai_api_key: Optional[str] = None,
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temperature: float = 0.7,
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) -> Union[BaseLanguageModel, BaseLLM]:
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# Assuming there is a class `ChatOpenAI` that takes these parameters
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# The `ChatOpenAI` class must be imported or defined elsewhere in the actual implementation
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return ChatOpenAI(
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@ -1,6 +1,6 @@
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from langflow import CustomComponent
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from langchain.field_typing import JsonSpec, Tool
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from langflow.field_typing import JsonSpec, Tool
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class JsonToolkitComponent(CustomComponent):
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display_name = "JsonToolkit"
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@ -1,8 +1,8 @@
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from langflow import CustomComponent
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from langchain.field_typing import AgentExecutor, TextRequestsWrapper
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from langflow.field_typing import AgentExecutor, TextRequestsWrapper
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from typing import Callable
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class OpenAPIToolkitComponent(CustomComponent):
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display_name = "OpenAPIToolkit"
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description = "Toolkit for interacting with an OpenAPI API."
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@ -1,13 +1,13 @@
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from langflow import CustomComponent
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from typing import Optional, List
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from langchain.vectorstores import Pinecone
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from langchain.field_typing import (
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from langflow.field_typing import (
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Document,
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Embeddings,
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NestedDict,
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)
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class PineconeComponent(CustomComponent):
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display_name = "Pinecone"
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description = "Construct Pinecone wrapper from raw documents."
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@ -20,7 +20,7 @@ class PineconeComponent(CustomComponent):
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"namespace": {"display_name": "Namespace"},
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"pinecone_api_key": {"display_name": "Pinecone API Key", "default": ""},
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"pinecone_env": {"display_name": "Pinecone Environment", "default": ""},
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"search_kwargs": {"display_name": "Search Kwargs", "default": '{}'},
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"search_kwargs": {"display_name": "Search Kwargs", "default": "{}"},
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}
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def build(
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@ -1,9 +1,9 @@
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from langflow import CustomComponent
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from langchain.vectorstores import Qdrant
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from langchain_community.vectorstores.qdrant import Qdrant
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from typing import Optional, List
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from langflow.field_typing import Document, Embeddings, NestedDict
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class QdrantComponent(CustomComponent):
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display_name = "Qdrant"
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description = "Construct Qdrant wrapper from a list of texts."
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@ -1,13 +1,13 @@
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from langflow import CustomComponent
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from typing import Optional, List
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from langchain.vectorstores import SupabaseVectorStore
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from langchain.field_typing import (
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from langflow.field_typing import (
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Document,
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Embeddings,
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NestedDict,
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)
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class SupabaseComponent(CustomComponent):
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display_name = "Supabase"
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description = "Return VectorStore initialized from texts and embeddings."
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@ -27,11 +27,11 @@ class SupabaseComponent(CustomComponent):
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self,
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embedding: Embeddings,
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documents: Optional[List[Document]] = None,
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query_name: str = '',
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query_name: str = "",
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search_kwargs: NestedDict = {},
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supabase_service_key: str = '',
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supabase_url: str = '',
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table_name: str = '',
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supabase_service_key: str = "",
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supabase_url: str = "",
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table_name: str = "",
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) -> SupabaseVectorStore:
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return SupabaseVectorStore(
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documents=documents,
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