feat: add embeddings, vectorstores and document loaders to list

src/backend/langflow/config.yaml

@@ -26,4 +26,13 @@ tools:
 memories:
   # - ConversationBufferMemory
 
+embeddings:
+  #
+
+vectorstores:
+  #
+
+documentloaders:
+  #
+
 dev: false

src/backend/langflow/interface/custom_lists.py

@@ -41,3 +41,165 @@ memory_type_to_cls_dict: dict[str, Any] = {
 
 # chain_type_to_cls_dict = type_to_loader_dict
 # chain_type_to_cls_dict["conversation_chain"] = ConversationChain
+
+
+## Embeddings
+from langchain.embeddings import (
+    CohereEmbeddings,
+    FakeEmbeddings,
+    HuggingFaceEmbeddings,
+    HuggingFaceInstructEmbeddings,
+    HuggingFaceHubEmbeddings,
+    OpenAIEmbeddings,
+    # SagemakerEndpointEmbeddings,
+    TensorflowHubEmbeddings,
+    SelfHostedHuggingFaceEmbeddings,
+    SelfHostedHuggingFaceInstructEmbeddings,
+    SelfHostedEmbeddings,
+)
+
+embedding_type_to_cls_dict = {
+    "OpenAIEmbeddings": OpenAIEmbeddings,
+    "HuggingFaceEmbeddings": HuggingFaceEmbeddings,
+    "CohereEmbeddings": CohereEmbeddings,
+    "HuggingFaceHubEmbeddings": HuggingFaceHubEmbeddings,
+    "TensorflowHubEmbeddings": TensorflowHubEmbeddings,
+    # "SagemakerEndpointEmbeddings": SagemakerEndpointEmbeddings,
+    "HuggingFaceInstructEmbeddings": HuggingFaceInstructEmbeddings,
+    "SelfHostedEmbeddings": SelfHostedEmbeddings,
+    "SelfHostedHuggingFaceEmbeddings": SelfHostedHuggingFaceEmbeddings,
+    "SelfHostedHuggingFaceInstructEmbeddings": SelfHostedHuggingFaceInstructEmbeddings,
+    "FakeEmbeddings": FakeEmbeddings,
+}
+
+## Vector Stores
+from langchain.vectorstores import (
+    ElasticVectorSearch,
+    FAISS,
+    VectorStore,
+    Pinecone,
+    Weaviate,
+    Qdrant,
+    Milvus,
+    Chroma,
+    OpenSearchVectorSearch,
+    AtlasDB,
+    DeepLake,
+)
+
+vectorstores_type_to_cls_dict = {
+    "ElasticVectorSearch": ElasticVectorSearch,
+    "FAISS": FAISS,
+    "VectorStore": VectorStore,
+    "Pinecone": Pinecone,
+    "Weaviate": Weaviate,
+    "Qdrant": Qdrant,
+    "Milvus": Milvus,
+    "Chroma": Chroma,
+    "OpenSearchVectorSearch": OpenSearchVectorSearch,
+    "AtlasDB": AtlasDB,
+    "DeepLake": DeepLake,
+}
+
+## Document Loaders
+
+from langchain.document_loaders import (
+    UnstructuredFileLoader,
+    UnstructuredFileIOLoader,
+    UnstructuredURLLoader,
+    DirectoryLoader,
+    NotionDirectoryLoader,
+    ReadTheDocsLoader,
+    GoogleDriveLoader,
+    UnstructuredHTMLLoader,
+    # BSHTMLLoader,
+    UnstructuredPowerPointLoader,
+    UnstructuredWordDocumentLoader,
+    UnstructuredPDFLoader,
+    UnstructuredImageLoader,
+    ObsidianLoader,
+    UnstructuredEmailLoader,
+    UnstructuredMarkdownLoader,
+    RoamLoader,
+    YoutubeLoader,
+    S3FileLoader,
+    TextLoader,
+    HNLoader,
+    GitbookLoader,
+    S3DirectoryLoader,
+    GCSFileLoader,
+    GCSDirectoryLoader,
+    WebBaseLoader,
+    IMSDbLoader,
+    AZLyricsLoader,
+    CollegeConfidentialLoader,
+    IFixitLoader,
+    GutenbergLoader,
+    PagedPDFSplitter,
+    PyPDFLoader,
+    EverNoteLoader,
+    AirbyteJSONLoader,
+    OnlinePDFLoader,
+    PDFMinerLoader,
+    PyMuPDFLoader,
+    TelegramChatLoader,
+    SRTLoader,
+    FacebookChatLoader,
+    NotebookLoader,
+    CoNLLULoader,
+    GoogleApiYoutubeLoader,
+    GoogleApiClient,
+    CSVLoader,
+    # BlackboardLoader
+)
+
+
+documentloaders_type_to_cls_dict = {
+    "UnstructuredFileLoader": UnstructuredFileLoader,
+    "UnstructuredFileIOLoader": UnstructuredFileIOLoader,
+    "UnstructuredURLLoader": UnstructuredURLLoader,
+    "DirectoryLoader": DirectoryLoader,
+    "NotionDirectoryLoader": NotionDirectoryLoader,
+    "ReadTheDocsLoader": ReadTheDocsLoader,
+    "GoogleDriveLoader": GoogleDriveLoader,
+    "UnstructuredHTMLLoader": UnstructuredHTMLLoader,
+    # "BSHTMLLoader": BSHTMLLoader,
+    "UnstructuredPowerPointLoader": UnstructuredPowerPointLoader,
+    "UnstructuredWordDocumentLoader": UnstructuredWordDocumentLoader,
+    "UnstructuredPDFLoader": UnstructuredPDFLoader,
+    "UnstructuredImageLoader": UnstructuredImageLoader,
+    "ObsidianLoader": ObsidianLoader,
+    "UnstructuredEmailLoader": UnstructuredEmailLoader,
+    "UnstructuredMarkdownLoader": UnstructuredMarkdownLoader,
+    "RoamLoader": RoamLoader,
+    "YoutubeLoader": YoutubeLoader,
+    "S3FileLoader": S3FileLoader,
+    "TextLoader": TextLoader,
+    "HNLoader": HNLoader,
+    "GitbookLoader": GitbookLoader,
+    "S3DirectoryLoader": S3DirectoryLoader,
+    "GCSFileLoader": GCSFileLoader,
+    "GCSDirectoryLoader": GCSDirectoryLoader,
+    "WebBaseLoader": WebBaseLoader,
+    "IMSDbLoader": IMSDbLoader,
+    "AZLyricsLoader": AZLyricsLoader,
+    "CollegeConfidentialLoader": CollegeConfidentialLoader,
+    "IFixitLoader": IFixitLoader,
+    "GutenbergLoader": GutenbergLoader,
+    "PagedPDFSplitter": PagedPDFSplitter,
+    "PyPDFLoader": PyPDFLoader,
+    "EverNoteLoader": EverNoteLoader,
+    "AirbyteJSONLoader": AirbyteJSONLoader,
+    "OnlinePDFLoader": OnlinePDFLoader,
+    "PDFMinerLoader": PDFMinerLoader,
+    "PyMuPDFLoader": PyMuPDFLoader,
+    "TelegramChatLoader": TelegramChatLoader,
+    "SRTLoader": SRTLoader,
+    "FacebookChatLoader": FacebookChatLoader,
+    "NotebookLoader": NotebookLoader,
+    "CoNLLULoader": CoNLLULoader,
+    "GoogleApiYoutubeLoader": GoogleApiYoutubeLoader,
+    "GoogleApiClient": GoogleApiClient,
+    "CSVLoader": CSVLoader,
+    # "BlackboardLoader",
+}

src/backend/langflow/interface/documentloaders.py

@@ -0,0 +1,27 @@
+from langflow.interface.custom_lists import documentloaders_type_to_cls_dict
+from langflow.settings import settings
+from langflow.interface.base import LangChainTypeCreator
+from langflow.utils.util import build_template_from_class
+from typing import Dict, List
+
+
+class DocumentLoaderCreator(LangChainTypeCreator):
+    type_name: str = "documentloader"
+
+    @property
+    def type_to_loader_dict(self) -> Dict:
+        return documentloaders_type_to_cls_dict
+
+    def get_signature(self, name: str) -> Dict | None:
+        """Get the signature of a document loader."""
+        try:
+            return build_template_from_class(name, documentloaders_type_to_cls_dict)
+        except ValueError as exc:
+            raise ValueError(f"Documment Loader {name} not found") from exc
+
+    def to_list(self) -> List[str]:
+        return [
+            documentloader.__name__
+            for documentloader in self.type_to_loader_dict.values()
+            if documentloader.__name__ in settings.documentloaders or settings.dev
+        ]

src/backend/langflow/interface/embeddings.py

@@ -0,0 +1,27 @@
+from langflow.interface.custom_lists import embedding_type_to_cls_dict
+from langflow.settings import settings
+from langflow.interface.base import LangChainTypeCreator
+from langflow.utils.util import build_template_from_class
+from typing import Dict, List
+
+
+class EmbeddingCreator(LangChainTypeCreator):
+    type_name: str = "embeddings"
+
+    @property
+    def type_to_loader_dict(self) -> Dict:
+        return embedding_type_to_cls_dict
+
+    def get_signature(self, name: str) -> Dict | None:
+        """Get the signature of an embedding."""
+        try:
+            return build_template_from_class(name, embedding_type_to_cls_dict)
+        except ValueError as exc:
+            raise ValueError(f"Embedding {name} not found") from exc
+
+    def to_list(self) -> List[str]:
+        return [
+            embedding.__name__
+            for embedding in self.type_to_loader_dict.values()
+            if embedding.__name__ in settings.embeddings or settings.dev
+        ]

src/backend/langflow/interface/types.py

@@ -4,6 +4,9 @@ from langflow.interface.llms import LLMCreator
 from langflow.interface.memories import MemoryCreator
 from langflow.interface.prompts import PromptCreator
 from langflow.interface.signature import get_signature
+from langflow.interface.embeddings import EmbeddingCreator
+from langflow.interface.vectorstore import VectorstoreCreator
+from langflow.interface.documentloaders import DocumentLoaderCreator
 from langchain import chains
 from langflow.interface.chains import ChainCreator
 from langflow.interface.tools import ToolCreator
@@ -29,6 +32,9 @@ def build_langchain_types_dict():
     tool_creator = ToolCreator()
     llm_creator = LLMCreator()
     memory_creator = MemoryCreator()
+    embedding_creator = EmbeddingCreator()
+    vectorstore_creator = VectorstoreCreator()
+    documentloader_creator = DocumentLoaderCreator()
 
     all_types = {}
 
@@ -39,6 +45,9 @@ def build_langchain_types_dict():
         llm_creator,
         memory_creator,
         tool_creator,
+        embedding_creator,
+        vectorstore_creator,
+        documentloader_creator,
     ]
 
     all_types = {}

src/backend/langflow/interface/vectorstore.py

@@ -0,0 +1,27 @@
+from langflow.interface.custom_lists import vectorstores_type_to_cls_dict
+from langflow.settings import settings
+from langflow.interface.base import LangChainTypeCreator
+from langflow.utils.util import build_template_from_class
+from typing import Dict, List
+
+
+class VectorstoreCreator(LangChainTypeCreator):
+    type_name: str = "vectorstore"
+
+    @property
+    def type_to_loader_dict(self) -> Dict:
+        return vectorstores_type_to_cls_dict
+
+    def get_signature(self, name: str) -> Dict | None:
+        """Get the signature of an embedding."""
+        try:
+            return build_template_from_class(name, vectorstores_type_to_cls_dict)
+        except ValueError as exc:
+            raise ValueError(f"Vector Store {name} not found") from exc
+
+    def to_list(self) -> List[str]:
+        return [
+            vectorstore
+            for vectorstore in self.type_to_loader_dict.keys()
+            if vectorstore in settings.vectorstores or settings.dev
+        ]

src/backend/langflow/settings.py

@@ -12,6 +12,9 @@ class Settings(BaseSettings):
     llms: Optional[List[str]] = Field(...)
     tools: Optional[List[str]] = Field(...)
     memories: Optional[List[str]] = Field(...)
+    embeddings: Optional[List[str]] = Field(...)
+    vectorstores: Optional[List[str]] = Field(...)
+    documentloaders: Optional[List[str]] = Field(...)
     dev: bool = Field(...)
 
     class Config:

src/backend/langflow/utils/util.py

@@ -88,28 +88,30 @@ def build_template_from_class(
             docs = get_class_doc(_class)
 
             variables = {"_type": _type}
-            for class_field_items, value in _class.__fields__.items():
-                if class_field_items in ["callback_manager"]:
-                    continue
-                variables[class_field_items] = {}
-                for name_, value_ in value.__repr_args__():
-                    if name_ == "default_factory":
-                        try:
-                            variables[class_field_items][
-                                "default"
-                            ] = get_default_factory(
-                                module=_class.__base__.__module__, function=value_
-                            )
-                        except Exception:
-                            variables[class_field_items]["default"] = None
-                    elif name_ not in ["name"]:
-                        variables[class_field_items][name_] = value_
 
-                variables[class_field_items]["placeholder"] = (
-                    docs["Attributes"][class_field_items]
-                    if class_field_items in docs["Attributes"]
-                    else ""
-                )
+            if "__fields__" in _class.__dict__:
+                for class_field_items, value in _class.__fields__.items():
+                    if class_field_items in ["callback_manager"]:
+                        continue
+                    variables[class_field_items] = {}
+                    for name_, value_ in value.__repr_args__():
+                        if name_ == "default_factory":
+                            try:
+                                variables[class_field_items][
+                                    "default"
+                                ] = get_default_factory(
+                                    module=_class.__base__.__module__, function=value_
+                                )
+                            except Exception:
+                                variables[class_field_items]["default"] = None
+                        elif name_ not in ["name"]:
+                            variables[class_field_items][name_] = value_
+
+                    variables[class_field_items]["placeholder"] = (
+                        docs["Attributes"][class_field_items]
+                        if class_field_items in docs["Attributes"]
+                        else ""
+                    )
             base_classes = get_base_classes(_class)
             # Adding function to base classes to allow
             # the output to be a function