feat: add vecstores, docloaders and embedding

src/backend/langflow/config.yaml

@@ -45,5 +45,6 @@ vectorstores:
 
 documentloaders:
   - TextLoader
+  - Text
 
 dev: false

src/backend/langflow/graph/base.py

@@ -153,6 +153,9 @@ class Node:
                         result = result.run  # type: ignore
                     elif hasattr(result, "get_function"):
                         result = result.get_function()  # type: ignore
+                elif key == "Document Loader":
+                    result = result.load()
+
                 self.params[key] = result
             elif isinstance(value, list) and all(
                 isinstance(node, Node) for node in value

src/backend/langflow/graph/graph.py

@@ -10,6 +10,9 @@ from langflow.graph.nodes import (
     ToolkitNode,
     ToolNode,
     WrapperNode,
+    EmbeddingNode,
+    VectorStoreNode,
+    DocumentLoaderNode,
 )
 from langflow.interface.agents.base import agent_creator
 from langflow.interface.chains.base import chain_creator
@@ -20,6 +23,9 @@ from langflow.interface.tools.base import tool_creator
 from langflow.interface.tools.constants import FILE_TOOLS
 from langflow.interface.tools.util import get_tools_dict
 from langflow.interface.wrappers.base import wrapper_creator
+from langflow.interface.embeddings.base import embedding_creator
+from langflow.interface.vectorStore.base import vectorstore_creator
+from langflow.interface.documentLoaders.base import documentloader_creator
 from langflow.utils import payload
 
 
@@ -130,6 +136,12 @@ class Graph:
                 or node_lc_type in llm_creator.to_list()
             ):
                 nodes.append(LLMNode(node))
+            elif node_type in embedding_creator.to_list():
+                nodes.append(EmbeddingNode(node))
+            elif node_type in vectorstore_creator.to_list():
+                nodes.append(VectorStoreNode(node))
+            elif node_type in documentloader_creator.to_list():
+                nodes.append(DocumentLoaderNode(node))
             else:
                 nodes.append(Node(node))
         return nodes

src/backend/langflow/graph/utils.py

@@ -31,6 +31,9 @@ def load_file(file_name, file_content, accepted_types) -> Any:
         # Load the csv content
         csv_reader = csv.DictReader(io.StringIO(decoded_string))
         return list(csv_reader)
+    elif suffix == "txt":
+        # Return the text content
+        return decoded_string
     else:
         raise ValueError(f"File {file_name} is not accepted")
 

src/backend/langflow/interface/documentLoaders/base.py

@@ -4,6 +4,7 @@ from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import documentloaders_type_to_cls_dict
 from langflow.settings import settings
 from langflow.utils.util import build_template_from_class
+from langflow.interface.documentLoaders.custom import CUSTOM_DOCUMENTLOADERS
 
 
 class DocumentLoaderCreator(LangChainTypeCreator):
@@ -11,7 +12,12 @@ class DocumentLoaderCreator(LangChainTypeCreator):
 
     @property
     def type_to_loader_dict(self) -> Dict:
-        return documentloaders_type_to_cls_dict
+        types = documentloaders_type_to_cls_dict
+
+        for name, documentloader in CUSTOM_DOCUMENTLOADERS.items():
+            types[name] = documentloader
+
+        return types
 
     def get_signature(self, name: str) -> Optional[Dict]:
         """Get the signature of a document loader."""

src/backend/langflow/interface/documentLoaders/custom.py

@@ -0,0 +1,27 @@
+"""Load text files."""
+from typing import List
+
+from langchain.docstore.document import Document
+from langchain.document_loaders.base import BaseLoader
+from langchain.text_splitter import CharacterTextSplitter
+
+
+class Text(BaseLoader):
+    """Load Text files."""
+
+    def __init__(self, file: str):
+        """Initialize with file path."""
+        self.file = file
+
+    def load(self) -> List[Document]:
+        """Load from file path."""
+        documents = [Document(page_content=self.file, metadata={"source": "loaded"})]
+
+        text_splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=0)
+
+        return text_splitter.split_documents(documents)
+
+
+CUSTOM_DOCUMENTLOADERS = {
+    "Text": Text,
+}

src/backend/langflow/interface/importing/utils.py

@@ -9,6 +9,7 @@ from langchain.chains.base import Chain
 from langchain.chat_models.base import BaseChatModel
 from langchain.llms.base import BaseLLM
 from langchain.tools import BaseTool
+from langflow.interface.documentLoaders.custom import CUSTOM_DOCUMENTLOADERS
 
 from langflow.interface.tools.util import get_tool_by_name
 
@@ -38,6 +39,9 @@ def import_by_type(_type: str, name: str) -> Any:
         "toolkits": import_toolkit,
         "wrappers": import_wrapper,
         "memory": import_memory,
+        "embeddings": import_embedding,
+        "vectorstores": import_vectorstore,
+        "documentloaders": import_documentloader,
     }
     if _type == "llms":
         key = "chat" if "chat" in name.lower() else "llm"
@@ -103,3 +107,21 @@ def import_tool(tool: str) -> BaseTool:
 def import_chain(chain: str) -> Chain:
     """Import chain from chain name"""
     return import_class(f"langchain.chains.{chain}")
+
+
+def import_embedding(embedding: str) -> Any:
+    """Import embedding from embedding name"""
+    return import_class(f"langchain.embeddings.{embedding}")
+
+
+def import_vectorstore(vectorstore: str) -> Any:
+    """Import vectorstore from vectorstore name"""
+    return import_class(f"langchain.vectorstores.{vectorstore}")
+
+
+def import_documentloader(documentloader: str) -> Any:
+    """Import documentloader from documentloader name"""
+    if documentloader in CUSTOM_DOCUMENTLOADERS:
+        return CUSTOM_DOCUMENTLOADERS[documentloader]
+
+    return import_class(f"langchain.document_loaders.{documentloader}")

src/backend/langflow/interface/loading.py

@@ -57,6 +57,14 @@ def instantiate_class(node_type: str, base_type: str, params: Dict) -> Any:
         if toolkits_creator.has_create_function(node_type):
             return load_toolkits_executor(node_type, loaded_toolkit, params)
         return loaded_toolkit
+    elif base_type == "embeddings":
+        params.pop("model")
+        return class_object(**params)
+    elif base_type == "vectorstores":
+        # Rename dict key
+        params["documents"] = params.pop("Document Loader")
+        params["embedding"] = params.pop("Embedding")
+        return class_object.from_documents(**params)
     else:
         return class_object(**params)
 

src/backend/langflow/interface/vectorStore/base.py

@@ -24,14 +24,12 @@ class VectorstoreCreator(LangChainTypeCreator):
                     "required": True,
                     "show": True,
                     "name": "Document Loader",
-                    "value": "",
                 },
                 "Embedding": {
                     "type": "Embeddings",
                     "required": True,
                     "show": True,
                     "name": "Embedding",
-                    "value": "",
                 },
             }
             return signature

src/frontend/src/utils.ts

@@ -77,8 +77,8 @@ export const nodeColors: {[char: string]: string} = {
   chat: "#454173",
   thought:"#272541",
   embeddings:"#FF9135",
-  documentloader:"#FF9135",
-  vectorstore: "#FF9135",
+  documentloaders:"#FF9135",
+  vectorstores: "#FF9135",
   unknown:"#9CA3AF"
 };
 
@@ -92,8 +92,8 @@ export const nodeNames:{[char: string]: string} = {
   advanced: "Advanced",
   chat: "Chat",
   embeddings: "Embeddings",
-  documentloader: "Document Loaders",
-  vectorstore: "Vector Stores",
+  documentloaders: "Document Loaders",
+  vectorstores: "Vector Stores",
   toolkits:"Toolkits",
   wrappers:"Wrappers",
   unknown:"Unknown"
@@ -109,8 +109,8 @@ export const nodeIcons:{[char: string]: React.ForwardRefExoticComponent<React.SV
   advanced: ComputerDesktopIcon,
   chat: Bars3CenterLeftIcon,
   embeddings:PaperClipIcon,
-  documentloader:PaperClipIcon,
-  vectorstore: PaperClipIcon,
+  documentloaders:PaperClipIcon,
+  vectorstores: PaperClipIcon,
   toolkits:WrenchScrewdriverIcon,
   wrappers:GiftIcon,
   unknown:QuestionMarkCircleIcon