🚀 feat(validate.py): remove unused imports and endpoint for node validation

🚀 feat(base.py): update import statement for loading module
🚀 feat(vector_store.py): add initialization functions for pinecone, chroma, and qdrant
The unused imports and endpoint for node validation were removed from validate.py. The import statement for the loading module was updated in base.py. Initialization functions for pinecone, chroma, and qdrant were added to vector_store.py to allow for the creation of objects from the respective services.

src/backend/langflow/api/v1/validate.py

@@ -1,5 +1,3 @@
-import json
-
 from fastapi import APIRouter, HTTPException
 
 from langflow.api.v1.base import (
@@ -9,8 +7,6 @@ from langflow.api.v1.base import (
     PromptValidationResponse,
     validate_prompt,
 )
-from langflow.graph.vertex.types import VectorStoreVertex
-from langflow.graph import Graph
 from langflow.utils.logger import logger
 from langflow.utils.validate import validate_code
 
@@ -37,26 +33,3 @@ def post_validate_prompt(prompt: Prompt):
     except Exception as e:
         logger.exception(e)
         raise HTTPException(status_code=500, detail=str(e)) from e
-
-
-# validate node
-@router.post("/node/{node_id}", status_code=200)
-def post_validate_node(node_id: str, data: dict):
-    try:
-        # build graph
-        graph = Graph.from_payload(data)
-        # validate node
-        node = graph.get_node(node_id)
-        if node is None:
-            raise ValueError(f"Node {node_id} not found")
-        if not isinstance(node, VectorStoreVertex):
-            node.build()
-        return json.dumps(
-            {
-                "valid": True,
-                "params": f"{str(node._built_object_repr())[:300]}...",
-            }
-        )
-    except Exception as e:
-        logger.exception(e)
-        return json.dumps({"valid": False, "params": str(e)})

src/backend/langflow/graph/vertex/base.py

@@ -1,5 +1,5 @@
 from langflow.graph.vertex.constants import DIRECT_TYPES
-from langflow.interface import loading
+from langflow.interface.initialize import loading
 from langflow.interface.listing import ALL_TYPES_DICT
 from langflow.utils.logger import logger
 from langflow.utils.util import sync_to_async

src/backend/langflow/interface/initialize/vector_store.py

@@ -0,0 +1,75 @@
+from typing import Any
+
+
+def docs_in_params(params: dict) -> bool:
+    """Check if params has documents OR texts and one of them is not an empty list"""
+    return ("documents" in params and params["documents"] != []) or (
+        "texts" in params and params["texts"] != []
+    )
+
+
+def initialize_pinecone(class_object: Any, params: dict):
+    """Initialize pinecone and return the class object"""
+    PINECONE_API_KEY = params.get("pinecone_api_key")
+    PINECONE_ENV = params.get("pinecone_env")
+
+    if PINECONE_API_KEY is None or PINECONE_ENV is None:
+        raise ValueError(
+            "Pinecone API key and environment must be provided in the params"
+        )
+
+    if not docs_in_params(params):
+        import pinecone
+
+        # initialize pinecone
+        pinecone.init(
+            api_key=PINECONE_API_KEY,  # find at app.pinecone.io
+            environment=PINECONE_ENV,  # next to api key in console
+        )
+        # If there are docs in the index, delete them
+        return class_object.from_existing_index(**params)
+    # If there are docs in the params, create a new index
+    if "texts" in params:
+        params["documents"] = params.pop("texts")
+    return class_object.from_documents(**params)
+
+
+def initialize_chroma(class_object, params):
+    """Initialize a ChromaDB object from the params"""
+    persist = params.pop("persist", False)
+    if not docs_in_params(params):
+        if "texts" in params:
+            params["documents"] = params.pop("texts")
+        for doc in params["documents"]:
+            if doc.metadata is None:
+                doc.metadata = {}
+            for key, value in doc.metadata.items():
+                if value is None:
+                    doc.metadata[key] = ""
+        chromadb = class_object.from_documents(**params)
+    else:
+        chromadb = class_object(**params)
+    if persist:
+        chromadb.persist()
+    return chromadb
+
+
+def initialize_qdrant(class_object, params):
+    if not docs_in_params(params):
+        if "location" not in params and "api_key" not in params:
+            raise ValueError("Location and API key must be provided in the params")
+        from qdrant_client import QdrantClient
+
+        client_params = {
+            "location": params.pop("location"),
+            "api_key": params.pop("api_key"),
+        }
+        lc_params = {
+            "collection_name": params.pop("collection_name"),
+            "embeddings": params.pop("embedding"),
+        }
+        client = QdrantClient(**client_params)
+
+        return class_object(client=client, **lc_params)
+
+    return class_object.from_documents(**params)