From b8141dca7dc8dd206e11d90b212ce3fa5118618c Mon Sep 17 00:00:00 2001
From: Gabriel Luiz Freitas Almeida <gabriel@logspace.ai>
Date: Thu, 22 Jun 2023 13:45:04 -0300
Subject: [PATCH] =?UTF-8?q?=F0=9F=9A=80=20feat(loading.py):=20move=20loadi?=
 =?UTF-8?q?ng=20into=20initialize=20module=20=F0=9F=93=9D=20docs(initializ?=
 =?UTF-8?q?e):=20add=20empty=20=5F=5Finit=5F=5F.py=20file=20to=20initializ?=
 =?UTF-8?q?e=20directory=20The=20initialize=20directory=20was=20added=20to?=
 =?UTF-8?q?=20the=20project,=20but=20it=20was=20missing=20an=20=5F=5Finit?=
 =?UTF-8?q?=5F=5F.py=20file.=20This=20file=20is=20necessary=20to=20make=20?=
 =?UTF-8?q?the=20directory=20a=20package=20and=20allow=20importing=20modul?=
 =?UTF-8?q?es=20from=20it.=20An=20empty=20=5F=5Finit=5F=5F.py=20file=20was?=
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---
 .../langflow/interface/initialize/__init__.py |  0
 .../interface/{ => initialize}/loading.py     | 45 ++++++++++++-------
 2 files changed, 29 insertions(+), 16 deletions(-)
 create mode 100644 src/backend/langflow/interface/initialize/__init__.py
 rename src/backend/langflow/interface/{ => initialize}/loading.py (93%)

diff --git a/src/backend/langflow/interface/initialize/__init__.py b/src/backend/langflow/interface/initialize/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/src/backend/langflow/interface/loading.py b/src/backend/langflow/interface/initialize/loading.py
similarity index 93%
rename from src/backend/langflow/interface/loading.py
rename to src/backend/langflow/interface/initialize/loading.py
index 260104323..9567d27c7 100644
--- a/src/backend/langflow/interface/loading.py
+++ b/src/backend/langflow/interface/initialize/loading.py
@@ -17,6 +17,11 @@ from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.loading import load_chain_from_config
 from langchain.llms.loading import load_llm_from_config
+from langflow.interface.initialize.vector_store import (
+    initialize_chroma,
+    initialize_pinecone,
+    initialize_qdrant,
+)
 from pydantic import ValidationError
 
 from langflow.interface.custom_lists import CUSTOM_NODES
@@ -153,30 +158,38 @@ def instantiate_embedding(class_object, params):
 
 
 def instantiate_vectorstore(class_object, params):
-    if len(params.get("documents", [])) == 0:
-        raise ValueError(
-            "The source you provided did not load correctly or was empty."
-            "This may cause an error in the vectorstore."
-        )
+    # could be documents or texts
+    if class_object.__name__ == "Pinecone":
+        return initialize_pinecone(class_object, params)
     # Chroma requires all metadata values to not be None
     if class_object.__name__ == "Chroma":
-        persist = params.pop("persist", False)
-        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] = ""
-        vector_store = class_object.from_documents(**params)
-        if persist:
-            vector_store.persist()
+        return initialize_chroma(class_object, params)
+
+    if class_object.__name__ == "Qdrant":
+        return initialize_qdrant(class_object, params)
     else:
+        if "texts" in params:
+            params["documents"] = params.pop("texts")
+
         vector_store = class_object.from_documents(**params)
     return vector_store
 
 
 def instantiate_documentloader(class_object, params):
-    return class_object(**params).load()
+    metadata = params.pop("metadata", None)
+    docs = class_object(**params).load()
+    if metadata:
+        if isinstance(metadata, str):
+            try:
+                metadata = json.loads(metadata)
+            except json.JSONDecodeError as exc:
+                raise ValueError(
+                    "The metadata you provided is not a valid JSON string."
+                ) from exc
+
+        for doc in docs:
+            doc.metadata = metadata
+    return docs
 
 
 def instantiate_textsplitter(class_object, params):