Update App/Embedding/utils/Initialize.py

App/Embedding/utils/Initialize.py

@@ -1,7 +1,7 @@
 from langchain.embeddings import HuggingFaceEmbeddings
 from langchain.docstore.document import Document
 from langchain.vectorstores import Pinecone
-
+from pinecone import PodSpec
 import pinecone
 import os
 
@@ -18,10 +18,11 @@ async def delete_documents(task_id):
     index_name = "transcript-bits"
     model_name = "thenlper/gte-base"
     embeddings = HuggingFaceEmbeddings(model_name=model_name)
+    spec = PodSpec()
 
 
-    pc=pinecone.Pinecone(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
-    vector_index = pc.Index(index_name=index_name)
+    pc=pinecone.Pinecone(api_key=PINECONE_API_KEY, environment=PINECONE_ENV,spec=spec)
+    vector_index = pc.Index(index_name)
     docsearch = Pinecone.from_existing_index(index_name, embeddings)
 
     docsearch.delete(
@@ -65,7 +66,7 @@ def search(query: str, task_id: str):
 
 
     pc=pinecone.Pinecone(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
-    vector_index = pc.Index(index_name=index_name)
+    vector_index = pc.Index(index_name)
     docsearch = Pinecone.from_existing_index(index_name, embeddings)
 
     filtering_conditions = {
@@ -91,7 +92,7 @@ def encode(temp: list[Document]):
 
 
     pc=pinecone.Pinecone(api_key=PINECONE_API_KEY, environment=PINECONE_ENV)
-    vector_index = pc.Index(index_name=index_name)
+    vector_index = pc.Index(index_name)
     docsearch = Pinecone.from_existing_index(index_name, embeddings)
     docsearch.add_documents(temp)
     # return  embeddings.embed_documents(texts = [d.page_content for d in temp])