Update app.py

app.py

@@ -1,19 +1,22 @@
-import os
-import pickle
-import time
-import gradio as gr
-from dotenv import load_dotenv
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain.chains import RetrievalQAWithSourcesChain
+from langchain.document_loaders import UnstructuredURLLoader
+from langchain.document_loaders import (
+    PyPDFLoader, TextLoader, Docx2txtLoader, UnstructuredHTMLLoader
+)
 from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.document_loaders import UnstructuredURLLoader, PyPDFLoader, TextLoader, Docx2txtLoader, UnstructuredHTMLLoader
+from langchain.chains.qa_with_sources.retrieval import RetrievalQAWithSourcesChain
+from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_google_genai import GoogleGenerativeAIEmbeddings
-from langchain.vectorstores import FAISS
+from langchain_community.docstore.in_memory import InMemoryDocstore
+from langchain_community.vectorstores import FAISS
+from sentence_transformers import SentenceTransformer
+from dotenv import load_dotenv
+import pickle
+import os
 
 load_dotenv()
 
 
-llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-001", google_api_key = api_key, temperature=0.5)
+llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash-001", temperature=0.5)
 file_path = "vector_db.pkl"
 
 def load_any_file(file_path):
@@ -49,7 +52,7 @@ def process_inputs(url, file):
     )
     docs = text_splitter.split_documents(data)
 
-    embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001",google_api_key = api_key)
+    embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
     vectorstore_openai = FAISS.from_documents(docs, embeddings)
 
     with open(file_path, "wb") as f:
@@ -90,4 +93,4 @@ with gr.Blocks(title="RockyBot: News Research Tool") as demo:
     process_btn.click(fn=process_inputs, inputs=[url_input, file_input], outputs=[process_status, answer_output])
     query_input.submit(fn=answer_question, inputs=query_input, outputs=[answer_output, sources_output])
 
-demo.launch()
+demo.launch()