Update app.py

app.py

@@ -17,20 +17,20 @@ def load_pdf(file):
 
 # Summarization function using GPT-4
 def summarize_pdf(file, openai_api_key):
-    # Set the API key dynamically
+    # Set the OpenAI API key dynamically
     openai.api_key = openai_api_key
 
     # Load and process the PDF
     documents = load_pdf(file)
 
     # Create embeddings for the documents
-    embeddings = OpenAIEmbeddings()
+    embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
 
     # Use LangChain's FAISS Vector Store to store and search the embeddings
     vector_store = FAISS.from_documents(documents, embeddings)
 
     # Create a RetrievalQA chain for summarization
-    llm = ChatOpenAI(model="gpt-4o")  # Using GPT-4 as the LLM
+    llm = ChatOpenAI(model="gpt-4")  # Using GPT-4 as the LLM
     qa_chain = RetrievalQA.from_chain_type(
         llm=llm,
         chain_type="stuff",
@@ -43,14 +43,14 @@ def summarize_pdf(file, openai_api_key):
 
 # Function to handle user queries and provide answers from the document
 def query_pdf(file, user_query, openai_api_key):
-    # Set the API key dynamically
+    # Set the OpenAI API key dynamically
     openai.api_key = openai_api_key
 
     # Load and process the PDF
     documents = load_pdf(file)
 
     # Create embeddings for the documents
-    embeddings = OpenAIEmbeddings()
+    embeddings = OpenAIEmbeddings(openai_api_key=openai_api_key)
 
     # Use LangChain's FAISS Vector Store to store and search the embeddings
     vector_store = FAISS.from_documents(documents, embeddings)