Update app.py

app.py

@@ -14,17 +14,23 @@ load_dotenv()  # Load the GROQ API KEY
 GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
 
 llm = ChatGroq(temperature=0, model_name='llama-3.1-8b-instant', groq_api_key=GROQ_API_KEY)
-prompt = ChatPromptTemplate.from_template("""Answer the questions based on the provided context only.
+
+prompt = ChatPromptTemplate.from_template("""
+Answer the questions based on the provided context only.
 Please provide the most accurate response based on the question
 <context>{context}</context>
-Question: {input}""")
+Question: {input}
+""")
 
 embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
 
-def initialize_vectors():
-    return None
+# Global variable to store the vector store
+vectors = None
 
-vectors = initialize_vectors()
+def clear_knowledge_base():
+    global vectors
+    vectors = None
+    return "Knowledge base cleared."
 
 def process_pdf(file):
     global vectors
@@ -41,12 +47,15 @@ def process_question(question):
     global vectors
     if vectors is None:
         return "Please upload a PDF first.", "", 0
+    
     document_chain = create_stuff_documents_chain(llm, prompt)
     retriever = vectors.as_retriever()
     retrieval_chain = create_retrieval_chain(retriever, document_chain)
     response = retrieval_chain.invoke({'input': question})
+    
     context = "\n\n".join([doc.page_content for doc in response["context"]])
     confidence_score = sum([doc.metadata.get('score', 0) for doc in response["context"]]) / len(response["context"])
+    
     return response['answer'], context, round(confidence_score, 2)
 
 CSS = """
@@ -71,6 +80,8 @@ with gr.Blocks(css=CSS, theme="Nymbo/Nymbo_Theme") as demo:
         pdf_file = gr.File(label="Upload PDF")
         upload_button = gr.Button("Process PDF")
         upload_output = gr.Textbox(label="Upload Status")
+        clear_button = gr.Button("Clear Knowledge Base")
+        clear_output = gr.Textbox(label="Clear Status")
     
     with gr.Tab("Q&A System"):
         question_input = gr.Textbox(lines=2, placeholder="Enter your question here...")
@@ -80,6 +91,7 @@ with gr.Blocks(css=CSS, theme="Nymbo/Nymbo_Theme") as demo:
         confidence_output = gr.Number(label="Confidence Score")
     
     upload_button.click(process_pdf, inputs=[pdf_file], outputs=[upload_output])
+    clear_button.click(clear_knowledge_base, outputs=[clear_output])
     submit_button.click(process_question, inputs=[question_input], outputs=[answer_output, context_output, confidence_output])
     
     gr.HTML(FOOTER_TEXT)