Update app.py

app.py

@@ -102,41 +102,30 @@ def cleanup_expired_files():
 
 ## Context Taking, PDF Upload, and Mode Selection
 with st.sidebar:
-    st.title("Upload PDF:")
-    
-    research_field = st.text_input(
-        "Research Field: ", 
-        key="research_field", 
-        placeholder="Enter research fields with commas"
+    st.title("Select Mode:")
+    option = st.selectbox(
+        'Choose your interaction mode',
+        ('Chat PDF', 'Chat LLM')
     )
-
-    if not research_field:
-        st.info("Please enter a research field to proceed.")
-        uploaded_file = st.file_uploader("", type=["pdf"], disabled=True)
+    
+    if option == "Chat PDF":
+        st.title("Upload PDF:")
+        research_field = st.text_input("Research Field: ", key="research_field", placeholder="Enter research fields with commas")
+        if not research_field:
+            st.info("Please enter a research field to proceed.")
+            uploaded_file = st.file_uploader("", type=["pdf"], disabled=True)
+        else:
+            uploaded_file = st.file_uploader("", type=["pdf"], disabled=False)
     else:
-        uploaded_file = st.file_uploader("", type=["pdf"], disabled=False)
-
-    temperature = st.slider(
-        "Select Temperature", 
-        min_value=0.0, 
-        max_value=1.0, 
-        value=0.05, 
-        step=0.01
-    )
-    selected_llm_model = st.selectbox(
-        "Select LLM Model", 
-        options=list(llm_model.keys()), 
-        index=3
-    )
-    top_k = st.slider(
-        "Select Top K Matches", 
-        min_value=1, 
-        max_value=20, 
-        value=5
-    )
+        research_field = None
+        uploaded_file = None
+
+    temperature = st.slider("Select Temperature", min_value=0.0, max_value=1.0, value=0.05, step=0.01)
+    selected_llm_model = st.selectbox("Select LLM Model", options=list(llm_model.keys()), index=3)
+    top_k = st.slider("Select Top K Matches", min_value=1, max_value=20, value=5)
 
-## Initialize unique ID, db_client, db_path, and timestamp if not already in session state
-if 'db_client' not in st.session_state:
+## Initialize unique ID, db_client, db_path, and timestamp if needed
+if 'db_client' not in st.session_state and option == "Chat PDF":
     unique_id = str(uuid.uuid4())
     st.session_state['unique_id'] = unique_id
     db_path = os.path.join(VECTOR_DB_DIR, unique_id)
@@ -148,18 +137,19 @@ if 'db_client' not in st.session_state:
     log_upload_time(unique_id)
 
 # Access session-stored variables
-db_client = st.session_state['db_client']
-unique_id = st.session_state['unique_id']
-db_path = st.session_state['db_path']
+if option == "Chat PDF":
+    db_client = st.session_state['db_client']
+    unique_id = st.session_state['unique_id']
+    db_path = st.session_state['db_path']
 
-if 'document_text' not in st.session_state:
-    st.session_state['document_text'] = None
+    if 'document_text' not in st.session_state:
+        st.session_state['document_text'] = None
 
-if 'text_embeddings' not in st.session_state:
-    st.session_state['text_embeddings'] = None
+    if 'text_embeddings' not in st.session_state:
+        st.session_state['text_embeddings'] = None
 
 ## Handle PDF Upload and Processing
-if uploaded_file is not None and st.session_state['document_text'] is None:
+if option == "Chat PDF" and uploaded_file is not None and st.session_state['document_text'] is None:
     os.makedirs(UPLOAD_DIR, exist_ok=True)
     file_path = os.path.join(UPLOAD_DIR, f"{unique_id}_paper.pdf")
     with open(file_path, "wb") as file:
@@ -169,24 +159,21 @@ if uploaded_file is not None and st.session_state['document_text'] is None:
     st.session_state['document_text'] = document_text
     
     text_content_chunks = contextChunks(document_text, chunk_size, chunk_overlap)
-    text_contents_embeddings = contextEmbeddingChroma(
-        embeddModel, 
-        text_content_chunks, 
-        db_client, 
-        db_path=db_path
-    )
+    text_contents_embeddings = contextEmbeddingChroma(embeddModel, text_content_chunks, db_client, db_path=db_path)
     st.session_state['text_embeddings'] = text_contents_embeddings
 
-if st.session_state['document_text'] and st.session_state['text_embeddings']:
+if option == "Chat PDF" and st.session_state['document_text'] and st.session_state['text_embeddings']:
     document_text = st.session_state['document_text']
     text_contents_embeddings = st.session_state['text_embeddings']
 else:
-    st.stop()
+    if option == "Chat PDF":
+        st.stop()
 
+## Chat Input for Both Modes
 q_input = st.chat_input(key="input", placeholder="Ask your question")
 
 if q_input:
-    if option == "Chat":
+    if option == "Chat PDF":
         query_embedding = ragQuery(embeddModel, q_input)
         top_k_matches = similarityChroma(query_embedding, db_client, top_k)
 
@@ -195,16 +182,25 @@ if q_input:
         prompt_template = q_input
         user_content = top_k_matches
         max_tokens = max_tokens[selected_llm_model]
-        print(max_tokens)
-        top_p = 1
-        stream = True
-        stop = None
 
-        groq_completion = GroqCompletion(groq_client, LLMmodel, domain, prompt_template, user_content, temperature, max_tokens, top_p, stream, stop)
+        groq_completion = GroqCompletion(groq_client, LLMmodel, domain, prompt_template, user_content, temperature, max_tokens, top_p=1, stream=True, stop=None)
+        result = groq_completion.create_completion()
+        
+        with st.spinner("Processing..."):
+            chat_response(q_input, result)
+
+    elif option == "Chat LLM":
+        LLMmodel = llm_model[selected_llm_model]
+        domain = "General"
+        prompt_template = q_input
+        user_content = ""
+        max_tokens = max_tokens[selected_llm_model]
+
+        groq_completion = GroqCompletion(groq_client, LLMmodel, domain, prompt_template, user_content, temperature, max_tokens, top_p=1, stream=True, stop=None)
         result = groq_completion.create_completion()
         
         with st.spinner("Processing..."):
             chat_response(q_input, result)
 
-## Call the cleanup function periodically
+## Periodic Cleanup
 cleanup_expired_files()