0.2

app.py

@@ -22,6 +22,8 @@ with st.sidebar:
     corpus_id = st.text_input("Vectara Corpus ID", value=str(os.getenv("CORPUS_ID", "")))
     openai_api_key = st.text_input("OpenAI API Key", value=os.getenv("OPENAI_API_KEY", ""))
     submit_button = st.button("Submit")
+    
+keys_provided = all([customer_id, api_key, corpus_id, openai_api_key])
 
 # Constants
 CUSTOMER_ID = customer_id if customer_id else os.getenv("CUSTOMER_ID")
@@ -60,50 +62,54 @@ prompt = PromptTemplate.from_template(
 runnable = prompt | ChatOpenAI(streaming=True, callbacks=[StreamingStdOutCallbackHandler()], openai_api_key=OPENAI_API_KEY) | StrOutputParser()
 
 # Main Streamlit App
-st.title("Legal Consultation Chat")
-
-# Initialize chat history
-if "messages" not in st.session_state:
-    st.session_state.messages = []
-
-# Display chat messages from history on app rerun
-for message in st.session_state.messages:
-    with st.chat_message(message["role"]):
-        st.markdown(message["content"])
-
-# Accept user input and run the main chat interaction
-if user_input := st.chat_input("Enter your issue:"):
-    st.session_state.messages.append({"role": "user", "content": user_input})
-    with st.chat_message("user"):
-        st.markdown(user_input)
-
-    knowledge_content = get_knowledge_content(vectara_client, user_input)
-    print("__________________ Start of knowledge content __________________")
-    print(knowledge_content)
-    response = runnable.invoke({"knowledge": knowledge_content, "issue": user_input})
-
-    response_words = response.split()
-    with st.chat_message("assistant"):
-        message_placeholder = st.empty()
-        full_response = ""
-        for word in response_words:
-            full_response += word + " "
-            time.sleep(0.05)
-            message_placeholder.markdown(full_response + "▌")
-        message_placeholder.markdown(full_response)
-
-    st.session_state.messages.append({"role": "assistant", "content": full_response})
-
-# Run when the submit button is pressed
-if submit_button and uploaded_file:
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmpfile:
-        tmpfile.write(uploaded_file.getvalue())
-        tmp_filename = tmpfile.name
-
-    try:
-        vectara_client.add_files([tmp_filename])
-        st.sidebar.success("PDF file successfully uploaded to Vectara!")
-    except Exception as e:
-        st.sidebar.error(f"An error occurred: {str(e)}")
-    finally:
-        os.remove(tmp_filename)  # Clean up temporary file
+if keys_provided:
+    st.title("Legal Consultation Chat")
+
+    # Initialize chat history
+    if "messages" not in st.session_state:
+        st.session_state.messages = []
+
+    # Display chat messages from history on app rerun
+    for message in st.session_state.messages:
+        with st.chat_message(message["role"]):
+            st.markdown(message["content"])
+
+    # Accept user input and run the main chat interaction
+    if user_input := st.chat_input("Enter your issue:"):
+        st.session_state.messages.append({"role": "user", "content": user_input})
+        with st.chat_message("user"):
+            st.markdown(user_input)
+
+        knowledge_content = get_knowledge_content(vectara_client, user_input)
+        print("__________________ Start of knowledge content __________________")
+        print(knowledge_content)
+        response = runnable.invoke({"knowledge": knowledge_content, "issue": user_input})
+
+        response_words = response.split()
+        with st.chat_message("assistant"):
+            message_placeholder = st.empty()
+            full_response = ""
+            for word in response_words:
+                full_response += word + " "
+                time.sleep(0.05)
+                message_placeholder.markdown(full_response + "▌")
+            message_placeholder.markdown(full_response)
+
+        st.session_state.messages.append({"role": "assistant", "content": full_response})
+
+    # Run when the submit button is pressed
+    if submit_button and uploaded_file:
+        with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmpfile:
+            tmpfile.write(uploaded_file.getvalue())
+            tmp_filename = tmpfile.name
+
+        try:
+            vectara_client.add_files([tmp_filename])
+            st.sidebar.success("PDF file successfully uploaded to Vectara!")
+        except Exception as e:
+            st.sidebar.error(f"An error occurred: {str(e)}")
+        finally:
+            os.remove(tmp_filename)  # Clean up temporary file
+else:
+    # Not all keys are provided, instruct the user to input them
+    st.warning("Please input all required API keys in the sidebar to proceed.")