Update app.py

app.py

@@ -8,6 +8,7 @@ import json
 from langchain.callbacks import get_openai_callback
 from langchain.chains import ConversationalRetrievalChain
 from langchain_openai import ChatOpenAI
+import base64
 
 st.set_page_config(layout="wide")
 os.environ["OPENAI_API_KEY"] = "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"
@@ -21,6 +22,24 @@ session_state_2_llm_chat_history = lambda session_state: [
 ai_message_format = lambda message, references: (
     f"{message}\n\n---\n\n{references}" if references != "" else message
 )
+welcome_message = """
+Hi I'm Agent Xi, your AI assistant, dedicated to making your journey through machine learning research papers as insightful and interactive as possible. Whether you're diving into the latest studies or brushing up on foundational papers, I'm here to help navigate, discuss, and analyze content with you.
+
+Here's a quick guide to getting started with me:
+
+| Command | Description |
+|---------|-------------|
+| `/upload` | Upload and process documents for our conversation. |
+| `/index` | View an index of processed documents to easily navigate your research. |
+| `/cost` | Calculate the cost of our conversation, ensuring transparency in resource usage. |
+| `/download` | Download conversation data for your records or further analysis. |
+
+<br>
+
+Feel free to use these commands to enhance your research experience. Let's embark on this exciting journey of discovery together!
+
+Use `/man` at any point of time to view this guide again.
+"""
 
 
 def process_documents_wrapper(inputs):
@@ -78,13 +97,9 @@ def download_conversation_wrapper(inputs=None):
             ),
         }
     )
-    st.sidebar.download_button(
-        "Download Conversation",
-        conversation_data,
-        file_name="conversation_data.json",
-        mime="application/json",
-    )
+    conversation_data = base64.b64encode(conversation_data.encode()).decode()
     st.session_state.messages.append(("/download", "Conversation data downloaded", ""))
+    return f'<a href="data:text/csv;base64,{conversation_data}" download="conversation_data.json">Download Conversation</a>'
 
 
 def query_llm_wrapper(inputs):
@@ -120,33 +135,17 @@ def query_llm_wrapper(inputs):
 
 
 def boot(command_center):
-    st.write(
-        """
-        # Agent Xi
-Hi I'm Agent Xi 📚 your AI assistant 🤖, dedicated to making your journey through machine learning research papers as insightful and interactive as possible. Whether you're diving into the latest studies or brushing up on foundational papers, I'm here to help navigate, discuss, and analyze content with you.
-
-Here's a quick guide to getting started with me:
-
-| Command | Description |
-|---------|-------------|
-| `/upload` | Upload and process documents for our conversation. |
-| `/index` | View an index of processed documents to easily navigate your research. |
-| `/cost` | Calculate the cost of our conversation, ensuring transparency in resource usage. |
-| `/download` | Download conversation data for your records or further analysis. |
-
-<br>
-
-Feel free to use these commands to enhance your research experience. Let's embark on this exciting journey of discovery together!
-    """,
-        unsafe_allow_html=True,
-    )
+    st.write("# Agent Xi")
     if "costing" not in st.session_state:
         st.session_state.costing = []
     if "messages" not in st.session_state:
         st.session_state.messages = []
+    st.chat_message("ai").write(welcome_message, unsafe_allow_html=True)
     for message in st.session_state.messages:
         st.chat_message("human").write(message[0])
-        st.chat_message("ai").write(ai_message_format(message[1], message[2]))
+        st.chat_message("ai").write(
+            ai_message_format(message[1], message[2]), unsafe_allow_html=True
+        )
     if query := st.chat_input():
         st.chat_message("human").write(query)
         response = command_center.execute_command(query)
@@ -154,9 +153,11 @@ Feel free to use these commands to enhance your research experience. Let's embar
             pass
         elif type(response) == tuple:
             result, references = response
-            st.chat_message("ai").write(ai_message_format(result, references))
+            st.chat_message("ai").write(
+                ai_message_format(result, references), unsafe_allow_html=True
+            )
         else:
-            st.chat_message("ai").write(response)
+            st.chat_message("ai").write(response, unsafe_allow_html=True)
 
 
 if __name__ == "__main__":
@@ -165,6 +166,7 @@ if __name__ == "__main__":
         ("/index", None, index_documents_wrapper),
         ("/cost", None, calculate_cost_wrapper),
         ("/download", None, download_conversation_wrapper),
+        ("/man", None, lambda x: welcome_message),
     ]
     command_center = CommandCenter(
         default_input_type=str,