Update app.py

app.py

@@ -88,7 +88,7 @@ def get_conversation_chain(vectorstore):
     - ConversationalRetrievalChain: An initialized conversational chain object.
     """
     try:
-        llm = ChatOpenAI(model_name="gpt-4-1106-preview")
+        llm = ChatOpenAI(model_name="gpt-4o")
         memory = ConversationBufferMemory(
             memory_key="chat_history", return_messages=True
         )
@@ -133,14 +133,15 @@ def get_user_chat_count(user_id):
         )
         cursor = conn.cursor()
 
-        cursor.execute("SELECT count FROM Chat WHERE user_id = %s", (user_id,))
+        cursor.execute("SELECT count FROM birdseye_chat WHERE user_id = %s", (user_id,))
         result = cursor.fetchone()
         if result:
             return result[0]
         else:
             # Insert a new row for the user if not found
             cursor.execute(
-                "INSERT INTO Chat (user_id, count) VALUES (%s, %s)", (user_id, 0)
+                "INSERT INTO birdseye_chat (user_id, count) VALUES (%s, %s)",
+                (user_id, 0),
             )
             conn.commit()
             return 0
@@ -216,32 +217,6 @@ def chat(slug, user_id):
     flow and displaying the chat history.
     Restricts chat based on user group and chat count.
     """
-    try:
-        conn = mysql.connector.connect(
-            user=os.getenv("SQL_USER"),
-            password=os.getenv("SQL_PWD"),
-            host=os.getenv("SQL_HOST"),
-            database="Birdseye_DB",
-        )
-        cursor = conn.cursor()
-
-        # Execute a query
-        cursor.execute("SELECT ocr_text FROM birdseye_temp WHERE slug = %s", (slug,))
-
-        # Fetch the results
-        rows = cursor.fetchall()
-        text = ""
-        for row in rows:
-            if row[0]:
-                text += row[0]
-
-    except mysql.connector.Error as err:
-        st.error(f"Error: {err}")
-        return
-    finally:
-        if conn.is_connected():
-            cursor.close()
-            conn.close()
 
     text_chunks = get_text_chunks(get_pdf_text(slug))
     vectorstore = get_vectorstore(text_chunks)