Update app.py

app.py

@@ -15,29 +15,27 @@ from langchain_community.utilities.sql_database import SQLDatabase
 from datasets import load_dataset
 import tempfile
 
-st.title("Blah Blah App 🚀")
+st.title("Blah Blah App \U0001F680")
 st.write("Analyze datasets using natural language queries.")
 
-# LLM Initialization
 def initialize_llm(model_choice):
     groq_api_key = os.getenv("GROQ_API_KEY")
     openai_api_key = os.getenv("OPENAI_API_KEY")
 
     if model_choice == "llama-3.3-70b":
         if not groq_api_key:
-            st.error("Groq API key is missing.")
+            st.error("Groq API key is missing. Please set the GROQ_API_KEY environment variable.")
             return None
         return ChatGroq(groq_api_key=groq_api_key, model="groq/llama-3.3-70b-versatile")
     elif model_choice == "GPT-4o":
         if not openai_api_key:
-            st.error("OpenAI API key is missing.")
+            st.error("OpenAI API key is missing. Please set the OPENAI_API_KEY environment variable.")
             return None
         return ChatOpenAI(api_key=openai_api_key, model="gpt-4o")
 
 model_choice = st.radio("Select LLM", ["GPT-4o", "llama-3.3-70b"], index=0, horizontal=True)
 llm = initialize_llm(model_choice)
 
-# Dataset Loading 
 def load_dataset_into_session():
     input_option = st.radio("Select Dataset Input:", ["Use Hugging Face Dataset", "Upload CSV File"])
     if input_option == "Use Hugging Face Dataset":
@@ -61,7 +59,6 @@ if "df" not in st.session_state:
     st.session_state.df = None
 load_dataset_into_session()
 
-# Database Initialization 
 def initialize_database(df):
     temp_dir = tempfile.TemporaryDirectory()
     db_path = os.path.join(temp_dir.name, "patent_data.db")
@@ -70,23 +67,24 @@ def initialize_database(df):
     db = SQLDatabase.from_uri(f"sqlite:///{db_path}")
     return db, temp_dir
 
-# SQL Tools
 def create_sql_tools(db):
     @tool("list_tables")
     def list_tables() -> str:
+        """List all tables in the patent database."""
         return ListSQLDatabaseTool(db=db).invoke("")
 
     @tool("tables_schema")
     def tables_schema(tables: str) -> str:
+        """Get schema and sample rows for given tables."""
         return InfoSQLDatabaseTool(db=db).invoke(tables)
 
     @tool("execute_sql")
     def execute_sql(sql_query: str) -> str:
+        """Execute a SQL query against the patent database."""
         return QuerySQLDataBaseTool(db=db).invoke(sql_query)
 
     return list_tables, tables_schema, execute_sql
 
-# Agent Initialization
 def initialize_agents(llm, tools):
     list_tables, tables_schema, execute_sql = tools
 
@@ -114,7 +112,6 @@ def initialize_agents(llm, tools):
 
     return sql_agent, analyst_agent, writer_agent
 
-# Crew and Tasks Setup
 def setup_crew(sql_agent, analyst_agent, writer_agent):
     extract_task = Task(
         description="Extract patents related to the query: {query}.",
@@ -143,7 +140,6 @@ def setup_crew(sql_agent, analyst_agent, writer_agent):
         verbose=True,
     )
 
-    # Execution Flow
 if st.session_state.df is not None:
     db, temp_dir = initialize_database(st.session_state.df)
     tools = create_sql_tools(db)
@@ -152,9 +148,12 @@ if st.session_state.df is not None:
 
     query = st.text_area("Enter Patent Analysis Query:", placeholder="e.g., 'How many patents related to Machine Learning were filed after 2016?'")
     if st.button("Submit Query"):
-        with st.spinner("Processing your query..."):
-            result = crew.kickoff(inputs={"query": query})
-            st.markdown("### 📊 Patent Analysis Report")
-            st.markdown(result)
+        if query.strip():
+            with st.spinner("Processing your query..."):
+                result = crew.kickoff(inputs={"query": query})
+                st.markdown("### 📊 Patent Analysis Report")
+                st.markdown(result)
+        else:
+            st.warning("Please enter a valid query.")
 else:
     st.info("Please load a patent dataset to proceed.")