Update app.py

app.py

@@ -9,12 +9,9 @@ from typing_extensions import TypedDict
 from langgraph.graph import StateGraph, START, END
 import csv
 
-# Load API keys
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-# --- Initialize Database from external CSV ---
 def init_db_from_csv(csv_path: str = "transactions.csv") -> None:
-    """Create 'transactions' table and load data from the provided CSV file."""
     conn = sqlite3.connect("shop.db")
     cur = conn.cursor()
     cur.execute(
@@ -23,7 +20,6 @@ def init_db_from_csv(csv_path: str = "transactions.csv") -> None:
     with open(csv_path, newline='') as f:
         reader = csv.DictReader(f)
         rows = [(row["date"], row["product"], float(row["amount"])) for row in reader]
-    # Replace old data
     cur.execute("DELETE FROM transactions")
     cur.executemany(
         "INSERT INTO transactions (date, product, amount) VALUES (?, ?, ?)", rows
@@ -31,11 +27,8 @@ def init_db_from_csv(csv_path: str = "transactions.csv") -> None:
     conn.commit()
     conn.close()
 
-# Initialize DB at startup (ensure transactions.csv is present)
 init_db_from_csv()
 
-# --- Business Logic Functions ---
-
 def db_agent(query: str) -> str:
     try:
         conn = sqlite3.connect("shop.db")
@@ -57,7 +50,6 @@ def db_agent(query: str) -> str:
     except sqlite3.OperationalError as e:
         return f"Database error: {e}. Please check 'transactions' table in shop.db."
 
-
 def web_search_agent(query: str) -> str:
     try:
         resp = requests.get(
@@ -71,7 +63,6 @@ def web_search_agent(query: str) -> str:
         pass
     return llm_agent(query)
 
-
 def llm_agent(query: str) -> str:
     response = openai.chat.completions.create(
         model="gpt-4o-mini",
@@ -83,7 +74,6 @@ def llm_agent(query: str) -> str:
     )
     return response.choices[0].message.content.strip()
 
-
 def stt_agent(audio_path: str) -> str:
     with open(audio_path, "rb") as afile:
         transcript = openai.audio.transcriptions.create(
@@ -92,20 +82,16 @@ def stt_agent(audio_path: str) -> str:
         )
     return transcript.text.strip()
 
-
 def tts_agent(text: str, lang: str = 'en') -> str:
     tts = gTTS(text=text, lang=lang)
     out_path = "response_audio.mp3"
     tts.save(out_path)
     return out_path
 
-# --- LangGraph State and Nodes ---
 class State(TypedDict):
     query: str
     result: str
 
-# Routing logic based on query
-
 def route_fn(state: State) -> str:
     q = state["query"].lower()
     if any(k in q for k in ["max revenue", "revenue"]):
@@ -114,8 +100,6 @@ def route_fn(state: State) -> str:
         return "web"
     return "llm"
 
-# Node implementations
-
 def router_node(state: State) -> dict:
     return {"query": state["query"]}
 
@@ -128,7 +112,6 @@ def web_node(state: State) -> dict:
 def llm_node(state: State) -> dict:
     return {"result": llm_agent(state["query"]) }
 
-# Build the LangGraph
 builder = StateGraph(State)
 builder.add_node("router", router_node)
 builder.set_entry_point("router")
@@ -145,7 +128,6 @@ builder.add_edge("web", END)
 builder.add_edge("llm", END)
 graph = builder.compile()
 
-# Handler integrates STT/TTS and graph execution
 def handle_query(audio_or_text: str):
     is_audio = audio_or_text.endswith('.wav') or audio_or_text.endswith('.mp3')
     if is_audio:
@@ -161,14 +143,12 @@ def handle_query(audio_or_text: str):
         return response, audio_path
     return response
 
-# --- Gradio UI ---
 with gr.Blocks() as demo:
     gr.Markdown("## Shop Voice-Box Assistant (Speech In/Out)")
     inp = gr.Audio(sources=["microphone"], type="filepath", label="Speak or type your question or upload transactions.csv separately in root")
     out_text = gr.Textbox(label="Answer (text)")
     out_audio = gr.Audio(label="Answer (speech)")
     submit = gr.Button("Submit")
-    # Examples
     gr.Examples(
         examples=[
             ["What is the max revenue product today?"],
@@ -181,4 +161,4 @@ with gr.Blocks() as demo:
     submit.click(fn=handle_query, inputs=inp, outputs=[out_text, out_audio])
 
 if __name__ == "__main__":
-    demo.launch(share=False, server_name="0.0.0.0", server_port=7860)
+    demo.launch(share=False, server_name="0.0.0.0", server_port=7860)