Update app.py

app.py

@@ -5,79 +5,75 @@ import requests
 import re
 import os
 
-# ✅ Securely load Together API Key
-def get_together_api_key():
-    key = os.environ.get("TOGETHER_API_KEY")
-    if key:
-        print("✅ TOGETHER_API_KEY loaded successfully.")
-        return key
-    raise RuntimeError("❌ TOGETHER_API_KEY not found. Set it in Hugging Face > Settings > Secrets.")
+# Load API Key
+def get_api_key():
+    key = os.getenv("TOGETHER_API_KEY")
+    print("🔐 API KEY:", "FOUND" if key else "NOT FOUND")
+    if not key:
+        raise RuntimeError("🔴 MISSING TOGETHER_API_KEY!")
+    return key
 
-TOGETHER_API_KEY = get_together_api_key()
+API_KEY = get_api_key()
 
-# 🧠 Generate SQL from prompt using Together's /inference endpoint
-def generate_sql_from_prompt(prompt, df):
-    schema = ", ".join([f"{col} ({str(dtype)})" for col, dtype in df.dtypes.items()])
-    full_prompt = f"""
-You are a SQL expert. Here is a table called 'df' with the following schema:
-{schema}
+# Generate SQL with detailed logging
+def generate_sql(prompt, df):
+    schema = ", ".join([f"{col} ({dtype})" for col, dtype in df.dtypes.items()])
+    full_prompt = f"""You are a SQL expert. Table 'df' schema: {schema}
 
 User question: "{prompt}"
-
-Write a valid SQL query using the 'df' table. Return only the SQL code.
-"""
+Return only valid SQL."""
+    print("📢 FULL PROMPT:\n", full_prompt)
 
     url = "https://api.together.xyz/v1/completions"
     headers = {
-        "Authorization": f"Bearer {TOGETHER_API_KEY}",
+        "Authorization": f"Bearer {API_KEY}",
         "Content-Type": "application/json"
     }
     payload = {
-        "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",  # You can use "meta-llama/Llama-3-8B-Instruct" too
+        "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
         "prompt": full_prompt,
-        "max_tokens": 300,
-        "temperature": 0.7,
+        "max_tokens": 200,
+        "temperature": 0.2
     }
+    print("📡 Calling Together API:", url, payload)
+    resp = requests.post(url, headers=headers, json=payload)
+    print("🟢 HTTP Status:", resp.status_code)
+    print("🧾 Response Body:", resp.text)
+    resp.raise_for_status()
+    j = resp.json()
+    if "choices" in j:
+        return j["choices"][0]["text"].strip()
+    return j.get("output", "")
 
-    response = requests.post(url, headers=headers, json=payload)
-    response.raise_for_status()
-    result = response.json()
-    return result['choices'][0]['text'].strip("```sql").strip("```").strip()
-
-# 🧽 Clean SQL for DuckDB compatibility
-def clean_sql_for_duckdb(sql, df_columns):
+# Clean SQL
+def clean_sql(sql, cols):
     sql = sql.replace("`", '"')
-    for col in df_columns:
-        if " " in col and f'"{col}"' not in sql:
-            pattern = r'\b' + re.escape(col) + r'\b'
-            sql = re.sub(pattern, f'"{col}"', sql)
+    for c in cols:
+        if " " in c and f'"{c}"' not in sql:
+            sql = re.sub(rf'\b{re.escape(c)}\b', f'"{c}"', sql)
     return sql
 
-# 💬 Main chatbot function
-def chatbot_interface(file, question):
+# Main function
+def chat_interface(file, q):
     try:
         df = pd.read_excel(file)
-        sql = generate_sql_from_prompt(question, df)
-        cleaned_sql = clean_sql_for_duckdb(sql, df.columns)
-        result = duckdb.query(cleaned_sql).to_df()
-        return f"📜 SQL Query:\n```sql\n{sql}\n```", result
+        sql = generate_sql(q, df)
+        sql = clean_sql(sql, df.columns)
+        print("✅ Final SQL:", sql)
+        df_res = duckdb.query(sql).to_df()
+        return f"📜 SQL:\n```sql\n{sql}\n```", df_res
     except Exception as e:
-        return f"❌ Error: {str(e)}", pd.DataFrame()
-
+        print("🔥 EXCEPTION:", repr(e))
+        return f"❌ Error: {e}", pd.DataFrame()
 
-
-# 🎛️ Gradio UI
 with gr.Blocks() as demo:
-    gr.Markdown("## 📊 Excel SQL Chatbot with Together API")
-    with gr.Row():
-        file_input = gr.File(label="📂 Upload Excel File (.xlsx)")
-        question = gr.Textbox(label="🧠 Ask a question", placeholder="e.g., Show average salary by department")
-    submit = gr.Button("🚀 Generate & Query")
-    sql_output = gr.Markdown()
-    result_table = gr.Dataframe()
-
-    submit.click(fn=chatbot_interface, inputs=[file_input, question], outputs=[sql_output, result_table])
+    gr.Markdown("## SQL Chatbot – Debug Mode")
+    file_in = gr.File(label="Upload Excel")
+    q_in = gr.Textbox(label="Question")
+    bt = gr.Button("Run")
+    md = gr.Markdown()
+    tbl = gr.Dataframe()
+    bt.click(chat_interface, [file_in, q_in], [md, tbl])
 
-# 🚀 Launch the app
 if __name__ == "__main__":
     demo.launch()