File size: 2,676 Bytes
17225cb
 
 
2fba167
17225cb
 
 
f173eae
17225cb
 
 
 
 
 
 
 
 
f173eae
17225cb
 
f173eae
17225cb
adca139
17225cb
adca139
f173eae
 
 
807b1cf
 
 
 
 
f173eae
 
 
 
807b1cf
adca139
807b1cf
17225cb
 
f173eae
17225cb
 
 
 
 
 
 
 
 
 
f173eae
17225cb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
adca139
17225cb
 
f173eae
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
import gradio as gr
import pandas as pd
import duckdb
import requests
import re
import os

# βœ… Load Together API key securely
def get_together_api_key():
    key = os.environ.get("TOGETHER_API_KEY")
    if key:
        print("βœ… TOGETHER_API_KEY loaded successfully.")
        return key
    raise RuntimeError("❌ TOGETHER_API_KEY not found. Set it in Hugging Face > Settings > Secrets.")

TOGETHER_API_KEY = get_together_api_key()

# 🧠 Generate SQL from prompt using Together API
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}

User question: "{prompt}"

Write a valid SQL query using the 'df' table. Return only the SQL code."""

    url = "https://api.together.xyz/inference"
    headers = {
        "Authorization": f"Bearer {TOGETHER_API_KEY}",
        "Content-Type": "application/json"
    }
    payload = {
        "model": "meta-llama/Llama-3-8B-Instruct",
        "prompt": full_prompt,
        "max_tokens": 300,
        "temperature": 0.5,
    }

    response = requests.post(url, headers=headers, json=payload)
    response.raise_for_status()
    result = response.json()
    return result['output'].strip("```sql").strip("```").strip()

# 🧽 Clean SQL for DuckDB compatibility
def clean_sql_for_duckdb(sql, df_columns):
    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)
    return sql

# πŸ’¬ Main Gradio function
def chatbot_interface(file, question):
    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"πŸ“œ SQL Query:\n```sql\n{sql}\n```", result
    except Exception as e:
        return f"❌ Error: {str(e)}", pd.DataFrame()

# πŸŽ›οΈ Gradio UI
with gr.Blocks() as demo:
    gr.Markdown("## πŸ“Š Excel SQL Chatbot with Together API")
    with gr.Row():
        file_input = gr.File(label="πŸ“‚ Upload Excel File (.xlsx)")
        question = gr.Textbox(label="🧠 Ask a question", placeholder="e.g., Show average salary by department")
    submit = gr.Button("πŸš€ Generate & Query")
    sql_output = gr.Markdown()
    result_table = gr.Dataframe()

    submit.click(fn=chatbot_interface, inputs=[file_input, question], outputs=[sql_output, result_table])

# πŸš€ Launch the app
if __name__ == "__main__":
    demo.launch()