Upload 3 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+Chinook.db filter=lfs diff=lfs merge=lfs -text

Chinook.db

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:7651ba378ac2fcd0dfc3c66fb101f7a7eed3ba39a612ec642b96e20702061f15
+size 1007616

app (1).py

@@ -0,0 +1,73 @@
+import sqlite3
+import pandas as pd
+import gradio as gr
+from langchain_community.llms import HuggingFacePipeline
+from transformers import AutoTokenizer, AutoModelForCausalLM, pipeline
+
+# ============================================================
+# 🚀 Load SQLCoder model
+# ============================================================
+model_id = "defog/sqlcoder-7b-2"
+
+tokenizer = AutoTokenizer.from_pretrained(model_id)
+model = AutoModelForCausalLM.from_pretrained(
+    model_id,
+    torch_dtype="auto",
+    device_map="auto"
+)
+
+pipe = pipeline(
+    "text-generation",
+    model=model,
+    tokenizer=tokenizer,
+    max_new_tokens=256,
+    do_sample=False
+)
+
+sqlcoder_llm = HuggingFacePipeline(pipeline=pipe)
+
+# ============================================================
+# 🧠 Define query function
+# ============================================================
+def ask_question(user_db, question):
+    """Takes an uploaded SQLite database + a question, returns SQL + result"""
+    if not user_db:
+        return "❌ Please upload a database file.", None
+
+    conn = sqlite3.connect(user_db.name)
+    cursor = conn.cursor()
+
+    # Create a Text-to-SQL prompt
+    prompt = f"Translate this question into an SQLite query:\nQuestion: {question}\nSQL:"
+    sql_query = sqlcoder_llm(prompt)
+
+    try:
+        cursor.execute(sql_query)
+        rows = cursor.fetchall()
+        columns = [desc[0] for desc in cursor.description]
+        df = pd.DataFrame(rows, columns=columns)
+        conn.close()
+        return sql_query, df
+    except Exception as e:
+        conn.close()
+        return f"❌ Error executing query: {e}", None
+
+# ============================================================
+# 🎨 Gradio UI
+# ============================================================
+demo = gr.Interface(
+    fn=ask_question,
+    inputs=[
+        gr.File(label="Upload SQLite Database (.db)"),
+        gr.Textbox(label="Ask your question")
+    ],
+    outputs=[
+        gr.Textbox(label="Generated SQL Query"),
+        gr.Dataframe(label="Query Result")
+    ],
+    title="🧠 Text-to-SQL on Your Own Database",
+    description="Upload your SQLite database and ask natural language questions."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements (1).txt

@@ -0,0 +1,11 @@
+gradio
+langchain
+langchain-community
+langchain-huggingface
+transformers
+accelerate
+bitsandbytes
+chromadb
+sqlalchemy
+huggingface_hub
+pandas