SQL Copilot: Qwen2.5-Coder-7B on ZeroGPU

README.md

@@ -1,13 +1,23 @@
 ---
-title: Sql Copilot
-emoji: 📚
-colorFrom: green
+title: SQL Copilot
+emoji: 🧮
+colorFrom: purple
 colorTo: blue
 sdk: gradio
-sdk_version: 6.29.1
-python_version: '3.12'
+sdk_version: 5.50.0
 app_file: app.py
 pinned: false
+license: apache-2.0
+short_description: Plain-English questions to DuckDB SQL (Qwen2.5-Coder-7B)
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# SQL Copilot
+
+Natural-language to DuckDB SQL for the Data Lab on Feliks Altymyshov's
+portfolio, using `Qwen/Qwen2.5-Coder-7B-Instruct` on ZeroGPU.
+
+- **Privacy:** the site sends only table schemas and a few sample rows, never
+  the full data. Queries run in the visitor's browser.
+- **API:** `/ask` takes `(question, schema)` and returns `[sql, error]`.
+
+Redeploy: `hf upload feliksKdm/sql-copilot hf-spaces/sql-copilot . --type space`

app.py

@@ -0,0 +1,102 @@
+"""
+SQL Copilot — plain-English questions to DuckDB SQL with Qwen2.5-Coder-7B on
+ZeroGPU. The portfolio's Data Lab sends table schemas (plus a few sample rows)
+and runs the returned SQL locally in DuckDB-WASM. Errors travel as data.
+"""
+
+import re
+import traceback
+
+import gradio as gr
+import spaces
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+MODEL = "Qwen/Qwen2.5-Coder-7B-Instruct"
+MAX_QUESTION = 500
+MAX_SCHEMA = 8000
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL)
+model = AutoModelForCausalLM.from_pretrained(MODEL, torch_dtype=torch.bfloat16).to("cuda")
+
+SYSTEM = """You are an expert data analyst who writes DuckDB SQL.
+Rules:
+- Answer with ONE DuckDB SQL query and nothing else: no explanation, no comments.
+- Use only the tables and columns in the schema. Quote identifiers with double quotes when they contain capitals, spaces or symbols.
+- Prefer readable column aliases, ORDER BY for rankings, and LIMIT 100 for row listings.
+- For dates use DuckDB functions such as date_trunc, strftime, extract.
+- Round averages and percentages to 2 decimals.
+- Read-only: never write CREATE, INSERT, UPDATE, DELETE, DROP, ALTER, COPY, ATTACH or INSTALL."""
+
+WRITE = re.compile(r"\b(create|insert|update|delete|drop|alter|copy|attach|install|load|pragma|export)\b", re.I)
+
+
+@spaces.GPU(duration=20)
+def complete(messages):
+    text = tokenizer.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
+    inputs = tokenizer([text], return_tensors="pt").to("cuda")
+    with torch.inference_mode():
+        out = model.generate(**inputs, max_new_tokens=400, do_sample=False, pad_token_id=tokenizer.eos_token_id)
+    return tokenizer.decode(out[0][inputs.input_ids.shape[1]:], skip_special_tokens=True)
+
+
+def extract_sql(reply):
+    m = re.search(r"```(?:sql)?\s*(.*?)```", reply, re.S | re.I)
+    sql = (m.group(1) if m else reply).strip().rstrip(";").strip()
+    return sql
+
+
+def ask(question, schema):
+    """API: returns (sql, error)."""
+    try:
+        question = (question or "").strip()
+        schema = (schema or "").strip()
+        if not question:
+            return "", "Ask a question about your data first."
+        if len(question) > MAX_QUESTION:
+            return "", f"Keep the question under {MAX_QUESTION} characters."
+        if not schema:
+            return "", "Load a table first."
+        schema = schema[:MAX_SCHEMA]
+        reply = complete([
+            {"role": "system", "content": SYSTEM},
+            {"role": "user", "content": f"Schema:\n{schema}\n\nQuestion: {question}"},
+        ])
+        sql = extract_sql(reply)
+        if not sql or not re.match(r"^\s*(with|select|from|summarize|describe|pivot|unpivot)\b", sql, re.I):
+            return "", "Couldn't turn that into a query. Try rephrasing it."
+        if WRITE.search(re.sub(r"'[^']*'", "''", sql)):
+            return "", "The copilot only writes read-only queries."
+        return sql, ""
+    except gr.Error as exc:
+        return "", str(exc.message)
+    except Exception as exc:
+        traceback.print_exc()
+        return "", f"The copilot failed ({type(exc).__name__}). Please try again."
+
+
+def ui_ask(question, schema):
+    sql, error = ask(question, schema)
+    if error:
+        raise gr.Error(error)
+    return sql
+
+
+with gr.Blocks(title="SQL Copilot") as demo:
+    gr.Markdown(
+        "# 🧮 SQL Copilot\nPlain-English questions to DuckDB SQL with Qwen2.5-Coder-7B. Part of "
+        "[Feliks Altymyshov's](https://github.com/feliksKdm) portfolio lab."
+    )
+    schema = gr.Textbox(label="Schema", lines=6, placeholder='orders(order_id BIGINT, order_date DATE, store VARCHAR, revenue DOUBLE)')
+    question = gr.Textbox(label="Question", placeholder="Which store had the highest revenue last month?")
+    btn = gr.Button("Write SQL", variant="primary")
+    out = gr.Code(label="SQL", language="sql")
+    btn.click(ui_ask, [question, schema], out, api_name=False)
+
+    with gr.Group(visible=False):
+        a_q, a_s, a_sql, a_err = gr.Textbox(), gr.Textbox(), gr.Textbox(), gr.Textbox()
+        a_btn = gr.Button()
+    a_btn.click(ask, [a_q, a_s], [a_sql, a_err], api_name="ask")
+
+if __name__ == "__main__":
+    demo.queue(default_concurrency_limit=2).launch()

requirements.txt

@@ -0,0 +1,3 @@
+torch
+transformers>=4.46
+accelerate