Update app.py

app.py

@@ -1,62 +1,23 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
+from transformers import pipeline
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# 加载 SQLCoder 模型
+sqlcoder = pipeline("text2text-generation", model="defog/sqlcoder-7b")
 
+def generate_sql(user_question, create_table_statements):
+    prompt = f"Generate a SQL query to answer this question: \"{user_question}\"\nDDL statements:\n{create_table_statements}\n"
+    result = sqlcoder(prompt)
+    return result[0]['generated_text']
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# 创建 Gradio 界面
+with gr.Blocks() as demo:
+    gr.Markdown("## SQL Query Generator")
+    user_question = gr.Textbox(label="User Question", placeholder="请输入您的问题...")
+    create_table_statements = gr.Textbox(label="DDL Statements", placeholder="请输入表的 DDL 语句...")
+    output_sql = gr.Textbox(label="Generated SQL Query", interactive=False)
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+    submit_btn = gr.Button("Generate SQL")
+    submit_btn.click(generate_sql, inputs=[user_question, create_table_statements], outputs=output_sql)
 
 
 if __name__ == "__main__":