run a demo

pilot/server/chatbot.py

@@ -1,3 +1,56 @@
 #!/usr/bin/env python3
 # -*- coding:utf-8 -*-
 
+import requests
+import json
+import time
+from urllib.parse import urljoin
+import gradio as gr
+from configs.model_config import *
+vicuna_base_uri = "http://192.168.31.114:21002/"
+vicuna_stream_path = "worker_generate_stream"
+vicuna_status_path = "worker_get_status"
+
+def generate(prompt):
+    params = {
+        "model": "vicuna-13b",
+        "prompt": "给出一个查询用户的SQL",
+        "temperature": 0.7,
+        "max_new_tokens": 512,
+        "stop": "###"
+    }
+
+    sts_response = requests.post(
+        url=urljoin(vicuna_base_uri, vicuna_status_path)
+    )
+    print(sts_response.text)
+
+    response = requests.post(
+        url=urljoin(vicuna_base_uri, vicuna_stream_path), data=json.dumps(params)
+    )
+
+    skip_echo_len = len(params["prompt"]) + 1 - params["prompt"].count("</s>") * 3
+    for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
+        if chunk:
+            data = json.loads(chunk.decode())
+            if data["error_code"] == 0:
+                output = data["text"]
+                yield(output) 
+            
+            time.sleep(0.02)
+
+if __name__ == "__main__":
+    print(LLM_MODEL)
+    with gr.Blocks() as demo:
+        gr.Markdown("数据库SQL生成助手")
+        with gr.Tab("SQL生成"):
+            text_input = gr.TextArea()
+            text_output = gr.TextArea()
+            text_button = gr.Button("提交")
+        
+
+        text_button.click(generate, inputs=text_input, outputs=text_output)
+
+    demo.queue(concurrency_count=3).launch(server_name="0.0.0.0") 
+
+