Upload chat_web_demo_hf.py

chat_web_demo_hf.py

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+# coding: utf-8
+import os
+
+import openai
+import gradio as gr
+
+MAX_TURNS = 20
+MAX_BOXES = MAX_TURNS * 2
+
+openai.api_key = "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"
+
+
+# 充当DM和NLG角色
+system_0 = "你来充当易鑫集团的一个礼貌的、专业的汽车贷款专员，来给客户打电话确认贷款情况。\
+客户是黄西虢先生，刚刚扫码申请了车辆抵押分期业务，想申请贷款。\
+对话时要注意以下几点：\
+1. 不要主动结束对话，要努力保持和客户的通话，一直到加上客户的微信后，再礼貌地和客户告别。\
+2. 不要问客户要身份信息。\
+3. 不要一开始就要联系方式，需要等时机成熟时再要。\
+4. 主要关注以下几点：客户车辆是贷款购买还是全款购买、客户车辆的购车时间和年限、客户车辆品牌、客户车辆裸车价、客户期望的贷款金额、贷款资金用途、是否有行驶证证书。\
+5. 你要一步一步地询问客户问题，一次只问一个问题。\
+6. 如果客户拒绝继续沟通，不要和客户结束通话。你可以告诉客户他有办理贷款的资格，并体现出我们的合作机构民生银行这个平台来吸引客户，然后继续和客户沟通。\
+7. 只要客户拥有全款购买的车辆，或按揭贷款购买且已还清贷款的车辆，那么客户就有贷款的资格，贷款额度为车辆购买价格的80%，贷款的利息很低。 \
+8. 在办理贷款时，需要把客户的行驶证证书抵押给银行，你需要询问客户是否可以接受这一条件。\
+9. 对话的目的是加上客户的微信，并促成客户的贷款业务。\
+10. 贷款额度是裸车价的80%。\
+11. 客户必须有行驶证才能贷款。"
+
+
+def api_inference(input, history):
+    """api_inference"""
+    print('api_inference...')
+
+    # api
+    role = "user"
+    user_input = {"role": role, "content": input}
+
+    try:
+        completion = openai.ChatCompletion.create(
+            model="gpt-3.5-turbo",
+            temperature=0.0,
+            messages= history + [user_input],
+        )
+    except Exception as e:
+        print(e)
+    # add user to history
+    history.append(user_input)
+    # assistant response
+    role = completion.choices[0].message["role"]
+    response = completion.choices[0].message["content"]
+    # add assistant to history
+    assert role == "assistant"
+    assistant_response = {"role": role, "content": response}
+    history.append(assistant_response)
+
+    print('api_inference done')
+    return [history]
+
+
+def predict(input, prompt, history=None):
+    """predict"""
+    print('predict...')
+
+    if history is None:
+        history = []
+
+    history[0]["content"] = prompt
+        
+    for history in api_inference(input, history):
+        updates = []
+        for item in history[1:]:
+            role = item["role"]
+            role_txt = role
+            if role == 'user':
+                role_txt = '客户'
+            if role == 'assistant':
+                role_txt = '坐席'
+            updates.append(gr.update(visible=True, value=role_txt + ': ' + item['content']))
+
+        if len(updates) < MAX_BOXES:
+            updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
+
+        yield [history] + updates
+
+
+with gr.Blocks(title='外呼场景测试Demo') as demo:
+
+    prompt = gr.Textbox(label='prompt: (change according to your ideas)', show_label=True, value=system_0, lines=9, 
+                        interactive=True).style(container=False)
+    
+    state = gr.State([{"role": "system", "content": prompt.value},])
+    text_boxes = []
+
+    for i in range(MAX_BOXES):
+        if i % 2 == 0:
+            text_boxes.append(gr.Markdown(visible=False, label="提问："))
+        else:
+            text_boxes.append(gr.Markdown(visible=False, label="回复："))
+
+    with gr.Row():
+        with gr.Column(scale=4):
+            txt = gr.Textbox(show_label=False, placeholder="Enter text and press enter", lines=9).style(
+                container=False)
+            button = gr.Button("Generate")
+
+        with gr.Column(scale=1):
+            max_length = gr.Slider(0, 4096, value=2048, step=1.0, label="Maximum length", interactive=False)
+            top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top p", interactive=False)
+            temperature = gr.Slider(0, 1, value=0.0, step=0.01, label="Temperature", interactive=False)
+
+    button.click(predict, [txt, prompt, state], [state] + text_boxes)
+
+demo.queue().launch(share=False, inbrowser=True, server_name="0.0.0.0", server_port=8006)
+
+# gr.close_all()