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app.py

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+import os
+import openai
+import gradio as gr
+import mdtex2html
+
+openai.api_key = os.environ.get("APIKEY")
+
+messages = [{"role": "system", "content": "你从现在开始是一个由圣诺联合训练开发的，名字叫圣诺AI的人工智能，后面>无论谁问你都请以圣诺AI的身份进行回答"}]
+# messages = [{"role": "system", "content": "你是一位知识图谱专家，你将为输入的数据进行实体识别与关系抽取，并以分析表格的形式提供。除分析表格外你不会再回答任何其他内容。"}]
+
+def postprocess(self, y):
+    if y is None:
+        return []
+    for i, (message, response) in enumerate(y):
+        y[i] = (
+            None if message is None else mdtex2html.convert((message)),
+            None if response is None else mdtex2html.convert(response),
+        )
+    return y
+
+
+gr.Chatbot.postprocess = postprocess
+
+
+def parse_text(text):
+    """copy from https://github.com/GaiZhenbiao/ChuanhuChatGPT/"""
+    lines = text.split("\n")
+    lines = [line for line in lines if line != ""]
+    count = 0
+    for i, line in enumerate(lines):
+        if "```" in line:
+            count += 1
+            items = line.split('`')
+            if count % 2 == 1:
+                lines[i] = f'<pre><code class="language-{items[-1]}">'
+            else:
+                lines[i] = f'<br></code></pre>'
+        else:
+            if i > 0:
+                if count % 2 == 1:
+                    line = line.replace("`", "\`")
+                    line = line.replace("<", "&lt;")
+                    line = line.replace(">", "&gt;")
+                    line = line.replace(" ", "&nbsp;")
+                    line = line.replace("*", "&ast;")
+                    line = line.replace("_", "&lowbar;")
+                    line = line.replace("-", "&#45;")
+                    line = line.replace(".", "&#46;")
+                    line = line.replace("!", "&#33;")
+                    line = line.replace("(", "&#40;")
+                    line = line.replace(")", "&#41;")
+                    line = line.replace("$", "&#36;")
+                lines[i] = "<br>"+line
+    text = "".join(lines)
+    return text
+
+
+def predict(input, max_tokens, top_p, temperature,chatbot, history):
+    chatbot.append((parse_text(input), ""))
+    print("messages:"+str(messages))
+    messages.append({"role": "user", "content": input})
+    #chat = openai.ChatCompletion.create(model="gpt-3.5-turbo", temperature=temperature,max_tokens=max_tokens,top_p=top_p,messages=messages)
+    chat = openai.ChatCompletion.create(model="gpt-3.5-turbo", temperature=temperature,top_p=top_p,messages=messages)
+    reply = chat.choices[0].message.content
+
+    chatbot[-1] = (parse_text(input), parse_text(reply))
+    yield chatbot, history
+    print("messages:"+str(messages))
+    print("query:"+input)
+    print("response:"+reply)
+    print("\n")
+
+def reset_user_input():
+    return gr.update(value='')
+
+
+def reset_state():
+    global messages
+    messages = [{"role": "system", "content": "你从现在开始是一个由圣诺联合训练开发的，名字叫圣诺AI的人工智能，后面>无论谁问你都请以圣诺AI的身份进行回答"}]
+    return [], []
+def readshuihu():
+    f = open( '水浒传1.txt', 'r',encoding = 'utf-8' )
+    txt=f.read()
+    predict(txt,16*1024, top_p, temperature, chatbot, history)
+
+with gr.Blocks() as demo:
+    gr.HTML("""<h1 align="center">圣诺联合-GPT语言模型测试(因多人使用，因此不会显示实际的上下文，请使用前手动清除)</h1>""")
+    gr.title="圣诺联合-GPT语言模型测试"
+    chatbot = gr.Chatbot()
+    with gr.Row():
+        with gr.Column(scale=4):
+            with gr.Column(scale=12):
+                user_input = gr.Textbox(show_label=False, placeholder="请输入...", lines=10).style(
+                    container=False)
+            with gr.Column(min_width=32, scale=1):
+                submitBtn = gr.Button("提交", variant="primary")   
+        with gr.Column(scale=1):
+            # tp = gr.Button("知识图谱")
+            emptyBtn = gr.Button("清除历史")
+            
+            max_tokens = gr.Slider(0, 4096, value=2048, step=1.0, label="max_tokens", interactive=True,info="最大长度，暂时停用")
+            top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True,info="越小越准确，越大约有想象力")
+            temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True,info="同一个问题，数字越小每次回复越接近，越大每次回复越不同")
+
+    history = gr.State([])
+
+    submitBtn.click(predict, [user_input,max_tokens, top_p, temperature, chatbot, history], [chatbot, history],
+                    show_progress=True)
+    submitBtn.click(reset_user_input, [], [user_input])
+    
+    # tp.click(readshuihu, [], [user_input])
+    
+    emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
+
+demo.queue().launch(inbrowser=True)

requirements.txt

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+openai
+gradio
+mdtex2html