Update app.py

app.py

@@ -1,70 +1,101 @@
 from transformers import AutoModel, AutoTokenizer
-import streamlit as st
-from streamlit_chat import message
-
-
-st.set_page_config(
-    page_title="帛凡 ChatGLM-6b-fitness-RLHF  演示",
-    page_icon=":robot:"
-)
-
-
-@st.cache_resource
-def get_model():
-    tokenizer = AutoTokenizer.from_pretrained("fb700/chatglm-fitness-RLHF/chatglm_rlhf", trust_remote_code=True)
-    #model = AutoModel.from_pretrained("THUDM/chatglm-6b", trust_remote_code=True).half().cuda()
-    model = AutoModel.from_pretrained("D:\glm\chatglm_webui\chatglm-6b", trust_remote_code=True).quantize(8).half().cuda()
-    model = model.eval()
-    return tokenizer, model
-
+import gradio as gr
+import mdtex2html
+
+tokenizer = AutoTokenizer.from_pretrained("fb700/chatglm-fitness-RLHF/chatglm_rlhf", trust_remote_code=True)
+model = AutoModel.from_pretrained("fb700/chatglm-fitness-RLHF/chatglm_rlhf", trust_remote_code=True).quantize(8).half().cuda()
+model = model.eval()
+
+"""Override Chatbot.postprocess"""
+
+
+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, chatbot, max_length, top_p, temperature, history):
+    chatbot.append((parse_text(input), ""))
+    for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
+                                               temperature=temperature):
+        chatbot[-1] = (parse_text(input), parse_text(response))       
 
-MAX_TURNS = 20
-MAX_BOXES = MAX_TURNS * 2
+        yield chatbot, history
 
 
-def predict(input, max_length, top_p, temperature, history=None):
-    tokenizer, model = get_model()
-    if history is None:
-        history = []
+def reset_user_input():
+    return gr.update(value='')
 
-    with container:
-        if len(history) > 0:
-            for i, (query, response) in enumerate(history):
-                message(query, avatar_style="big-smile", key=str(i) + "_user")
-                message(response, avatar_style="bottts", key=str(i))
 
-        message(input, avatar_style="big-smile", key=str(len(history)) + "_user")
-        st.write("AI正在回复:")
-        with st.empty():
-            for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
-                                               temperature=temperature):
-                query, response = history[-1]
-                st.write(response)
+def reset_state():
+    return [], []
 
-    return history
 
+with gr.Blocks() as demo:
+    gr.HTML("""<h1 align="center">帛凡 ChatGLM-6b-fitness-RLHF  演示</h1>""")
 
-container = st.container()
+    chatbot = gr.Chatbot()
+    with gr.Row():
+        with gr.Column(scale=4):
+            with gr.Column(scale=12):
+                user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=10).style(
+                    container=False)
+            with gr.Column(min_width=32, scale=1):
+                submitBtn = gr.Button("Submit", variant="primary")
+        with gr.Column(scale=1):
+            emptyBtn = gr.Button("Clear History")
+            max_length = gr.Slider(0, 409600, value=2048, step=1.0, label="Maximum length", interactive=True)
+            top_p = gr.Slider(0, 1, value=0.7, step=0.01, label="Top P", interactive=True)
+            temperature = gr.Slider(0, 1, value=0.95, step=0.01, label="Temperature", interactive=True)
 
-# create a prompt text for the text generation
-prompt_text = st.text_area(label="用户命令输入",
-            height = 100,
-            placeholder="请在这儿输入您的命令")
+    history = gr.State([])
 
-max_length = st.sidebar.slider(
-    'max_length', 0, 40960, 20480, step=1
-)
-top_p = st.sidebar.slider(
-    'top_p', 0.0, 1.0, 0.6, step=0.01
-)
-temperature = st.sidebar.slider(
-    'temperature', 0.0, 1.0, 0.95, step=0.01
-)
+    submitBtn.click(predict, [user_input, chatbot, max_length, top_p, temperature, history], [chatbot, history],
+                    show_progress=True)
+    submitBtn.click(reset_user_input, [], [user_input])
 
-if 'state' not in st.session_state:
-    st.session_state['state'] = []
+    emptyBtn.click(reset_state, outputs=[chatbot, history], show_progress=True)
 
-if st.button("发送", key="predict"):
-    with st.spinner("AI正在思考，请稍等........"):
-        # text generation
-        st.session_state["state"] = predict(prompt_text, max_length, top_p, temperature, st.session_state["state"])
+demo.queue().launch(share=True, inbrowser=True)