Update app.py

app.py

@@ -1,27 +1,32 @@
 from transformers import AutoModel, AutoTokenizer
 import gradio as gr
 import json
-model_path = 'THUDM/chatglm-6b'
+model_path = 'THUDM/chatglm-6b-int4-qe'
 tokenizer = AutoTokenizer.from_pretrained(model_path, trust_remote_code=True)
-model = AutoModel.from_pretrained(model_path, trust_remote_code=True).bfloat16()
+model = AutoModel.from_pretrained(model_path, trust_remote_code=True).half().float()
 model = model.eval()
 
 MAX_TURNS = 20
 MAX_BOXES = MAX_TURNS * 2
 
 
-def predict(input, max_length, top_p, temperature, history=None):
-    if history is None:
-        history = []
-    response, history = model.chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
-                                   temperature=temperature)
-    updates = []
-    for query, response in history:
-        updates.append(gr.update(visible=True, value="用户：" + query))
-        updates.append(gr.update(visible=True, value="ChatGLM-6B：" + response))
-    if len(updates) < MAX_BOXES:
-        updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
-    return [history] + updates
+def predict(input, max_length, top_p, temperature, history=None, state=None):
+    if state is None:
+        state = []
+    if history is None or history == "":
+        history = state
+    else:
+        history = json.loads(history)
+
+    for response, history in model.stream_chat(tokenizer, input, history, max_length=max_length, top_p=top_p,
+                                               temperature=temperature):
+        updates = []
+        for query, response in history:
+            updates.append(gr.update(visible=True, value=query))
+            updates.append(gr.update(visible=True, value=response))
+        if len(updates) < MAX_BOXES:
+            updates = updates + [gr.Textbox.update(visible=False)] * (MAX_BOXES - len(updates))
+        yield [history] + updates
 
 
 with gr.Blocks() as demo:
@@ -29,9 +34,9 @@ with gr.Blocks() as demo:
     text_boxes = []
     for i in range(MAX_BOXES):
         if i % 2 == 0:
-            text_boxes.append(gr.Markdown(visible=False, label="提问："))
+            text_boxes.append(gr.Text(visible=False, label="提问："))
         else:
-            text_boxes.append(gr.Markdown(visible=False, label="回复："))
+            text_boxes.append(gr.Text(visible=False, label="回复："))
 
     with gr.Row():
         with gr.Column(scale=4):
@@ -41,6 +46,7 @@ with gr.Blocks() as demo:
             max_length = gr.Slider(0, 4096, 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)
+            history = gr.TextArea(visible=False)
             button = gr.Button("Generate")
-    button.click(predict, [txt, max_length, top_p, temperature, state], [state] + text_boxes)
-demo.queue().launch(share=True, inbrowser=True)
+    button.click(predict, [txt, max_length, top_p, temperature, history, state], [state] + text_boxes, queue=True)
+demo.queue(concurrency_count=10).launch(enable_queue=True, max_threads=2)