Update app.py

app.py

@@ -1,109 +1,71 @@
-import argparse
-from pathlib import Path
-
+import urllib
 import chatglm_cpp
 import gradio as gr
 
-import urllib
-
 DEFAULT_MODEL_PATH = "chatglm3-6b.bin"
-
 urllib.request.urlretrieve(
-    "https://huggingface.co/Braddy/chatglm3-6b-chitchat/resolve/main/q5_1_loss_304.bin?download=true", 
+    "https://huggingface.co/Braddy/chatglm3-6b-chitchat/resolve/main/q5_1.bin?download=true", 
     DEFAULT_MODEL_PATH
     )
 
-parser = argparse.ArgumentParser()
-parser.add_argument("-m", "--model", default=DEFAULT_MODEL_PATH, type=Path, help="model path")
-parser.add_argument("--mode", default="chat", type=str, choices=["chat", "generate"], help="inference mode")
-parser.add_argument("-l", "--max_new_tokens", default=64, type=int, help="max total output tokens")
-parser.add_argument("-c", "--max_context_length", default=1024, type=int, help="max context length")
-parser.add_argument("--top_k", default=40, type=int, help="top-k sampling")
-parser.add_argument("--top_p", default=0.75, type=float, help="top-p sampling")
-parser.add_argument("--temp", default=0.5, type=float, help="temperature")
-parser.add_argument("--repeat_penalty", default=1.0, type=float, help="penalize repeat sequence of tokens")
-parser.add_argument("-t", "--threads", default=0, type=int, help="number of threads for inference")
-parser.add_argument("--plain", action="store_true", help="display in plain text without markdown support")
-args = parser.parse_args()
 
-pipeline = chatglm_cpp.Pipeline(args.model)
+pipeline = chatglm_cpp.Pipeline(DEFAULT_MODEL_PATH)
 system_message = chatglm_cpp.ChatMessage(role="system", content="请你现在扮演一个软件工程师，名字叫做贺英旭。你需要以这个身份和朋友们对话。")
 
 
-def postprocess(text):
-    if args.plain:
-        return f"<pre>{text}</pre>"
-    return text
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_new_tokens,
+    temperature,
+    top_p,
+):
+    messages = [chatglm_cpp.ChatMessage(role="system", content=system_message)]
+    # messages = [{"role": "system", "content": system_message}]
 
+    for val in history:
+        if val[0]:
+            # messages.append({"role": "user", "content": val[0]})
+            messages.append(chatglm_cpp.ChatMessage(role="user", content=val[0]))
+        if val[1]:
+            messages.append(chatglm_cpp.ChatMessage(role="assistant", content=val[1]))
 
-def predict(input, chatbot, max_new_tokens, top_p, temperature, messages):
-    chatbot.append((postprocess(input), ""))
-    messages.append(chatglm_cpp.ChatMessage(role="user", content=input))
-    full_messages = [system_message] + messages
+    messages.append(chatglm_cpp.ChatMessage(role="user", content=message))
 
     generation_kwargs = dict(
         max_new_tokens=max_new_tokens,
-        max_context_length=args.max_context_length,
         do_sample=temperature > 0,
-        top_k=args.top_k,
         top_p=top_p,
         temperature=temperature,
-        repetition_penalty=args.repeat_penalty,
-        num_threads=args.threads,
         stream=True,
     )
 
     response = ""
-    chunks = []
-    for chunk in pipeline.chat(full_messages, **generation_kwargs):
+    for chunk in pipeline.chat(messages, **generation_kwargs):
         response += chunk.content
-        chunks.append(chunk)
-        chatbot[-1] = (chatbot[-1][0], postprocess(response))
-        yield chatbot, messages
-    messages.append(pipeline.merge_streaming_messages(chunks))
-
-    yield chatbot, messages
-
-
-def reset_user_input():
-    return gr.update(value="")
-
+        yield response
 
-def reset_state():
-    return [], []
 
-title = """
-<div style="text-align: center">
-    <h1>Chichat</h1>
-    <p style="text-align: center;">Free feel to talk about anything :)</p>
-</div>
 """
-
-
-with gr.Blocks() as demo:
-    gr.HTML(title)
-
-    chatbot = gr.Chatbot(height=300, label="Check this out!")
-    with gr.Row():
-        with gr.Column(scale=4):
-            user_input = gr.Textbox(show_label=False, placeholder="Input...", lines=8)
-            submitBtn = gr.Button("Submit", variant="primary")
-        with gr.Column(scale=1):
-            max_new_tokens = gr.Slider(0, 512, value=args.max_new_tokens, step=1.0, label="Maximum output tokens", interactive=True)
-            top_p = gr.Slider(0, 1, value=args.top_p, step=0.01, label="Top P", interactive=True)
-            temperature = gr.Slider(0, 1, value=args.temp, step=0.01, label="Temperature", interactive=True)
-            emptyBtn = gr.Button("Clear History")
-
-    messages = gr.State([])
-
-    submitBtn.click(
-        predict,
-        [user_input, chatbot, max_new_tokens, top_p, temperature, messages],
-        [chatbot, messages],
-        show_progress=True,
-    )
-    submitBtn.click(reset_user_input, [], [user_input])
-
-    emptyBtn.click(reset_state, outputs=[chatbot, messages], show_progress=True)
-
-demo.queue().launch(share=False, inbrowser=True)
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
+
+
+if __name__ == "__main__":
+    demo.launch()