Create app.py

app.py

@@ -0,0 +1,127 @@
+import os
+import gradio as gr
+import mdtex2html
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from transformers.generation import GenerationConfig
+
+# Initialize model and tokenizer
+tokenizer = AutoTokenizer.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True)
+model = AutoModelForCausalLM.from_pretrained("Qwen/Qwen-7B-Chat", device_map="auto", trust_remote_code=True).eval()
+model.generation_config = GenerationConfig.from_pretrained("Qwen/Qwen-7B-Chat", trust_remote_code=True)
+
+# Postprocess function
+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
+
+# Text parsing function
+def _parse_text(text):
+    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("`", r"\`")
+                    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
+
+# Demo launching function
+def _launch_demo(args, model, tokenizer, config):
+    def predict(_query, _chatbot, _task_history):
+        print(f"User: {_parse_text(_query)}")
+        _chatbot.append((_parse_text(_query), ""))
+        full_response = ""
+
+        for response in model.chat_stream(tokenizer, _query, history=_task_history, generation_config=config):
+            _chatbot[-1] = (_parse_text(_query), _parse_text(response))
+
+            yield _chatbot
+            full_response = _parse_text(response)
+
+        print(f"History: {_task_history}")
+        _task_history.append((_query, full_response))
+        print(f"Qwen-Chat: {_parse_text(full_response)}")
+
+    def regenerate(_chatbot, _task_history):
+        if not _task_history:
+            yield _chatbot
+            return
+        item = _task_history.pop(-1)
+        _chatbot.pop(-1)
+        yield from predict(item[0], _chatbot, _task_history)
+
+    def reset_user_input():
+        return gr.update(value="")
+
+    def reset_state(_chatbot, _task_history):
+        _task_history.clear()
+        _chatbot.clear()
+        import gc
+        gc.collect()
+        torch.cuda.empty_cache()
+        return _chatbot
+
+    with gr.Blocks() as demo:
+        gr.Markdown("""
+    ## Qwen-14B-Chat: A Large Language Model by Alibaba Cloud
+    **Space created by [@artificialguybr](https://twitter.com/artificialguybr) based on QWEN Code. Thanks HF for GPU!**
+
+    ### Performance Metrics:
+    - **MMLU Accuracy**: 
+      - 0-shot: 64.6
+      - 5-shot: 66.5
+    - **HumanEval Pass@1**: 43.9
+    - **GSM8K Accuracy**: 
+      - 0-shot: 60.1
+      - 8-shot: 59.3
+    """)
+        chatbot = gr.Chatbot(label='Qwen-Chat', elem_classes="control-height", queue=True)
+        query = gr.Textbox(lines=2, label='Input')
+        task_history = gr.State([])
+
+        with gr.Row():
+            empty_btn = gr.Button("🧹 Clear History")
+            submit_btn = gr.Button("🚀 Submit")
+            regen_btn = gr.Button("🤔️ Regenerate")
+
+        submit_btn.click(predict, [query, chatbot, task_history], [chatbot], show_progress=True, queue=True)  # Enable queue
+        submit_btn.click(reset_user_input, [], [query])
+        empty_btn.click(reset_state, [chatbot, task_history], outputs=[chatbot], show_progress=True)
+        regen_btn.click(regenerate, [chatbot, task_history], [chatbot], show_progress=True, queue=True)  # Enable queue
+    demo.queue(max_size=20)
+    demo.launch(share=True)
+
+
+# Main execution
+if __name__ == "__main__":
+    _launch_demo(None, model, tokenizer, model.generation_config)