Update app.py

app.py

@@ -1,56 +1,9 @@
-from threading import Thread
-from typing import Iterator
-
 import gradio as gr
-import spaces
-import torch
-from transformers import AutoModelForCausalLM, AutoTokenizer, TextIteratorStreamer
-
-MAX_MAX_NEW_TOKENS = 2048
-DEFAULT_MAX_NEW_TOKENS = 1024
-MAX_INPUT_TOKEN_LENGTH = 4096
-
-DESCRIPTION = """\
-# ChatSDB
-
-这是SequioaDB旗下的AI智能大语言模型，训练超过上万条真实数据和7亿参数。
-ChatSDB是SequoiaDB旗下的AI智能大语言模型，训练超过上万条真实数据和7亿参数</h3>
-<br><strong>模型🔗: <a>https://huggingface.co/wangzhang/ChatSDB </a></strong>
-<br><strong>Dataset🔗: <a>https://huggingface.co/datasets/wangzhang/sdb </a></strong>
-<br><strong> API Doc🔗: <a>https://zgg3nzdpswxy4a-80.proxy.runpod.net/docs/ <a> </strong>
-"""
-
-LICENSE = """ """
-
-if not torch.cuda.is_available():
-    DESCRIPTION += "\n<p>Running on CPU 🥶 This demo does not work on CPU.</p>"
-
-
-if torch.cuda.is_available():
-    model_id = "wangzhang/ChatSDB-hf"
-    model = AutoModelForCausalLM.from_pretrained(model_id, torch_dtype=torch.float16, device_map="auto")
-    tokenizer = AutoTokenizer.from_pretrained(model_id)
-    tokenizer.use_default_system_prompt = False
+from huggingface_hub import InferenceClient
 
+client = InferenceClient(model="wangzhang/chatSDB-test")
 
-@spaces.GPU
-def generate(
-    message: str,
-    chat_history: list[tuple[str, str]],
-    system_prompt: str,
-    max_new_tokens: int = 512,
-    temperature: float = 0.2,
-    top_p: float = 0.9,
-    top_k: int = 10,
-    repetition_penalty: float = 1.2,
-) -> Iterator[str]:
-    conversation = []
-    if system_prompt:
-        conversation.append({"role": "system", "content": system_prompt})
-    for user, assistant in chat_history:
-        conversation.extend([{"role": "user", "content": user}, {"role": "assistant", "content": assistant}])
-    conversation.append({"role": "user", "content": message})
-
+def inference(message, history):
     prompt = f"""### Instruction:
 
             ### Task:
@@ -61,85 +14,23 @@ def generate(
             
             ### Response:
             """
-    inputs = tokenizer(prompt, return_tensors="pt", truncation=True).input_ids.cuda()
-    if len(inputs) > MAX_INPUT_TOKEN_LENGTH:
-        inputs = inputs[-MAX_INPUT_TOKEN_LENGTH:]
-        gr.Warning("Trimmed input from conversation as it was longer than {MAX_INPUT_TOKEN_LENGTH} tokens.")
-
-    streamer = TextIteratorStreamer(tokenizer, timeout=10.0, skip_prompt=True, skip_special_tokens=True)
-    generate_kwargs = dict(
-        inputs,
-        streamer=streamer,
-        max_new_tokens=max_new_tokens,
-        do_sample=True,
-        top_p=top_p,
-        top_k=top_k,
-        temperature=temperature,
-        num_beams=1,
-        repetition_penalty=repetition_penalty,
-    )
-    t = Thread(target=model.generate, kwargs=generate_kwargs)
-    t.start()
-
-    outputs = []
-    for text in streamer:
-        outputs.append(text)
-        yield "".join(outputs)
-
-
-chat_interface = gr.ChatInterface(
-    fn=generate,
-    additional_inputs=[
-        gr.Textbox(label="System prompt", lines=6),
-        gr.Slider(
-            label="Max new tokens",
-            minimum=1,
-            maximum=MAX_MAX_NEW_TOKENS,
-            step=1,
-            value=DEFAULT_MAX_NEW_TOKENS,
-        ),
-        gr.Slider(
-            label="Temperature",
-            minimum=0.1,
-            maximum=4.0,
-            step=0.1,
-            value=0.6,
-        ),
-        gr.Slider(
-            label="Top-p (nucleus sampling)",
-            minimum=0.05,
-            maximum=1.0,
-            step=0.05,
-            value=0.9,
-        ),
-        gr.Slider(
-            label="Top-k",
-            minimum=1,
-            maximum=1000,
-            step=1,
-            value=50,
-        ),
-        gr.Slider(
-            label="Repetition penalty",
-            minimum=1.0,
-            maximum=2.0,
-            step=0.05,
-            value=1.2,
-        ),
-    ],
-    stop_btn=None,
-    examples=[
-        ["如何安装巨杉数据库SequioaDB？"],
-        ["巨杉数据库SequioaDB有哪些优势？"],
-        ["巨杉数据库SequioaDB是什么？"],
-    ],
-)
-
-with gr.Blocks(css="style.css") as demo:
-    gr.Markdown(DESCRIPTION)
-    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
-    chat_interface.render()
-    gr.Markdown(LICENSE)
-
-if __name__ == "__main__":
-    demo.queue(max_size=20).launch()
+    partial_message = ""
+    for token in client.text_generation(prompt=prompt, max_new_tokens=512, stream=True, best_of=1, temperature=0.1, 
+                                        top_p=0.99, do_sample=True, repetition_penalty=1.2):
+        if token.startswith("<s>"):
+            return partial_message
+        partial_message += token
+        yield partial_message
+
+gr.ChatInterface(
+    inference,
+    chatbot=gr.Chatbot(height=300, scale=7),
+    textbox=gr.Textbox(placeholder="你可以问我任何关于SequioaDB的��题!", container=False, scale=7),
+    description="这是SequioaDB旗下的AI智能大语言模型，训练超过上万条真实数据和7亿参数。",
+    title="ChatSDB",
+    examples=["SequoiaDB巨杉数据库是什么？", "SequoiaDB巨杉数据库支持哪些类型的数据库实例？"],
+    retry_btn="重试",
+    undo_btn="撤销",
+    clear_btn="清除",
+    submit_btn="提问",
+).queue().launch()