ncc

app.py

@@ -9,28 +9,25 @@ transformers
 sentencepiece
 torch
 
-"""
-# pylint: disable=line-too-long, missing-module-docstring, missing-function-docstring
-# import torch
 import gradio as gr
-from examples_list import examples_list
-from transformers import AutoModel, AutoTokenizer  # AutoModelForCausalLM,
 
-# device = "cuda" if torch.cuda.is_available() else "cpu"
+def greet(name):
+    return "Hello " + name + "!"
 
-# tokenizer = AutoTokenizer.from_pretrained("stabilityai/StableBeluga2", use_fast=False)
-# model = AutoModelForCausalLM.from_pretrained("stabilityai/StableBeluga2", torch_dtype=torch.float16, low_cpu_mem_usage=True, device_map="auto")
-# system_prompt = "### System:\nYou are Stable Beluga, an AI that follows instructions extremely well. Help as much as you can. Remember, be safe, and don't do anything illegal.\n\n"
-# pipeline = pipeline(task="text-generation", model="meta-llama/Llama-2-7b")
+with gr.Blocks() as demo:
+    name = gr.Textbox(label="Name")
+    output = gr.Textbox(label="Output Box")
+    greet_btn = gr.Button("Greet")
+    greet_btn.click(fn=greet, inputs=name, outputs=output, api_name="greet")
+
+
+demo.launch()
 
-_ = """
-tokenizer = AutoTokenizer.from_pretrained(
-    "THUDM/chatglm2-6b-int4", trust_remote_code=True
-)
-chat_model = AutoModel.from_pretrained(
-    "THUDM/chatglm2-6b-int4", trust_remote_code=True  # 3.92G
-).float()
 """
+# pylint: disable=line-too-long, missing-module-docstring, missing-function-docstring
+# import torch
+import gradio as gr
+
 
 def stream_chat():
     """samples:
@@ -75,17 +72,16 @@ def update_chatbot():
         message = yield
         print(f"{message=}")
 
+def greet(name):
+    return "Hello " + name + "!"
 
-def chat1(message, history):
-    # prompt = f"{system_prompt}### User: {message}\n\n### Assistant:\n"
-    # inputs = tokenizer(prompt, return_tensors="pt").to(device=device)
-    # output = model.generate(**inputs, do_sample=True, top_p=0.95, top_k=0, max_new_tokens=256)
-    # return tokenizer.decode(output[0], skip_special_tokens=True)
-    for response, _ in chat_model.stream_chat(
-        tokenizer, message, history, max_length=2048, top_p=0.7, temperature=0.95
-    ):
-        yield response, _
+with gr.Blocks() as block:
+    name = gr.Textbox(label="Name")
+    output = gr.Textbox(label="Output Box")
+    greet_btn = gr.Button("Greet")
+    greet_btn.click(fn=greet, inputs=name, outputs=output, api_name="greet")
 
+_ = """
 with gr.Blocks(theme=gr.themes.Glass(text_size="sm", spacing_size="sm"),) as block:
     chatbot = gr.Chatbot()
     msg = gr.Textbox()
@@ -98,3 +94,6 @@ block(
     # title="gradio-chatinterface-tryout",
     # examples=examples_list,
 ).queue(max_size=2).launch()
+# """
+
+block.queue(max_size=2).launch()