Delete app.py

app.py

@@ -1,49 +0,0 @@
-import gradio as gr
-from transformers import AutoModelForCausalLM, AutoTokenizer
-import torch
-
-# Load the model and tokenizer
-model_name = "Artples/L-MChat-7b"
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-model = AutoModelForCausalLM.from_pretrained(model_name)
-
-# Ensure the model uses CPU
-device = torch.device("cpu")
-model.to(device)
-
-def chat_with_model(json_input):
-    prompt = json_input['prompt']
-    # Tokenize the input prompt
-    inputs = tokenizer.encode(prompt, return_tensors="pt")
-    inputs = inputs.to(device)
-
-    # Generate a response
-    output = model.generate(inputs, max_length=100, num_return_sequences=1)
-    response_text = tokenizer.decode(output[0], skip_special_tokens=True)
-
-    return {"choices": [{"text": response_text}]}
-
-# Define the JSON input component
-json_schema = {
-    "title": "Request",
-    "type": "object",
-    "properties": {
-        "prompt": {
-            "type": "string",
-            "description": "Enter your prompt here."
-        }
-    },
-    "required": ["prompt"]
-}
-
-# Create Gradio interface
-iface = gr.Interface(
-    fn=chat_with_model,
-    inputs=gr.inputs.JSON(schema=json_schema),
-    outputs="json",
-    title="Chat with L-MChat-7b",
-    description="API-like interface using Gradio to simulate OpenAI API behavior."
-)
-
-# Run the Gradio app
-iface.launch()