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Create app.py
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app.py
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import gradio as gr
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from llama_cpp import Llama
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llm = Llama(model_path="model.gguf", n_ctx=4000, n_threads=2, chat_format="chatml")
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def generate(message, history,temperature=0.1,max_tokens=512):
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system_prompt = "You are StableCode, a superintelligent coding AI assistant."
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formatted_prompt = [{"role": "system", "content": system_prompt}]
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for user_prompt, bot_response in history:
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formatted_prompt.append({"role": "user", "content": user_prompt})
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formatted_prompt.append({"role": "assistant", "content": bot_response })
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formatted_prompt.append({"role": "user", "content": message})
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stream_response = llm.create_chat_completion(messages=formatted_prompt, temperature=temperature, max_tokens=max_tokens, stream=True)
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response = ""
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for chunk in stream_response:
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if len(chunk['choices'][0]["delta"]) != 0 and "content" in chunk['choices'][0]["delta"]:
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response += chunk['choices'][0]["delta"]["content"]
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yield response
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mychatbot = gr.Chatbot(
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avatar_images=["user.png", "botsc.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=True,)
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iface = gr.ChatInterface(fn=generate, chatbot=mychatbot, retry_btn=None, undo_btn=None)
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with gr.Blocks() as demo:
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gr.HTML("<center><h1>Tomoniai's Chat with Stable Code Instruct 3b</h1></center>")
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iface.render()
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demo.queue().launch(show_api=False, server_name="0.0.0.0")
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