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| import json | |
| import gradio as gr | |
| from llama_cpp import Llama | |
| system_message = "\nBelow is an instruction that describes a task. Write a response that appropriately completes the request." | |
| title = "MY First Llama2 7B Chatbot" | |
| description = """ | |
| 基于6000条问答数据微调过后的Llama2,初步激活了Llama2的中文能力,使其能够说中文。 | |
| """ | |
| css = """.toast-wrap { display: none !important } """ | |
| examples=[ | |
| '使用python写一个post请求', | |
| '使用swiftui自定义图片大小', | |
| ] | |
| # | |
| llm = Llama(model_path="ggml-model-q4_0.bin", n_ctx=2048) | |
| def predict(message, chatbot): | |
| input_prompt = f"[INST] <<SYS>>\n{system_message}\n<</SYS>>\n\n " | |
| for interaction in chatbot: | |
| input_prompt = input_prompt + str(interaction[1]) + " [/INST] " + str(interaction[0]) + " </s><s> [INST] " | |
| "Question: What are the names of the planets in the solar system? Answer: ", | |
| input_prompt = input_prompt + str(message) + " [/INST] " | |
| stream = llm( | |
| input_prompt, | |
| max_tokens=512, | |
| stop=["[INST]"], | |
| stream=True) | |
| partial_message = "" | |
| for line in stream: | |
| # Load as JSON | |
| try: | |
| if 'choices' in line: | |
| partial_message = partial_message + line["choices"][0]["text"] | |
| yield partial_message | |
| else: | |
| gr.Warning(f"The key 'token' does not exist in this JSON object: {line}") | |
| except json.JSONDecodeError: | |
| gr.Warning(f"This line is not valid JSON: {line}") | |
| continue | |
| except KeyError as e: | |
| gr.Warning(f"KeyError: {e} occurred for JSON object: {line}") | |
| continue | |
| # Gradio Demo | |
| with gr.Blocks() as demo: | |
| with gr.Tab("Streaming"): | |
| gr.ChatInterface(predict, title=title, description=description, css=css, examples=examples, cache_examples=False) | |
| # gr.ChatInterface(predict, title=title, css=css, examples=examples, cache_examples=False) | |
| demo.queue(concurrency_count=75).launch(debug=True) | |