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from huggingface_hub import InferenceClient |
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import gradio as gr |
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import requests |
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import json |
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client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1") |
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def google_search(query, **kwargs): |
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api_key = 'AIzaSyDseKKQCAUBmPidu_QapnpJCGLueDWYJbE' |
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cse_id = '001ae9bf840514e61' |
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service_url = 'https://www.googleapis.com/customsearch/v1' |
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params = { |
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'key': api_key, |
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'cx': cse_id, |
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'q': query, |
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**kwargs |
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} |
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response = requests.get(service_url, params=params) |
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if response.status_code == 200: |
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return json.loads(response.text)['items'] |
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else: |
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print(f'Error: {response.status_code}') |
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return [] |
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def tokenize(text): |
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return text |
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def format_prompt(message, history): |
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prompt = "" |
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for user_prompt, bot_response in history: |
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prompt += "<s>" + tokenize("[INST]") + tokenize(user_prompt) + tokenize("[/INST]") |
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prompt += tokenize(bot_response) + "</s> " |
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prompt += tokenize("[INST]") + tokenize(message) + tokenize("[/INST]") |
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return prompt |
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def generate(prompt, history, system_prompt, temperature=0.2, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0): |
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temperature = float(temperature) |
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if temperature < 1e-2: |
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temperature = 1e-2 |
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top_p = float(top_p) |
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generate_kwargs = dict( |
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temperature=temperature, |
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max_new_tokens=max_new_tokens, |
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top_p=top_p, |
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repetition_penalty=repetition_penalty, |
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do_sample=True, |
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seed=42, |
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) |
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formatted_prompt = format_prompt(f"{system_prompt}, {prompt}", history) |
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stream = client.text_generation(formatted_prompt, **generate_kwargs, stream=True, details=True, return_full_text=False) |
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output = "" |
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for response in stream: |
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print(response.token.text + "/n") |
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output += response.token.text |
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yield output |
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return output |
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def generateS(prompt, history, system_prompt, temperature=0.2, max_new_tokens=512, top_p=0.95, repetition_penalty=1.0): |
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stream = google_search(prompt) |
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output = "" |
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for response in stream: |
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output += json.dumps(response) |
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yield output |
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return output |
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additional_inputs=[ |
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gr.Textbox( |
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label="System Prompt", |
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max_lines=1, |
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interactive=True, |
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), |
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gr.Slider( |
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label="Temperature", |
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value=0.2, |
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minimum=0.0, |
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maximum=1.0, |
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step=0.05, |
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interactive=True, |
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info="Higher values produce more diverse outputs", |
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), |
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gr.Slider( |
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label="Max new tokens", |
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value=512, |
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minimum=0, |
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maximum=1048, |
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step=64, |
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interactive=True, |
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info="The maximum numbers of new tokens", |
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), |
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gr.Slider( |
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label="Top-p (nucleus sampling)", |
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value=0.95, |
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minimum=0.0, |
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maximum=1, |
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step=0.05, |
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interactive=True, |
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info="Higher values sample more low-probability tokens", |
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), |
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gr.Slider( |
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label="Repetition penalty", |
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value=1, |
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minimum=1.0, |
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maximum=2.0, |
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step=0.05, |
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interactive=True, |
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info="Penalize repeated tokens", |
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) |
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] |
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mychatbot = gr.Chatbot( |
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avatar_images=["./user.png", "./botm.png"], bubble_full_width=False, show_label=False, show_copy_button=True, likeable=False) |
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demo = gr.ChatInterface(fn=generate, |
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chatbot=mychatbot, |
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additional_inputs=additional_inputs, |
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title="Kamran's Mixtral 8x7b Chat", |
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retry_btn=None, |
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undo_btn=None |
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) |
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demo.queue().launch(show_api=False) |
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