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Parent(s):
e9bf215
Create app.py
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app.py
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import gradio as gr
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from huggingface_hub import Repository, InferenceClient
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import os
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import json
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API_TOKEN = os.environ.get("API_TOKEN")
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API_ENDPOINT = os.environ.get("API_ENDPOINT")
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KEY = os.environ.get("KEY")
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API_ENDPOINTS = {
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"Falcon": "tiiuae/falcon-180B-chat",
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"Llama": "meta-llama/Llama-2-70b-chat-hf"
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}
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CHOICES = []
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CLIENTS = {}
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for model_name, model_endpoint in API_ENDPOINTS.items():
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CHOICES.append(model_name)
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CLIENTS[model_name] = InferenceClient(model_endpoint, headers = { "Authorization": f"Bearer {API_TOKEN}" })
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def predict(input, access_key, model, temperature, top_p, top_k, rep_p, max_tokens, stop_seqs, seed):
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if (access_key != KEY):
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print(">>> MODEL FAILED: Input: " + input + ", Attempted Key: " + access_key)
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return ("[UNAUTHORIZED ACCESS]", input);
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stops = json.loads(stop_seqs)
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response = CLIENTS[model].text_generation(
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input,
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temperature = temperature,
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max_new_tokens = max_tokens,
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top_p = top_p,
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top_k = top_k,
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repetition_penalty = rep_p,
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stop_sequences = stops,
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do_sample = True,
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seed = seed,
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stream = False,
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details = False,
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return_full_text = False
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)
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print(f"---\nUSER: {input}\nBOT: {response}\n---")
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return (response, input)
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def maintain_cloud():
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print(">>> SPACE MAINTAINED!")
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return ("SUCCESS!", "SUCCESS!")
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with gr.Blocks() as demo:
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with gr.Row(variant = "panel"):
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gr.Markdown("⚛️ This is a private LLM Space owned within STC Holdings!\n\n\nhttps://discord.gg/6JRtGawz7B")
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with gr.Row():
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with gr.Column():
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input = gr.Textbox(label = "Input", lines = 4)
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access_key = gr.Textbox(label = "Access Key", lines = 1)
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run = gr.Button("▶")
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cloud = gr.Button("☁️")
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with gr.Column():
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model = gr.Dropdown(choices = CHOICES, value = next(iter(API_ENDPOINTS)), interactive = True, label = "Model")
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temperature = gr.Slider( minimum = 0, maximum = 2, value = 1, step = 0.01, interactive = True, label = "Temperature" )
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top_p = gr.Slider( minimum = 0.01, maximum = 0.99, value = 0.95, step = 0.01, interactive = True, label = "Top P" )
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top_k = gr.Slider( minimum = 1, maximum = 2048, value = 50, step = 1, interactive = True, label = "Top K" )
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rep_p = gr.Slider( minimum = 0.01, maximum = 2, value = 1.2, step = 0.01, interactive = True, label = "Repetition Penalty" )
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max_tokens = gr.Slider( minimum = 1, maximum = 2048, value = 32, step = 64, interactive = True, label = "Max New Tokens" )
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stop_seqs = gr.Textbox(label = "Stop Sequences ( JSON Array / 4 Max )", lines = 1, value = '["‹", "›"]')
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seed = gr.Slider( minimum = 0, maximum = 8192, value = 42, step = 1, interactive = True, label = "Seed" )
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with gr.Row():
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with gr.Column():
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output = gr.Textbox(label = "Output", value = "", lines = 50)
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run.click(predict, inputs = [input, access_key, model, temperature, top_p, top_k, rep_p, max_tokens, stop_seqs, seed], outputs = [output, input])
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cloud.click(maintain_cloud, inputs = [], outputs = [input, output])
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demo.queue(concurrency_count = 500, api_open = True).launch(show_api = True)
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