Create app.py

app.py

@@ -0,0 +1,82 @@
+import gradio as gr
+from huggingface_hub import Repository, InferenceClient
+import os
+import json
+
+API_TOKEN = os.environ.get("API_TOKEN")
+API_ENDPOINT = os.environ.get("API_ENDPOINT")
+
+KEY = os.environ.get("KEY")
+
+API_ENDPOINTS = {
+    "Falcon": "tiiuae/falcon-180B-chat",
+    "Llama": "meta-llama/Llama-2-70b-chat-hf"
+}
+
+CHOICES = []
+CLIENTS = {}
+
+for model_name, model_endpoint in API_ENDPOINTS.items():
+    CHOICES.append(model_name)
+    CLIENTS[model_name] = InferenceClient(model_endpoint, headers = { "Authorization": f"Bearer {API_TOKEN}" })
+
+def predict(input, access_key, model, temperature, top_p, top_k, rep_p, max_tokens, stop_seqs, seed):
+
+    if (access_key != KEY):
+        print(">>> MODEL FAILED: Input: " + input + ", Attempted Key: " + access_key)
+        return ("[UNAUTHORIZED ACCESS]", input);
+        
+    stops = json.loads(stop_seqs)
+    
+    response = CLIENTS[model].text_generation(
+        input,
+        temperature = temperature,
+        max_new_tokens = max_tokens,
+        top_p = top_p,
+        top_k = top_k,
+        repetition_penalty = rep_p,
+        stop_sequences = stops,
+        do_sample = True,
+        seed = seed,
+        stream = False,
+        details = False,
+        return_full_text = False
+    )
+
+    print(f"---\nUSER: {input}\nBOT: {response}\n---")
+
+    return (response, input)
+
+def maintain_cloud():
+    print(">>> SPACE MAINTAINED!")
+    return ("SUCCESS!", "SUCCESS!")
+    
+with gr.Blocks() as demo:
+    with gr.Row(variant = "panel"):
+        gr.Markdown("⚛️ This is a private LLM Space owned within STC Holdings!\n\n\nhttps://discord.gg/6JRtGawz7B")
+            
+    with gr.Row():
+        with gr.Column():
+            input = gr.Textbox(label = "Input", lines = 4)
+            access_key = gr.Textbox(label = "Access Key", lines = 1)
+            run = gr.Button("▶")
+            cloud = gr.Button("☁️")
+            
+        with gr.Column():
+            model = gr.Dropdown(choices = CHOICES, value = next(iter(API_ENDPOINTS)), interactive = True, label = "Model")
+            temperature = gr.Slider( minimum = 0, maximum = 2, value = 1, step = 0.01, interactive = True, label = "Temperature" )
+            top_p = gr.Slider( minimum = 0.01, maximum = 0.99, value = 0.95, step = 0.01, interactive = True, label = "Top P" )
+            top_k = gr.Slider( minimum = 1, maximum = 2048, value = 50, step = 1, interactive = True, label = "Top K" )
+            rep_p = gr.Slider( minimum = 0.01, maximum = 2, value = 1.2, step = 0.01, interactive = True, label = "Repetition Penalty" )
+            max_tokens = gr.Slider( minimum = 1, maximum = 2048, value = 32, step = 64, interactive = True, label = "Max New Tokens" )
+            stop_seqs = gr.Textbox(label = "Stop Sequences ( JSON Array / 4 Max )", lines = 1, value = '["‹", "›"]')
+            seed = gr.Slider( minimum = 0, maximum = 8192, value = 42, step = 1, interactive = True, label = "Seed" )
+            
+    with gr.Row():
+        with gr.Column():
+            output = gr.Textbox(label = "Output", value = "", lines = 50)
+
+    run.click(predict, inputs = [input, access_key, model, temperature, top_p, top_k, rep_p, max_tokens, stop_seqs, seed], outputs = [output, input])
+    cloud.click(maintain_cloud, inputs = [], outputs = [input, output])
+    
+demo.queue(concurrency_count = 500, api_open = True).launch(show_api = True)