placed just the generation into ui for llama3-8b

app.py

@@ -3,4 +3,64 @@ import pandas as pd
 import numpy as np
 import gradio as gr
 import re
-from transformers import AutoTokenizer, AutoModelForCausalLM
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import re
+from huggingface_hub import login
+import os
+
+# HF_TOKEN
+TOKEN = os.getenv('HF_AUTH_TOKEN')
+login(token=TOKEN,
+      add_to_git_credential=False)
+
+# Open ai api key
+API_KEY = os.getenv('OPEN_AI_API_KEY')
+
+DESCRIPTION = '''
+<div>
+<h1 style="text-align: center;">Amphisbeana 🐍</h1>
+<p>This uses Llama 3 and GPT-4o as generation, both of these make the final generation. <a href="https://huggingface.co/meta-llama/Meta-Llama-3-8B"><b>Llama3-8b</b></a>and <a href="https://platform.openai.com/docs/models/gpt-4o"><b>GPT-4o</b></a></p>
+</div>
+'''
+
+# Place transformers in hardware to prepare for process and generation
+llama_tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3-8B")
+llama_model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3-8B", token=TOKEN, torch_dtype=torch.float16).to('cuda')
+
+# Place just input pass and return generation output
+def llama_generation(input_text):
+    """
+    Pass input texts, tokenize, output and back to text.
+    """
+
+    input_ids = llama_tokenizer.encode(input_text,
+                                       return_tensors='pt')
+    
+    output_ids = llama_model.generate(**input_ids)
+
+    # Decode
+    output_text = llama_tokenizer.decode(output_ids,
+                                         skip_special_tokens=True)
+    
+    return output_text
+
+# Let's just make sure the llama is returning as it should and than place that return output into a function making it fit into a base
+# Prompt for gpt-4o
+
+chatbot=gr.Chatbot(height=600, label="Amphisbeana AI")
+
+with gr.Blocks(fill_height=True) as demo:
+    gr.Markdown(DESCRIPTION)
+    gr.ChatInterface(
+        fn=llama_generation,
+        chatbot=chatbot,
+        fill_height=True,
+        examples=["Make a poem of batman inside willy wonka",
+                  "How can you a burrito with just flour?",
+                  "How was saturn formed in 3 sentences",
+                  "How does the frontal lobe effect playing soccer"],
+        cache_examples=False
+    )
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -3,4 +3,5 @@ pandas
 numpy
 gradio
 transformers
-openai
+openai
+huggingface_hub