Update app.py

app.py

@@ -1,46 +1,56 @@
 import os
-# import json
-# import gradio as gr
-# from transformers import AutoTokenizer, AutoModelForCausalLM
+import gradio as gr
+from transformers import AutoModelForSeq2SeqLM, AutoTokenizer
+from huggingface_hub import login
 
-# tokenizer = AutoTokenizer.from_pretrained("google/gemma-7b-it")
-# model = AutoModelForCausalLM.from_pretrained("google/gemma-7b-it")
+# Get the Hugging Face token from environment variables
 HF_TOKEN = os.getenv('HF')
-print(HF_TOKEN)
-# def generate(text):
-#     try:
-#         # Tokenize the input text
-#         inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
+
+if not HF_TOKEN:
+    raise ValueError("The HF environment variable is not set. Please set it to your Hugging Face token.")
+
+# Authenticate with Hugging Face
+login(HF_TOKEN)
+
+# Load the model and tokenizer using the Hugging Face token
+model_name = "google/gemma-7b-it"
+tokenizer = AutoTokenizer.from_pretrained(model_name, use_auth_token=True)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name, use_auth_token=True)
+
+def generate(text):
+    try:
+        # Tokenize the input text
+        inputs = tokenizer(text, return_tensors="pt", max_length=512, truncation=True)
         
-#         # Generate the response
-#         outputs = model.generate(
-#             inputs["input_ids"],
-#             max_length=1024,
-#             num_beams=5,
-#             early_stopping=True,
-#         )
+        # Generate the response
+        outputs = model.generate(
+            inputs["input_ids"],
+            max_length=1024,
+            num_beams=5,
+            early_stopping=True,
+        )
         
-#         # Decode the output tokens to text
-#         response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+        # Decode the output tokens to text
+        response_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
         
-#         return response_text if response_text else "No valid response generated."
+        return response_text if response_text else "No valid response generated."
     
-#     except Exception as e:
-#         return str(e)
-
-# iface = gr.Interface(
-#     fn=generate,
-#     inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
-#     outputs="text",
-#     title="Chuunibyou Text Generator",
-#     description="Transform text into an elaborate and formal style with a nobleman tone.",
-#     live=False
-# )
-
-# def launch_custom_interface():
-#     iface.launch()
-#     with gr.TabbedInterface(fn=generate, inputs=gr.Textbox(lines=2, placeholder="Enter text here..."), outputs=gr.HTML(label="Output")) as ti:
-#         ti.add(custom_html)
-
-# if __name__ == "__main__":
-#     launch_custom_interface()
+    except Exception as e:
+        return str(e)
+
+iface = gr.Interface(
+    fn=generate,
+    inputs=gr.Textbox(lines=2, placeholder="Enter text here..."),
+    outputs="text",
+    title="Chuunibyou Text Generator",
+    description="Transform text into an elaborate and formal style with a nobleman tone.",
+    live=False
+)
+
+def launch_custom_interface():
+    iface.launch()
+    with gr.TabbedInterface(fn=generate, inputs=gr.Textbox(lines=2, placeholder="Enter text here..."), outputs=gr.HTML(label="Output")) as ti:
+        ti.add(custom_html)
+
+if __name__ == "__main__":
+    launch_custom_interface()