switch to Gemini API

app.py

@@ -1,42 +1,22 @@
+import google.generativeai as genai
 import gradio as gr
-from prompt_prefix import prompt_prefix
+import os
 import re
-from transformers import AutoTokenizer, AutoModelForCausalLM
-import torch
 
-# Modell und Tokenizer laden
-# distilgpt2 is only 80MB -> no inference model, thus add prompt_prefix or train
-tokenizer = AutoTokenizer.from_pretrained("distilgpt2")
-model = AutoModelForCausalLM.from_pretrained("distilgpt2")
+# Load Google AI API
+genai.configure(api_key=os.getenv('GEMINI_API_KEY'))
 
-# conversion method
-def text_to_emoji(input_text):
-    # Eingabetext bereinigen (optional)
-    cleaned_text = re.sub(r"[.,!?;:]", "", input_text)
+# Specify model
+model = genai.GenerativeModel('gemini-2.5-pro-exp-03-25')
 
-    # Pattern-based prompt with data from prompt_prefix
-    #prompt = "(\n" + "".join(f'"{line}\\n"\n' for line in prompt_prefix) + f"\"{input_text} →\"" + ")"
-    prompt = "(\n" + "".join(f'{line}\n' for line in prompt_prefix) + f"{input_text}"
-    
-    # Tokenisierung und Generation
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(
-        **inputs,
-        max_new_tokens=10,
-        do_sample=True,
-        temperature=0.9,
-        top_k=50,
-        pad_token_id=tokenizer.eos_token_id  # Prevents warning
-    )
+# Function to translate text into emojis using OpenAI API
+def text_to_emoji(text):
+    text_cleaned = re.sub(r"[.,!?;:]", "", text)
+    prompt = f"Convert this sentence into an emoji-sequence of the same meaning and return only the emojis, no explanation:\n\n\"{text_cleaned}\""
 
-    # Decodieren
-    generated_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    response = model.generate_content(prompt)
+    return response.text.strip()
 
-    # Nur den generierten Teil nach dem letzten "→"
-    emoji_part = generated_text.split("→")[-1].strip().split("\n")[0]
-
-    return emoji_part
-    
 # Gradio UI
 iface = gr.Interface(
     fn=text_to_emoji,
@@ -46,4 +26,4 @@ iface = gr.Interface(
     description="Enter a sentence, and the AI will transform it into an emoji-version 🥳"
 )
 
-iface.launch()
+iface.launch(debug=True)