Update app.py

app.py

@@ -1,5 +1,6 @@
 import requests
 import io
+import os
 from PIL import Image
 import gradio as gr
 from transformers import MarianMTModel, MarianTokenizer
@@ -8,6 +9,9 @@ model_name = "Helsinki-NLP/opus-mt-mul-en"
 model = MarianMTModel.from_pretrained(model_name)
 tokenizer = MarianTokenizer.from_pretrained(model_name)
 
+gemini_api_key = os.getenv("GEMINI_API_KEY")
+huggingface_api_key = os.getenv("HUGGINGFACE_API_KEY")
+
 
 def translate_text(tamil_text):
     inputs = tokenizer(tamil_text, return_tensors="pt")
@@ -15,46 +19,40 @@ def translate_text(tamil_text):
     translation = tokenizer.decode(translated_tokens[0], skip_special_tokens=True)
     return translation
 
-def query_gemini_api(translated_text, gemini_api_key):
-    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-flash-latest:generateContent"
+def query_gemini_api(translated_text):
+    url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-turbo:generateText"
     headers = {"Content-Type": "application/json"}
-    prompt = f"Based on the following sentence, continue the story: {translated_text}"
     payload = {
-        "contents": [{"parts": [{"text": prompt}]}]
+        "prompt": {"text": translated_text},
+        "temperature": 0.7
     }
     response = requests.post(f"{url}?key={gemini_api_key}", headers=headers, json=payload)
 
     if response.status_code == 200:
         result = response.json()
-        creative_text = result['candidates'][0]['content']['parts'][0]['text']
+        creative_text = result['candidates'][0]['output']
         return creative_text
     else:
         return f"Error: {response.status_code} - {response.text}"
 
-
-
-def query_image(payload, huggingface_api_key):
+def query_image(payload):
     API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
     headers = {"Authorization": f"Bearer {huggingface_api_key}"}
     response = requests.post(API_URL, headers=headers, json=payload)
     return response.content
 
 
-def process_input(tamil_input, gemini_api_key, huggingface_api_key):
+def process_input(tamil_input):
     translated_output = translate_text(tamil_input)
-    creative_output = query_gemini_api(translated_output, gemini_api_key)
-    image_bytes = query_image({"inputs": translated_output}, huggingface_api_key)
+    creative_output = query_gemini_api(translated_output)
+    image_bytes = query_image({"inputs": translated_output})
     image = Image.open(io.BytesIO(image_bytes))
     return translated_output, creative_output, image
 
 
 iface = gr.Interface(
     fn=process_input,
-    inputs=[
-        gr.Textbox(label="Input Tamil Text"),
-        gr.Textbox(label="Enter your Gemini API Key", type="password"),
-        gr.Textbox(label="Enter your Hugging Face API Key", type="password"),
-    ],
+    inputs=gr.Textbox(label="Input Tamil Text"),
     outputs=[
         gr.Textbox(label="Translated Text"),
         gr.Textbox(label="Creative Text"),
@@ -63,5 +61,4 @@ iface = gr.Interface(
     title="TRANSART🎨 BY Sakthi",
     description="Enter Tamil text to translate to English and generate an image based on the translated text."
 )
-
 iface.launch()