update app.py

app.py

@@ -1,10 +1,10 @@
 import streamlit as st
-import openai
+import google.generativeai as genai
 import hashlib
 import random
 
-# Set the OpenAI API key from Streamlit secrets
-openai.api_key = st.secrets["OPENAI_API_KEY"]
+# Set the Gemini API key
+genai.configure(api_key=st.secrets["GEMINI_API_KEY"])
 
 # Cache responses to avoid redundant API calls
 @st.cache_data
@@ -14,9 +14,6 @@ def get_cached_response(key, response=None):
     return st.session_state.get(key)
 
 def create_prompt(prompt: str, template: str, tone: str) -> str:
-    """
-    Creates a custom prompt based on the user's selected template and tone.
-    """
     templates = {
         "Formal": f"Please make this sound professional and polished:\n\n{prompt}",
         "Empathetic": f"Express warmth and empathy:\n\n{prompt}",
@@ -26,7 +23,7 @@ def create_prompt(prompt: str, template: str, tone: str) -> str:
         "General": f"Make this sound natural and conversational:\n\n{prompt}",
     }
     custom_prompt = templates.get(template, f"Make this sound natural and conversational:\n\n{prompt}")
-    
+
     tones = {
         "Warm": "Use a warm, approachable tone.",
         "Confident": "Sound friendly but confident.",
@@ -39,15 +36,9 @@ def create_prompt(prompt: str, template: str, tone: str) -> str:
     return f"{tone_instruction}\n\n{custom_prompt}"
 
 def refine_text(text: str) -> str:
-    """
-    Apply additional transformations to simulate human-like writing.
-    """
-    # List of phrases to introduce conversational tones
     conversational_inserts = [
         "Honestly,", "Frankly speaking,", "In a nutshell,", "To put it simply,", "If I may add,"
     ]
-    
-    # Substitute some formal words with informal counterparts
     replacements = {
         "do not": "don't", "cannot": "can't", "will not": "won't",
         "it is": "it's", "let us": "let's", "for example": "like,"
@@ -55,7 +46,6 @@ def refine_text(text: str) -> str:
     for formal, casual in replacements.items():
         text = text.replace(formal, casual, 1)
 
-    # Add conversational inserts randomly
     if random.random() > 0.5:
         insert = random.choice(conversational_inserts)
         sentences = text.split(".")
@@ -63,30 +53,25 @@ def refine_text(text: str) -> str:
             index = random.randint(1, len(sentences) - 2)
             sentences.insert(index, insert)
             text = ". ".join(sentences).replace("..", ".")
-    
+
     return text.strip()
-    
+
 def generate_text(prompt: str, max_tokens: int, temperature: float) -> str:
-    """
-    Generates humanized text using OpenAI's API based on the prompt.
-    """
     try:
-        response = openai.ChatCompletion.create(
-            model="gpt-3.5-turbo",
-            messages=[
-                {"role": "system", "content": "Write as if you're a real person, natural and relatable."},
-                {"role": "user", "content": prompt}
-            ],
-            max_tokens=max_tokens,
-            temperature=temperature,
-            top_p=0.9,
-            frequency_penalty=0.4,
-            presence_penalty=0.8,
-        )
-        
-        # Refine the response to add human-like nuances
-        refined_text = refine_text(response.choices[0].message.content.strip())
-        return refined_text
+        model = genai.GenerativeModel("gemini-pro")
+        response = model.generate_content(prompt, generation_config={
+            "temperature": temperature,
+            "max_output_tokens": max_tokens,
+            "top_p": 0.9,
+            "top_k": 40
+        })
+
+        if hasattr(response, "text"):
+            return refine_text(response.text)
+        else:
+            st.error("No response text returned from Gemini.")
+            return None
+
     except Exception as e:
         st.error(f"Error generating text: {e}")
         return None
@@ -96,7 +81,6 @@ def main():
     st.title("📝 HumanizeIt")
     st.write("Transform your text into something more conversational and human-like.")
 
-    # Input fields
     st.markdown("### Enter text to humanize:")
     prompt = st.text_area("", height=150)
 
@@ -109,7 +93,6 @@ def main():
             tone = st.selectbox("Select a Tone:", ["Neutral", "Optimistic", "Confident", "Apologetic", "Warm", "Excited"])
             temperature = st.slider("Creativity Level:", 0.1, 1.0, 0.7)
 
-    # Generate and display humanized text
     generate_button = st.button("✨ Generate Humanized Text")
     if generate_button:
         if prompt.strip():
@@ -117,7 +100,7 @@ def main():
                 user_prompt = create_prompt(prompt, template, tone)
                 cache_key = hashlib.md5(user_prompt.encode()).hexdigest()
                 cached_response = get_cached_response(cache_key)
-                
+
                 if cached_response:
                     st.write("Retrieved from cache.")
                     humanized_text = cached_response
@@ -126,14 +109,12 @@ def main():
                     if humanized_text:
                         get_cached_response(cache_key, humanized_text)
 
-            # Display result
             if humanized_text:
                 st.subheader("💡 Humanized Text:")
                 st.write(humanized_text)
         else:
             st.warning("Please enter text to humanize.")
 
-    # Feedback section
     st.markdown("---")
     st.subheader("Your Feedback Matters!")
     feedback = st.radio("Was this helpful?", ["👍 Yes", "👎 No", "😐 Neutral"], horizontal=True)
@@ -141,7 +122,6 @@ def main():
 
     if st.button("Submit Feedback"):
         st.success("Thank you for your feedback!")
-        # Here, you can add code to save the feedback if needed
 
 if __name__ == "__main__":
     main()