Update app3.py

app3.py

@@ -2,7 +2,8 @@
 import streamlit as st
 from langchain_community.llms import OpenAI
 #from langchain_community.llms import Gemini
-from langchain_google_gemini import Gemini 
+#from langchain_google_gemini import Gemini 
+from langchain_google_genai import ChatGoogleGenerativeAI
 
 
 def main():
@@ -31,12 +32,13 @@ def generate_openai_post(role, temp):
         # Enhanced prompt with additional context for better post generation
         prompt = (
             f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
+            f"Adjust the tone and style based on a temperature of {temp}. " 
             "It should start with an attention grabbing hook based on audience pain. "
             "Then a line to agitate the user. This should be in the next line. "
             "The post should be concise, informative, and suitable for a professional audience. "
             "It should provide value, insights, or thought-provoking content related to the topic. "
             "And only contain 3 points. "
-            "The tone should be positive and encouraging, suitable for networking and professional growth."
+            
         )
         llm = OpenAI(temperature=temp, openai_api_key=st.secrets["OPENAI_API_KEY"])  # Corrected variable name
         response = llm(prompt)
@@ -52,12 +54,24 @@ def generate_openai_post(role, temp):
             st.error("Please enter a topic to generate a post.")
 
 def generate_gemini_post(role, temp):
-    # Define a function to generate LinkedIn posts using the Gemini API
+  {  # Define a function to generate LinkedIn posts using the Gemini API
     # Example implementation:
-    gemini = Gemini(api_key=st.secrets["YOUR_GEMINI_API_KEY"], temperature=temp)
+    #gemini = Gemini(api_key=st.secrets["YOUR_GEMINI_API_KEY"], temperature=temp)
+        user_input = (
+             f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
+             f"Adjust the tone and style based on a temperature of {temp}. " 
+             "It should start with an attention grabbing hook based on audience pain. "
+             "Then a line to agitate the user. This should be in the next line. "
+             "The post should be concise, informative, and suitable for a professional audience. "
+             "It should provide value, insights, or thought-provoking content related to the topic. "
+             "And only contain 3 points. "
+        ) 
+    llm = ChatGoogleGenerativeAI(model="gemini-pro")
+  result = llm.invoke(user_input)
+  return print(result.content)
     # Call Gemini API functions to generate LinkedIn post
     # gemini.generate_linkedin_post(topic, role)
     st.error("Gemini API integration is not yet implemented.")
-
+ }
 if __name__ == "__main__":
     main()