Create app3.py

app3.py

@@ -0,0 +1,60 @@
+import streamlit as st
+from langchain_community.llms import OpenAI
+from langchain_community.llms import Gemini
+
+def main():
+    st.title("Open AI or Gemini Options")
+
+    # Radio
+    st.header("Radio:")
+    radio = st.radio("Radio", ["Open AI", "Gemini", "TBD"])  # Removed extra space after "Gemini"
+    st.write("Selected option:", radio)
+    role = st.text_input("Enter Role")
+    st.write("Entered role:", role)   
+        
+    # Slider
+    st.header("Slider:")
+    temp = st.slider("Temperature", min_value=0.0, max_value=1.0, value=0.7, step=0.1)  # Corrected slider label
+    st.write("Selected value:", temp)
+    
+    if radio == "Open AI":  # Corrected if statement syntax and comparison
+        generate_openai_post(role, temp)
+    
+    elif radio == "Gemini":
+        generate_gemini_post(role, temp)
+
+def generate_openai_post(role, temp):
+    def generate_linkedin_post(topic, role):
+        # Enhanced prompt with additional context for better post generation
+        prompt = (
+            f"You as {role} Create a professional, engaging LinkedIn post about {topic}. "
+            "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)
+        return response
+    
+    with st.form("my_form"):
+        topic = st.text_area("Enter the topic for your LinkedIn post:")
+        submitted = st.form_submit_button("Generate Post")
+        if submitted and topic:
+            post = generate_linkedin_post(topic, role)
+            st.info(post)
+        elif submitted and not topic:
+            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
+    # Example implementation:
+    gemini = Gemini(api_key="YOUR_GEMINI_API_KEY", temperature=temp)
+    # 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()