Create app4.py

app4.py

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+import streamlit as st
+from langchain_community.llms import OpenAI
+from langchain_google_genai import ChatGoogleGenerativeAI
+st.set_page_config(layout="wide")
+
+
+# Function to handle AI invocation and response
+def analyze_job_description(topic, model ):
+    prompt = (
+        f"As an HR Manager, I need you to analyze the following job description and identify the key technical skills, nice-to-have skills, must-have skills, and soft skills required for the role: {topic}. "
+        "The post should be concise, informative, and suitable for a professional audience. "
+        "List top 5 points for technical skills, nice-to-have skills, must-have skills, and soft skills required for the role."
+    )
+    if model == "Open AI":
+        llm = OpenAI(openai_api_key=st.secrets["OPENAI_API_KEY"])
+        response = llm(prompt)
+        return response
+    elif model == "Gemini":
+        llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=st.secrets["YOUR_GEMINI_API_KEY"])
+        result = llm.invoke(prompt)
+        return result.content
+
+def main():
+    st.title("JD Analysis")
+    # Radio selection for AI model
+    st.header("Select AI:")
+    model = st.radio("Model", ["Open AI", "Gemini"])
+    st.write("Selected option:", model)
+    
+    # Text area for job description input
+    with st.form("my_form"):
+        topic = st.text_area("Copy Paste the JD here:")
+        submitted = st.form_submit_button("Analyze Now")
+        if submitted and topic:
+            result = analyze_job_description(topic, model )
+            st.info(result)
+        elif submitted and not topic:
+            st.error("Please enter a JD details to analyze.")
+
+
+if __name__ == "__main__":
+    main()