sync wih remote

aiutils.py

@@ -0,0 +1,113 @@
+import streamlit as st
+import google.generativeai as genai
+from openai import OpenAI
+from huggingface_hub import InferenceClient
+import time
+import os
+
+GEMINI_MODEL_ID = "gemini-2.0-flash-exp" 
+gemini_api_key = os.getenv("GEMINI_API_KEY")
+model_id = GEMINI_MODEL_ID
+genai.configure(api_key=gemini_api_key)
+
+gpt_api_key = os.getenv("OPENAI_API_KEY")
+gptclient = OpenAI(api_key=gpt_api_key)
+
+LLAMA_MODEL_ID = "meta-llama/Llama-3.2-3B-Instruct"
+hf_token = os.getenv("HF_TOKEN")
+llamaclient = InferenceClient(api_key=hf_token)
+
+
+def ask_gemini(prompt):
+    """Generates Gemini response to the  prompt."""
+    try:
+        model = genai.GenerativeModel(GEMINI_MODEL_ID)
+        chat = model.start_chat()
+            
+        # Record the time before sending the prompt
+        start_time = time.time()
+
+        # Send a text prompt to Gemini API
+        response = chat.send_message(
+            [
+                prompt
+            ],
+        )
+
+        # Record the time after receiving the response
+        end_time = time.time()
+
+        # Calculate the elapsed time
+        elapsed_time = end_time - start_time
+
+        # Format the elapsed time as a string
+        elapsed_time_str = f"{elapsed_time:.2f} seconds"
+
+        return response.text, elapsed_time_str
+   
+    except Exception as e:
+        st.error(f"An error occurred while generating AI response from Gemini: {e}")
+        return None, None
+
+
+def ask_gpt(prompt):
+    try:
+
+        # Record the time before sending the prompt
+        start_time = time.time()
+
+        completion = gptclient.chat.completions.create(
+            model = "gpt-4o",
+            messages = [{"role": "user", "content": prompt}],
+            temperature=0.2,
+            top_p=0.7,
+            max_tokens=1024,
+        )
+
+       # Record the time after receiving the response
+        end_time = time.time()
+
+        # Calculate the elapsed time
+        elapsed_time = end_time - start_time
+
+        # Format the elapsed time as a string
+        elapsed_time_str = f"{elapsed_time:.2f} seconds"
+
+        return completion.choices[0].message.content, elapsed_time_str
+        
+    except Exception as e:
+        st.error(f"Error processing GPT 4o response: {e}")
+        return None, None
+
+def ask_llama(prompt):
+    try:
+        messages = [
+            {
+                "role": "user",
+                "content": prompt
+            }
+        ]
+
+        # Record the time before sending the prompt
+        start_time = time.time()
+
+        completion = llamaclient.chat.completions.create(
+            model=LLAMA_MODEL_ID, 
+            messages=messages, 
+            max_tokens=1024
+        )
+
+       # Record the time after receiving the response
+        end_time = time.time()
+
+        # Calculate the elapsed time
+        elapsed_time = end_time - start_time
+
+        # Format the elapsed time as a string
+        elapsed_time_str = f"{elapsed_time:.2f} seconds"
+
+        return completion.choices[0].message.content, elapsed_time_str
+        
+    except Exception as e:
+        st.error(f"Error: {e}")
+        return None, None

app.py

@@ -1,46 +1,69 @@
 import streamlit as st
+from aiutils import ask_gemini, ask_gpt, ask_llama
 
-# App title
-st.title("AI Task Generator")
-
-# Step 1: Model selection
-st.header("Select AI Model")
-ai_model = st.selectbox(
-    "Choose one of the following AI models:",
-    ["Gemini 2.0", "OpenAI GPT 4.0", "Meta Llama 3.2"],
-)
-
-# Step 2: Task selection
-st.header("Select Task")
-
-task = st.selectbox(
-    "What do you want to generate?",
-    ["Generate a syllabus", "Generate an exam", "Create a program"],
-)
-
-# Step 3: Generate prompt
-if st.button("Generate Prompt"):
-    # Create a prompt based on the user's choices
-    prompt = f"You selected {ai_model} to {task.lower()}"
-    st.write(f"**Prompt:** {prompt}")
-
-    # Dummy responses for AI models
-    gemini_response = f"[Gemini 2.0 Response] Dummy output for: {task}"
-    gpt_response = f"[OpenAI GPT 4.0 Response] Dummy output for: {task}"
-    llama_response = f"[Meta Llama 3.2 Response] Dummy output for: {task}"
-
-    # Step 4: Display responses in tabs
-    st.header("AI Model Outputs")
-    tab1, tab2, tab3 = st.tabs(["Gemini 2.0", "OpenAI GPT 4.0", "Meta Llama 3.2"])
-
-    with tab1:
-        st.subheader("Gemini 2.0")
-        st.write(gemini_response)
-
-    with tab2:
-        st.subheader("OpenAI GPT 4.0")
-        st.write(gpt_response)
-
-    with tab3:
-        st.subheader("Meta Llama 3.2")
-        st.write(llama_response)
+
+def main():
+    # App title
+    st.title("Three-way Comparison of AI Models")
+
+    # Step 1: Task selection
+    st.header("Select Task")
+
+    task = st.selectbox(
+        "What do you want to generate?",
+        ["Generate a syllabus", "Generate an exam", "Create a program"],
+    )
+
+    # Step 2: Generate prompt
+    prompt = ""
+    if task == "Generate a syllabus":
+        prompt = """Generate a syllabus for the couse Intelligent Systems 
+        for 3rd year Computers Science students of the College of ICT of 
+        West Visayas State University. The course with use the book 
+        'Building Intelligent Systems Using Machine Learning and 
+        Deep Learning'.  CCS 229  is a 3-unit lecture 
+        course that will run for 18 weeks (54 hours)."""
+
+    elif task == "Generate an exam":
+        prompt = """Generate a 10-item multiple choice test with 4 options 
+        on the topic Machine Learning.  The test should require higher order
+        thinking skills and should be appropriate for 3rd year 
+        Computer Science students."""
+    
+    elif task == "Create a program":
+        prompt = """Create a streamlit app that generates a random password 
+        that complies with the following requirements: 1) at least 8 characters
+        2) at least one uppercase letter 3) at least one lowercase letter
+        4) at least one number 5) at least one special character."""
+
+    st.write(f"Prompt: {prompt}")   
+
+    if st.button("Generate Prompt"):
+        st.write("Please wait. This is a compute intensive process...")
+        with st.spinner("Asking AI Models..."):
+            # Dummy responses for AI models
+            gemini_response, gemini_rt = ask_gemini(prompt)
+            gpt_response, gpt_rt = ask_gpt(prompt)
+            llama_response, llama_rt = ask_llama(prompt)
+
+            # Step 3: Display responses in tabs
+            st.header("AI Model Outputs")
+            tab1, tab2, tab3 = st.tabs(["Gemini 2.0", "OpenAI GPT 4.0", "Meta Llama 3.2"])
+
+            with tab1:
+                st.subheader("Gemini 2.0")
+                st.write(f"Response Time: {gemini_rt}")
+                st.write(gemini_response)
+
+            with tab2:
+                st.subheader("OpenAI GPT 4.0")
+                st.write(f"Response Time: {gpt_rt}")    
+                st.write(gpt_response)
+
+            with tab3:
+                st.subheader("Meta Llama 3.2")
+                st.write(f"Response Time: {llama_rt}")  
+                st.write(llama_response)
+
+if __name__ == "__main__":
+    main()  

requirements.txt

@@ -0,0 +1,4 @@
+streamlit
+openai
+google-generativeai
+huggingface_hub