app.py

import streamlit as st
from openai import OpenAI
import os

# Set up NVIDIA API client
client = OpenAI(
    base_url="https://integrate.api.nvidia.com/v1",
    api_key=os.environ.get("NVIDIA_API_KEY")
)
st.markdown("## 🛠️ Response Specification Features")
st.markdown("**The expanders below are parameters that you can adjust to customize the AI response bihh.**")
with st.expander("🎨 **Temperature (Creativity Control)**"):
    st.write("""
    This parameter controls the **creativity** of the AI's responses:
    - **0.0**: Always the same response (deterministic).  
    - **0.1 - 0.3**: Mostly factual and repetitive.  
    - **0.4 - 0.7**: Balanced between coherence and creativity.  
    - **0.8 - 1.0**: Highly creative but less predictable.
    """)

with st.expander("📏 **Max Tokens (Response Length)**"):
    st.write("Defines the maximum number of words/subwords in the response.")

with st.expander("🎯 **Top-p (Nucleus Sampling)**"):
    st.write("""
    Controls word diversity by sampling from top-probability tokens:
    - **High `top_p` + Low `temperature`** → More factual, structured responses.
    - **High `top_p` + High `temperature`** → More diverse, unexpected responses.
    """)

with st.expander("🔄 **Number of Responses**"):
    st.write("Specifies how many response variations the AI should generate.")

with st.expander("✅ **Fact-Checking**"):
    st.write("""
    - If **enabled**, AI prioritizes factual accuracy.  
    - If **disabled**, AI prioritizes creativity.
    """)

st.markdown("""
### 🔎 **Summary**  
- `temperature` → Adjusts **creativity vs accuracy**.  
- `max_tokens` → Defines **response length**.  
- `top_p` → Fine-tunes **word diversity**.  
- `fact_check` → Ensures **factual correctness** (but may reduce fluency).  
- `num_responses` → Generates **different variations** of the same prompt.
""")

def query_ai_model(prompt, model="meta/llama-3.1-405b-instruct", temperature=0.7, max_tokens=512, top_p=0.9, fact_check=False, num_responses=1):
    responses = []
    
    try:
        if fact_check:
            prompt = "Ensure factual accuracy. " + prompt

        for _ in range(num_responses):  # Response Loop para sa number of responses
            completion = client.chat.completions.create(
                model=model,
                messages=[{"role": "user", "content": prompt}],
                temperature=temperature,
                top_p=top_p,
                max_tokens=max_tokens
            )
            response = completion.choices[0].message.content
            responses.append(response)

    except Exception as e:
        st.error(f"An error occurred: {str(e)}")
    
    return responses  # Return a list of responses

# Simple streamlit UI palang this
st.title("Mark's AI Chatbot")
st.write("Provide a topic and customize the response criteria.")

# Input Fields
user_input = st.text_area("Your Prompt:", placeholder="Type something...")

# Dropdown Menus
output_format = st.selectbox("Select Output Format:", ["Story", "Poem", "Article", "Code"])
tone_style = st.selectbox("Select Tone/Style:", ["Formal", "Informal", "Humorous", "Technical"])

# Sliders
creativity_level = st.slider("Creativity Level:", min_value=0.0, max_value=1.0, value=0.7, step=0.1)
max_length = st.slider("Max Length (tokens):", min_value=100, max_value=1024, value=512, step=50)

#Numeric Inputs
num_responses = st.number_input("Number of Responses:", min_value=1, max_value=5, value=1, step=1)

# Checkboxes
enable_creativity = st.checkbox("Enable Creative Mode", value=True)
fact_checking = st.checkbox("Enable Fact-Checking")

if st.button("Generate Answer"):
    if user_input.strip():
        with st.spinner("Generating response..."):
            full_prompt = f"Format: {output_format}\nTone: {tone_style}\nPrompt: {user_input}"
            ai_responses = query_ai_model(
                full_prompt,
                temperature=creativity_level if enable_creativity else 0.2,
                max_tokens=max_length,
                top_p=0.9 if enable_creativity else 0.7,
                fact_check=fact_checking,
                num_responses=num_responses
            )

        st.success("AI Responses:")
        for i, response in enumerate(ai_responses, 1):
            st.markdown(f"### Response {i}")
            st.write(response)
    else:
        st.warning("Please enter a prompt before clicking the button.")