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import streamlit as st
import os
from openai import OpenAI
# Set up NVIDIA API client
client = OpenAI(
base_url="https://integrate.api.nvidia.com/v1",
api_key=os.environ.get("NVIDIA_API_KEY")
)
# Streamlit UI
st.title("AI-Powered Text Generation App")
st.write("Interact with an AI model to generate text based on your inputs.")
# Response specification features
st.markdown("## 🛠️ Response Specification Features")
st.markdown("*The expanders below are parameters that you can adjust to customize the AI response.*")
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.
""")
# Function to query the AI model (based on your friend's code)
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 for multiple 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
# Input Fields for Streamlit UI
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")
# Button to generate response
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.") |