Examples & Use Cases

import openai
import streamlit as st

# Configure API
openai.api_key = "YOUR_API_KEY"
openai.api_base = "https://inference.braintwin.ai/v1"

st.title("AI Chatbot")

if "messages" not in st.session_state:
    st.session_state.messages = []

# Display chat history
for message in st.session_state.messages:
    with st.chat_message(message["role"]):
        st.markdown(message["content"])

# Chat input
if prompt := st.chat_input("What's on your mind?"):
    st.session_state.messages.append({"role": "user", "content": prompt})
    
    with st.chat_message("user"):
        st.markdown(prompt)
    
    with st.chat_message("assistant"):
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=st.session_state.messages,
            temperature=0.7,
            stream=True
        )
        
        message_placeholder = st.empty()
        full_response = ""
        
        for chunk in response:
            if chunk.choices[0].delta.get("content"):
                full_response += chunk.choices[0].delta.content
                message_placeholder.markdown(full_response + "▌")
        
        message_placeholder.markdown(full_response)
    
    st.session_state.messages.append({"role": "assistant", "content": full_response})

import openai

openai.api_key = "YOUR_API_KEY"
openai.api_base = "https://inference.braintwin.ai/v1"

def summarize_text(text, max_words=100):
    """Summarize long text using AI"""
    
    prompt = f"""
    Please provide a concise summary of the following text in approximately {max_words} words:

    {text}

    Summary:
    """
    
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=[
            {"role": "system", "content": "You are a helpful assistant that creates concise, accurate summaries."},
            {"role": "user", "content": prompt}
        ],
        temperature=0.3,
        max_tokens=150
    )
    
    return response.choices[0].message.content

# Example usage
long_text = """
[Your long text here...]
"""

summary = summarize_text(long_text)
print(f"Summary: {summary}")