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Create A ChatBot On Your Data

Kulbinder Dio2024-07-16
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Are you tired of clunky chatbot interfaces that limit your creativity? Do you want to harness the power of artificial intelligence to build a conversational app that meets your unique needs? Look no further! With bionicGPT's OpenAI-compatible API, you can create a simple yet powerful chatbot in just a few lines of code.

The Ultimate Flexibility

bionicGPT offers a vast range of options, but what if you want to create a minimalist interface that still leverages the models and RAG functionality already implemented? That's where bionicGPT's API comes in! With just two libraries - Streamlit and OpenAI - you can unlock the full potential of AI-powered chatbots.

Get Started in Minutes

  1. Obtain an API key from bionicGPT and unlock access to a world of AI possibilities. alt text

  2. Install the required libraries: Streamlit and OpenAI.

  3. Copy and paste the code below to get started.

The Code

import streamlit as st
from openai import OpenAI

st.title("bionicGPT API example")

# Set OpenAI API key from Streamlit secrets
client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"],base_url=st.secrets["OPENAI_API_BASE"])

# Set a default model
if "openai_model" not in st.session_state:
   st.session_state["openai_model"] = "llama3-70b-8192"

# Initialize chat history
if "messages" not in st.session_state:
   st.session_state.messages = []

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

if prompt := st.chat_input("What is up?"):
   st.session_state.messages.append({"role": "user", "content": prompt})
   with st.chat_message("user"):
       st.markdown(prompt)

   with st.chat_message("assistant"):
       stream = client.chat.completions.create(
           model=st.session_state["openai_model"],
           messages=[
               {"role": m["role"], "content": m["content"]}
               for m in st.session_state.messages
           ],
           stream=True,
       )
       response = st.write_stream(stream)
   st.session_state.messages.append({"role": "assistant", "content": response})

For the above to work you need to create a secrets.toml file under a folder call .streamlit with the following contents

OPENAI_API_KEY = "bionicAPIKey"
OPENAI_API_BASE= "URL of your bionicGPT instance /v1"

You run the code using streamlit run app.py and you now have a web enabled chatbot for your specific needs

For further details on using Streamlit to build LLM chat apps see Build a basic LLM chat app

Note : A bionicGPT API key gives you full access to an AI Assistant that you create. The AI Assistant in turn specifies a model and optionally a Dataset that has been populated with your documents

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The beauty of having an OpenAI compatible API means we can cut down on the code we need to write. You just have to be aware of specifying a different base address so it accesses your version of bionicGPT or even our SaaS offering.

You're seconds away from trying us out

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