teaching_llm_agents

Rapid prototyping

• Lecture on deeplearning.ai

• ⬆️📎 Code github

Co-creating an MVP with GenAI

• Lecture

• Use a GenAI app to prototype (turn PDF notes into clinical insight)

• Brainstorm end goal

• Who is audience? (non-technical people)

• What does the app look like?

• Features (drag and drop, export to csv, etc.)

• be specific (do not give open ended tasks to GenAI apps)

⚠️ NOTE

Give the AI a role act as a product manager

⬆️📎 Tools

Lecture

• Google Colab

• Streamlit

• ngrok account and auth token

• Sarvam AI API key

Optional

• Python

• Local files

Streamlit

• streamlit

• Interactive streamlit GDP dashboard

• Deploy on streamlit.io

• Click on New app

• Here is a deployed app

• Push your code to github and deploy

• Course on deeplearning.ai on streamlit

• Setup a repository in github

• Or run in Google Colab

• Run streamlit using

streamlit run script.py

• Here is an example script

import streamlit as st
import pandas as pd
import numpy as np

st.write("Streamlit supports a wide range of data visualizations")

all_users = ["Alice", "Bob", "Charly"]
with st.container(border=True):
    users = st.multiselect("Users", all_users, default=all_users)
    rolling_average = st.toggle("Rolling average")

np.random.seed(19)
data = pd.DataFrame(np.random.randn(20, len(users)), columns=users)

if rolling_average:
    data = data.rolling(7).mean().dropna()

tab1, tab2 = st.tabs(["Chart", "Dataframe"])
tab1.line_chart(data, height=250)
tab2.dataframe(data, height=250, use_container_width=True)

• ngrok signup

• create an auth token

• Google Colab notebook

• To save your ngrok authtoken securely in Google Colab, you should use Colab’s Secrets feature. This allows you to store sensitive information like API keys or tokens without embedding them directly in your code, which is important for security and when sharing notebooks.

1. Open the Secrets Panel: In the left sidebar of your Colab notebook, click on the “🔑 Secrets” icon (it looks like a key).
2. Add a new secret: Click the ”+ Add new secret” button.
3. Name the secret: For your ngrok authtoken, you could name it YOUR_AUTHTOKEN (or any other descriptive name you prefer, but remember it for later).
4. Enter the secret value: Paste your ngrok authtoken into the “Value” field.
5. Save: Click “Save secret”.

Once saved, you can access this secret in your Python code using from google.colab import userdata and then userdata.get('YOUR_AUTHTOKEN') (replacing 'YOUR_AUTHTOKEN' with the name you gave your secret).

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