tp_3

3. Create a Gemini-like Interface

The goal of this session is to create a chatbot-like interface that will be able to answer the user's questions.

3.1 Create the Streamlit App

Edit the app.py file to have the following features:

• st.chat_message to display the conversation (documentation here)
• An option for the user to choose the temperature of the model
• An option for the user to select the answer language ("French", "English", "Arabic")
• Keep the history of the conversation in a list and display it in the chat messages

3.2 Create the API Logic

Edit the api.py file to:

• Receive in an /answer endpoint the user's question, the temperature, and the language
• Return the question, language, and temperature in the response as a sentence: "The user asked the question: <question> in <language> with a temperature of <temperature>"

3.3 Test Locally the Streamlit App and the API

• Use TP 2 to test the app and the API locally.

Goal:

3.4 Edit the api.py File to Use a Gemini Model Using LangChain Accelerator

• Edit the .env file with the GOOGLE_API_KEY variables provided by the instructor
• Follow this tutorial here
• Install the requirements in the requirements.txt file
• Test the Streamlit app by adjusting the temperature and the language

Goal:

3.5 Create a Short Story Generator

• Edit the prompt to generate a short story about a user-input theme
• Edit the app.py to ask for a theme instead of a question
• Leave the UserInput class variables unchanged

Goal:

3.6 Protect Our Environment Variable

3.7 Deploy Your Story Generator on Cloud Run

• Deploy the FastAPI app

# May change depending on your platform
# Replace <my-docker-image-name> and <my-app-name> with your initials + _api
# Florian Bastin -> <my-docker-image-name>fb_api
# Replace docker buildx build --platform linux/amd64 with docker build -t if it does not work
docker buildx build --platform linux/amd64 --push -t europe-west1-docker.pkg.dev/dauphine-437611/dauphine-ar/<my-docker-name>:latest -f Dockerfile_api .

# Be careful, the default port is 8080 for Cloud Run.
# If you have an error message, edit the default Cloud Run port on the interface or in the command line
gcloud run deploy <my-app-name> \
    --image=<my-region>-docker.pkg.dev/<my-project-id>/<my-registry-name>/<my-docker-name>:latest \
    --platform=managed \
    --region=<my-region> \
    --allow-unauthenticated \
    --set-env-vars GOOGLE_API_KEY=[INSERT_GOOGLE_API_KEY] \
    --port 8181

# Note that a SECRET KEY like this should be provided by GOOGLE SECRET MANAGER for more safety.
# For simplicity, we will use the env variable here.

• Change the HOST in your app.py to the URL of the FastAPI Example: HOST = "https://fb-1021317796643.europe-west1.run.app/answer"

• Deploy the Streamlit app

# May change depending on your platform
# Replace <my-docker-image-name> and <my-app-name> with your initials + _streamlit
# Florian Bastin -> <my-docker-image-name>fb_streamlit
# Replace docker buildx build --platform linux/amd64 with docker build -t if it does not work
docker buildx build --platform linux/amd64 --push -t europe-west1-docker.pkg.dev/dauphine-437611/dauphine-ar/<my-docker-name>:latest -f Dockerfile .

gcloud run deploy <initials>-streamlit \
    --image=europe-west1-docker.pkg.dev/dauphine-437611/dauphine-ar/<initials>-streamlit:latest \
    --platform=managed \
    --region=europe-west1 \
    --allow-unauthenticated \
    --port 8080

Goal: