PROGRESS.md

Project Progress Log

This document tracks the step-by-step process of creating and deploying the Simple Sentiment Analyzer application.

1. Prerequisites & Initial Setup

• Goal: Build and deploy a sentiment analysis web application using Hugging Face.
• Accounts: A new Hugging Face account was created and verified via email. A GitHub account was already available.
• Tools: Confirmed that python and git were installed locally on the Ubuntu system.

2. Local Project Initialization

• Directory: Created a project directory named sentiment-app.
• Dependency Management: Chose to use Poetry for modern Python package and environment management.
• Poetry Setup:
  • Initialized the project with poetry init, creating the pyproject.toml configuration file.
  • Added the required libraries (transformers, torch, and gradio) using the poetry add command. This automatically created a virtual environment and installed the dependencies.

3. Application Development

• Main Application (app.py):

  • Created the app.py file.
  • Wrote the Python code to load a pre-trained sentiment analysis model using the transformers pipeline.
  • Wrote a function analyze_sentiment to process user input and return the model's prediction.
  • Built a web user interface using Gradio, creating a title, description, and a simple textbox input/output.

• Deployment Dependencies (requirements.txt):

  • To ensure compatibility with Hugging Face Spaces, a requirements.txt file was generated from the Poetry environment using the poetry export command.

4. Local Testing

• Execution: The application was run locally from the terminal using poetry run python app.py.
• Verification: The Gradio server started successfully. The application was accessed via a local URL (http://127.0.0.1:7860) in a web browser.
• Functionality Check: Tested the app with both positive and negative sentences to confirm it was working as expected.
• Shutdown: The local server was stopped gracefully using Ctrl+C in the terminal.

5. Deployment to Hugging Face Spaces

• Git Initialization: The project was already a Git repository. New files (app.py, pyproject.toml, poetry.lock, requirements.txt) were staged with git add and committed with git commit.

• Space Creation:

  • A new "Space" was created on the Hugging Face website.
  • The Space was configured with the Gradio SDK.

• Connecting Local to Remote:

  • The new Hugging Face Space's Git URL was added as a remote to the local repository under the name huggingface (git remote add ...).

• First Push & Reconciliation:

  • The initial git push huggingface main failed due to the remote Space having its own initial commit (with a README.md file), causing "divergent histories".
  • This was resolved by pulling the remote changes first using git pull huggingface main --allow-unrelated-histories. This merged the remote's README.md into the local project.

• Documentation:

  • The default README.md was updated with a detailed description of the project, its technologies, and usage instructions.
  • This PROGRESS.md file was created to document the project's entire lifecycle.