{"id":28628438,"url":"https://github.com/gabya06/content_summarization","last_synced_at":"2025-08-16T18:10:09.432Z","repository":{"id":298226690,"uuid":"999273174","full_name":"Gabya06/content_summarization","owner":"Gabya06","description":"AI-powered Streamlit app for summarizing Reddit posts and comparing the outputs of two transformer models: BART and T5-Large","archived":false,"fork":false,"pushed_at":"2025-07-01T22:05:46.000Z","size":662,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-07-01T23:20:23.941Z","etag":null,"topics":["ai","google-cloud","llm","python","streamlt","text-summarizer"],"latest_commit_sha":null,"homepage":"https://content-summarization-app-61465655650.us-east1.run.app","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/Gabya06.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null}},"created_at":"2025-06-10T02:28:17.000Z","updated_at":"2025-07-01T22:05:49.000Z","dependencies_parsed_at":"2025-06-10T03:41:19.580Z","dependency_job_id":null,"html_url":"https://github.com/Gabya06/content_summarization","commit_stats":null,"previous_names":["gabya06/content_summarization"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Gabya06/content_summarization","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabya06%2Fcontent_summarization","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabya06%2Fcontent_summarization/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabya06%2Fcontent_summarization/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabya06%2Fcontent_summarization/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Gabya06","download_url":"https://codeload.github.com/Gabya06/content_summarization/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gabya06%2Fcontent_summarization/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270749519,"owners_count":24638751,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-08-16T02:00:11.002Z","response_time":91,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["ai","google-cloud","llm","python","streamlt","text-summarizer"],"created_at":"2025-06-12T10:33:36.393Z","updated_at":"2025-08-16T18:10:09.422Z","avatar_url":"https://github.com/Gabya06.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# AI Transformer Model Comparison: Reddit Post Summarization\n\nThis is an **AI-powered Streamlit app** for summarizing Reddit posts and comparing the outputs of two transformer models: **BART** and **T5-Large**. It uses Google Gemini to generate a concise summary and highlight differences between the model-generated summaries. \n\n* To learn more about the Hugging Face pipeline, `BART` and `T5-Large` transfomer models, you can follow along on [Medium.com](https://medium.com/@gabya06/t5-vs-bart-the-battle-of-the-summarization-models-c1e6d37e56ca).\n\n* The Reddit API was used to generate the data for this repo; you can read about it [here](https://medium.com/@gabya06/automating-reddit-summaries-pulling-data-with-python-91afeb6acdb3).\n\n---\n\n## Features\n\n- **Upload CSVs** with `BART` and `T5-Large` summaries for Reddit posts\n- **AI-generated summary \u0026 comparison** using Google Gemini\n- **Visualize sentiment** (with emoji) and number of comments (progress bar)\n- **Interactive UI** built with Streamlit\n- **Batch processing** of multiple posts\n- **Docker-ready** for easy deployment\n\n---\n\n## Project Structure\n\n```\ncontent_summarization/\n│\n├── app.py                  # Streamlit app entry point\n├── summarize.py            # Summarization logic and ContentSummary class\n├── requirements.txt        # Python dependencies\n├── Dockerfile              # Docker build instructions\n├── .env.example            # Example environment variables\n├── README.md               # Project documentation\n│\n├── data/                   # Sample data\n│\n└── tests/                  # (TODO) Unit tests\n```\n\n---\n\n## Setup\n\n### 1. Clone the repository\n\n```bash\ngit clone https://github.com/gabya06/content_summarization.git\ncd content_summarization\n```\n\n### 2. Install dependencies\n\n```bash\npip install -r requirements.txt\n```\n\n### 3. Set up environment variables\n\nCopy `.env.example` to `.env` and add your [Google Gemini API key](https://aistudio.google.com/app/apikey):\n\n```\nGEMINI_API_KEY=your-key-here\n```\n\n---\n\n## Usage\n\n### Run locally\n\n```bash\nstreamlit run app.py\n```\n\n- Upload your BART and T5-Large CSV files in the sidebar.\n- Select the number of posts to summarize.\n- Click **Summarize and Compare** to view results.\n\n### CSV Format\n\nYour CSVs should have at least these columns:\n\n- `title`\n- `cleaned_text`\n- `summary_bart` (for BART CSV)\n- `summary_t5` (for T5-Large CSV)\n- `sentiment`\n- `num_comments`\n\n---\n\n## Docker Deployment\n\n### Build and run with Docker\n\n```bash\ndocker build -t content-summarization .\ndocker run -p 8501:8501 --env-file .env content-summarization\n```\n\nThen open [http://localhost:8501](http://localhost:8501) in your browser.\n\n---\n## Google Cloud \nCheck out the app in [Google Cloud!](https://content-summarization-app-61465655650.us-east1.run.app)\n## Customization\n\n- Edit `summarize.py` to change prompt logic or add more models.\n- Tweak `app.py` for UI changes or new visualizations.\n\n---\n\n## Acknowledgements\n\n- [Google Gemini](https://aistudio.google.com/)\n- [Streamlit](https://streamlit.io/)\n- [Hugging Face Transformers](https://huggingface.co/transformers/)\n\n---\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabya06%2Fcontent_summarization","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgabya06%2Fcontent_summarization","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgabya06%2Fcontent_summarization/lists"}