{"id":20114104,"url":"https://github.com/papireddy903/resume-data-extractor","last_synced_at":"2026-05-10T08:49:50.560Z","repository":{"id":214762681,"uuid":"737290413","full_name":"papireddy903/resume-data-extractor","owner":"papireddy903","description":"A Streamlit application powered by Google's Gemini Pro Vision model to effortlessly extract data from PDF resumes, simplifying the resume screening process.","archived":false,"fork":false,"pushed_at":"2023-12-31T11:03:17.000Z","size":3,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-03-09T19:38:44.210Z","etag":null,"topics":["gemini-pro-vision","genai","generative-ai","python","streamlit"],"latest_commit_sha":null,"homepage":"","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/papireddy903.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}},"created_at":"2023-12-30T13:53:09.000Z","updated_at":"2024-11-27T18:44:47.000Z","dependencies_parsed_at":"2024-11-13T18:33:03.382Z","dependency_job_id":"5fde3c0a-6efc-4b9c-976e-c75fd263968b","html_url":"https://github.com/papireddy903/resume-data-extractor","commit_stats":null,"previous_names":["papireddy903/resume-data-extractor"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/papireddy903/resume-data-extractor","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/papireddy903%2Fresume-data-extractor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/papireddy903%2Fresume-data-extractor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/papireddy903%2Fresume-data-extractor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/papireddy903%2Fresume-data-extractor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/papireddy903","download_url":"https://codeload.github.com/papireddy903/resume-data-extractor/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/papireddy903%2Fresume-data-extractor/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286079811,"owners_count":27282121,"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":"2025-11-27T02:00:05.795Z","response_time":58,"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":["gemini-pro-vision","genai","generative-ai","python","streamlit"],"created_at":"2024-11-13T18:28:10.795Z","updated_at":"2025-11-27T08:02:19.790Z","avatar_url":"https://github.com/papireddy903.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Resume Data Extractor with Gemini Pro Vision\n\nThis Streamlit web application leverages the Gemini Pro Vision API to extract data from resume in PDF format. Users can upload a resume, view the resume image, and extract relevant data by asking questions.\n\n## Features\n\n- Upload a resume in PDF format.\n- View the resume image.\n- Extract data by asking specific questions.\n- Extract all available data from the resume.\n\n## Prerequisites\n\n- Python 3.10\n- [Streamlit](https://streamlit.io/)\n- [Gemini Pro Vision API Key](https://ai.google.dev/tutorials/python_quickstart)\n\n## Installation\n\n1. **Clone the repository:**\n   ```bash\n   git clone https://github.com/your-username/your-repo.git\n   ```\n2. **Navigate to the project directory:**\n   ```bash\n   cd your-repo\n   ```\n3. **Install the required Python packages:**\n   ```bash\n   pip install -r requirements.txt\n   ```\n4. **Create a .env file in the project root and add your Gemini Pro Vision API key:**\n   ```bash\n   GOOGLE_API_KEY=your-google-api-key\n   ```\n5. **Usage**\n   Run the Streamlit app with the following command:\n   ```bash\n   streamlit run app.py\n   ```\n   \n![image](https://github.com/papireddy903/resume-data-extractor/assets/97383201/b42496b2-2571-408d-91de-6b80dc6e115b)\n\n![image](https://github.com/papireddy903/resume-data-extractor/assets/97383201/c80cdf88-12a5-4c15-a669-540edb48446a)\n![image](https://github.com/papireddy903/resume-data-extractor/assets/97383201/92cca72d-c25f-4004-9104-49966ad630a5)\n\n\n\n**Issues and Contributions**\nIf you encounter any issues or have suggestions for improvements, please open an issue or submit a pull request.\n\n\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpapireddy903%2Fresume-data-extractor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fpapireddy903%2Fresume-data-extractor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fpapireddy903%2Fresume-data-extractor/lists"}