{"id":26399541,"url":"https://github.com/shrutakeerti/assignments-combined","last_synced_at":"2026-04-27T01:31:42.811Z","repository":{"id":272232603,"uuid":"863979081","full_name":"Shrutakeerti/Assignments-Combined","owner":"Shrutakeerti","description":"This is the repo to keep all the assigments combined I did till now ","archived":false,"fork":false,"pushed_at":"2025-03-17T21:08:16.000Z","size":9184,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-07-01T01:44:21.541Z","etag":null,"topics":["ai","aiml","api","ml","streamlit","web"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","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/Shrutakeerti.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":"2024-09-27T09:12:03.000Z","updated_at":"2025-03-17T21:08:20.000Z","dependencies_parsed_at":"2025-01-13T05:28:33.299Z","dependency_job_id":"e8fc2498-5624-4b5e-94d9-731a318f3c70","html_url":"https://github.com/Shrutakeerti/Assignments-Combined","commit_stats":null,"previous_names":["shrutakeerti/assignment---27-09-2024"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/Shrutakeerti/Assignments-Combined","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shrutakeerti%2FAssignments-Combined","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shrutakeerti%2FAssignments-Combined/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shrutakeerti%2FAssignments-Combined/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shrutakeerti%2FAssignments-Combined/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Shrutakeerti","download_url":"https://codeload.github.com/Shrutakeerti/Assignments-Combined/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Shrutakeerti%2FAssignments-Combined/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":32319559,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-26T23:26:28.701Z","status":"ssl_error","status_checked_at":"2026-04-26T23:26:25.802Z","response_time":129,"last_error":"SSL_read: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"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","aiml","api","ml","streamlit","web"],"created_at":"2025-03-17T13:30:21.491Z","updated_at":"2026-04-27T01:31:42.792Z","avatar_url":"https://github.com/Shrutakeerti.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"#  Programming Test: Learning Activations in Neural Networks\n\n## Overview\nThis project is a Breast Cancer Prediction System that utilizes a Neural Network model to predict whether a tumor is malignant or benign based on input features. Additionally, the project integrates a chatbot assistant to guide users in using the system or answer basic questions.\n\n## Features\n- **Breast Cancer Prediction**: Enter tumor features to get a prediction (malignant or benign).\n- **Interactive Chatbot**: A simple rule-based chatbot to assist users with the prediction process.\n- **Streamlit UI**: User-friendly interface built using Streamlit for both prediction and chatbot interactions.\n- **Flask API**: Backend server powered by Flask that handles prediction requests and chatbot interactions.\n\n## Table of Contents\n- Project Structure\n- Installation\n- Usage\n- Endpoints\n- Technology Stack\n- Screenshots\n- License\n- Contributors\n- Contact\n\n## Project Structure\n```bash\n.\n├── app.py                 # Flask API for prediction and chatbot\n├── streamlit_app.py        # Streamlit app for prediction UI and chatbot interface\n├── model.pth               # Pretrained PyTorch model\n├── README.md               # Project readme file\n└── requirements.txt        # List of dependencies\n```\n## Installation\n\n### 1.Clone the repository:\n```bash\ngit clone https://github.com/your-username/breast-cancer-prediction-chatbot.git\ncd breast-cancer-prediction-chatbot\n```\n### 2. Set up a virtual environment:\n\n#### For Windows:\n```bash\npython -m venv venv\nvenv\\Scripts\\activate\n```\n#### For macOS/Linux:\n```bash\npython3 -m venv venv\nsource venv/bin/activate\n```\n### 3. Install dependencies:\n```bash\npip install -r requirements.txt\n```\n#### Download the pretrained model:\n#### Make sure you have the model.pth file in the project directory.\n## Usage\n\n### Start the Flask API:\n```bash\npython app.py\n```\n### This will start the Flask server on http://127.0.0.1:5000. The server handles both prediction and chatbot routes.\n\n### Run the Streamlit App.In a separate terminal, run the following command to launch the Streamlit app:\n```bash\nstreamlit run streamlit_app.py\n\n```\n\n## Endpoints\n\n### Prediction Endpoint:\n- **URL**: `/predict`\n- **Method**: `POST`\n- **Request Body**:\n```json\n{\n  \"features\": [feature_1, feature_2, ..., feature_31]\n}\n```\n\n- **Response**:\n```json\n{\n  \"prediction\": \"malignant\" or \"benign\"\n}\n```\n### Chatbot Endpoint:\n- **URL**: `/chatbot`\n- **Method**: `POST`\n- **Request Body**:\n```json\n{\n  \"message\": \"user's message\"\n}\n```\n- **Response**:\n```json\n{\n  \"response\": \"chatbot's response\"\n}\n```\n## Technology Stack\n- **Frontend**: Streamlit (for UI)\n- **Backend**: Flask (API)\n- **ML Model**: PyTorch\n- **Libraries**:\n  - `torch`: For neural network model\n  - `pandas`, `numpy`: Data manipulation\n  - `sklearn`: Data preprocessing (StandardScaler)\n  - `requests`: API requests\n\n## Screenshot\n\n![Chatbot](https://github.com/Shrutakeerti/Assignment---27-09-2024/blob/main/Chatbot%20(2).png)\n![Prediction features](https://github.com/Shrutakeerti/Assignment---27-09-2024/blob/main/prediction.jpeg)\n\n\n\n\n## This is deployed using streamlit\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshrutakeerti%2Fassignments-combined","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fshrutakeerti%2Fassignments-combined","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fshrutakeerti%2Fassignments-combined/lists"}