{"id":23042990,"url":"https://github.com/cjunwon/rebbit-mirror","last_synced_at":"2025-04-03T01:19:07.849Z","repository":{"id":154041809,"uuid":"631311461","full_name":"cjunwon/Rebbit-Mirror","owner":"cjunwon","description":"LA Hacks 2023","archived":false,"fork":false,"pushed_at":"2023-04-23T09:54:52.000Z","size":145,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-08T15:32:48.383Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"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/cjunwon.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":"2023-04-22T16:07:25.000Z","updated_at":"2023-09-10T17:14:22.000Z","dependencies_parsed_at":null,"dependency_job_id":"4c5cf25e-77a9-49a2-a135-e731cbbf9982","html_url":"https://github.com/cjunwon/Rebbit-Mirror","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cjunwon%2FRebbit-Mirror","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cjunwon%2FRebbit-Mirror/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cjunwon%2FRebbit-Mirror/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cjunwon%2FRebbit-Mirror/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cjunwon","download_url":"https://codeload.github.com/cjunwon/Rebbit-Mirror/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246916989,"owners_count":20854558,"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","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":[],"created_at":"2024-12-15T20:38:10.278Z","updated_at":"2025-04-03T01:19:07.828Z","avatar_url":"https://github.com/cjunwon.png","language":"Jupyter Notebook","readme":"\u003e A person who has good thoughts cannot ever be ugly. You can have a wonky nose and a crooked mouth and a double chin and stick-out teeth, but if you have good thoughts it will shine out of your face like sunbeams and you will always look lovely. - Roald Dahl\n\n## Inspiration\n\nWe 👦💰 😱😙 spend 🎈 🎈 a lottt of time 🐢 🤣 on 🔥 🥵 our 💩 ✂️✂️ favorite 😘😍 👏 website, Rebbit. Often 💰 🍆💰💰 times, 🕐😆 💦 we 👩‍👩‍👦‍👦 👩‍👩‍👦‍👦 wonder 😮 😮 what 👏😱 👏 some 👨💭 🍯🤔 of our 💩 💦💩 dear 🔆 🔆 redditor friends 🐷 🐷 and colleagues look 🎱 🧐 like 🤮 😛 in 💁 ⭐ real 😾 😾 life. 🔈🌎 😂👨 Sometimes, 🕐 ✨ these 🌍 🍆 people 👫 👨 have 😣✅ 👃🈶 wacky 😜 😜 posts 📱💻 📱💻 and comments that 🤒 🍆 really 😕 👷🏼💳🚡 allow 👨‍👨‍👦‍👦🎫🎫 👨‍👨‍👦‍👦🎫🎫 for 😘 😊 their 🍷 😴 real 🔎 😼 personality to shine! ✨✨✨ ✨✨✨ We 👩‍👩‍👦‍👦 💏🏼 hope 🙏 🙏🏼👏🏼 to find 🔎🔎🔎🔎 🔍 out 😵😵 😰 what 😦 😦 our 💰 💰👶 friends 👯👯‍♂️👯‍♀️ 👥 look 👀 👁️‍🗨️ like 😗 💒😄 in 🙌👏 👉 real 📷 💯 life! 😛 🧬. I am so scawwed.\n\n## What it does\n\nWhen tagged, our Reddit bot creates a photorealistic image of a user based on their history of posts and comments on Reddit.\n\n## How we built it\n\nFor this project, we utilized Python as our primary programming language and Cohere's language model and the DALL-E API to generate photorealistic images of Reddit users. **we fine-tuned co:here generate endpoint to produce descriptive DALL-E prompts to generate the images based on reddit history.** It was interesting to engineer our prompts so that the co:here model could understand an Internet conversation and infer dispositions.\n\nOur Python scripts fetch user data through the Reddit API, create a prompt that feeds into Cohere's generative language model API, which then outputs an optimized prompt to feed into OpenAI's DALL-E model. The resulting image is photorealistic and encapsulates the user's characteristics based on their online presence. We hosted our entire pipeline on Docker, which simplified deployment and testing.\n\n## Challenges we ran into\n\nA primary challenge that we faced was guiding Cohere to generate a prompt for DALL-E in a consistent manner. Using Cohere's model training feature, we fed a dataset of formatted yet diversified prompts that were descriptive and optimized for DALL-E image generation. After training Cohere's generative language model, we achieved successful results that were consistent and descriptive.\n\n## Accomplishments that we're proud of\nWhat man could sleep at the end of the day, proud of what little he accomplished is this cosmic masquerade we call life.\n\n\n## What we learned\n- Reddit API (PRAW)\n- Cohere\n- What DALL-E likes\n\n## What's next for Reddit Mirror\n-More fine tuning for the model will be needed, so that our images can get more sentiment behind them\n-Current models don't return as descriptive an image that they could. We need more tags that can be translated by Dall-E.\n\n\u003e The portrait would be to him the most magical of mirrors. As it had revealed to him his own body, so it would reveal to him his own soul. - Oscar Wilde \n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcjunwon%2Frebbit-mirror","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcjunwon%2Frebbit-mirror","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcjunwon%2Frebbit-mirror/lists"}