{"id":22428114,"url":"https://github.com/gxrco/llm-class","last_synced_at":"2026-04-13T16:31:30.137Z","repository":{"id":252827820,"uuid":"840493078","full_name":"Gxrco/LLM-Class","owner":"Gxrco","description":"Projects developed for Desing \u0026 Innovation with AI and LLM class at UVG.","archived":false,"fork":false,"pushed_at":"2024-11-21T14:10:49.000Z","size":2112,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-01T11:43:06.327Z","etag":null,"topics":["agents","bot","langchain","openai","python"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":false,"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/Gxrco.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":"2024-08-09T20:48:43.000Z","updated_at":"2024-10-11T19:21:26.000Z","dependencies_parsed_at":"2024-08-16T21:44:08.250Z","dependency_job_id":null,"html_url":"https://github.com/Gxrco/LLM-Class","commit_stats":null,"previous_names":["gxrco/llm-class"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gxrco%2FLLM-Class","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gxrco%2FLLM-Class/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gxrco%2FLLM-Class/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/Gxrco%2FLLM-Class/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/Gxrco","download_url":"https://codeload.github.com/Gxrco/LLM-Class/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245798537,"owners_count":20673901,"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":["agents","bot","langchain","openai","python"],"created_at":"2024-12-05T20:13:48.764Z","updated_at":"2026-04-13T16:31:25.111Z","avatar_url":"https://github.com/Gxrco.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"\n# LLM - Agents\n\nThis project/script generates a brief summary and two interesting facts about a person using information scraped from their LinkedIn profile. It utilizes LangChain to format prompts and interact with OpenAI's gpt-3.5-turbo model for text generation. The Proxycurl library is used to scrape LinkedIn data, which is then processed through a chain that combines the prompt template and the language model.\n\n## Libraries\n\n- LangChain: For managing the prompt template and integrating with OpenAI's language model.\n- Proxycurl: For scraping LinkedIn profile data.\n- dotenv: For securely handling environment variables.\n\n## Classes\n\n- Laboratory 01 - Content by prompt \n- Laboratory 02 - Summary with scrapping ⬅️\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgxrco%2Fllm-class","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fgxrco%2Fllm-class","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fgxrco%2Fllm-class/lists"}