{"id":14155153,"url":"https://github.com/hamelsmu/code_search","last_synced_at":"2025-06-19T06:37:48.425Z","repository":{"id":39740518,"uuid":"132466169","full_name":"hamelsmu/code_search","owner":"hamelsmu","description":"Code For Medium Article: \"How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning\"","archived":false,"fork":false,"pushed_at":"2022-12-08T02:10:59.000Z","size":77209,"stargazers_count":488,"open_issues_count":28,"forks_count":137,"subscribers_count":24,"default_branch":"master","last_synced_at":"2025-02-27T00:04:32.945Z","etag":null,"topics":["code-search","data-science","deep-learning","fastai","keras","machine-learning","machine-learning-on-source-code","ml-on-code","natural-language-processing","nlp","python","pytorch","search","search-algorithm","searching-algorithms","semantic-search","semantic-search-engine","tensorflow","tutorial"],"latest_commit_sha":null,"homepage":"https://medium.com/@hamelhusain/semantic-code-search-3cd6d244a39c","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/hamelsmu.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2018-05-07T13:41:00.000Z","updated_at":"2025-01-10T12:36:22.000Z","dependencies_parsed_at":"2023-01-25T03:15:22.981Z","dependency_job_id":null,"html_url":"https://github.com/hamelsmu/code_search","commit_stats":null,"previous_names":[],"tags_count":1,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hamelsmu%2Fcode_search","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hamelsmu%2Fcode_search/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hamelsmu%2Fcode_search/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/hamelsmu%2Fcode_search/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/hamelsmu","download_url":"https://codeload.github.com/hamelsmu/code_search/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243718765,"owners_count":20336589,"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":["code-search","data-science","deep-learning","fastai","keras","machine-learning","machine-learning-on-source-code","ml-on-code","natural-language-processing","nlp","python","pytorch","search","search-algorithm","searching-algorithms","semantic-search","semantic-search-engine","tensorflow","tutorial"],"created_at":"2024-08-17T08:02:17.020Z","updated_at":"2025-03-15T10:30:52.101Z","avatar_url":"https://github.com/hamelsmu.png","language":"Jupyter Notebook","readme":"[![GitHub license](https://img.shields.io/github/license/hamelsmu/code_search.svg)](https://github.com/hamelsmu/code_search/blob/master/LICENSE)\n[![Python 3.6](https://img.shields.io/badge/python-3.6-blue.svg)](https://www.python.org/downloads/release/python-360/)\n[![GitHub issues](https://img.shields.io/github/issues/hamelsmu/code_search.svg)](https://github.com/hamelsmu/code_search/issues)\n\n\n## Semantic Code Search\n\nCode For Medium Article: \"[How To Create Natural Language Semantic Search for Arbitrary Objects With Deep Learning](https://medium.com/@hamelhusain/semantic-code-search-3cd6d244a39c)\"\n\n![Alt text](./gifs/live_search.gif)\n\n---\n\n## Warning - This Project Is Deprecated In Favor Of [CodeSearchNet](https://github.com/github/codesearchnet)\n\n**The techniques presented here are old and have been significantly refined in a subsequent project called [CodeSearchNet](https://github.com/github/codesearchnet), with an associated [paper](https://arxiv.org/abs/1909.09436).**\n\nI recommend looking at the aforementioned project for a more modern approach to this topic, as in retrospect this blog post is somewhat of an ugly hack.\n\n## Resources\n\n#### Docker Containers\n\nYou can use these container to reproduce the environment the authors used for this tutorial.  Incase it is helpful, I have provided a [requirements.txt](./requirements/requirements.txt) file, however, we highly recommend using the docker containers provided below as the dependencies can be complicated to build yourself.\n\n - [hamelsmu/ml-gpu](https://hub.docker.com/r/hamelsmu/ml-gpu/): Use this container for any *gpu* bound parts of the tutorial.  We recommend running the entire tutorial on an aws `p3.8xlarge` and using this image.\n\n - [hamelsmu/ml-cpu](https://hub.docker.com/r/hamelsmu/ml-cpu/): Use this container for any *cpu* bound parts of this tutorial.\n\n\n #### Notebooks\n\n The [notebooks](./notebooks) folder contains 5 Jupyter notebooks that correspond to Parts 1-5 of the tutorial.\n\n\n#### Related Blog Posts\n\nThis tutorial assumes knowledge of the material presented in [a previous tutorial on sequence-to-sequence models](https://towardsdatascience.com/how-to-create-data-products-that-are-magical-using-sequence-to-sequence-models-703f86a231f8).\n\n---\n## PRs And Comments Are Welcome\n\nWe have made best attempts to make sure running this tutorial is as painless as possible.  If you think something can be improved, please submit a PR!   \n","funding_links":[],"categories":["tutorial"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamelsmu%2Fcode_search","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fhamelsmu%2Fcode_search","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fhamelsmu%2Fcode_search/lists"}