{"id":19747973,"url":"https://github.com/tensorchord/modelz-template-streamlit","last_synced_at":"2026-03-02T22:04:47.200Z","repository":{"id":156777741,"uuid":"633186308","full_name":"tensorchord/modelz-template-streamlit","owner":"tensorchord","description":null,"archived":false,"fork":false,"pushed_at":"2023-04-27T02:01:34.000Z","size":9,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-11-22T22:04:48.127Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Dockerfile","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/tensorchord.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}},"created_at":"2023-04-27T01:02:59.000Z","updated_at":"2023-04-27T02:04:43.000Z","dependencies_parsed_at":"2024-01-23T22:05:38.162Z","dependency_job_id":null,"html_url":"https://github.com/tensorchord/modelz-template-streamlit","commit_stats":null,"previous_names":[],"tags_count":4,"template":true,"template_full_name":null,"purl":"pkg:github/tensorchord/modelz-template-streamlit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Fmodelz-template-streamlit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Fmodelz-template-streamlit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Fmodelz-template-streamlit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Fmodelz-template-streamlit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tensorchord","download_url":"https://codeload.github.com/tensorchord/modelz-template-streamlit/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tensorchord%2Fmodelz-template-streamlit/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":30021826,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-03-02T21:50:36.781Z","status":"ssl_error","status_checked_at":"2026-03-02T21:50:28.329Z","response_time":60,"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":[],"created_at":"2024-11-12T02:19:40.378Z","updated_at":"2026-03-02T22:04:47.162Z","avatar_url":"https://github.com/tensorchord.png","language":"Dockerfile","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Modelz Streamlit Template\n\nThis is a template for creating a [Streamlit](https://streamlit.io/) app on [Modelz](https://modelz.ai/).\n\nBuilding an Streamlit app could be straightforward. You will need to provide three key components:\n\n- A `main.py` file: This file contains the code for making predictions.\n- A `requirements.txt` file: This file lists all the dependencies required for the server code to run.\n- A `Dockerfile` or a simpler [`build.envd`](https://envd.tensorchord.ai/guide/getting-started.html): This file contains instructions for building a Docker image that encapsulates the server code and its dependencies.\n\n## Build\n\nIn the `Dockerfile`, you need to define the instructions for building a Docker image that encapsulates the server code and its dependencies.\n\nIn most cases, you could use the template in the repository.\n\n```bash\ndocker build -t docker.io/USER/IMAGE .\ndocker push docker.io/USER/IMAGE\n\n# GPU\ndocker build -t docker.io/USER/IMAGE -f Dockerfile.gpu .\ndocker push docker.io/USER/IMAGE\n```\n\nOn the other hand, a [`build.envd`](https://envd.tensorchord.ai/guide/getting-started.html) is a simplified alternative to a Dockerfile. It provides python-based interfaces that contains configuration settings for building a image. \n\nIt is easier to use than a Dockerfile as it involves specifying only the dependencies of your machine learning model, not the instructions for CUDA, conda, and other system-level dependencies.\n\n```bash\nenvd build --output type=image,name=docker.io/USER/IMAGE,push=true\n# GPU\nenvd build --output type=image,name=docker.io/USER/IMAGE,push=true -f :build_gpu\n```\n\n## Deploy\n\nPlease refer to the [Modelz documentation](https://docs.modelz.ai/gettingstarted/deploy) for more details.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorchord%2Fmodelz-template-streamlit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftensorchord%2Fmodelz-template-streamlit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftensorchord%2Fmodelz-template-streamlit/lists"}