{"id":23268419,"url":"https://github.com/anasaber/mlflow_with_rag","last_synced_at":"2026-02-06T07:38:13.866Z","repository":{"id":267272541,"uuid":"900732508","full_name":"AnasAber/MLflow_with_RAG","owner":"AnasAber","description":"Using MLflow to deploy your RAG pipeline, using LLamaIndex, Langchain and Ollama/HuggingfaceLLMs/Groq","archived":false,"fork":false,"pushed_at":"2025-01-20T20:27:30.000Z","size":63611,"stargazers_count":1,"open_issues_count":1,"forks_count":1,"subscribers_count":1,"default_branch":"master","last_synced_at":"2025-02-12T14:17:34.971Z","etag":null,"topics":["cicd","deployment","evaluation-metrics","llamaindex","llamaindex-rag","mlflow","mlflow-deployement","mlflow-projects","mlflow-tracking","mlflow-tracking-server","mlflow-ui","mlops","mlops-project","mlops-template","rag","rag-evaluation","rag-pipeline"],"latest_commit_sha":null,"homepage":"","language":"Python","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/AnasAber.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":"2024-12-09T11:21:46.000Z","updated_at":"2025-01-16T19:11:39.000Z","dependencies_parsed_at":"2025-01-10T01:33:13.513Z","dependency_job_id":"e88639b9-c672-4a2d-ac2f-c8ab00d410cf","html_url":"https://github.com/AnasAber/MLflow_with_RAG","commit_stats":{"total_commits":8,"total_committers":1,"mean_commits":8.0,"dds":0.0,"last_synced_commit":"c569bb934facffddba285392bc6dc73c36b411c3"},"previous_names":["anasaber/mlflow_with_rag"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnasAber%2FMLflow_with_RAG","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnasAber%2FMLflow_with_RAG/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnasAber%2FMLflow_with_RAG/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AnasAber%2FMLflow_with_RAG/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AnasAber","download_url":"https://codeload.github.com/AnasAber/MLflow_with_RAG/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247457727,"owners_count":20941905,"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":["cicd","deployment","evaluation-metrics","llamaindex","llamaindex-rag","mlflow","mlflow-deployement","mlflow-projects","mlflow-tracking","mlflow-tracking-server","mlflow-ui","mlops","mlops-project","mlops-template","rag","rag-evaluation","rag-pipeline"],"created_at":"2024-12-19T17:18:33.142Z","updated_at":"2026-02-06T07:38:13.821Z","avatar_url":"https://github.com/AnasAber.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"### MLflow Deployement of a RAG pipeline 🥀\n\nThis project is for people that want to deploy a RAG pipeline using MLflow.\n\nThe project uses:\n- `LlamaIndex` and `langchain` as orchestrators\n- `Ollama` and `HuggingfaceLLMs`\n- `MLflow` as an MLOps framework for deploying and tracking\n\n![Project Overview Diagram](images/mlflow_rag_schema.png)\n### How to start\n\n1. Clone the repository\n```bash\ngit clone https://github.com/AnasAber/RAG_in_CPU.git\n```\n\n2. Install the dependencies\n```bash\npip install -r requirements.txt\n```\nMake sure to put your api_keys into the `example.env`, and rename it to `.env`\n\n\n3. Notebook Prep:\n- Put your own data files in the data/ folder\n- Go to the notebook, and replace \"api_key_here\" with your huggingface_api_key\n- If you have GPU, you're fine, if not, run it on google colab, and make sure to download the json file output at the end of the run.\n\n4. Go to `deployement` folder, and open two terminals:\n```bash\npython workflow.py\n```\nAnd after the run, go to your mlflow run, and pick the run ID:\n![Run ID](images/run_id.png)\nPlace it into this command:\n```bash\nmlflow models serve -m runs:/\u003crun id\u003e/rag_deployement -p 5001\n```\nIn the other terminal, make sure to run\n```bash\napp.py\n```\n5. Open another terminal, and move to the `frontend` folder, and run:\n```bash\nnpm start\n```\n\nNow, you should be seeing a web interface, and the two terminals are running.\n![Interface](images/interface.png)\n\nIf you got errors, try to see what's missing in the requirements.txt.\n\nEnjoy!","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanasaber%2Fmlflow_with_rag","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fanasaber%2Fmlflow_with_rag","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fanasaber%2Fmlflow_with_rag/lists"}