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A complete Agentic RAG infrastructure using ZenML pipelines including ETL, Dataset generation, Embedding, Inference and Evaluation

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Usage:

Add .env files:

/offline

NOTION_SECRET_KEY= OPENAI_MODEL_ID= OPENAI_API_KEY= HUGGINGFACE_ACCESS_TOKEN= HUGGINGFACE_DEDICATED_ENDPOINT=

/online

OPENAI_MODEL_ID= OPENAI_API_KEY= HUGGINGFACE_ACCESS_TOKEN= HUGGINGFACE_DEDICATED_ENDPOINT= COMET_API_KEY=

MongoDB

make local-docker-infrastructure-up

Set pipeline configs

./offline/configs/*.yaml

Collect raw data

make collect-notion-data-pipeline make collect-apple-notes-data-pipeline

Extract, Transform, Load pipeline

make etl-notion-pipeline make etl-apple-notes-pipeline

Generate custom dataset

make generate-dataset-pipeline

RAG Ingestion - Chunk, embed, load

make compute-rag-vector-index-openai-parent-pipeline

Run agentic rag - query CLI

make run_agent_query

Run agentic rag - GradioUI Chat

make run_agent_app

Evaluate RAG system

make evaluate_agent

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A complete Agentic RAG infrastructure using ZenML pipelines including ETL, Dataset generation, Embedding, Inference and Evaluation

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