Overview

from ragrails import RagRails

rag = RagRails(
    collection="support",
    vector_store={"provider": "qdrant", "url": "http://localhost:6333"},
    embedding={"provider": "voyage", "model": "voyage-3"},
    llm={"provider": "openai", "model": "gpt-4o-mini"},
)

rag.ingest(docs="files/refund-policy.pdf")

matches = rag.query("How long do I have to request a refund?", retrieval={"top_k": 5})
answer = rag.chat("How long do I have to request a refund?", history=[])

print(matches.items[0].text)
print(answer.answer)

ragrails ingest \
  --docs files/refund-policy.pdf \
  --vector-db qdrant \
  --collection support \
  --url http://localhost:6333 \
  --provider voyage \
  --model voyage-3

ragrails query "How long do I have to request a refund?" \
  --vector-db qdrant \
  --collection support \
  --url http://localhost:6333 \
  --top-k 5 \
  --provider voyage \
  --model voyage-3

ragrails chat "How long do I have to request a refund?" \
  --vector-db qdrant \
  --collection support \
  --url http://localhost:6333 \
  --embedder-provider voyage \
  --embedder-model voyage-3 \
  --llm-provider openai \
  --llm-model gpt-4o-mini

curl -X POST http://127.0.0.1:8000/v1/pipelines/ingest \
  -H "Content-Type: application/json" \
  -d '{
    "docs": "files/refund-policy.pdf",
    "embedding": {"provider": "voyage", "model": "voyage-3"},
    "storage": {"vector_db": "qdrant", "collection": "support", "url": "http://localhost:6333"}
  }'

curl -X POST http://127.0.0.1:8000/v1/pipelines/query \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How long do I have to request a refund?",
    "embedding": {"provider": "voyage", "model": "voyage-3"},
    "retrieval": {"vector_db": "qdrant", "collection": "support", "url": "http://localhost:6333", "top_k": 5}
  }'

curl -X POST http://127.0.0.1:8000/v1/chat \
  -H "Content-Type: application/json" \
  -d '{
    "query": "How long do I have to request a refund?",
    "llm_provider": "openai",
    "llm_model": "gpt-4o-mini",
    "embedder_provider": "voyage",
    "embedder_model": "voyage-3",
    "vector_db": "qdrant",
    "collection": "support",
    "url": "http://localhost:6333",
    "history": []
  }'