crewai-infino 0.1.0rc1

CrewAI integration for Infino — vector, BM25, hybrid, and SQL retrieval as agent tools over one engine on object storage.

crewai-infino

CrewAI integration for Infino — give your agents semantic (vector), full-text (BM25), hybrid, and SQL retrieval as tools over one store on object storage. No second vector DB, no separate metadata store, no client-side fusion: one Infino table answers all four ways, and the agent picks the right one at runtime.

pip install crewai-infino

Agent in minutes

Build and populate a table with InfinoIndex, then hand its tools to an agent:

import infino
from crewai import Agent, Task, Crew
from crewai_infino import InfinoIndex

# Your embedding model — any callables that turn text into vectors.
# (e.g. sentence-transformers; dim must match.)
from my_embeddings import embed_documents, embed_query  # -> list[list[float]] / list[float]

conn = infino.connect("./infino-data")
index = InfinoIndex.create(
    conn, "kb",
    embed_documents=embed_documents, embed_query=embed_query, dim=384,
)
index.add_texts(
    ["Reset the X200 by holding power for 10s.", "Error E-507 means a stale cache."],
    metadatas=[{"product": "X200"}, {"product": "X200"}],
)

analyst = Agent(
    role="Support Analyst",
    goal="Answer customer questions from the knowledge base",
    backstory="You retrieve before you answer.",
    tools=index.as_tools(),          # semantic + keyword + hybrid + SQL, over one store
)

crew = Crew(agents=[analyst], tasks=[
    Task(description="How do I fix error E-507 on the X200?",
         expected_output="A concise fix.", agent=analyst),
])
print(crew.kickoff())

The tools

index.as_tools() (or infino_tools(searcher)) returns four crewai.tools.BaseTools:

Tool	Backed by	Use for
InfinoSemanticSearchTool	vector kNN	intent / how-to / paraphrased questions
InfinoKeywordSearchTool	BM25 (mode="and" default)	exact codes, SKUs, names, error strings
InfinoHybridSearchTool	BM25 + vector fused by RRF, one SQL call	strong default — exact and semantic
InfinoSQLTool	query_sql	point lookups, GROUP BY aggregates, joins

Attach individual tools to different agents, or the whole set to one. The package bundles no embedding model — you pass embed callables, so you keep full control of the model (and the examples stay key-free with a local one).

Lower-level API

• InfinoIndex — create / open a table, add_texts, delete, as_tools().
• InfinoSearcher — the read path: .semantic(), .keyword(), .hybrid(), .sql() returning plain row dicts. The tools are thin wrappers over it.

The table schema matches langchain-infino, so a table built by one adapter is queryable by the other.

Status

Tools are the stable, shipping surface. CrewAI Knowledge (auto-grounding) and Memory (durable agent memory) backends are planned next; they target CrewAI's KnowledgeStorage / RAGStorage seams, which are still stabilizing upstream, so they will land version-pinned.

Development

make install     # editable install with test + lint extras
make unit        # engine-free unit tests
make integration # full suite against the engine
make lint type   # ruff + mypy

Apache-2.0.