flowfoundry 1.0.1

FlowFoundry: a strategy-first, cloud-agnostic agentic workflow framework (LangGraph/LangChain)

FlowFoundry

A strategy-first, cloud-agnostic framework for LLM workflows.
Compose chunking, indexing, retrieval, reranking, and agentic flows — with Keras-like ergonomics over LangChain / LangGraph.

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✨ Features

• Strategies: chunking, indexing, retrieval, reranking
• Functional API: call strategies directly as Python functions
• Blocks API: compose strategies like layers
• Nodes & Graphs: LangGraph-backed workflows (YAML or Python)
• Extensible: register custom strategies or nodes

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Installation

Core only:

pip install flowfoundry

With extras:

pip install "flowfoundry[rag,search,rerank,qdrant,openai,llm-openai]"

Extras include: chromadb, qdrant-client, sentence-transformers, rank-bm25, openai, etc. All examples run offline by default (echo LLM). Missing deps no-op gracefully.

Sanity check:

from flowfoundry import ping, hello
print(ping())          # -> "flowfoundry: ok"
print(hello("there"))  # -> "hello, there!"

Quickstart (Functional API)

from flowfoundry.functional import (
  chunk_recursive, index_chroma_upsert, index_chroma_query, preselect_bm25
)

text   = "FlowFoundry lets you mix strategies to build RAG."
chunks = chunk_recursive(text, size=120, overlap=20, doc_id="demo")

# Index & query (requires chromadb extra)
index_chroma_upsert(chunks, path=".ff_chroma", collection="docs")
hits = index_chroma_query("What is FlowFoundry?", path=".ff_chroma", collection="docs", k=8)

# Optional rerank (requires rank-bm25)
hits = preselect_bm25("What is FlowFoundry?", hits, top_k=5)

print(hits[0]["text"])

CLI + YAML

start: retrieve
nodes:
  - id: retrieve
    type: strategy.retrieve
    params: { name: chroma_query, path: .ff_chroma, collection: docs, k: 8 }
  - id: rerank
    type: strategy.rerank
    params: { name: bm25_preselect, top_k: 8 }
  - id: prompt
    type: prompt.rag
  - id: answer
    type: llm.chat
    params: { provider: echo, model: gpt-4o-mini }
edges:
  - { source: retrieve, target: rerank }
  - { source: rerank,   target: prompt }
  - { source: prompt,   target: answer }

Run:

flowfoundry run rag_local.yaml --state '{"query":"Hello!"}'

Functional API Reference

Available in flowfoundry.functional:

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Chunking

Function	Purpose	Extra deps
chunk_fixed	Fixed-size splitter	–
chunk_recursive	Recursive splitter	langchain-text-splitters
chunk_hybrid	Hybrid splitter	–

chunk_fixed(text, *, size=800, overlap=80, doc_id="doc") -> list[Chunk]
chunk_recursive(text, *, size=800, overlap=80, doc_id="doc") -> list[Chunk]
chunk_hybrid(text, **kwargs) -> list[Chunk]

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Indexing (Chroma)

Function	Purpose	Extra deps
index_chroma_upsert	Upsert chunks into Chroma	chromadb
index_chroma_query	Query Chroma	chromadb

index_chroma_upsert(chunks, *, path=".ff_chroma", collection="docs") -> str
index_chroma_query(query, *, k=5, path, collection) -> list[Hit]

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Indexing (Qdrant)

Function	Purpose	Extra deps
index_qdrant_upsert	Upsert chunks into Qdrant	qdrant-client
index_qdrant_query	Query Qdrant	qdrant-client

index_qdrant_upsert(chunks, *, url, collection, dim=None) -> str
index_qdrant_query(query, *, url, collection, k=5, vector=None) -> list[Hit]

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Reranking

Function	Purpose	Extra deps
rerank_identity	No-op reranker	–
preselect_bm25	BM25 preselect	rank-bm25
rerank_cross_encoder	Cross-encoder reranker	sentence-transformers

rerank_identity(query, hits) -> list[Hit]
preselect_bm25(query, hits, top_k=20) -> list[Hit]
rerank_cross_encoder(query, hits, *, model, top_k=None) -> list[Hit]