bae359e3bf
The execute_code description gains the toc.json node shape, the patterns the evals put into the analysis instructions (one list_documents call to map a title to an id, files carry no source, toc before search for a known document, doc_item_refs are items self_refs, chunk ids join files and are not citations) and the sandbox's read-only, no-network, time-limit and output facts, which the analysis instructions now state too. The skill gains pictures as images, image search when offered, and citing chunk metadata locators. docs/mcp.md lists the interpreter's limits under Code. pydantic-monty>=0.0.23 brings collections, itertools, functools, dataclasses, function decorators and str.format into the sandbox; every layer names the same modules, and a test imports them. Monty now caps host callbacks per checkout at 1000 by default; the sandbox raises it out of reach, since the time budgets govern.
110 lines
3.1 KiB
TOML
110 lines
3.1 KiB
TOML
[project]
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name = "haiku.rag-slim"
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description = "Local-first agentic RAG with citations - hybrid search, reranking and multimodal retrieval over your own documents, no database server required - Minimal dependencies"
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version = "0.82.1"
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authors = [{ name = "Yiorgis Gozadinos", email = "ggozadinos@gmail.com" }]
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license = { text = "MIT" }
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readme = { file = "README.md", content-type = "text/markdown" }
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requires-python = ">=3.12"
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keywords = [
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"RAG",
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"agentic-rag",
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"lancedb",
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"vector-database",
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"hybrid-search",
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"reranking",
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"multimodal-rag",
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"embeddings",
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"citations",
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"document-ingestion",
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"mcp",
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"mcp-server",
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"pydantic-ai",
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"docling",
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]
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classifiers = [
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"Development Status :: 4 - Beta",
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"Environment :: Console",
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"Intended Audience :: Developers",
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"Operating System :: Microsoft :: Windows :: Windows 10",
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"Operating System :: Microsoft :: Windows :: Windows 11",
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"Operating System :: MacOS",
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"Operating System :: POSIX :: Linux",
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"Programming Language :: Python :: 3.12",
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"Programming Language :: Python :: 3.13",
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"Typing :: Typed",
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]
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dependencies = [
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"docling-core>=2.82.0,<3.0.0",
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"httpx>=0.28.1",
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"jinja2>=3.1.0",
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"fastmcp>=4.0.2,<5.0.0",
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"lancedb==0.37.1",
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"pathspec>=1.0.4",
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"pydantic>=2.12.5",
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"pydantic-ai-slim[openai,logfire,ag-ui]>=2.18.0,<3.0.0",
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"pydantic-monty>=0.0.23",
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"pypdfium2>=5.0",
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"python-dotenv>=1.2.2",
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"pyyaml>=6.0.3",
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"rich>=14.3.3",
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"textual-image>=0.8.5",
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"typer>=0.21.0,<0.22.0",
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"watchfiles>=1.1.1",
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"zstandard>=0.23.0; python_version<'3.14'",
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]
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[project.urls]
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Homepage = "https://ggozad.github.io/haiku.rag/"
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Documentation = "https://ggozad.github.io/haiku.rag/"
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Repository = "https://github.com/ggozad/haiku.rag"
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Issues = "https://github.com/ggozad/haiku.rag/issues"
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Changelog = "https://ggozad.github.io/haiku.rag/changelog/"
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[project.optional-dependencies]
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# Document processing
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docling = ["docling>=2.102.2,<3.0.0", "opencv-python-headless>=4.6.0.66,<5.0.0.0"]
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# S3 / object-storage monitoring
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s3 = ["obstore>=0.9,<0.10"]
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# Embedding providers
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voyageai = ["pydantic-ai-slim[voyageai]"]
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# Rerankers
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cohere = ["cohere>=5.21.1"]
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zeroentropy = ["zeroentropy>=0.1.0a11"]
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jina = ["transformers>=4.40.0", "torch>=2.0.0"]
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cross-encoder = ["sentence-transformers>=3.0.0"]
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# Production ingester (queue, workers, API)
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ingester = [
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"fastapi>=0.125",
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"uvicorn[standard]>=0.32",
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"sqlalchemy[asyncio]>=2.0",
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"aiosqlite>=0.20",
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"asyncpg>=0.29",
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"haiku.rag-slim[s3]",
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]
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# TUI (chat and inspect commands)
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tui = [
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"textual>=8.2.4",
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"tree-sitter>=0.25.2",
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"tree-sitter-json>=0.24.8",
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]
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# Model providers (delegated to pydantic-ai-slim)
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anthropic = ["pydantic-ai-slim[anthropic]"]
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groq = ["pydantic-ai-slim[groq]"]
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google = ["pydantic-ai-slim[google]"]
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mistral = ["pydantic-ai-slim[mistral]"]
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bedrock = ["pydantic-ai-slim[bedrock]"]
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vertexai = ["pydantic-ai-slim[google]"]
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[project.scripts]
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haiku-rag = "haiku.rag.cli:cli"
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haiku-ingester = "haiku.rag.ingester.cli:cli"
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[build-system]
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requires = ["hatchling"]
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build-backend = "hatchling.build"
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[tool.hatch.build.targets.wheel]
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packages = ["haiku"]
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