Robert Helewka
2df22941d2
- Remove Phase 4 RAG pipeline in favor of retrieval-only architecture - Add FastMCP server exposing search, get_chunk, list_libraries tools - Mount MCP endpoints (streamable HTTP + SSE) via Starlette in ASGI config - Update README to clarify Mnemosyne is a retrieval engine, not RAG - Let calling LLMs drive synthesis and iterative retrieval themselves
50 lines
1.2 KiB
TOML
50 lines
1.2 KiB
TOML
[project]
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name = "mnemosyne"
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version = "0.1.0"
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description = "Content-type-aware, multimodal personal knowledge management system"
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readme = "README.md"
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license = {text = "MIT"}
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requires-python = ">=3.12"
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dependencies = [
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"Django>=5.2,<6.0",
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"djangorestframework>=3.14,<4.0",
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"django-neomodel>=0.1,<1.0",
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"neomodel>=5.3,<6.0",
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"neo4j>=5.0,<6.0",
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"celery>=5.3,<6.0",
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"django-storages[boto3]>=1.14,<2.0",
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"django-environ>=0.11,<1.0",
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"psycopg[binary]>=3.1,<4.0",
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"dj-database-url>=2.1,<3.0",
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"shortuuid>=1.0,<2.0",
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"gunicorn>=21.0,<24.0",
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"cryptography>=41.0,<45.0",
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"flower>=2.0,<3.0",
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"pymemcache>=4.0,<5.0",
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"openai>=1.0,<2.0",
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"django-prometheus>=2.3,<3.0",
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# Phase 2: Embedding Pipeline
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"PyMuPDF>=1.24,<2.0",
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"pymupdf4llm>=0.0.17,<1.0",
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"semantic-text-splitter>=0.20,<1.0",
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"tokenizers>=0.20,<1.0",
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"Pillow>=10.0,<12.0",
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"requests>=2.31,<3.0",
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# Phase 5: MCP Server
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"fastmcp>=2.0,<3.0",
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"uvicorn[standard]>=0.30,<1.0",
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]
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[project.optional-dependencies]
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dev = [
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"django-debug-toolbar>=4.0,<5.0",
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"docker>=7.0,<8.0",
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]
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[build-system]
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requires = ["setuptools>=68.0"]
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build-backend = "setuptools.build_meta"
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[tool.setuptools.packages.find]
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where = ["mnemosyne"]
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