From e7ac7766a51fb2e632c14b05835e7091ccb69903 Mon Sep 17 00:00:00 2001 From: Tarik Moussa Date: Thu, 4 Jun 2026 11:19:10 +0200 Subject: [PATCH] feat: initial project scaffold pyproject.toml (Python 3.12, uv), codex/ package (config, db, models), infra/ (docker-compose + schema), .env.example, .gitignore, README. Co-Authored-By: Claude Sonnet 4.6 --- .env.example | 25 + .gitignore | 35 + README.md | 113 +++ codex/__init__.py | 0 codex/config.py | 85 ++ codex/db.py | 57 ++ codex/models.py | 80 ++ codex/parsing/__init__.py | 0 codex/sources/__init__.py | 0 infra/docker-compose.yml | 47 ++ infra/schema.sql | 90 +++ pyproject.toml | 46 ++ uv.lock | 1558 +++++++++++++++++++++++++++++++++++++ 13 files changed, 2136 insertions(+) create mode 100644 .env.example create mode 100644 .gitignore create mode 100644 README.md create mode 100644 codex/__init__.py create mode 100644 codex/config.py create mode 100644 codex/db.py create mode 100644 codex/models.py create mode 100644 codex/parsing/__init__.py create mode 100644 codex/sources/__init__.py create mode 100644 infra/docker-compose.yml create mode 100644 infra/schema.sql create mode 100644 pyproject.toml create mode 100644 uv.lock diff --git a/.env.example b/.env.example new file mode 100644 index 0000000..733a1ad --- /dev/null +++ b/.env.example @@ -0,0 +1,25 @@ +# Copy this file to .env and fill in your values. +# Never commit .env to version control. + +# PostgreSQL connection string (psycopg / asyncpg format) +# Example: postgresql://researcher:change_me@localhost:5432/papers +DATABASE_URL=postgresql://researcher:change_me@localhost:5432/papers + +# GROBID service base URL (containerised — see infra/docker-compose.yml) +GROBID_URL=http://localhost:8070 + +# Ollama base URL for optional local LLM Q&A layer +OLLAMA_BASE_URL=http://localhost:11434 + +# Sentence-transformers model for dense embeddings. +# BGE-M3 (BAAI/bge-m3) produces 1024-dimensional vectors and supports +# dense + sparse (hybrid) retrieval. Change together with EMBEDDING_DIM. +EMBEDDING_MODEL=BAAI/bge-m3 + +# Dimension of the embedding vectors. Must match EMBEDDING_MODEL output. +# BGE-M3 = 1024 | Jina v4 = 2048 | Qwen3-Embedding-0.6B = 1024 +EMBEDDING_DIM=1024 + +# E-mail address for the OpenAlex Polite Pool (faster rate limits). +# Required by OpenAlex ToS when making automated requests. +OPENALEX_MAILTO=you@example.com diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..cda1e51 --- /dev/null +++ b/.gitignore @@ -0,0 +1,35 @@ +# Python +__pycache__/ +*.py[cod] +*.pyo +*.pyd +*.so + +# Virtual environments +.venv/ +venv/ +env/ + +# Distribution / packaging +dist/ +build/ +*.egg-info/ +*.egg + +# Environment secrets — NEVER commit +.env + +# Type-checker and linter caches +.mypy_cache/ +.ruff_cache/ + +# Test caches +.pytest_cache/ +.coverage +htmlcov/ + +# Editor / OS artefacts +.DS_Store +.idea/ +.vscode/ +*.swp diff --git a/README.md b/README.md new file mode 100644 index 0000000..f3a3282 --- /dev/null +++ b/README.md @@ -0,0 +1,113 @@ +# codex — Personal Paper Knowledge Base + +A self-hostable tool for managing scientific papers: ingest PDFs and arXiv +sources, build a citation graph, and link C++ implementations back to the +papers that describe them. + +--- + +## Quick start + +```bash +# 1. Start Postgres (pgvector) + GROBID +docker compose -f infra/docker-compose.yml up -d + +# 2. Copy and edit environment variables +cp .env.example .env +$EDITOR .env + +# 3. Install Python dependencies (requires uv) +uv sync + +# 4. Apply the database schema (first run only) +uv run python -c " +from codex.db import get_conn, apply_schema +with get_conn() as conn: + apply_schema(conn) +print('Schema applied.') +" +``` + +--- + +## Environment variables + +| Variable | Default | Description | +|---|---|---| +| `DATABASE_URL` | `postgresql://researcher:change_me@localhost:5432/papers` | libpq connection string | +| `GROBID_URL` | `http://localhost:8070` | GROBID HTTP API base URL | +| `OLLAMA_BASE_URL` | `http://localhost:11434` | Local Ollama endpoint (optional) | +| `EMBEDDING_MODEL` | `BAAI/bge-m3` | sentence-transformers model name | +| `EMBEDDING_DIM` | `1024` | Embedding vector dimension (must match model) | +| `OPENALEX_MAILTO` | *(empty)* | E-mail for OpenAlex Polite Pool (required for automated use) | + +See `.env.example` for a documented template. + +--- + +## Three-layer data model + +All data lives in a single Postgres instance with the pgvector extension. + +### Layer 1 — Semantics (`papers`, `chunks`) + +Papers are stored with metadata and an abstract-level dense embedding +(BGE-M3, 1024 dimensions). Full-text is split into `chunks`, each with its +own dense embedding and a Postgres full-text (GIN) index. +Hybrid search combines nearest-neighbour vector search with keyword (FTS) +retrieval for robust handling of exact mathematical terminology. + +### Layer 2 — Citations (`citations`) + +Directed edges in the citation graph. The `cited_id` column has **no +foreign-key constraint** on purpose: edges pointing to papers that have not +yet been ingested are kept as-is. Those "dangling" targets are your +**discovery leads** — papers frequently cited by your collection that you +have not yet read. + +```sql +-- Top discovery leads +SELECT cited_id, count(*) AS pull +FROM citations +WHERE cited_id NOT IN (SELECT id FROM papers) +GROUP BY cited_id +ORDER BY pull DESC +LIMIT 20; +``` + +### Layer 3 — Provenance (`code_links`) + +Maps C++ symbols (qualified names or `file.cpp:line` references) to the +papers they implement. The workflow: + +1. Tag C++ source with `@cite ` in Doxygen comments. +2. Run `codex provenance sync --lib-path ` to scan and resolve tags. +3. Run `codex provenance export-bib ` to generate a `.bib` file + containing **only the cited subset** of your collection. + +The exported `.bib` is a derived view of the master catalogue — regenerate +it at any time; it is not the source of truth. + +--- + +## CLI reference (coming in F-07) + +``` +codex ingest # ingest one paper by arXiv ID or DOI +codex ingest-file # bulk ingest from a file of IDs +codex search "" [--hybrid] +codex discover leads +codex provenance sync --lib-path +codex provenance export-bib +codex ask "" # optional LLM Q&A via Ollama +``` + +--- + +## Development + +```bash +uv run ruff check . && uv run ruff format --check . # lint +uv run mypy codex/ # type-check +uv run pytest # tests +``` diff --git a/codex/__init__.py b/codex/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/codex/config.py b/codex/config.py new file mode 100644 index 0000000..2e02ccc --- /dev/null +++ b/codex/config.py @@ -0,0 +1,85 @@ +"""Application configuration via environment variables / .env file. + +All settings are read from the environment (or a .env file in the project +root). Import :func:`get_settings` wherever you need configuration; the +returned object is cached after the first call. +""" + +from __future__ import annotations + +from functools import lru_cache + +from pydantic import Field +from pydantic_settings import BaseSettings, SettingsConfigDict + + +class Settings(BaseSettings): + """Centralised, env-driven configuration for the codex application.""" + + model_config = SettingsConfigDict( + env_file=".env", + env_file_encoding="utf-8", + case_sensitive=False, + extra="ignore", + ) + + # ------------------------------------------------------------------ + # Database + # ------------------------------------------------------------------ + database_url: str = Field( + default="postgresql://researcher:change_me@localhost:5432/papers", + description=( + "libpq-compatible connection string consumed by psycopg. " + "Example: postgresql://user:pass@host:5432/dbname" + ), + ) + + # ------------------------------------------------------------------ + # External services + # ------------------------------------------------------------------ + grobid_url: str = Field( + default="http://localhost:8070", + description="Base URL of the GROBID HTTP API (containerised).", + ) + + ollama_base_url: str = Field( + default="http://localhost:11434", + description="Base URL of the local Ollama endpoint (optional Q&A layer).", + ) + + # ------------------------------------------------------------------ + # Embeddings + # ------------------------------------------------------------------ + embedding_model: str = Field( + default="BAAI/bge-m3", + description=( + "sentence-transformers model identifier. " + "Must match EMBEDDING_DIM. Default: BAAI/bge-m3 (1024 dims)." + ), + ) + + embedding_dim: int = Field( + default=1024, + gt=0, + description=( + "Dimension of the dense embedding vectors. " + "Must match the output dimension of EMBEDDING_MODEL." + ), + ) + + # ------------------------------------------------------------------ + # API etiquette + # ------------------------------------------------------------------ + openalex_mailto: str = Field( + default="", + description=( + "E-mail address for the OpenAlex Polite Pool (faster rate limits). " + "Required by OpenAlex ToS for automated access." + ), + ) + + +@lru_cache(maxsize=1) +def get_settings() -> Settings: + """Return the cached application settings singleton.""" + return Settings() diff --git a/codex/db.py b/codex/db.py new file mode 100644 index 0000000..e86678f --- /dev/null +++ b/codex/db.py @@ -0,0 +1,57 @@ +"""Database connection helpers. + +Provides: +- :func:`get_conn` — a context manager that yields a psycopg connection. +- :func:`apply_schema` — idempotently applies ``infra/schema.sql``. + +The connection pool (psycopg_pool) is intentionally deferred to F-05 +(ingest); here we expose a simple per-call ``psycopg.connect`` wrapper +that is sufficient for schema migration and unit-testing without requiring +an additional ``psycopg[pool]`` dependency at scaffold stage. +""" + +from __future__ import annotations + +from collections.abc import Generator +from contextlib import contextmanager +from pathlib import Path + +import psycopg +import psycopg.rows + +from codex.config import get_settings + + +@contextmanager +def get_conn() -> Generator[psycopg.Connection[psycopg.rows.DictRow], None, None]: + """Yield a psycopg connection with dict-row factory. + + The connection is opened from :func:`codex.config.get_settings` + ``database_url`` and closed automatically when the context exits. + + Usage:: + + with get_conn() as conn: + conn.execute("SELECT 1") + """ + settings = get_settings() + with psycopg.connect( + settings.database_url, + row_factory=psycopg.rows.dict_row, + ) as conn: + yield conn + + +def apply_schema(conn: psycopg.Connection[psycopg.rows.DictRow]) -> None: + """Idempotently apply ``infra/schema.sql`` to the connected database. + + Safe to call on every startup — all DDL statements use + ``CREATE … IF NOT EXISTS``. + + Args: + conn: An open psycopg connection (obtained via :func:`get_conn`). + """ + schema_path = Path(__file__).parent.parent / "infra" / "schema.sql" + sql = schema_path.read_text(encoding="utf-8") + conn.execute(sql) + conn.commit() diff --git a/codex/models.py b/codex/models.py new file mode 100644 index 0000000..881e9b4 --- /dev/null +++ b/codex/models.py @@ -0,0 +1,80 @@ +"""Domain dataclasses. + +Each class maps directly to a table in ``infra/schema.sql``. +Field names and types are kept in sync with the DDL. + +All fields that are nullable in the schema are typed as ``… | None`` +with a default of ``None`` so instances can be constructed incrementally. +""" + +from __future__ import annotations + +from dataclasses import dataclass, field +from datetime import datetime + + +@dataclass +class Paper: + """Maps to the ``papers`` table (Layer 1 — semantic search). + + ``id`` is the canonical identifier: an arXiv ID (e.g. ``2301.00001``) + or a DOI (e.g. ``10.1145/3592430``). + """ + + id: str + title: str + openalex_id: str | None = None + bibkey: str | None = None + authors: list[str] = field(default_factory=list) + year: int | None = None + abstract: str | None = None + source_path: str | None = None + # abstract_emb is a list of floats representing the pgvector column; + # pgvector's Python driver accepts list[float] for vector columns. + abstract_emb: list[float] | None = None + added_at: datetime | None = None + + +@dataclass +class Chunk: + """Maps to the ``chunks`` table (Layer 1 — full-text chunks). + + ``id`` is set by the database (BIGSERIAL); leave it as ``None`` + when constructing a new chunk before insertion. + """ + + paper_id: str + ord: int + content: str + id: int | None = None + embedding: list[float] | None = None + + +@dataclass +class Citation: + """Maps to the ``citations`` table (Layer 2 — citation graph). + + ``cited_id`` intentionally has no foreign-key constraint in the schema; + citations to not-yet-ingested papers are preserved as discovery leads. + """ + + citing_id: str + cited_id: str + context: str | None = None + + +@dataclass +class CodeLink: + """Maps to the ``code_links`` table (Layer 3 — provenance). + + ``symbol`` is a C++ qualified name or ``file.cpp:line`` reference. + ``role`` is a free-text description such as 'implements Thm 3.2'. + ``id`` is set by the database (BIGSERIAL). + """ + + symbol: str + paper_id: str | None = None + role: str | None = None + note: str | None = None + id: int | None = None + added_at: datetime | None = None diff --git a/codex/parsing/__init__.py b/codex/parsing/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/codex/sources/__init__.py b/codex/sources/__init__.py new file mode 100644 index 0000000..e69de29 diff --git a/infra/docker-compose.yml b/infra/docker-compose.yml new file mode 100644 index 0000000..f7c8912 --- /dev/null +++ b/infra/docker-compose.yml @@ -0,0 +1,47 @@ +# Paper knowledge base: Provenance + Citation graph + Semantic search +# A single Postgres instance (pgvector) covers all three layers. +# GROBID parses references / structure from PDFs without an arXiv source. +# +# Quick start: +# docker compose up -d +# psql "${DATABASE_URL}" # see .env.example for default value + +services: + db: + image: pgvector/pgvector:pg17 # official pgvector image + container_name: papers-db + environment: + POSTGRES_DB: papers + POSTGRES_USER: researcher + POSTGRES_PASSWORD: change_me # change before production use + ports: + - "5432:5432" + volumes: + - pgdata:/var/lib/postgresql/data + # schema.sql is executed automatically on first start: + - ./schema.sql:/docker-entrypoint-initdb.d/01-schema.sql:ro + healthcheck: + test: ["CMD-SHELL", "pg_isready -U researcher -d papers"] + interval: 10s + timeout: 5s + retries: 5 + restart: unless-stopped + + grobid: + # CRF-only image is sufficient for reference extraction and is lighter than + # the full deeplearning variant. Check https://hub.docker.com/r/grobid/grobid + # for the latest 0.8.x tag before deploying. + image: grobid/grobid:0.8.2 + container_name: papers-grobid + ports: + - "8070:8070" + restart: unless-stopped + # GROBID is RAM-hungry; uncomment to cap usage on constrained hardware + # (e.g. Nvidia Jetson): + # deploy: + # resources: + # limits: + # memory: 4g + +volumes: + pgdata: diff --git a/infra/schema.sql b/infra/schema.sql new file mode 100644 index 0000000..fb7cc8d --- /dev/null +++ b/infra/schema.sql @@ -0,0 +1,90 @@ +-- ===================================================================== +-- Schema: Paper knowledge base +-- Layer 1 papers, chunks -> semantic search (pgvector) +-- Layer 2 citations -> citation graph / discovery +-- Layer 3 code_links -> provenance (C++ symbol <-> paper) +-- +-- Adjust EMBEDDING_DIM to match your model (see .env.example): +-- BGE-M3 = 1024 | Qwen3-Embedding-0.6B = 1024 | Jina v4 = 2048 +-- ===================================================================== + +CREATE EXTENSION IF NOT EXISTS vector; + +-- --------------------------------------------------------------------- +-- Layer 1: Papers + full-text chunks +-- --------------------------------------------------------------------- +CREATE TABLE papers ( + id TEXT PRIMARY KEY, -- canonical ID: arXiv ID or DOI + openalex_id TEXT UNIQUE, -- e.g. W2741809807 + bibkey TEXT UNIQUE, -- BibTeX key -> .bib + Doxygen @cite + title TEXT NOT NULL, + authors TEXT[], + year INT, + abstract TEXT, + source_path TEXT, -- path to parsed .tex / .mmd file + abstract_emb vector(1024), -- paper-level embedding (similarity) + added_at TIMESTAMPTZ DEFAULT now() +); + +-- HNSW index for fast approximate nearest-neighbour search on abstracts. +CREATE INDEX papers_abstract_emb_idx + ON papers USING hnsw (abstract_emb vector_cosine_ops); + +CREATE TABLE chunks ( + id BIGSERIAL PRIMARY KEY, + paper_id TEXT REFERENCES papers(id) ON DELETE CASCADE, + ord INT NOT NULL, -- position within the paper + content TEXT NOT NULL, + embedding vector(1024) +); + +CREATE INDEX chunks_emb_idx + ON chunks USING hnsw (embedding vector_cosine_ops); +CREATE INDEX chunks_paper_idx ON chunks (paper_id); + +-- Sparse / keyword hits for exact mathematical terminology (hybrid search). +-- Dense (above) + full-text (below) combined = robust against math terms. +CREATE INDEX chunks_fts_idx + ON chunks USING gin (to_tsvector('english', content)); + +-- --------------------------------------------------------------------- +-- Layer 2: Citation graph +-- cited_id has NO foreign key ON PURPOSE: +-- edges to not-yet-ingested papers are intentionally preserved — +-- those are your discovery leads. +-- --------------------------------------------------------------------- +CREATE TABLE citations ( + citing_id TEXT REFERENCES papers(id) ON DELETE CASCADE, + cited_id TEXT NOT NULL, -- arXiv/DOI/OpenAlex ID of the target + context TEXT, -- optional: citation context (S2) + PRIMARY KEY (citing_id, cited_id) +); + +CREATE INDEX citations_cited_idx ON citations (cited_id); + +-- --------------------------------------------------------------------- +-- Layer 3: Provenance (the "cleanly couple" goal) +-- --------------------------------------------------------------------- +CREATE TABLE code_links ( + id BIGSERIAL PRIMARY KEY, + symbol TEXT NOT NULL, -- e.g. 'dec::hodge_star' or 'file.cpp:120' + paper_id TEXT REFERENCES papers(id) ON DELETE SET NULL, + role TEXT, -- e.g. 'implements Thm 3.2', 'uses Eq 5' + note TEXT, + added_at TIMESTAMPTZ DEFAULT now() +); + +CREATE INDEX code_links_symbol_idx ON code_links (symbol); +CREATE INDEX code_links_paper_idx ON code_links (paper_id); + +-- --------------------------------------------------------------------- +-- Example query: discovery leads +-- Papers referenced by multiple already-ingested papers but not yet +-- collected themselves — ranked by how often they are cited locally. +-- --------------------------------------------------------------------- +-- SELECT cited_id, count(*) AS pull +-- FROM citations +-- WHERE cited_id NOT IN (SELECT id FROM papers) +-- GROUP BY cited_id +-- ORDER BY pull DESC +-- LIMIT 20; diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..ccaaa85 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,46 @@ +[build-system] +requires = ["hatchling"] +build-backend = "hatchling.build" + +[project] +name = "codex" +version = "0.1.0" +description = "Personal knowledge base for scientific papers — provenance, citation graph, semantic search." +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "psycopg[binary]>=3.1", + "pgvector>=0.3", + "pydantic-settings>=2", + "sentence-transformers>=3", + "typer>=0.12", + "httpx>=0.27", + "tenacity>=8", +] + +[project.scripts] +codex = "codex.cli:app" + +[dependency-groups] +dev = [ + "ruff>=0.4", + "mypy>=1.10", + "pytest>=8", + "pytest-mock>=3", +] + +[tool.ruff] 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