mirror of
https://github.com/github/awesome-copilot.git
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Nixon Kurian
746ba555b6
* add mini-context-graph skill * remove pycache files * filename case update to SKILL.md * update readme
91 lines
2.8 KiB
Python
91 lines
2.8 KiB
Python
"""
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index_store.py — Maintains entity and keyword indexes for fast lookup.
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Handles:
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- Entity index: name → [node_ids]
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- Keyword index: token → [node_ids]
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- Persist to index.json
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"""
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from __future__ import annotations
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import json
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import os
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import re
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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import config
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_DATA_DIR = Path(os.environ.get("MINI_CONTEXT_GRAPH_DATA_DIR", str(config.DATA_DIR)))
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_INDEX_FILE = _DATA_DIR / "index.json"
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_STOPWORDS = frozenset(
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[
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"a", "an", "the", "is", "are", "was", "were", "be", "been", "being",
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"have", "has", "had", "do", "does", "did", "will", "would", "could",
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"should", "may", "might", "shall", "can", "to", "of", "in", "on",
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"at", "by", "for", "with", "from", "and", "or", "but", "not", "it",
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"its", "this", "that", "these", "those", "i", "you", "he", "she",
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"we", "they", "what", "which", "who", "how", "why", "when", "where",
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]
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)
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def _load() -> dict:
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if _INDEX_FILE.exists():
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with open(_INDEX_FILE, "r") as f:
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return json.load(f)
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return {"entity_index": {}, "keyword_index": {}}
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def _save(index: dict) -> None:
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_DATA_DIR.mkdir(parents=True, exist_ok=True)
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with open(_INDEX_FILE, "w") as f:
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json.dump(index, f, indent=2)
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def _tokenize(text: str) -> list[str]:
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"""Split text into lowercase tokens, removing stopwords and short tokens."""
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tokens = re.findall(r"[a-z0-9]+", text.lower())
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return [t for t in tokens if t not in _STOPWORDS and len(t) > 1]
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def add_entity(name: str, node_id: str) -> None:
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"""Register an entity name → node_id in both entity and keyword indexes."""
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index = _load()
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name_lower = name.strip().lower()
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# Entity index
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if name_lower not in index["entity_index"]:
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index["entity_index"][name_lower] = []
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if node_id not in index["entity_index"][name_lower]:
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index["entity_index"][name_lower].append(node_id)
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# Keyword index
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for token in _tokenize(name_lower):
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if token not in index["keyword_index"]:
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index["keyword_index"][token] = []
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if node_id not in index["keyword_index"][token]:
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index["keyword_index"][token].append(node_id)
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_save(index)
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def search(query: str) -> list[str]:
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"""Search for node_ids matching the query via entity name or keywords."""
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index = _load()
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query_lower = query.strip().lower()
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matched_ids: set[str] = set()
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# Exact entity name match
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if query_lower in index["entity_index"]:
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matched_ids.update(index["entity_index"][query_lower])
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# Keyword match
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for token in _tokenize(query_lower):
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if token in index["keyword_index"]:
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matched_ids.update(index["keyword_index"][token])
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return list(matched_ids)
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