Add embed script

.envrc

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+source_up_if_exists
+layout python3

.gitignore

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+.direnv

README.md

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+# Bible Embeddings
+
+## Setup
+
+```sh
+direnv allow
+just install-deps
+```
+
+## Usage
+
+```sh
+just embed bsb BAAI/bge-large-en
+```
+
+This will create a directory structure with json files like such:
+
+```
+embeddings
+├── Exodus
+│   ├── 001
+│   │   └── bsb-bge-large-en.json
+│   ├── 002
+│   │   └── bsb-bge-large-en.json
+│   ├── 003
+│   │   └── bsb-bge-large-en.json
+│   └── etc
+├── Genesis
+│   ├── 001
+│   │   └── bsb-bge-large-en.json
+│   ├── 002
+│   │   └── bsb-bge-large-en.json
+│   ├── 003
+│   │   └── bsb-bge-large-en.json
+│   └── etc
+└── Leviticus
+    ├── 001
+    │   └── bsb-bge-large-en.json
+    ├── 002
+    │   └── bsb-bge-large-en.json
+    ├── 003
+    │   └── bsb-bge-large-en.json
+    └── etc
+```

embed.py

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+import argparse
+import json
+import os
+from itertools import groupby
+from sentence_transformers import SentenceTransformer
+
+arg_parser = argparse.ArgumentParser(prog="embed", description="Creating embeddings of Bible verses")
+arg_parser.add_argument("translation", help="Located at text/<translation>.json")
+arg_parser.add_argument("model", help="SentenceTransformer model")
+
+args = arg_parser.parse_args()
+
+with open(f"text/{args.translation}.json") as f:
+    bible_data = json.load(f)
+
+grouped_bible_data = groupby(bible_data, lambda item: (item["book"], item["chapter"]))
+
+model = SentenceTransformer(args.model)
+model_name = args.model.split("/")[-1]
+
+for (book, chapter), grouped in grouped_bible_data:
+    print(f"Embedding {book} {chapter}")
+    verses = list(grouped)
+    data = []
+    base_path = os.path.join("embeddings", book, str(chapter).zfill(3))
+    os.makedirs(base_path, exist_ok=True)
+    sentences = [verse["text"] for verse in verses]
+    embeddings = model.encode(sentences, normalize_embeddings=True)
+    for i, verse in enumerate(verses):
+        data.append({ "book": verse["book"], "chapter": verse["chapter"], "verse": verse["verse"], "embedding": embeddings[i].tolist() })
+    with open(os.path.join(base_path, f"{args.translation}-{model_name}.json"), "w", encoding='utf-8') as f:
+        json.dump(data, f, indent=2)

justfile

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 download-bsb:
   curl https://bereanbible.com/bsb.txt | iconv -f windows-1252 -t utf-8 > text/bsb.txt
+
+install-deps:
+  pip install -r requirements.txt
+
+embed translation model:
+  python embed.py {{translation}} {{model}}

requirements.txt

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+sentence-transformers==2.2.2