c919e83526
- Add ELAI avatar seed data (7 avatars with codes, URLs, voice configs) from the original backend's avatars.json - Add missing system parameters: encoach.aws_region (eu-west-1), encoach.whisper_workers (4) - Add training tips import script with pathways_2_rw.json data source - Add action_compute_embeddings() method to training tip model for computing sentence-transformer embeddings on demand Made-with: Cursor
77 lines
2.3 KiB
Python
77 lines
2.3 KiB
Python
"""Import training tips from pathways JSON into encoach.training.tip model.
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Run inside the Odoo container via:
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odoo shell -d encoach < /mnt/custom/scripts/import_training_tips.py
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This script:
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1. Reads pathways_2_rw.json
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2. Creates encoach.training.tip records (tip_id, category, content)
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3. Computes sentence-transformer embeddings and stores them
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"""
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import json
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import os
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import pickle
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import sys
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SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
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JSON_PATH = os.path.join(SCRIPT_DIR, "pathways_2_rw.json")
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def main():
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with open(JSON_PATH, "r", encoding="utf-8") as f:
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data = json.load(f)
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TipModel = env["encoach.training.tip"].sudo()
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tips_data = []
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for unit in data["units"]:
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for page in unit["pages"]:
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for tip in page["tips"]:
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category = tip["category"].lower().replace(" ", "_")
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tips_data.append({
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"tip_id": tip["id"],
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"category": category,
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"content": tip["text"],
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})
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created = 0
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skipped = 0
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for td in tips_data:
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existing = TipModel.search([("tip_id", "=", td["tip_id"])], limit=1)
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if existing:
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skipped += 1
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continue
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TipModel.create(td)
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created += 1
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env.cr.commit()
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print(f"Tips import complete: {created} created, {skipped} skipped (already exist)")
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try:
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from sentence_transformers import SentenceTransformer
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import numpy as np
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print("Computing embeddings with all-MiniLM-L6-v2...")
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model = SentenceTransformer("all-MiniLM-L6-v2")
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tips = TipModel.search([("embedding", "=", False)])
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if not tips:
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print("All tips already have embeddings.")
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return
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for i, tip in enumerate(tips):
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vec = model.encode([tip.content]).astype(np.float32)[0]
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tip.embedding = pickle.dumps(vec)
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if (i + 1) % 10 == 0:
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print(f" Embedded {i + 1}/{len(tips)} tips...")
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env.cr.commit()
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print(f"Embeddings computed for {len(tips)} tips.")
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except ImportError:
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print("WARNING: sentence-transformers not available. Tips created without embeddings.")
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print("Embeddings can be computed later by re-running this script.")
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main()
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