f7c780e7e6
Binary fields default to attachment storage in Odoo 19, but FAISS embedding vectors need to be loaded in bulk via direct SQL for performance. Using attachment=False stores them in the table column. Made-with: Cursor
49 lines
1.6 KiB
Python
49 lines
1.6 KiB
Python
import logging
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import pickle
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from odoo import api, models, fields
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_logger = logging.getLogger(__name__)
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class EncoachTrainingTip(models.Model):
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_name = "encoach.training.tip"
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_description = "EnCoach Training Tip"
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tip_id = fields.Char(required=True, index=True)
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category = fields.Selection(
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[
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("ct_focus", "CT Focus"),
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("language_for_writing", "Language for Writing"),
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("reading_skill", "Reading Skill"),
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("strategy", "Strategy"),
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("writing_skill", "Writing Skill"),
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("word_link", "Word Link"),
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("word_partners", "Word Partners"),
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],
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string="Category",
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)
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content = fields.Text(required=True)
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embedding = fields.Binary(string="FAISS Embedding Vector", attachment=False)
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def action_compute_embeddings(self):
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"""Compute sentence-transformer embeddings for tips missing them."""
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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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except ImportError:
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_logger.error("sentence-transformers not installed; cannot compute embeddings")
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return
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tips = self.search([("embedding", "=", False)])
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if not tips:
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_logger.info("All tips already have embeddings")
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return
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model = SentenceTransformer("all-MiniLM-L6-v2")
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for tip in 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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_logger.info("Computed embeddings for %d tips", len(tips))
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