[ADD] field_vector_config

.copier-answers.yml

@@ -1,5 +1,5 @@
 # Do NOT update manually; changes here will be overwritten by Copier
-_commit: v1.42
+_commit: v1.43
 _src_path: git+https://github.com/OCA/oca-addons-repo-template
 additional_ruff_rules: []
 convert_readme_fragments_to_markdown: true
@@ -16,6 +16,7 @@ odoo_test_flavor: Both
 odoo_version: 18.0
 org_name: Odoo Community Association (OCA)
 org_slug: OCA
+postgres_image: pgvector/pgvector:pg16
 rebel_module_groups: []
 repo_description: ai
 repo_name: ai

.github/workflows/test.yml

@@ -42,7 +42,7 @@ jobs:
             makepot: "true"
     services:
       postgres:
-        image: postgres:12
+        image: pgvector/pgvector:pg16
         env:
           POSTGRES_USER: odoo
           POSTGRES_PASSWORD: odoo

field_vector_config/README.rst

@@ -0,0 +1,145 @@
+=================
+Field Vector Fill
+=================
+
+.. 
+   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+   !! This file is generated by oca-gen-addon-readme !!
+   !! changes will be overwritten.                   !!
+   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+   !! source digest: sha256:722ec05a7f6f24bb142697333fdd71c40ae7a2539242bd672c0affe2056d77c6
+   !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
+
+.. |badge1| image:: https://img.shields.io/badge/maturity-Beta-yellow.png
+    :target: https://odoo-community.org/page/development-status
+    :alt: Beta
+.. |badge2| image:: https://img.shields.io/badge/licence-AGPL--3-blue.png
+    :target: http://www.gnu.org/licenses/agpl-3.0-standalone.html
+    :alt: License: AGPL-3
+.. |badge3| image:: https://img.shields.io/badge/github-OCA%2Fai-lightgray.png?logo=github
+    :target: https://github.com/OCA/ai/tree/18.0/field_vector_config
+    :alt: OCA/ai
+.. |badge4| image:: https://img.shields.io/badge/weblate-Translate%20me-F47D42.png
+    :target: https://translation.odoo-community.org/projects/ai-18-0/ai-18-0-field_vector_config
+    :alt: Translate me on Weblate
+.. |badge5| image:: https://img.shields.io/badge/runboat-Try%20me-875A7B.png
+    :target: https://runboat.odoo-community.org/builds?repo=OCA/ai&target_branch=18.0
+    :alt: Try me on Runboat
+
+|badge1| |badge2| |badge3| |badge4| |badge5|
+
+This module allows to configure vector fields dynamically. Quite
+interesting if you want to handle them by using AI.
+
+**Table of contents**
+
+.. contents::
+   :local:
+
+Use Cases / Context
+===================
+
+The original field_vector module implements vector configuration,
+however, it is hard to handle how to create and search them.
+
+With this module, we added the functionality to do it.
+
+Configuration
+=============
+
+With this module, we can easily add a configuration on a vector to
+configure it dynamically on our database.
+
+.. code:: python
+
+   from odoo.addons.field_vector_config.fields import ComputedVector
+
+
+   class ResPartner(models.Model):
+       _inherit = "res.partner"
+
+       embedding = ComputedVector(string="Embedding")
+
+With that, we can go to **Settings / Technical / Database Structure** to
+add the field manually and configure it. There you can configure the
+size of the vector (depends on the method and model), computation
+information and so on.
+
+Important notes:
+
+- If you make a field that is computed, we recommend to create it in a
+  pre_init_hook to avoid the creation and allow the user to configure it
+  properly
+- If you change the size of the vector, update the column. It will
+  update the size and do nothing if it has the proper size.
+
+Usage
+=====
+
+After the configuration, we can easily compute and search using this
+vector. For example:
+
+.. code:: python
+
+   from odoo.addons.ai_tool.tools import aitool
+
+
+   class ProductProduct(models.Model):
+
+       _inherit = "product.product"
+
+       product_vector = ComputedVector(
+           compute="_compute_product_vector",
+           store=True,
+       )
+
+       @api.depends("name", "description")
+       def _compute_product_vector(self):
+           for record in self:
+               record.product_vector = record._encode_vector("product_vector", f"{record.name}\n{record.description}\n{record.description_purchase}")[0]
+
+       def _find_vector_product(self, value, limit=5):
+           records = self.search_vector("product_vector", value, limit=limit)
+           return [{"id": r.id, "name": r.name, "description": r.description} for r in records]
+
+Bug Tracker
+===========
+
+Bugs are tracked on `GitHub Issues <https://github.com/OCA/ai/issues>`_.
+In case of trouble, please check there if your issue has already been reported.
+If you spotted it first, help us to smash it by providing a detailed and welcomed
+`feedback <https://github.com/OCA/ai/issues/new?body=module:%20field_vector_config%0Aversion:%2018.0%0A%0A**Steps%20to%20reproduce**%0A-%20...%0A%0A**Current%20behavior**%0A%0A**Expected%20behavior**>`_.
+
+Do not contact contributors directly about support or help with technical issues.
+
+Credits
+=======
+
+Authors
+-------
+
+* Dixmit
+
+Contributors
+------------
+
+- `Dixmit <https://www.dixmit.com>`__
+
+  - Enric Tobella
+
+Maintainers
+-----------
+
+This module is maintained by the OCA.
+
+.. image:: https://odoo-community.org/logo.png
+   :alt: Odoo Community Association
+   :target: https://odoo-community.org
+
+OCA, or the Odoo Community Association, is a nonprofit organization whose
+mission is to support the collaborative development of Odoo features and
+promote its widespread use.
+
+This module is part of the `OCA/ai <https://github.com/OCA/ai/tree/18.0/field_vector_config>`_ project on GitHub.
+
+You are welcome to contribute. To learn how please visit https://odoo-community.org/page/Contribute.

field_vector_config/__init__.py

@@ -0,0 +1,2 @@
+from . import models
+from . import fields

field_vector_config/__manifest__.py

@@ -0,0 +1,19 @@
+# Copyright 2026 Dixmit
+# License AGPL-3.0 or later (https://www.gnu.org/licenses/agpl).
+
+{
+    "name": "Field Vector Fill",
+    "summary": """Autogenerate vectors and add search functions""",
+    "version": "18.0.1.0.0",
+    "license": "AGPL-3",
+    "author": "Dixmit,Odoo Community Association (OCA)",
+    "website": "https://github.com/OCA/ai",
+    "depends": [
+        "field_vector",
+    ],
+    "data": [
+        "security/ir.model.access.csv",
+        "views/ir_model_field_vector.xml",
+    ],
+    "demo": [],
+}

field_vector_config/fields.py

@@ -0,0 +1,43 @@
+# Copyright 2026 Dixmit
+# License AGPL-3.0 or later (https://www.gnu.org/licenses/agpl).
+
+from odoo.addons.field_vector.fields import Vector
+
+
+def split_text_chunks(text, max_words=350, overlap=50):
+    words = text.split()
+    chunks = []
+    start = 0
+    while start < len(words):
+        chunk = " ".join(words[start : start + max_words])
+        chunks.append(chunk)
+        start += max_words - overlap
+    return chunks
+
+
+class ComputedVector(Vector):
+    type = "computed_vector"
+
+    def __init__(
+        self,
+        dimensions=10,
+        **kwargs,
+    ):
+        # We set a default dimensions value
+        super().__init__(dimensions=dimensions, **kwargs)
+
+    @property
+    def column_type(self):
+        return ("vector", "vector")
+
+    def vector_dimensions(self, model):
+        dimensions = (
+            model.env["ir.model.fields"]
+            .sudo()
+            .search(
+                [("model", "=", model._name), ("name", "=", self.name)],
+                limit=1,
+            )
+            .vector_configuration_ids.dimensions
+        )
+        return dimensions or super().vector_dimensions(model)

field_vector_config/models/__init__.py

@@ -0,0 +1,3 @@
+from . import ir_model_field_vector
+from . import ir_model_fields
+from . import base

field_vector_config/models/base.py

@@ -0,0 +1,82 @@
+# Copyright 2026 Dixmit
+# License AGPL-3.0 or later (https://www.gnu.org/licenses/agpl).
+
+from odoo import api, fields, models
+from odoo.exceptions import UserError
+from odoo.tools import sql
+
+from ..fields import ComputedVector
+
+
+class Base(models.AbstractModel):
+    _inherit = "base"
+
+    @api.model
+    @api.readonly
+    @api.returns("self")
+    def search_vector(self, field_name, data, domain=None, limit=5, minim=0.5):
+        if domain is None:
+            domain = []
+        if not isinstance(self._fields[field_name], ComputedVector):
+            raise UserError(f"Field {field_name} is not a computed_vector field")
+        to_search = self._encode_vector(field_name, data, is_search=True)[0]
+        query = self._search(domain, limit=limit)
+        distance = sql.SQL(
+            "%s <=> %s::vector",
+            self._field_to_sql(self._table, field_name, query),
+            to_search,
+        )
+        sql_terms = [
+            self._field_to_sql(self._table, "id", "query"),
+            sql.SQL("%s as distance", distance),
+        ]
+        query.order = "distance ASC"
+        if minim:
+            query.add_where(sql.SQL("%s < %s", distance, minim))
+        self.env.cr.execute(query.select(*sql_terms))
+        return self.browse([row[0] for row in self.env.cr.fetchall()])
+
+    @api.model
+    @api.readonly
+    @api.returns("self")
+    def search_vector_grouped(
+        self, field_name, data, final_field, domain=None, limit=5, minim=0.5
+    ):
+        if domain is None:
+            domain = []
+        if not isinstance(self._fields[field_name], ComputedVector):
+            raise UserError(f"Field {field_name} is not a computed_vector field")
+        if not isinstance(self._fields[final_field], fields.Many2one):
+            raise UserError(f"Field {final_field} is not a Many2one field")
+        to_search = self._encode_vector(field_name, data, is_search=True)[0]
+        query = self._search(domain, limit=limit)
+        distance = sql.SQL(
+            "MIN(%s <=> %s::vector)",
+            self._field_to_sql(self._table, field_name, query),
+            to_search,
+        )
+        sql_terms = [
+            self._field_to_sql(self._table, final_field, "query"),
+            sql.SQL("%s as distance", distance),
+        ]
+        query.order = "distance ASC"
+        query.groupby = self._field_to_sql(self._table, final_field, query)
+        if minim:
+            query.having = sql.SQL("%s < %s", distance, minim)
+        self.env.cr.execute(query.select(*sql_terms))
+        rows = self.env.cr.fetchall()
+        return self[final_field].browse([row[0] for row in rows])
+
+    def _encode_vector(self, field_name, data, is_search=False):
+        config = (
+            self.env["ir.model.fields"]
+            .sudo()
+            .search(
+                [("model", "=", self._name), ("name", "=", field_name)],
+                limit=1,
+            )
+            .vector_configuration_ids
+        )
+        if not config:
+            raise UserError(f"Field {field_name} is not configured")
+        return config._encode_vector(data, is_search=is_search)