diff --git a/db/migrate/20240611170904_upgrade_pgvector_070.rb b/db/migrate/20240611170904_upgrade_pgvector_070.rb
new file mode 100644
index 00000000..875b5362
--- /dev/null
+++ b/db/migrate/20240611170904_upgrade_pgvector_070.rb
@@ -0,0 +1,17 @@
+# frozen_string_literal: true
+
+class UpgradePgvector070 < ActiveRecord::Migration[7.0]
+  def up
+    minimum_target_version = "0.7.0"
+    installed_version =
+      DB.query_single("SELECT extversion FROM pg_extension WHERE extname = 'vector';").first
+
+    if Gem::Version.new(installed_version) < Gem::Version.new(minimum_target_version)
+      DB.exec("ALTER EXTENSION vector UPDATE TO '0.7.0';")
+    end
+  end
+
+  def down
+    raise ActiveRecord::IrreversibleMigration
+  end
+end
diff --git a/db/migrate/20240611170905_move_embeddings_to_single_table_per_type.rb b/db/migrate/20240611170905_move_embeddings_to_single_table_per_type.rb
new file mode 100644
index 00000000..55563763
--- /dev/null
+++ b/db/migrate/20240611170905_move_embeddings_to_single_table_per_type.rb
@@ -0,0 +1,158 @@
+# frozen_string_literal: true
+
+class MoveEmbeddingsToSingleTablePerType < ActiveRecord::Migration[7.0]
+  def up
+    create_table :ai_topic_embeddings, id: false do |t|
+      t.integer :topic_id, null: false
+      t.integer :model_id, null: false
+      t.integer :model_version, null: false
+      t.integer :strategy_id, null: false
+      t.integer :strategy_version, null: false
+      t.text :digest, null: false
+      t.column :embeddings, "halfvec", null: false
+      t.timestamps
+
+      t.index %i[model_id strategy_id topic_id],
+              unique: true,
+              name: "index_ai_topic_embeddings_on_model_strategy_topic"
+    end
+
+    create_table :ai_post_embeddings, id: false do |t|
+      t.integer :post_id, null: false
+      t.integer :model_id, null: false
+      t.integer :model_version, null: false
+      t.integer :strategy_id, null: false
+      t.integer :strategy_version, null: false
+      t.text :digest, null: false
+      t.column :embeddings, "halfvec", null: false
+      t.timestamps
+
+      t.index %i[model_id strategy_id post_id],
+              unique: true,
+              name: "index_ai_post_embeddings_on_model_strategy_post"
+    end
+
+    create_table :ai_document_fragment_embeddings, id: false do |t|
+      t.integer :rag_document_fragment_id, null: false
+      t.integer :model_id, null: false
+      t.integer :model_version, null: false
+      t.integer :strategy_id, null: false
+      t.integer :strategy_version, null: false
+      t.text :digest, null: false
+      t.column :embeddings, "halfvec", null: false
+      t.timestamps
+
+      t.index %i[model_id strategy_id rag_document_fragment_id],
+              unique: true,
+              name: "index_ai_fragment_embeddings_on_model_strategy_fragment"
+    end
+
+    # Copy data from old tables to new tables
+    execute <<-SQL
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 1, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_1_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 2, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_2_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 3, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_3_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 4, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_4_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 5, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_5_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 6, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_6_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 7, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_7_1;
+
+      INSERT INTO ai_topic_embeddings (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT topic_id, 8, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_topic_embeddings_8_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 1, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_1_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 2, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_2_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 3, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_3_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 4, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_4_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 5, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_5_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 6, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_6_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 7, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_7_1;
+
+      INSERT INTO ai_post_embeddings (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT post_id, 8, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_post_embeddings_8_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 1, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_1_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 2, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_2_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 3, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_3_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 4, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_4_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 5, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_5_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 6, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_6_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 7, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_7_1;
+
+      INSERT INTO ai_document_fragment_embeddings (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+      SELECT rag_document_fragment_id, 8, model_version, 1, strategy_version, digest, embeddings, created_at, updated_at
+      FROM ai_document_fragment_embeddings_8_1;
+    SQL
+
+    begin
+      strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
+      vector_rep =
+        DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
+      vector_rep.consider_indexing
+    rescue StandardError => e
+      Rails.logger.error("Failed to index embeddings: #{e}")
+    end
+  end
+end
diff --git a/db/post_migrate/20240611170906_drop_old_embeddings_tables.rb b/db/post_migrate/20240611170906_drop_old_embeddings_tables.rb
new file mode 100644
index 00000000..31546785
--- /dev/null
+++ b/db/post_migrate/20240611170906_drop_old_embeddings_tables.rb
@@ -0,0 +1,30 @@
+# frozen_string_literal: true
+
+class DropOldEmbeddingsTables < ActiveRecord::Migration[7.0]
+  def up
+    drop_table :ai_topic_embeddings_1_1
+    drop_table :ai_topic_embeddings_2_1
+    drop_table :ai_topic_embeddings_3_1
+    drop_table :ai_topic_embeddings_4_1
+    drop_table :ai_topic_embeddings_5_1
+    drop_table :ai_topic_embeddings_6_1
+    drop_table :ai_topic_embeddings_7_1
+    drop_table :ai_topic_embeddings_8_1
+    drop_table :ai_post_embeddings_1_1
+    drop_table :ai_post_embeddings_2_1
+    drop_table :ai_post_embeddings_3_1
+    drop_table :ai_post_embeddings_4_1
+    drop_table :ai_post_embeddings_5_1
+    drop_table :ai_post_embeddings_6_1
+    drop_table :ai_post_embeddings_7_1
+    drop_table :ai_post_embeddings_8_1
+    drop_table :ai_document_fragment_embeddings_1_1
+    drop_table :ai_document_fragment_embeddings_2_1
+    drop_table :ai_document_fragment_embeddings_3_1
+    drop_table :ai_document_fragment_embeddings_4_1
+    drop_table :ai_document_fragment_embeddings_5_1
+    drop_table :ai_document_fragment_embeddings_6_1
+    drop_table :ai_document_fragment_embeddings_7_1
+    drop_table :ai_document_fragment_embeddings_8_1
+  end
+end
diff --git a/lib/embeddings/vector_representations/all_mpnet_base_v2.rb b/lib/embeddings/vector_representations/all_mpnet_base_v2.rb
index 60560ff4..1a4b8002 100644
--- a/lib/embeddings/vector_representations/all_mpnet_base_v2.rb
+++ b/lib/embeddings/vector_representations/all_mpnet_base_v2.rb
@@ -53,7 +53,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_ip_ops"
+          "halfvec_ip_ops"
         end
 
         def tokenizer
diff --git a/lib/embeddings/vector_representations/base.rb b/lib/embeddings/vector_representations/base.rb
index 6d2c3d65..f55b341c 100644
--- a/lib/embeddings/vector_representations/base.rb
+++ b/lib/embeddings/vector_representations/base.rb
@@ -52,10 +52,13 @@ module DiscourseAi
             # Using extension maintainer's recommendation for ivfflat indexes
             # Results are not as good as without indexes, but it's much faster
             # Disk usage is ~1x the size of the table, so this doubles table total size
-            count = DB.query_single("SELECT count(*) FROM #{table_name};").first
+            count =
+              DB.query_single(
+                "SELECT count(*) FROM #{table_name} WHERE model_id = #{id} AND strategy_id = #{@strategy.id};",
+              ).first
             lists = [count < 1_000_000 ? count / 1000 : Math.sqrt(count).to_i, 10].max
             probes = [count < 1_000_000 ? lists / 10 : Math.sqrt(lists).to_i, 1].max
-            Discourse.cache.write("#{table_name}-probes", probes)
+            Discourse.cache.write("#{table_name}-#{id}-#{@strategy.id}-probes", probes)
 
             existing_index = DB.query_single(<<~SQL, index_name: index_name).first
               SELECT
@@ -83,7 +86,7 @@ module DiscourseAi
                 .to_i || 0
             new_rows =
               DB.query_single(
-                "SELECT count(*) FROM #{table_name} WHERE created_at > '#{Time.at(existing_index_age)}';",
+                "SELECT count(*) FROM #{table_name} WHERE model_id = #{id} AND strategy_id = #{@strategy.id} AND created_at > '#{Time.at(existing_index_age)}';",
               ).first
             existing_lists = existing_index.match(/lists='(\d+)'/)&.captures&.first&.to_i
 
@@ -128,9 +131,11 @@ module DiscourseAi
               ON
                 #{table_name}
               USING
-                ivfflat (embeddings #{pg_index_type})
+                ivfflat ((embeddings::halfvec(#{dimensions})) #{pg_index_type})
               WITH
-                (lists = #{lists});
+                (lists = #{lists})
+              WHERE
+                model_id = #{id} AND strategy_id = #{@strategy.id};
             SQL
           rescue PG::ProgramLimitExceeded => e
             parsed_error = e.message.match(/memory required is (\d+ [A-Z]{2}), ([a-z_]+)/)
@@ -175,6 +180,8 @@ module DiscourseAi
             FROM
               #{table_name(target)}
             WHERE
+              model_id = #{id} AND
+              strategy_id = #{@strategy.id} AND
               #{target_column} = :target_id
             LIMIT 1
           SQL
@@ -191,8 +198,11 @@ module DiscourseAi
               topic_id
             FROM
               #{topic_table_name}
+            WHERE
+              model_id = #{id} AND
+              strategy_id = #{@strategy.id}
             ORDER BY
-              embeddings #{pg_function} '[:query_embedding]'
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions})
             LIMIT 1
           SQL
         end
@@ -203,8 +213,11 @@ module DiscourseAi
               post_id
             FROM
               #{post_table_name}
+            WHERE
+              model_id = #{id} AND
+              strategy_id = #{@strategy.id}
             ORDER BY
-              embeddings #{pg_function} '[:query_embedding]'
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions})
             LIMIT 1
           SQL
         end
@@ -214,11 +227,13 @@ module DiscourseAi
             #{probes_sql(topic_table_name)}
             SELECT
               topic_id,
-              embeddings #{pg_function} '[:query_embedding]' AS distance
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions}) AS distance
             FROM
               #{topic_table_name}
+            WHERE
+              model_id = #{id} AND strategy_id = #{@strategy.id}
             ORDER BY
-              embeddings #{pg_function} '[:query_embedding]'
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions})
             LIMIT :limit
             OFFSET :offset
           SQL
@@ -238,15 +253,17 @@ module DiscourseAi
             #{probes_sql(post_table_name)}
             SELECT
               post_id,
-              embeddings #{pg_function} '[:query_embedding]' AS distance
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions}) AS distance
             FROM
               #{post_table_name}
             INNER JOIN
               posts AS p ON p.id = post_id
             INNER JOIN
               topics AS t ON t.id = p.topic_id AND t.archetype = 'regular'
+            WHERE
+              model_id = #{id} AND strategy_id = #{@strategy.id}
             ORDER BY
-              embeddings #{pg_function} '[:query_embedding]'
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions})
             LIMIT :limit
             OFFSET :offset
           SQL
@@ -274,15 +291,17 @@ module DiscourseAi
             #{probes_sql(post_table_name)}
             SELECT
               rag_document_fragment_id,
-              embeddings #{pg_function} '[:query_embedding]' AS distance
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions}) AS distance
             FROM
               #{rag_fragments_table_name}
             INNER JOIN
               rag_document_fragments AS rdf ON rdf.id = rag_document_fragment_id
             WHERE
+              model_id = #{id} AND
+              strategy_id = #{@strategy.id} AND
               rdf.ai_persona_id = :persona_id
             ORDER BY
-              embeddings #{pg_function} '[:query_embedding]'
+              embeddings::halfvec(#{dimensions}) #{pg_function} '[:query_embedding]'::halfvec(#{dimensions})
             LIMIT :limit
             OFFSET :offset
           SQL
@@ -309,16 +328,21 @@ module DiscourseAi
               topic_id
             FROM
               #{topic_table_name}
+            WHERE
+              model_id = #{id} AND
+              strategy_id = #{@strategy.id}
             ORDER BY
-              embeddings #{pg_function} (
+              embeddings::halfvec(#{dimensions}) #{pg_function} (
                 SELECT
                   embeddings
                 FROM
                   #{topic_table_name}
                 WHERE
+                  model_id = #{id} AND
+                  strategy_id = #{@strategy.id} AND
                   topic_id = :topic_id
                 LIMIT 1
-              )
+              )::halfvec(#{dimensions})
             LIMIT 100
           SQL
         rescue PG::Error => e
@@ -329,15 +353,15 @@ module DiscourseAi
         end
 
         def topic_table_name
-          "ai_topic_embeddings_#{id}_#{@strategy.id}"
+          "ai_topic_embeddings"
         end
 
         def post_table_name
-          "ai_post_embeddings_#{id}_#{@strategy.id}"
+          "ai_post_embeddings"
         end
 
         def rag_fragments_table_name
-          "ai_document_fragment_embeddings_#{id}_#{@strategy.id}"
+          "ai_document_fragment_embeddings"
         end
 
         def table_name(target)
@@ -354,11 +378,11 @@ module DiscourseAi
         end
 
         def index_name(table_name)
-          "#{table_name}_search"
+          "#{table_name}_#{id}_#{@strategy.id}_search"
         end
 
         def probes_sql(table_name)
-          probes = Discourse.cache.read("#{table_name}-probes")
+          probes = Discourse.cache.read("#{table_name}-#{id}-#{@strategy.id}-probes")
           probes.present? ? "SET LOCAL ivfflat.probes TO #{probes};" : ""
         end
 
@@ -400,9 +424,9 @@ module DiscourseAi
           if target.is_a?(Topic)
             DB.exec(
               <<~SQL,
-              INSERT INTO #{topic_table_name} (topic_id, model_version, strategy_version, digest, embeddings, created_at, updated_at)
-              VALUES (:topic_id, :model_version, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
-              ON CONFLICT (topic_id)
+              INSERT INTO #{topic_table_name} (topic_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+              VALUES (:topic_id, :model_id, :model_version, :strategy_id, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
+              ON CONFLICT (strategy_id, model_id, topic_id)
               DO UPDATE SET
                 model_version = :model_version,
                 strategy_version = :strategy_version,
@@ -411,7 +435,9 @@ module DiscourseAi
                 updated_at = CURRENT_TIMESTAMP
               SQL
               topic_id: target.id,
+              model_id: id,
               model_version: version,
+              strategy_id: @strategy.id,
               strategy_version: @strategy.version,
               digest: digest,
               embeddings: vector,
@@ -419,9 +445,9 @@ module DiscourseAi
           elsif target.is_a?(Post)
             DB.exec(
               <<~SQL,
-              INSERT INTO #{post_table_name} (post_id, model_version, strategy_version, digest, embeddings, created_at, updated_at)
-              VALUES (:post_id, :model_version, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
-              ON CONFLICT (post_id)
+              INSERT INTO #{post_table_name} (post_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+              VALUES (:post_id, :model_id, :model_version, :strategy_id, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
+              ON CONFLICT (model_id, strategy_id, post_id)
               DO UPDATE SET
                 model_version = :model_version,
                 strategy_version = :strategy_version,
@@ -430,7 +456,9 @@ module DiscourseAi
                 updated_at = CURRENT_TIMESTAMP
               SQL
               post_id: target.id,
+              model_id: id,
               model_version: version,
+              strategy_id: @strategy.id,
               strategy_version: @strategy.version,
               digest: digest,
               embeddings: vector,
@@ -438,9 +466,9 @@ module DiscourseAi
           elsif target.is_a?(RagDocumentFragment)
             DB.exec(
               <<~SQL,
-              INSERT INTO #{rag_fragments_table_name} (rag_document_fragment_id, model_version, strategy_version, digest, embeddings, created_at, updated_at)
-              VALUES (:fragment_id, :model_version, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
-              ON CONFLICT (rag_document_fragment_id)
+              INSERT INTO #{rag_fragments_table_name} (rag_document_fragment_id, model_id, model_version, strategy_id, strategy_version, digest, embeddings, created_at, updated_at)
+              VALUES (:fragment_id, :model_id, :model_version, :strategy_id, :strategy_version, :digest, '[:embeddings]', CURRENT_TIMESTAMP, CURRENT_TIMESTAMP)
+              ON CONFLICT (model_id, strategy_id, rag_document_fragment_id)
               DO UPDATE SET
                 model_version = :model_version,
                 strategy_version = :strategy_version,
@@ -449,7 +477,9 @@ module DiscourseAi
                 updated_at = CURRENT_TIMESTAMP
               SQL
               fragment_id: target.id,
+              model_id: id,
               model_version: version,
+              strategy_id: @strategy.id,
               strategy_version: @strategy.version,
               digest: digest,
               embeddings: vector,
diff --git a/lib/embeddings/vector_representations/bge_large_en.rb b/lib/embeddings/vector_representations/bge_large_en.rb
index bdc2f157..601c85a1 100644
--- a/lib/embeddings/vector_representations/bge_large_en.rb
+++ b/lib/embeddings/vector_representations/bge_large_en.rb
@@ -78,7 +78,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_ip_ops"
+          "halfvec_ip_ops"
         end
 
         def tokenizer
diff --git a/lib/embeddings/vector_representations/bge_m3.rb b/lib/embeddings/vector_representations/bge_m3.rb
index 822f6cb1..c220cf75 100644
--- a/lib/embeddings/vector_representations/bge_m3.rb
+++ b/lib/embeddings/vector_representations/bge_m3.rb
@@ -44,7 +44,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_ip_ops"
+          "halfvec_ip_ops"
         end
 
         def tokenizer
diff --git a/lib/embeddings/vector_representations/gemini.rb b/lib/embeddings/vector_representations/gemini.rb
index 39b9d22e..86b7afae 100644
--- a/lib/embeddings/vector_representations/gemini.rb
+++ b/lib/embeddings/vector_representations/gemini.rb
@@ -39,7 +39,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_cosine_ops"
+          "halfvec_cosine_ops"
         end
 
         def vector_from(text, asymetric: false)
diff --git a/lib/embeddings/vector_representations/multilingual_e5_large.rb b/lib/embeddings/vector_representations/multilingual_e5_large.rb
index a65a4094..8267f938 100644
--- a/lib/embeddings/vector_representations/multilingual_e5_large.rb
+++ b/lib/embeddings/vector_representations/multilingual_e5_large.rb
@@ -65,7 +65,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_cosine_ops"
+          "halfvec_cosine_ops"
         end
 
         def tokenizer
diff --git a/lib/embeddings/vector_representations/text_embedding_3_large.rb b/lib/embeddings/vector_representations/text_embedding_3_large.rb
index 890657e8..626428c9 100644
--- a/lib/embeddings/vector_representations/text_embedding_3_large.rb
+++ b/lib/embeddings/vector_representations/text_embedding_3_large.rb
@@ -41,7 +41,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_cosine_ops"
+          "halfvec_cosine_ops"
         end
 
         def vector_from(text, asymetric: false)
diff --git a/lib/embeddings/vector_representations/text_embedding_3_small.rb b/lib/embeddings/vector_representations/text_embedding_3_small.rb
index c307f684..fbac4bc7 100644
--- a/lib/embeddings/vector_representations/text_embedding_3_small.rb
+++ b/lib/embeddings/vector_representations/text_embedding_3_small.rb
@@ -39,7 +39,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_cosine_ops"
+          "halfvec_cosine_ops"
         end
 
         def vector_from(text, asymetric: false)
diff --git a/lib/embeddings/vector_representations/text_embedding_ada_002.rb b/lib/embeddings/vector_representations/text_embedding_ada_002.rb
index d90b555a..2079e028 100644
--- a/lib/embeddings/vector_representations/text_embedding_ada_002.rb
+++ b/lib/embeddings/vector_representations/text_embedding_ada_002.rb
@@ -39,7 +39,7 @@ module DiscourseAi
         end
 
         def pg_index_type
-          "vector_cosine_ops"
+          "halfvec_cosine_ops"
         end
 
         def vector_from(text, asymetric: false)
diff --git a/spec/lib/modules/ai_bot/personas/persona_spec.rb b/spec/lib/modules/ai_bot/personas/persona_spec.rb
index b773d86d..824ed4da 100644
--- a/spec/lib/modules/ai_bot/personas/persona_spec.rb
+++ b/spec/lib/modules/ai_bot/personas/persona_spec.rb
@@ -339,7 +339,10 @@ RSpec.describe DiscourseAi::AiBot::Personas::Persona do
       fab!(:llm_model) { Fabricate(:fake_model) }
 
       it "will run the question consolidator" do
-        context_embedding = [0.049382, 0.9999]
+        strategy = DiscourseAi::Embeddings::Strategies::Truncation.new
+        vector_rep =
+          DiscourseAi::Embeddings::VectorRepresentations::Base.current_representation(strategy)
+        context_embedding = vector_rep.dimensions.times.map { rand(-1.0...1.0) }
         EmbeddingsGenerationStubs.discourse_service(
           SiteSetting.ai_embeddings_model,
           consolidated_question,