Milvus BM25 Full-Text Search Configuration and Migration

Background

FastGPT full-text search defaults to MongoDB $text. When Milvus is used as the vector store, full-text search automatically switches to Milvus BM25 (single modeldata_v2 table, vector + full-text in one collection) and stops writing the MongoDB full-text table. This requires Milvus ≥ 2.5.16; below 2.5.16 FastGPT fails to start with an explicit error — it never silently downgrades.

The full-text backend follows the actual vector store: Milvus → BM25; other vector stores (PG / OceanBase / SeekDB / openGauss) keep MongoDB $text. There is no separate full-text engine switch to configure.

Configuration and Migration

1. Backup

Back up before upgrading so you can roll back:

• Milvus data volume (the milvus data directory of the standalone instance, containing vectors)
• Milvus companion etcd / MinIO volumes
• MongoDB (dataset_datas, dataset_collections, datasets and other business data)

2. Stop Writes

Run during a low-write window, or stop FastGPT app writes first. If you must keep serving during migration, avoid writing dataset data concurrently (see step 5 "New data during migration").

3. Upgrade Milvus to 2.5.16+

Keep the existing Milvus data volume and the old modeldata collection during the upgrade. Replace the image tag and restart:

# Milvus service in docker-compose
image: milvusdb/milvus:v2.5.16

The old modeldata collection is the vector source for the migration. After upgrading, verify that the collection exists and is non-empty. If it is missing or empty, stop the migration and restore the Milvus data from backup.

4. Verify Version

Start FastGPT — Milvus initialization calls getVersion() to gate the version; below 2.5.16, or when the version cannot be fetched/parsed, startup terminates. You can also verify manually:

# Confirm the server version is >= v2.5.16 via milvus-cli / Attu / SDK getVersion

5. Migrate

After confirming that the old Milvus modeldata collection exists and contains vectors, call the migration API. This is a pure copy and does not regenerate embeddings.

# 1. Dry run to preview stats
curl 'http://host/api/admin/4162/milvus?dryRun=1' \
  -H 'rootkey: YOUR_ROOT_KEY'

# 2. Real migration
curl 'http://host/api/admin/4162/milvus?batchSize=500' \
  -H 'rootkey: YOUR_ROOT_KEY'

# 3. If the request is interrupted by a gateway timeout, resume with the returned migrationId
curl 'http://host/api/admin/4162/milvus?resumeMigrationId=<uuid>' \
  -H 'rootkey: YOUR_ROOT_KEY'

The migration iterates Milvus modeldata vector rows, looks up the original text from MongoDB dataset_datas.indexes, and writes the result to modeldata_v2. imageEmbedding indexes keep their vectors but use empty BM25 text. The migration supports resumable progress, persists failed rows for self-healing retries, verifies the actual modeldata_v2 row count on completion, and uses idempotent upsert, making retries safe.

6. Verify the Migration

• API returns status: done and targetCount >= processedCount.
• Smoke-test full-text / hybrid search in a dataset to confirm hits.

7. Actively Delete the Old modeldata Table

After migration, the old modeldata table is never auto-deleted. Once the admin confirms the migration is correct, delete it explicitly:

• Via the migration API (drop after validation + clear the MongoDB legacy full-text table):

  curl 'http://host/api/admin/4162/milvus?removeOld=1' \
    -H 'rootkey: YOUR_ROOT_KEY'

• Or drop modeldata manually via milvus-cli / SDK.

After deletion, FastGPT restart does not recreate or access the old table: normal init only creates/loads modeldata_v2; modeldata is detected/loaded only by the migration script.

8. Rollback

• If removeOld was not run (old table intact): downgrade the FastGPT image and restore backups; the legacy full-text data is still in MongoDB.
• If removeOld was run (old table dropped): restore the Milvus data volume from backup before downgrading.
• Migration is re-runnable (idempotent upsert); on failure, resume with resumeMigrationId.

FAQ

• Startup fails with Milvus version ... is not supported: Milvus is below 2.5.16; upgrade to 2.5.16+.
• Migration reports that the old modeldata collection is missing or empty: stop the migration and check whether FastGPT is connected to the correct Milvus instance and whether the data volume is mounted correctly. Restore from backup if the data is lost.
• Migration stays failed with targetCount < processedCount: the target table has fewer actual rows than written; check Milvus health (OOM / released collection) and resume with resumeMigrationId.
• Full-text search returns nothing after migration: confirm the migration finished with status: done; an empty modeldata_v2 means no full-text hits.