---
title: V4.5 (Complex Update Required)
description: FastGPT V4.5 Update
---

FastGPT V4.5 introduces PgVector 0.5's HNSW index, which dramatically improves knowledge base search performance — roughly 3x to 10x faster than the `IVFFlat` index, easily achieving millisecond-level searches across millions of records. The downside is that index building is very slow: on a 4C16G machine with 5 million records, a `parallel build` took about 48 hours. For detailed parameter configuration, refer to the [PgVector official documentation](https://github.com/pgvector/pgvector).

The following database operations are required for the upgrade:

## PgVector Upgrade: Sealos Deployment

1. Open the Database app from the [Sealos Desktop](https://cloud.sealos.io?uid=fnWRt09fZP).
2. Click on the details of the **pg** database.
3. Click Restart in the upper-right corner and wait for it to complete.
4. Click "One-Click Connect" on the left sidebar and wait for the Terminal to open.
5. Run the following SQL commands in order:

```sql
-- Upgrade the extension
ALTER EXTENSION vector UPDATE;
-- Verify the upgrade was successful — the vector extension version should be 0.5.0 (previously 0.4.1)
\dx

-- The following two statements set the memory available to PG during index building. Adjust based on your database specs — a good rule of thumb is 1/4 of total memory.
alter system set maintenance_work_mem = '2400MB';
select pg_reload_conf();

-- Rebuild database indexes and collation
REINDEX DATABASE postgres;

-- Start building the index. This takes a very long time — just close the Terminal by clicking the X in the upper-right corner.
CREATE INDEX CONCURRENTLY vector_index ON modeldata USING hnsw (vector vector_ip_ops) WITH (m = 16, ef_construction = 64);
-- You can reconnect to the Terminal and run the command below. If you see "vector_index" hnsw (vector vector_ip_ops) WITH (m='16', ef_construction='64'), the build is complete (make sure there is no INVALID at the end).
\d modeldata
```

|                      |                      |
| -------------------- | -------------------- |
| ![](/imgs/v45-1.jpg) | ![](/imgs/v45-2.jpg) |
| ![](/imgs/v45-3.jpg) | ![](/imgs/v45-4.jpg) |

## PgVector Upgrade: Docker Compose Deployment

The commands below are based on the provided docker-compose template. If you've changed the database username or password, adjust accordingly.

1. Update the PG image version in `docker-compose.yml` to `ankane/pgvector:v0.5.0` or `registry.cn-hangzhou.aliyuncs.com/fastgpt/pgvector:v0.5.0`.
2. Restart the PG container (`docker-compose pull && docker-compose up -d`) and wait for it to complete.
3. Enter the container: `docker exec -it pg bash`
4. Connect to the database: `psql 'postgresql://username:password@localhost:5432/postgres'`
5. Run the following SQL commands:

```sql
-- Upgrade the extension
ALTER EXTENSION vector UPDATE;
-- Verify the upgrade was successful — the vector extension version should be 0.5.0 (previously 0.4.2)
\dx

-- The following two statements set the memory available to PG during index building. Adjust based on your database specs — a good rule of thumb is 1/4 of total memory.
alter system set maintenance_work_mem = '2400MB';
select pg_reload_conf();

-- Rebuild database indexes and collation
REINDEX DATABASE postgres;
ALTER DATABASE postgres REFRESH COLLATION VERSION;

-- Start building the index. This takes a very long time — just close the terminal window. Do NOT use ctrl+c to cancel.
CREATE INDEX CONCURRENTLY vector_index ON modeldata USING hnsw (vector vector_ip_ops) WITH (m = 16, ef_construction = 64);
-- You can reconnect to the database and run the command below. If you see "vector_index" hnsw (vector vector_ip_ops) WITH (m='16', ef_construction='64'), the build is complete (make sure there is no INVALID at the end).
\d modeldata


```

## New Features

### Fast GPT V4.5

1. New - Upgraded PgVector extension with HNSW index, dramatically improving knowledge base search speed.
2. New - AI Chat node now includes a "Return AI Content" option, allowing you to prevent AI responses from being sent directly to the browser.
3. New - Support for selecting models in the Question Classifier.
4. Improved - TextSplitter now uses a recursive splitting approach.
5. Improved - Advanced orchestration UX performance.
6. Fixed - Share link authentication issue.

## Configuration File Changes Required

For the latest configuration, refer to: [V4.5 Latest config.json](/docs/self-host/config/json)