---
title: Relevance Tuning
description: Tune the BM25 score by adjusting the weights of individual queries
canonical: https://docs.paradedb.com/documentation/sorting/boost
---

## Boosting

ParadeDB offers several ways to tune a document's [BM25 score](/documentation/sorting/score).
The first is boosting, which increases or decreases the impact of a specific query by multiplying its contribution to the overall BM25 score.

To boost a query, cast the query to the `boost` type. In this example, the `shoes` query is weighted twice as heavily as the `footwear` query.

<CodeGroup>
```sql SQL
SELECT id, pdb.score(id), description, category
FROM mock_items
WHERE description ||| 'shoes'::pdb.boost(2) OR category ||| 'footwear'
ORDER BY score DESC
LIMIT 5;
```

```ts Drizzle
import { desc, or } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    id: mockItems.id,
    score: search.score(mockItems.id),
    description: mockItems.description,
    category: mockItems.category,
  })
  .from(mockItems)
  .where(
    or(
      search.matchAny(mockItems.description, search.boost("shoes", 2)),
      search.matchAny(mockItems.category, "footwear"),
    ),
  )
  .orderBy(desc(search.score(mockItems.id)))
  .limit(5);
```

```python Django
from django.db.models import Q
from paradedb import Boost, MatchAny, ParadeDB, Score

MockItem.objects.filter(
    Q(description=ParadeDB(MatchAny(Boost('shoes', 2)))) |
    Q(category=ParadeDB(MatchAny('footwear')))
).annotate(
    score=Score()
).values('id', 'score', 'description', 'category').order_by('-score')[:5]
```

```python SQLAlchemy
from sqlalchemy import desc, or_, select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import pdb, search

stmt = (
    select(
        MockItem.id,
        pdb.score(MockItem.id).label("score"),
        MockItem.description,
        MockItem.category,
    )
    .where(
        or_(
            search.match_any(MockItem.description, "shoes", boost=2.0),
            search.match_any(MockItem.category, "footwear"),
        )
    )
    .order_by(desc("score"))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .matching_any("shoes", boost: 2)
        .or(MockItem.search(:category).matching_any("footwear"))
        .with_score
        .select(:id, :description, :category)
        .order(search_score: :desc)
        .limit(5)
```

```cs EF Core
await dbContext
    .MockItems.Where(item =>
        EF.Functions.MatchAny(item.Description, Pdb.Boost("shoes", 2))
        || EF.Functions.MatchAny(item.Category, "footwear")
    )
    .Select(item => new
    {
        item.Id,
        Score = EF.Functions.Score(item.Id),
        item.Description,
        item.Category
    })
    .OrderByDescending(item => item.Score)
    .Take(5)
    .ToListAsync();
```

</CodeGroup>

`boost` takes a numeric value, which is the multiplicative boost factor. It can be any floating point number between `-2048` and `2048`.

[Query builder functions](/documentation/query-builder/overview) can also be boosted:

<CodeGroup>
```sql SQL
SELECT id, description, category, pdb.score(id)
FROM mock_items
WHERE description @@@ pdb.regex('key.*')::pdb.boost(2)
ORDER BY score DESC
LIMIT 5;
```

```ts Drizzle
import { desc } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    id: mockItems.id,
    description: mockItems.description,
    category: mockItems.category,
    score: search.score(mockItems.id),
  })
  .from(mockItems)
  .where(search.boost(search.regex(mockItems.description, "key.*"), 2))
  .orderBy(desc(search.score(mockItems.id)))
  .limit(5);
```

```python Django
from paradedb import Boost, ParadeDB, Regex, Score

MockItem.objects.filter(
    description=ParadeDB(Boost(Regex('key.*'), 2))
).annotate(
    score=Score()
).values('id', 'description', 'category', 'score').order_by('-score')[:5]
```

```python SQLAlchemy
from sqlalchemy import desc, select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import pdb, search

stmt = (
    select(
        MockItem.id,
        MockItem.description,
        MockItem.category,
        pdb.score(MockItem.id).label("score"),
    )
    .where(search.regex(MockItem.description, "key.*", boost=2.0))
    .order_by(desc("score"))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .regex("key.*", boost: 2)
        .with_score
        .select(:id, :description, :category)
        .order(search_score: :desc)
        .limit(5)
```

```cs EF Core
await dbContext
    .MockItems.Where(item =>
        Pdb.Boost(EF.Functions.Regex(item.Description, "key.*"), 2)
    )
    .Select(item => new
    {
        item.Id,
        item.Description,
        item.Category,
        Score = EF.Functions.Score(item.Id)
    })
    .OrderByDescending(item => item.Score)
    .Take(5)
    .ToListAsync();
```

</CodeGroup>

Boost can be used in conjunction with other type casts, like [fuzzy](/documentation/full-text/fuzzy):

<CodeGroup>
```sql SQL
SELECT id, description, category, pdb.score(id)
FROM mock_items
WHERE description ||| 'shose'::pdb.fuzzy(2)::pdb.boost(2)
ORDER BY score DESC
LIMIT 5;
```

```ts Drizzle
import { desc } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    id: mockItems.id,
    description: mockItems.description,
    category: mockItems.category,
    score: search.score(mockItems.id),
  })
  .from(mockItems)
  .where(
    search.matchAny(
      mockItems.description,
      search.boost(search.fuzzy("shose", 2), 2),
    ),
  )
  .orderBy(desc(search.score(mockItems.id)))
  .limit(5);
```

```python Django
from paradedb import Boost, Fuzzy, MatchAny, ParadeDB, Score

MockItem.objects.filter(
    description=ParadeDB(MatchAny(Boost(Fuzzy('shose', 2), 2)))
).annotate(
    score=Score()
).values('id', 'description', 'category', 'score').order_by('-score')[:5]
```

```python SQLAlchemy
from sqlalchemy import desc, select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import pdb, search

stmt = (
    select(
        MockItem.id,
        MockItem.description,
        MockItem.category,
        pdb.score(MockItem.id).label("score"),
    )
    .where(search.match_any(MockItem.description, "shose", distance=2, boost=2.0))
    .order_by(desc("score"))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .matching_any("shose", distance: 2, boost: 2)
        .with_score
        .select(:id, :description, :category)
        .order(search_score: :desc)
        .limit(5)
```

```cs EF Core
await dbContext
    .MockItems.Where(item =>
        EF.Functions.MatchAny(item.Description, Pdb.Boost(Pdb.Fuzzy("shose", 2), 2))
    )
    .Select(item => new
    {
        item.Id,
        item.Description,
        item.Category,
        Score = EF.Functions.Score(item.Id)
    })
    .OrderByDescending(item => item.Score)
    .Take(5)
    .ToListAsync();
```

</CodeGroup>

## Constant Scoring

Constant scoring assigns the same score to all documents that match a query. To apply a constant score, cast the query to the `const` type with a
numeric value.

For instance, the following query assigns a score of `1` to all documents matching the query `shoes`.

<CodeGroup>
```sql SQL
SELECT id, pdb.score(id), description, category
FROM mock_items
WHERE description ||| 'shoes'::pdb.const(1)
ORDER BY score DESC
LIMIT 5;
```

```ts Drizzle
import { desc } from "drizzle-orm";
import { search } from "@paradedb/drizzle-paradedb";

await db
  .select({
    id: mockItems.id,
    score: search.score(mockItems.id),
    description: mockItems.description,
    category: mockItems.category,
  })
  .from(mockItems)
  .where(search.matchAny(mockItems.description, search.constant("shoes", 1)))
  .orderBy(desc(search.score(mockItems.id)))
  .limit(5);
```

```python Django
from paradedb import Const, MatchAny, ParadeDB, Score

MockItem.objects.filter(
    description=ParadeDB(MatchAny(Const('shoes', 1)))
).annotate(
    score=Score()
).values('id', 'score', 'description', 'category').order_by('-score')[:5]
```

```python SQLAlchemy
from sqlalchemy import desc, select
from sqlalchemy.orm import Session
from paradedb.sqlalchemy import pdb, search

stmt = (
    select(
        MockItem.id,
        pdb.score(MockItem.id).label("score"),
        MockItem.description,
        MockItem.category,
    )
    .where(search.match_any(MockItem.description, "shoes", const=1.0))
    .order_by(desc("score"))
    .limit(5)
)

with Session(engine) as session:
    session.execute(stmt).all()
```

```ruby Rails
MockItem.search(:description)
        .matching_any("shoes", constant_score: 1)
        .with_score
        .select(:id, :description, :category)
        .order(search_score: :desc)
        .limit(5)
```

```cs EF Core
await dbContext
    .MockItems.Where(item => EF.Functions.MatchAny(item.Description, Pdb.Const("shoes", 1)))
    .Select(item => new
    {
        item.Id,
        Score = EF.Functions.Score(item.Id),
        item.Description,
        item.Category
    })
    .OrderByDescending(item => item.Score)
    .Take(5)
    .ToListAsync();
```

</CodeGroup>
