> ## Documentation Index
> Fetch the complete documentation index at: https://upstash-vector.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Upsert

## Methods

The `upsert` method enables you to insert or update vectors in the index.
You can perform upsert operations in three ways: using a vector object, a tuple, or a dictionary.

### Upsert Via Vector Object

```python
from upstash_vector import Index, Vector
import random

index = Index.from_env()

dimension = 128  # Adjust based on your index's dimension
upsert_amount = 100

vectors = [
    Vector(
        id=f"generated-id-{i}",
        vector=[random.random() for _ in range(dimension)],
        metadata={"some_field": f"some_value-{i}"}
    ) for i in range(upsert_amount)
]

index.upsert(vectors=vectors)
```

### Upsert Via Tuple

```python
from upstash_vector import Index
import random

index = Index.from_env()

dimension = 128  # Adjust based on your index's dimension
upsert_amount = 100

vectors = [
    (f"generated-id-{i}", [random.random() for _ in range(dimension)], {"some_field": f"some_value-{i}"})
    for i in range(upsert_amount)
]

index.upsert(vectors=vectors)
```

### Upsert Via Dictionary

```python
from upstash_vector import Index
import random

index = Index.from_env()

dimension = 128  # Adjust based on your index's dimension
upsert_amount = 100

vectors = [
    {"id": f"generated-id-{i}", "vector": [random.random() for _ in range(dimension)], "metadata": {"some_field": f"some_value-{i}"}}
    for i in range(upsert_amount)
]

index.upsert(vectors=vectors)

```