> ## Documentation Index
> Fetch the complete documentation index at: https://docs.mixpeek.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.
# Passthrough Extractor
> Copy source fields without processing for metadata propagation and vector passthrough
Runnable reference for this extractor — inputs, parameters, output fields, embedding models, and copy-paste examples. Auto-generated from the live registry.
The passthrough extractor copies source fields without any ML processing. By default, all source fields are included. Use `field_passthrough` to specify specific fields or `include_all_source_fields` to control behavior. Supports vector passthrough from collection to collection.
View extractor details at [api.mixpeek.com/v1/collections/features/extractors/passthrough\_extractor\_v1](https://api.mixpeek.com/v1/collections/features/extractors/passthrough_extractor_v1) or fetch programmatically with `GET /v1/collections/features/extractors/{feature_extractor_id}`.
## When to Use
| Use Case | Description |
| -------------------------------------- | --------------------------------------------------------------------------------------- |
| **Metadata propagation** | Pass metadata fields from bucket objects to collection documents without transformation |
| **Vector passthrough** | Copy pre-computed embeddings from one collection to another |
| **Schema normalization** | Select specific fields to include in the output schema |
| **Collection-to-collection pipelines** | Route data through multi-tier processing without re-embedding |
## When NOT to Use
* When you need to generate embeddings → Use [text\_extractor](/processing/extractors/text) or [multimodal\_extractor](/processing/extractors/multimodal)
* When you need to transform or enrich data → Use extractors with ML models
* When you need to decompose content (chunking, video splitting) → Use appropriate extractors
## Input Schema
The passthrough extractor accepts **any input type** and copies fields as-is.
```json theme={null}
{
"type": "object",
"properties": {},
"description": "Accepts any fields - no required inputs"
}
```
## Output Schema
The output mirrors the input based on configuration:
| Configuration | Behavior |
| ------------------------------------------- | ---------------------------------- |
| Default (`include_all_source_fields: true`) | All source fields copied to output |
| `field_passthrough` specified | Only listed fields copied |
| `include_all_source_fields: false` | Must specify `field_passthrough` |
## Parameters
The passthrough extractor has **no required parameters**. Configuration is handled through `field_passthrough` and `input_mappings` at the collection level.
## Configuration Examples
```json Copy All Fields theme={null}
{
"feature_extractor": {
"feature_extractor_name": "passthrough_extractor",
"version": "v1",
"input_mappings": {},
"field_passthrough": [],
"parameters": {}
}
}
```
```json Select Specific Fields theme={null}
{
"feature_extractor": {
"feature_extractor_name": "passthrough_extractor",
"version": "v1",
"input_mappings": {},
"field_passthrough": [
{ "source_path": "metadata.category" },
{ "source_path": "metadata.brand" },
{ "source_path": "metadata.price" }
],
"parameters": {}
}
}
```
```json Vector Passthrough theme={null}
{
"feature_extractor": {
"feature_extractor_name": "passthrough_extractor",
"version": "v1",
"input_mappings": {},
"field_passthrough": [
{ "source_path": "text_extractor_v1_embedding" },
{ "source_path": "metadata.product_id" }
],
"parameters": {}
}
}
```
```json Rename Fields During Passthrough theme={null}
{
"feature_extractor": {
"feature_extractor_name": "passthrough_extractor",
"version": "v1",
"input_mappings": {},
"field_passthrough": [
{ "source_path": "metadata.old_name", "target_path": "new_name" },
{ "source_path": "payload.description", "target_path": "content" }
],
"parameters": {}
}
}
```
## Performance & Costs
| Metric | Value |
| ------------------ | ---------------------------- |
| **Latency** | \< 1ms |
| **Cost** | Free |
| **GPU Required** | No |
| **Max Throughput** | Unlimited (no ML processing) |
## Vector Indexes
The passthrough extractor creates **no vector indexes**. If you pass through existing embeddings, they retain their original index configuration from the source collection.
## Best Practices
1. **Use for multi-tier pipelines** – When downstream collections need upstream data without reprocessing
2. **Minimize field selection** – Only pass through fields you need to reduce storage and query overhead
3. **Preserve lineage** – The passthrough extractor maintains `root_object_id` and `source_collection_id` for data lineage tracking
4. **Combine with other extractors** – Use passthrough fields alongside ML extractors in the same collection to include metadata with generated features
## Related
* [Feature Extractors Overview](/processing/feature-extractors)
* [Text Extractor](/processing/extractors/text)
* [Multimodal Extractor](/processing/extractors/multimodal)