Chaithanya Kumar
30469aec17
Co-authored-by: kartik-mem0 <kartik.labhshetwar@mem0.ai> Co-authored-by: Saket Aryan <saketaryan2002@gmail.com>
80 lines
2.5 KiB
Plaintext
80 lines
2.5 KiB
Plaintext
---
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title: "Turbopuffer"
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description: "Use Turbopuffer as a serverless vector database in Mem0 for low-latency search at scale with native metadata filtering."
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---
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[Turbopuffer](https://turbopuffer.com) is a serverless vector database optimized for low-latency search at scale. It offers cost-effective vector storage with native metadata filtering.
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### Usage
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```python
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import os
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from mem0 import Memory
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os.environ["OPENAI_API_KEY"] = "sk-xx"
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os.environ["TURBOPUFFER_API_KEY"] = "tpuf_xxxxxxxxxxxx"
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config = {
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"vector_store": {
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"provider": "turbopuffer",
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"config": {
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"collection_name": "movie_preferences",
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"embedding_model_dims": 1536,
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"region": "gcp-us-central1",
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}
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}
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}
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m = Memory.from_config(config)
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messages = [
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{"role": "user", "content": "I'm planning to watch a movie tonight. Any recommendations?"},
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{"role": "assistant", "content": "How about thriller movies? They can be quite engaging."},
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{"role": "user", "content": "I'm not a big fan of thrillers but I love sci-fi."},
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{"role": "assistant", "content": "Got it! I'll suggest sci-fi movies instead."}
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]
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m.add(messages, user_id="alice", metadata={"category": "movies"})
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# Search memories
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results = m.search(query="sci-fi recommendations", filters={"user_id": "alice"})
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```
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### Config
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Here are the parameters available for configuring Turbopuffer:
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| Parameter | Description | Default Value |
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| --- | --- | --- |
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| `collection_name` | Name of the namespace/collection | `mem0` |
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| `embedding_model_dims` | Dimensions of the embedding model (must match your chosen embedding model) | `1536` |
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| `api_key` | Turbopuffer API key | Environment variable: `TURBOPUFFER_API_KEY` |
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| `region` | Turbopuffer region | `gcp-us-central1` |
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| `distance_metric` | Distance metric for vector similarity (`cosine_distance` or `euclidean_squared`) | `cosine_distance` |
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| `batch_size` | Batch size for bulk operations | `100` |
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| `extra_params` | Additional parameters for the Turbopuffer client | `None` |
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### Regions
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| Region | Location |
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| --- | --- |
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| `gcp-us-central1` | Iowa, USA (Default) |
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| `aws-us-west-2` | Oregon, USA |
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### Config Example
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```python
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config = {
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"vector_store": {
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"provider": "turbopuffer",
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"config": {
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"collection_name": "my_memories",
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"embedding_model_dims": 1536,
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"api_key": "tpuf_xxxxxxxxxxxx",
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"region": "aws-us-west-2",
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"distance_metric": "cosine_distance",
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"batch_size": 200,
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}
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}
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}
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```
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