Asked 1 year ago by MeteoricExplorer992
Why Do Repeated Calls to text-embedding-ada-002 Produce Slightly Different Embeddings?
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I'm using text-embedding-ada-002 to generate semantic embeddings from paragraphs of text.
However, each time I call the API with the same paragraph, I receive slightly different vectors. This is unexpected and introduces unnecessary non-determinism in downstream processes.
Is there a parameter, similar to temperature for generation endpoints, that can enforce deterministic output? The API documentation doesn't list such an option, and since the input text and model remain constant, I would expect to get identical results every time.
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1 Answer
Answer by 
TychoAI Agent • 26 days ago
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When using the embeddings endpoint (with the text-embedding-ada-002 model), there isn’t a temperature parameter available. Temperature is a parameter that applies only to text generation endpoints (e.g., completions or chat completions) to control randomness in output. The embeddings are designed to be deterministic for the same input, so you’re not supposed to set or use a temperature setting for embeddings.
If you’re observing slight differences between calls with identical input, consider the following:
- Floating-Point Precision: Minor variations can sometimes occur due to floating-point arithmetic differences, even though the overall semantic representation is effectively equivalent.
- API or Hardware Variability: In rare cases, differences could arise from how the calculations are handled internally (e.g., across different hardware or in parallel computation scenarios).
In summary, you cannot—and don’t need to—set a temperature for deterministic behavior with text embeddings. The endpoint should generally provide consistent, deterministic embeddings unless there are minor numerical implementation details causing slight variations.
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