chunksRetrievalV1ChunksPost method
Chunks Retrieval
Given a text, returns the most relevant chunks from the ingested documents. The returned information can be used to generate prompts that can be passed to /completions or /chat/completions APIs. Note: it is usually a very fast API, because only the Embeddings model is involved, not the LLM. The returned information contains the relevant chunk text together with the source document it is coming from. It also contains a score that can be used to compare different results. The max number of chunks to be returned is set using the limit param. Previous and next chunks (pieces of text that appear right before or after in the document) can be fetched by using the prev_next_chunks field. The documents being used can be filtered using the context_filter and passing the document IDs to be used. Ingested documents IDs can be found using /ingest/list endpoint. If you want all ingested documents to be used, remove context_filter altogether.
Parameters:
- ChunksBody chunksBody (required):
Implementation
Future<ChunksResponse?> chunksRetrievalV1ChunksPost(ChunksBody chunksBody,) async {
final response = await chunksRetrievalV1ChunksPostWithHttpInfo(chunksBody,);
if (response.statusCode >= HttpStatus.badRequest) {
throw ApiException(response.statusCode, await _decodeBodyBytes(response));
}
// When a remote server returns no body with a status of 204, we shall not decode it.
// At the time of writing this, `dart:convert` will throw an "Unexpected end of input"
// FormatException when trying to decode an empty string.
if (response.body.isNotEmpty && response.statusCode != HttpStatus.noContent) {
return await apiClient.deserializeAsync(await _decodeBodyBytes(response), 'ChunksResponse',) as ChunksResponse;
}
return null;
}