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:mlMachine learningMachine learningbug"" muted="" aria-describedby="MDU6TGFiZWwyMzE3Mw==-tooltip :R1aqdb:">>bugFeature:GenAIFeatures around GenAIFeatures around GenAITeam:MLMeta label for the ML teamMeta label for the ML team
Description
Elasticsearch Version
Serverless
Installed Plugins
No response
Java Version
bundled
OS Version
Serverless
Problem Description
Ingesting semantic_text content using Amazon Titan is returning inference failures.
Digging into what might be causing this error, it's potentially a combination of this line (from 5 months ago) - with a hardcoded InputType.INGEST for chunked inference - combined with the logic here added last month.
Steps to Reproduce
Perform the following requests, using Amazon Bedrock credentials with support for amazon.titan-embed-text-v2:0:
PUT /_inference/text_embedding/my-bedrock-embeddings { "service": "amazonbedrock", "service_settings": { "access_key": "...", "secret_key": "...", "provider": "amazontitan", "model": "amazon.titan-embed-text-v2:0", "region": "us-east-1" } } PUT my-test-index { "mappings": { "properties": { "semantic_field": { "type": "semantic_text", "inference_id": "my-bedrock-embeddings" } } } } PUT my-test-index/_doc/1 { "semantic_field": "The Jedi Master Yoda said, do or do not, there is no try" } The ingest request will return the following inference error:
{ "error": { "root_cause": [ { "type": "validation_exception", "reason": "Validation Failed: 1: Invalid value [ingest] received. [input_type] is not allowed for provider [amazontitan];" } ], "type": "validation_exception", "reason": "Validation Failed: 1: Invalid value [ingest] received. [input_type] is not allowed for provider [amazontitan];" }, "status": 400 } The following script has been verified to work on 8.17.4 but is failing in serverless.
Logs (if relevant)
No response
sunder-ch
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:mlMachine learningMachine learningbug"" muted="" aria-describedby="MDU6TGFiZWwyMzE3Mw==-tooltip :R2hehb:">>bugFeature:GenAIFeatures around GenAIFeatures around GenAITeam:MLMeta label for the ML teamMeta label for the ML team