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add openai embedding model blueprint (#1583)
Signed-off-by: Yaliang Wu <[email protected]>
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docs/remote_inference_blueprints/openai_connector_embedding_blueprint.md
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| # OpenAI connector blueprint example for embedding model | ||
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| ## 1. Create connector for OpenAI embedding model: | ||
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| Refer to OpenAI [official doc](https://platform.openai.com/docs/guides/embeddings). | ||
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| If you are using self-managed Opensearch, you should supply OpenAI API key: | ||
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| ```json | ||
| POST /_plugins/_ml/connectors/_create | ||
| { | ||
| "name": "<YOUR CONNECTOR NAME>", | ||
| "description": "<YOUR CONNECTOR DESCRIPTION>", | ||
| "version": "<YOUR CONNECTOR VERSION>", | ||
| "protocol": "http", | ||
| "parameters": { | ||
| "model": "text-embedding-ada-002" | ||
| }, | ||
| "credential": { | ||
| "openAI_key": "<PLEASE ADD YOUR OPENAI API KEY HERE>" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "predict", | ||
| "method": "POST", | ||
| "url": "https://api.openai.com/v1/embeddings", | ||
| "headers": { | ||
| "Authorization": "Bearer ${credential.openAI_key}" | ||
| }, | ||
| "request_body": "{ \"input\": ${parameters.input}, \"model\": \"${parameters.model}\" }", | ||
| "pre_process_function": "connector.pre_process.openai.embedding", | ||
| "post_process_function": "connector.post_process.openai.embedding" | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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| If using the AWS Opensearch Service, you can provide Secret ARN and IAM role arn that allows access to the Secret ARN. | ||
| Refer to this [AWS doc](https://docs.aws.amazon.com/opensearch-service/latest/developerguide/ml-external-connector.html) | ||
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| ```json | ||
| POST /_plugins/_ml/connectors/_create | ||
| { | ||
| "name": "<YOUR CONNECTOR NAME>", | ||
| "description": "<YOUR CONNECTOR DESCRIPTION>", | ||
| "version": "<YOUR CONNECTOR VERSION>", | ||
| "protocol": "http", | ||
| "parameters": { | ||
| "model": "text-embedding-ada-002" | ||
| }, | ||
| "credential": { | ||
| "secretArn": "<YOUR SECRET ARN>", | ||
| "roleArn": "<YOUR IAM ROLE ARN>" | ||
| }, | ||
| "actions": [ | ||
| { | ||
| "action_type": "predict", | ||
| "method": "POST", | ||
| "url": "https://api.openai.com/v1/embeddings", | ||
| "headers": { | ||
| "Authorization": "Bearer ${credential.secretArn.<YOUR OPENAI SECRET KEY IN SECRET MANAGER>}" | ||
| }, | ||
| "request_body": "{ \"input\": ${parameters.input}, \"model\": \"${parameters.model}\" }", | ||
| "pre_process_function": "connector.pre_process.openai.embedding", | ||
| "post_process_function": "connector.post_process.openai.embedding" | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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| Sample response: | ||
| ```json | ||
| { | ||
| "connector_id": "OyB0josB2yd36FqHy3lO" | ||
| } | ||
| ``` | ||
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| ## 2. Create model group: | ||
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| ```json | ||
| POST /_plugins/_ml/model_groups/_register | ||
| { | ||
| "name": "remote_model_group", | ||
| "description": "This is an example description" | ||
| } | ||
| ``` | ||
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| Sample response: | ||
| ```json | ||
| { | ||
| "model_group_id": "TWR0josByE8GuSOJ629m", | ||
| "status": "CREATED" | ||
| } | ||
| ``` | ||
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| ## 3. Register model to model group & deploy model: | ||
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| ```json | ||
| POST /_plugins/_ml/models/_register | ||
| { | ||
| "name": "OpenAI embedding model", | ||
| "function_name": "remote", | ||
| "model_group_id": "TWR0josByE8GuSOJ629m", | ||
| "description": "test model", | ||
| "connector_id": "OyB0josB2yd36FqHy3lO" | ||
| } | ||
| ``` | ||
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| Sample response: | ||
| ```json | ||
| { | ||
| "task_id": "PCB1josB2yd36FqHAXk9", | ||
| "status": "CREATED" | ||
| } | ||
| ``` | ||
| Get model id from task | ||
| ```json | ||
| GET /_plugins/_ml/tasks/PCB1josB2yd36FqHAXk9 | ||
| ``` | ||
| Deploy model, in this demo the model id is `PSB1josB2yd36FqHAnl1` | ||
| ```json | ||
| POST /_plugins/_ml/models/PSB1josB2yd36FqHAnl1/_deploy | ||
| ``` | ||
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| ## 4. Test model inference | ||
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| ```json | ||
| POST /_plugins/_ml/models/PSB1josB2yd36FqHAnl1/_predict | ||
| { | ||
| "parameters": { | ||
| "input": [ "What is the meaning of life?" ] | ||
| } | ||
| } | ||
| ``` | ||
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| Response: | ||
| ```json | ||
| { | ||
| "inference_results": [ | ||
| { | ||
| "output": [ | ||
| { | ||
| "name": "sentence_embedding", | ||
| "data_type": "FLOAT32", | ||
| "shape": [ | ||
| 1536 | ||
| ], | ||
| "data": [ | ||
| -0.0043460787, | ||
| -0.029653417, | ||
| -0.008173223, | ||
| ... | ||
| ] | ||
| } | ||
| ], | ||
| "status_code": 200 | ||
| } | ||
| ] | ||
| } | ||
| ``` | ||
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