事前準備
請確認您已向模型端點管理服務註冊模型端點。 詳情請參閱「在 AlloyDB Omni 中註冊及呼叫遠端 AI 模型」。
叫用一般模型的預測功能
使用 google_ml.predict_row()
SQL 函式呼叫已註冊的通用模型端點,以叫用預測。
SELECT
google_ml.predict_row(
model_id => 'MODEL_ID',
request_body => 'REQUEST_BODY');
更改下列內容:
MODEL_ID
:註冊模型端點時定義的模型 ID。REQUEST_BODY
:預測函式的參數,採用 JSON 格式。
範例
本節提供一些範例,說明如何使用已註冊的模型端點叫用預測。
如要為已註冊的 gemini-1.5-pro:streamGenerateContent
模型端點產生預測結果,請執行下列陳述式:
SELECT
json_array_elements( google_ml.predict_row( model_id => 'gemini-1.5-pro:streamGenerateContent',
request_body => '{ "contents": [ { "role": "user", "parts": [ { "text": "For TPCH database schema as mentioned here https://www.tpc.org/TPC_Documents_Current_Versions/pdf/TPC-H_v3.0.1.pdf , generate a SQL query to find all supplier names which are located in the India nation." } ] } ] }'))-> 'candidates' -> 0 -> 'content' -> 'parts' -> 0 -> 'text';
如要為 Hugging Face 上已註冊的 facebook/bart-large-mnli
模型端點產生預測結果,請執行下列陳述式:
SELECT
google_ml.predict_row(
model_id => 'facebook/bart-large-mnli',
request_body =>
'{
"inputs": "Hi, I recently bought a device from your company but it is not working as advertised and I would like to get reimbursed!",
"parameters": {"candidate_labels": ["refund", "legal", "faq"]}
}'
);
如要為已註冊的 Anthropic claude-3-opus-20240229
模型端點產生預測結果,請執行下列陳述式:
SELECT
google_ml.predict_row('anthropic-opus', '{
"model": "claude-3-opus-20240229",
"max_tokens": 1024,
"messages": [
{"role": "user", "content": "Hello, world"}
]
}');