AI_AskLLM Examples | Teradata Vantage - Examples: How to Use AI_AskLLM - Teradata Analytics

SELECT * FROM AI_AskLLM( 
      ON conversation_data AS InputTable partition by id
      USING   
      TextColumn('text_data')
      ApiType('azure')
      ApiBase('<API_BASE>')
      ApiVersion('<API_VERSION>')
      ApiKey('<API_KEY>')
      DeploymentId('<DEPLOYMENT_ID>')
      ModelName('gpt-3.5-turbo')
      ContextColumn('text_data')
      Prompt('Your task is to analyze the following transcript and determine 1) if the customer was happy or not.  Respond with a H:Y if happy, H:N if not and do not comment further. #DATA#')
	  DATAPOSITION('#DATA#')
      isDebug('true')
      Accumulate('[0:]')
      ShowNumTokens('true')  
      RefreshCredentialTimeSeconds('1800')  
    ) as dt;

Output

API Key can be empty as it will be generated from Azure VMs. It will be refreshed every RefreshCredentialTimeSeconds.

SELECT * FROM AI_AskLLM( 
      ON question AS InputTable partition by id
      ON context_data AS ContextTable partition by id
      USING   
      TextColumn('text_data')
      ApiType('azure')
      ApiBase('<api base>')
      ApiVersion('<api version>')
      ApiKey('')
      DeploymentId('<engine id>')
      ModelName('gpt-3.5-turbo')
      ContextColumn('text_data')
      Prompt('Provide an answer to the question using data as information relevant to the question. \nQuestion: #QUESTION# \n Data: #DATA#')
      DATAPOSITION('#DATA#')
      QUESTIONPOSITION('#QUESTION#')
      isDebug('true')
      Accumulate('[0:]')
      ShowNumTokens('true')  
      RefreshCredentialTimeSeconds('1800')  
    ) as dt;

Output

SELECT * FROM AI_AskLLM(
      ON question AS InputTable partition by id
      ON context_data AS ContextTable partition by id
      USING
      TextColumn('text_data')
      ApiType('litellm')
      ApiBase('{litellm_api_base}')
      ApiKey('{litellm_api_key}')
      ModelName('anthropic.claude-3-7-sonnet-20250219-v1:0')
      ContextColumn('text_data')
      Prompt('Provide an answer to the question using data as information relevant to the question. 
Question: #QUESTION# 
 Data: #DATA#')
      DATAPOSITION('#DATA#')
      QUESTIONPOSITION('#QUESTION#')
      isDebug('true')
      Accumulate('[0:]')
 ) as dt;

Output

Input

create authorization td_gen_litellm_auth 
                user '{litellm_api_base}' 
                password '{litellm_api_key}';

Query

SELECT * FROM AI_AskLLM(
      ON question AS InputTable partition by id
      ON context_data AS ContextTable partition by id
      USING
      TextColumn('text_data')
      ApiType('litellm')
      Authorization(td_gen_litellm_auth)
      ModelName('anthropic.claude-3-7-sonnet-20250219-v1:0')
      ContextColumn('text_data')
      Prompt('Provide an answer to the question using data as information relevant to the question. 
Question: #QUESTION# 
 Data: #DATA#')
      DATAPOSITION('#DATA#')
      QUESTIONPOSITION('#QUESTION#')
      isDebug('true')
      Accumulate('[0:]')
      ShowNumTokens('true')
 ) as dt;

Output

SELECT * FROM AI_AskLLM(
      ON question AS InputTable partition by id
      ON context_data AS ContextTable partition by id
      USING
      TextColumn('text_data')
      ApiType('litellm')
      ApiBase('{litellm_api_base}')
      ApiKey('{litellm_api_key}')
      ModelName('anthropic.claude-3-7-sonnet-20250219-v1:0')
      ContextColumn('text_data')
      Prompt('Provide an answer to the question using data as information relevant to the question. 
Question: #QUESTION# 
 Data: #DATA#')
      DATAPOSITION('#DATA#')
      QUESTIONPOSITION('#QUESTION#')
      isDebug('true')
      Accumulate('[0:]')
      ShowNumTokens('true')
 ) as dt;

Output

SELECT * FROM AI_AskLLM( 
      ON question AS InputTable partition by id
      ON context_data AS ContextTable partition by id
      USING   
      TextColumn('text_data')
      ApiType('nim')
      ApiBase('{nim_full_url_token}')
      ApiKey('{password}')
      ModelName('meta/llama-3.1-8b-instruct')
      ContextColumn('text_data')
      Prompt('Provide an answer to the question using data as information relevant to the question. \nQuestion: #QUESTION# \n Data: #DATA#')
      DATAPOSITION('#DATA#')
      QUESTIONPOSITION('#QUESTION#')
      isDebug('true')
      Accumulate('[0:]')
      ShowNumTokens('t')      
    ) as dt;

Output