AI agent capability extract
The AI Agent to be used for extraction.
ai_agent_extractThe type of AI agent to be used for extraction.
Value is always ai_agent_extract
enabledThe state of the AI Agent capability. Possible values are: enabled and disabled.
AI agent processor used to handle basic text.
falseTrue if system message contains custom instructions placeholder, false otherwise
The parameters for the LLM endpoint specific to OpenAI / Google models.
azure__openai__gpt_4o_miniThe model used for the AI agent for basic text. For specific model values, see the available models list.
84001The number of tokens for completion.
(\{user_question\}[\s\S]*?\{content\}|\{content\}[\s\S]*?\{user_question\})It is `{current_date}`, consider these travel options `{content}` and answer the `{user_question}`.10000The prompt template contains contextual information of the request and the user prompt.
When passing prompt_template parameters, you must include inputs for {user_question} and {content}.
{current_date} is optional, depending on the use.
You are a helpful travel assistant specialized in budget travelSystem messages try to help the LLM "understand" its role and what it is supposed to do.
This is a custom instructionCustom instructions for the agent.
This is ASK AgentThe description of the AI Agent.
AI agent processor used to to handle longer text.
azure__openai__text_embedding_ada_002The model used for the AI agent for calculating embeddings.
basicThe strategy used for the AI agent for calculating embeddings.
641512The number of tokens per chunk.
falseTrue if system message contains custom instructions placeholder, false otherwise
The parameters for the LLM endpoint specific to OpenAI / Google models.
azure__openai__gpt_4o_miniThe model used for the AI agent for basic text. For specific model values, see the available models list.
84001The number of tokens for completion.
(\{user_question\}[\s\S]*?\{content\}|\{content\}[\s\S]*?\{user_question\})It is `{current_date}`, consider these travel options `{content}` and answer the `{user_question}`.10000The prompt template contains contextual information of the request and the user prompt.
When passing prompt_template parameters, you must include inputs for {user_question} and {content}.
{current_date} is optional, depending on the use.
You are a helpful travel assistant specialized in budget travelSystem messages try to help the LLM "understand" its role and what it is supposed to do.
Response Example
{
"type": "ai_agent_extract",
"access_state": "enabled",
"basic_text": {
"is_custom_instructions_included": false,
"llm_endpoint_params": {
"type": "openai_params",
"frequency_penalty": 1.5,
"presence_penalty": 1.5,
"stop": "<|im_end|>",
"temperature": 0,
"top_p": 1
},
"model": "azure__openai__gpt_4o_mini",
"num_tokens_for_completion": 8400,
"prompt_template": "It is `{current_date}`, consider these travel options `{content}` and answer the `{user_question}`.",
"system_message": "You are a helpful travel assistant specialized in budget travel"
},
"custom_instructions": "This is a custom instruction",
"description": "This is ASK Agent",
"long_text": {
"embeddings": {
"model": "azure__openai__text_embedding_ada_002",
"strategy": {
"id": "basic",
"num_tokens_per_chunk": 64
}
},
"is_custom_instructions_included": false,
"llm_endpoint_params": {
"type": "openai_params",
"frequency_penalty": 1.5,
"presence_penalty": 1.5,
"stop": "<|im_end|>",
"temperature": 0,
"top_p": 1
},
"model": "azure__openai__gpt_4o_mini",
"num_tokens_for_completion": 8400,
"prompt_template": "It is `{current_date}`, consider these travel options `{content}` and answer the `{user_question}`.",
"system_message": "You are a helpful travel assistant specialized in budget travel"
}
}