Overview
This node implements an enhanced AI agent designed to perform a wide range of tasks by leveraging structured prompts and intelligent tool management. It allows users to create specialized AI agents tailored to different roles such as conversational agents, task solvers, data analysts, or creative writers. The node integrates with an external AI service via API calls and supports advanced configuration options including cost estimation, token limits, and tool validation.
Common scenarios where this node is beneficial include:
- Building chatbots or conversational interfaces that require contextual understanding.
- Automating specific task-solving workflows with step-by-step instructions.
- Analyzing data and generating insights based on user-defined objectives.
- Creating creative content like stories, marketing copy, or scripts with controlled style and constraints.
Practical example: A marketing analyst could configure the node as a "Data Analyst" agent with expertise in social media analytics, instructing it to analyze engagement metrics and provide optimization recommendations formatted as JSON. The node would then generate structured output suitable for further automation or reporting.
Properties
| Name | Meaning |
|---|---|
| Agent Type | Type of AI agent to create. Options: Conversational Agent (for chatbots), Task Solver (specialized task completion), Data Analyst (data analysis and insights), Creative Writer (creative content generation). |
| Role and Expertise | Defines the agent's role and specialized knowledge (e.g., "a marketing expert specialized in social media analytics"). This is a required field. |
| Objective | Clear statement of what the agent should accomplish (e.g., "analyze social media engagement metrics and provide optimization recommendations"). This is a required field. |
| Instructions | Detailed step-by-step instructions for the agent. Multiple instructions can be provided to guide the agent’s behavior precisely. |
| Output Format | Expected response format specified as a JSON schema. Helps validate that the agent's output matches the desired structure (e.g., { "analysis": "string", "recommendations": ["string"] }). |
| Constraints | Limitations and restrictions for the agent to follow during execution (e.g., avoid certain topics or styles). Multiple constraints can be added. |
| Examples | Reference input-output examples to guide the agent’s responses. Includes one example input and expected output to improve prompt quality. |
| Advanced Options | Collection of fine-tuning parameters: • Max Tokens: maximum tokens to generate. • Temperature: randomness control (0 deterministic, 1 creative). • Top P: nucleus sampling diversity. • Frequency Penalty: reduce repetition. • Presence Penalty: encourage new topics. • Enable Cost Estimation: toggle cost tracking. • Max Credits per Request: safety limit on credits spent. • Prefer Cost Efficiency: optimize for lower cost models and parameters. |
| Tool Management | Settings related to external tool usage: • Enable Tool Validation: check tools before use. • Max Tool Retries: number of retries for failed tools. • Enable Tool Caching: cache results to reduce API calls. |
Output
The node outputs a JSON object containing the AI agent's response under the json field. The structure of this output corresponds to the user-defined "Output Format" JSON schema property, ensuring the response matches expected keys and types.
Additionally, if cost estimation is enabled, the output includes detailed metadata about the operation, such as:
- Actual and estimated credits used
- Token counts (input, output, total)
- Cost in USD and profit margin percentage
- Model provider and model name used
- Execution time in milliseconds
If the node is connected to an AI language model input, it uses that model to generate the response. The node also supports integration with external tools, whose results may influence the final output.
No binary data output is produced by this node.
Dependencies
- Requires connection to an external AI service via an API key credential.
- Needs an AI language model node connected to its "Model" input for generating responses (compatible with OpenAI, Anthropic, or similar).
- Optionally connects to external tools via the "Tools" input for enhanced capabilities.
- Requires valid API credentials for the AI service to validate subscription and execute requests.
- Uses HTTP requests internally to communicate with the AI service endpoint
/agents/enhanced.
Troubleshooting
Common Issues:
Missing AI Language Model Input:
Error thrown if no AI language model node is connected to the "Model" input. Remedy by connecting a compatible LLM node.Invalid or Missing API Credentials:
If the API key or subscription is invalid, the node throws an error indicating credential issues. Verify and update the API key credential.Quota Exceeded (HTTP 429):
When usage limits are surpassed, the node reports quota exceeded with details on estimated credits. Users should monitor usage or increase quota.Insufficient Credits (HTTP 402):
If account balance is too low to cover the request cost, an error shows current balance and cost estimate. Replenish credits or reduce request complexity.Service Unavailable (HTTP 503):
Temporary AI service downtime causes an error advising to retry later.Output Format Validation Failure:
If the agent's output does not match the expected JSON schema, an error is raised. Adjust the output format schema or review agent instructions.
Tips:
- Enable cost estimation to monitor and control spending.
- Use tool caching and validation to improve reliability and reduce redundant API calls.
- Provide clear instructions and examples to improve agent accuracy.
- Adjust advanced options like temperature and max tokens to balance creativity and cost.