merlyn/server/utils/agentFlows/executors/llm-instruction.js
2026-04-07 12:03:07 -07:00

48 lines
1.6 KiB
JavaScript

/**
* Execute an LLM instruction flow step
* @param {Object} config Flow step configuration
* @param {{introspect: Function, logger: Function}} context Execution context with introspect function
* @returns {Promise<string>} Processed result
*/
async function executeLLMInstruction(config, context) {
const { instruction, resultVariable } = config;
const { introspect, logger, aibitat } = context;
logger(
`\x1b[43m[AgentFlowToolExecutor]\x1b[0m - executing LLM Instruction block`
);
introspect(`Processing data with LLM instruction...`);
try {
logger(
`Sending request to LLM (${aibitat.defaultProvider.provider}::${aibitat.defaultProvider.model})`
);
introspect(`Sending request to LLM...`);
// Ensure the input is a string since we are sending it to the LLM direct as a message
let input = instruction;
if (typeof input === "object") input = JSON.stringify(input);
if (typeof input !== "string") input = String(input);
let completion;
const provider = aibitat.getProviderForConfig(aibitat.defaultProvider);
if (provider.supportsAgentStreaming) {
completion = await provider.stream(
[{ role: "user", content: input }],
[],
null
);
} else {
completion = await provider.complete([{ role: "user", content: input }]);
}
introspect(`Successfully received LLM response`);
if (resultVariable) config.resultVariable = resultVariable;
return completion.textResponse;
} catch (error) {
logger(`LLM processing failed: ${error.message}`, error);
throw new Error(`LLM processing failed: ${error.message}`);
}
}
module.exports = executeLLMInstruction;