Files
toolLooper/modelDialog.js

199 lines
8.0 KiB
JavaScript

import OpenAI from 'openai';
import 'dotenv/config';
import EventEmitter from 'events';
import path from 'path';
import fs from 'fs/promises';
import { fileURLToPath } from 'node:url';
import chalk from 'chalk';
async function loadTools() {
const __dirname = path.dirname(fileURLToPath(import.meta.url));
const toolsDir = path.join(__dirname, "tools");
const dirents = await fs.readdir(toolsDir, { withFileTypes: true });
const toolEntries = await Promise.all(
dirents
.filter((dirent) => dirent.isFile() && dirent.name.endsWith(".js"))
.map(async (dirent) => {
const fileName = dirent.name.replace(/\.js$/, "");
const module = await import(`file://${path.join(toolsDir, dirent.name)}`);
return [fileName, { def: module.default, run: module.run }];
})
);
return Object.fromEntries(toolEntries);
}
const toolsByFile = await loadTools();
const openai = new OpenAI({ apiKey: process.env.OPENAI_API_KEY });
const systemprompt = {"role": "developer", "content": [ { "type": "input_text","text":
`You are a helpful assistant.`
}]};
if (!Array.fromAsync) {
Array.fromAsync = async function fromAsync(asyncIterable) {
const array = [];
for await (const item of asyncIterable) {
array.push(item);
}
return array;
};
}
class ModelDialog {
constructor(options) {
this.options = options;
this.messages = [systemprompt];
this.messagesSent = [];
this.isActive = false;
this.currentStream = null;
this.previousResponseId = null;
this.emitter = new EventEmitter();
this.inputTokens = {};
this.outputTokens = {};
this.cachedTokens = {};
this.lastDebouncedUpdate = 0;
};
handleUsage = (usage, model) => {
if (typeof this.inputTokens[model] !== 'number') this.inputTokens[model] = 0;
if (typeof this.outputTokens[model] !== 'number') this.outputTokens[model] = 0;
if (typeof this.cachedTokens[model] !== 'number') this.cachedTokens[model] = 0;
this.inputTokens[model] += usage.input_tokens - usage.input_tokens_details.cached_tokens;
this.outputTokens[model] += usage.output_tokens;
this.cachedTokens[model] += usage.input_tokens_details.cached_tokens;
}
on = (event, callback) => {
const debounceTime = 1000; // 1 second
const debouncedCallback = (...args) => {
const now = Date.now();
if (now - this.lastDebouncedUpdate >= debounceTime) {
this.lastDebouncedUpdate = now;
callback(...args);
}
};
this.emitter.on(event, debouncedCallback);
}
interrogate = async (prompt) => {
if(this.isActive) return;
this.isActive = true;
this.messages.push({"role": "user", "content": [ {"type": "input_text","text": prompt }]});
const outputs = [];
do{
const messagesToSend = this.messages.splice(0);
console.log(chalk.blue('sending messages:'),messagesToSend.length);
//console.log(chalk.blue('messages:'),JSON.stringify(messagesToSend,null,2));
this.messagesSent.push(...messagesToSend);
const model = this.options.model || 'gpt-5-mini';
if(!['gpt-5', 'gpt-5-mini', 'gpt-5-nano', 'gpt-4.1', 'gpt-4.1-mini'].includes(model)){
throw new Error('Invalid model: ' + model);
}
const call = {
model: model,
input: messagesToSend,
text: { format: { type: 'text' } },
tools: Object.values(toolsByFile).map(t => t.def),
store: true,
previous_response_id: this.previousResponseId,
parallel_tool_calls: true,
include: ['reasoning.encrypted_content']
}
if(model.startsWith('gpt-5')){
call.reasoning = { effort: 'low', summary: 'detailed' };
//call.text.format.verbosity = 'low';
}
this.currentStream = openai.responses.stream(call);
this.currentStream.on('response.created', (event) => {
this.previousResponseId = event.response.id;
});
const deltas = [];
this.currentStream.on('response.output_text.delta', (event) => {
deltas.push(event.delta);
this.emitter.emit('outputUpdate', deltas.join(''));
});
const reasoningDeltas = [];
this.currentStream.on('response.reasoning_summary_text.delta', (event) => {
if(!reasoningDeltas[event.summary_index]) reasoningDeltas[event.summary_index] = [];
reasoningDeltas[event.summary_index].push(event.delta);
this.emitter.emit('reasoningUpdate', reasoningDeltas[event.summary_index].join(''));
});
this.currentStream.on('response.reasoning_summary_text.done', (event) => {
//console.log(event);
});
this.currentStream.on('response.function_call_arguments.delta', (event) => {
process.stdout.write(chalk.yellow(event.delta));
});
this.currentStream.on('response.function_call_arguments.done', (event) => {
process.stdout.write("\n");
});
this.currentStream.on('response.completed', async (event) => {
//console.log(chalk.blue('response completed:'),event.response.usage);
this.handleUsage(event.response.usage, event.response.model);
outputs.push(...event.response.output);
for(const toolCall of event.response.output.filter(i => i.type === 'function_call')){
// Limit the 'arguments' field to 400 characters for logging
const limitedArgs = typeof toolCall.arguments === 'string'
? (toolCall.arguments.length > 400 ? toolCall.arguments.slice(0, 400) + '...[truncated]' : toolCall.arguments)
: toolCall.arguments;
const tool = toolsByFile[toolCall.name];
let args;
try{
args = JSON.parse(toolCall.arguments);
} catch(e){
console.error(chalk.red('Error parsing arguments:'), e, toolCall.arguments);
this.messages.push({
type: "function_call_output",
call_id: toolCall.call_id,
output: {error: 'Exception in parsing arguments', exception: e},
});
continue;
}
const result = await tool.run(args);
console.log(chalk.green('function call result:'),'<toolCall.name>',toolCall.name,'</toolCall.name>\n','<args>',limitedArgs,'</args>\n','<result>',JSON.stringify(result).slice(0,100),'...</result>');
this.messages.push({
type: "function_call_output",
call_id: toolCall.call_id,
output: JSON.stringify(result),
});
}
});
await Array.fromAsync(this.currentStream);
console.log(chalk.green('Tico'),[Object.values(this.inputTokens),Object.values(this.cachedTokens),Object.values(this.outputTokens)]);
console.log(chalk.green('Do we need to loop? messages in array = '),this.messages.length)
} while(this.messages.length > 0);
this.isActive = false;
this.lastDebouncedUpdate = 0;
return {
output: outputs.filter(i => i.type === 'message').map(i => i.content[0].text) ,
reasoning: outputs.filter(i => i.type === 'reasoning').map(i => i.summary.map(j => j.text).join('\n')),
inputTokens: this.inputTokens, outputTokens: this.outputTokens, cachedTokens: this.cachedTokens
};
}
}
export default ModelDialog;