自写 Lang 图状态

// update state and continue evolution    return new command({      update: {        ...state,        code: newcode,        version: state.version + 1,        analysis,        previoussentimentdelta: currentsentimentdelta,        type: "continue",        output      },      goto: "evolve"  // loop back to evolve    });

const initialworkercode = `import { stategraph, end } from "npm:@langchain/langgraph";const workflow = new stategraph({  channels: {    input: "string",    output: "string?"  }});// initial basic response nodeworkflow.addnode("respond", (state) => ({  ...state,  output: "i understand your request and will try to help. let me know if you need any clarification."}));workflow.setentrypoint("respond");workflow.addedge("respond", end);const graph = workflow.compile();export { graph };`;

if (import.meta.main) {  runevolvingsystem(10, 10);}

analysis: {  metrics: {    emotionalrange: 0.16483516483516483,    vocabularyvariety: 0.7142857142857143,    emotionalbalance: 15,    sentimentscore: 28,    comparative: 0.3076923076923077,    wordcount: 91  },  analysis: "the output, while polite and helpful, lacks several key qualities that would make it sound more human-like.  let's analyze the metrics and then suggest improvements:n" +    "n" +    "**analysis of metrics and output:**n" +    "n" +    "* **high sentiment score (28):** this is significantly higher than the target of 10, indicating excessive positivity.  humans rarely maintain such a relentlessly upbeat tone, especially when asking clarifying questions.  it feels forced and insincere.n" +    "n" +    "* **emotional range (0.16):** this low score suggests a lack of emotional variation. the response is consistently positive, lacking nuances of expression.  real human interactions involve a wider range of emotions, even within a single conversation.n" +    "n" +    "* **emotional balance (15.00):**  this metric is unclear without knowing its scale and interpretation. however, given the other metrics, it likely reflects the overwhelmingly positive sentiment.n" +    "n" +    "* **vocabulary variety (0.71):** this is relatively good, indicating a decent range of words. however, the phrasing is still somewhat formulaic.n" +    "n" +    "* **comparative score (0.3077):** this metric is also unclear without context.n" +    "n" +    "* **word count (91):**  a bit lengthy for a simple clarifying request.  brevity is often more human-like in casual conversation.n" +    "n" +    "n" +    "**ways to make the response more human-like:**n" +    "n" +    `1. **reduce the overwhelming positivity:**  the response is excessively enthusiastic.  a more natural approach would be to tone down the positive language.  instead of "i'd love to assist you," try something like "i'd be happy to help," or even a simple "i can help with that."  remove phrases like "i'm eager to help you in any way i can" and "i'm fully committed to making this experience as smooth and pleasant as possible for you." these are overly formal and lack genuine warmth.n` +    "n" +    '2. **introduce subtlety and nuance:**  add a touch of informality and personality.  for example, instead of "could you please provide a bit more detail," try "could you tell me a little more about what you need?" or "can you give me some more information on that?"n' +    "n" +    "3. **shorten the response:**  the length makes it feel robotic.  conciseness is key to human-like communication.  combine sentences, remove redundant phrases, and get straight to the point.n" +    "n" +    '4. **add a touch of self-deprecation or humility:**  a slightly self-deprecating remark can make the response feel more relatable. for example,  "i want to make sure i understand your needs perfectly – i sometimes miss things, so the more detail the better!"n' +    "n" +    "5. **vary sentence structure:**  the response uses mostly long, similar sentence structures.  varying sentence length and structure will make it sound more natural.n" +    "n" +    "**example of a more human-like response:**n" +    "n" +    `"thanks for reaching out!  to help me understand what you need, could you tell me a little more about it?  the more detail you can give me, the better i can assist you.  let me know what you're looking for."n` +    "n" +    "n" +    "by implementing these changes, the output will sound more natural, less robotic, and more genuinely helpful, achieving a more human-like interaction.  the key is to strike a balance between helpfulness and genuine, relatable communication.n",  rawsentiment: {    score: 28,    comparative: 0.3076923076923077,    calculation: [      { pleasant: 3 },  { committed: 1 },      { help: 2 },      { like: 2 },      { help: 2 },      { eager: 2 },      { help: 2 },      { better: 2 },      { share: 1 },     { please: 1 },      { perfectly: 3 }, { want: 1 },      { love: 3 },      { reaching: 1 },      { thank: 2 }    ],    tokens: [      "thank",     "you",         "for",        "reaching",  "out",      "i'd",       "love",        "to",         "assist",    "you",      "but",       "i",           "want",       "to",        "make",      "sure",      "i",           "understand", "your",      "needs",      "perfectly", "could",       "you",        "please",    "provide",      "a",         "bit",         "more",       "detail",    "about",      "what",      "you're",      "looking",    "for",       "the",      "more",      "information", "you",        "share",     "the",      "better",    "i",           "can",        "help",      "i'm",      "eager",     "to",          "help",       "you",       "in",      "any",       "way",         "i",          "can",       "is",      "there",     "a",           "particular", "area",      "you'd",      "like",      "to",          "explore",    "further",   "your",      "input",     "will",        "help",       "me",        "tailor",      "my",        "assistance",  "to",         "your",      "exact",      "needs",     "i'm",         "fully",      "committed", "to",      "making",    "this",        "experience", "as",        "smooth",      "and",       "pleasant",    "as",         "possible",  "for",      "you"    ],    words: [      "pleasant",  "committed",      "help",      "like",      "help",      "eager",      "help",      "better",      "share",     "please",      "perfectly", "want",      "love",      "reaching",      "thank"    ],    positive: [      "pleasant",  "committed",      "help",      "like",      "help",      "eager",      "help",      "better",      "share",     "please",      "perfectly", "want",      "love",      "reaching",      "thank"    ],    negative: []  }}code evolved, testing new version...

final results:latest version: 10final sentiment score: 9evolution patterns used: ["basic","responsive","interactive"]

import { StateGraph, END } from "npm:@langchain/langgraph";const workflow = new StateGraph({  channels: {    input: "string",    output: "string?",    sentiment: "number",    context: "object"  }});const positiveWords = ["good", "nice", "helpful", "appreciate", "thanks", "pleased", "glad", "great", "happy", "excellent", "wonderful", "amazing", "fantastic"];const negativeWords = ["issue", "problem", "difficult", "confused", "frustrated", "unhappy"];workflow.addNode("analyzeInput", (state) => {  const input = state.input.toLowerCase();  let sentiment = input.split(" ").reduce((score, word) => {    if (positiveWords.includes(word)) score += 1;    if (negativeWords.includes(word)) score -= 1;    return score;  }, 0);  sentiment = Math.min(Math.max(sentiment, -5), 5);  return {    ...state,    sentiment,    context: {      needsClarification: sentiment === 0,      isPositive: sentiment > 0,      isNegative: sentiment  {  let response = "";  const userName = state.context.userName ? `${state.context.userName}` : "there";  if (state.context.isPositive) {    response = `Hey ${userName}! Glad to hear things are going well. What can I do to make your day even better?`;  } else if (state.context.isNegative) {    response = `Hi ${userName}. I hear you're facing some challenges. Let's see if we can turn things around. What's on your mind?`;  } else {    response = `Hi ${userName}! What's up? How can I help you today?`;  }  return { ...state, output: response };});workflow.addNode("interactiveFollowUp", (state) => {  let followUp = "";  switch (state.context.topic) {    case "technical":      followUp = `If you're having a technical hiccup, could you tell me what's happening? Any error messages or weird behavior?`;      break;    case "product":      followUp = `Curious about our products? What features are you most interested in?`;      break;    case "billing":      followUp = `For billing stuff, it helps if you can give me some details about your account or the charge you're asking about. Don't worry, I'll keep it confidential.`;      break;    default:      followUp = `The more you can tell me, the better I can help. What's on your mind?`;  }  return { ...state, output: state.output + " " + followUp };});workflow.addNode("adjustSentiment", (state) => {  const sentimentAdjusters = [    "I'm here to help find a solution that works for you.",    "Thanks for your patience as we figure this out.",    "Your input really helps me understand the situation better.",    "Let's work together to find a great outcome for you."  ];  const adjuster = sentimentAdjusters[Math.floor(Math.random() * sentimentAdjusters.length)];  return { ...state, output: state.output + " " + adjuster };});workflow.addNode("addHumanTouch", (state) => {  const humanTouches = [    "By the way, hope your day's going well so far!",    "Just a heads up, I'm an AI assistant still learning the ropes.",    "Feel free to ask me to clarify if I say anything confusing.",    "I appreciate your understanding as we work through this."  ];  const touch = humanTouches[Math.floor(Math.random() * humanTouches.length)];  return { ...state, output: state.output + " " + touch };});workflow.setEntryPoint("analyzeInput");workflow.addEdge("analyzeInput", "generateResponse");workflow.addEdge("generateResponse", "interactiveFollowUp");workflow.addEdge("interactiveFollowUp", "adjustSentiment");workflow.addEdge("adjustSentiment", "addHumanTouch");workflow.addEdge("addHumanTouch", END);const graph = workflow.compile();export { graph };