!7

static new L thoughtBots;
static long started;
static Class theoryModule;
static Lock theoryLock = lock();
static double delay = 0;
static S selectedWord;

p {
  started = sysNow();
  db();
  load('selectedWord);
  autoRestart();
  serveHttp(4678);
  typicalDownload();
  bot("Smart Bot.");
  loadPage_forcedTimeout = 70000;
  thoughtBots.add(mc());
  loadBots(#1010753, #1010821, #1010825, #1001951);
  stefansChat_onLine_lookback = 2;
  stefansChat_onLine_safe(voidfunc(S text) {
    sleepSeconds(delay);
    print("> " + text);
    S answer = scanMultipleBots(thoughtBots, text);
    if (nempty(answer))
      postToStefansChat(answer);
  });
  //stefansChat_post("Smart Bot Upgraded! Boot took: " + formatDouble(fromMS(sysNow()-started), 1) + " s");
  
  runInNewThread(#1010793); // Post on UAIP
  
  loadTheory();
}

svoid loadTheory {
  lock theoryLock;
  cleanUp(theoryModule);
  theoryModule = null;
  theoryModule = run(#1010963);
  setOpt(theoryModule, 'onUpdate, r { call(theoryModule, 'react) });
  call(theoryModule, 'react);
  print("Theory module loaded.");
}

static int lineCount;

answer {
  ++lineCount;
  bool authed = isTrue(stefansChat_onLine_fullParams->get('auth));
  
  int safety = 0;
  replaceloop: while (safety++ < 10) {
    s = trim(s);
    if (authed) {
      if (lineCount >= stefansChat_onLine_lookback) {
        if (eqic(s, "!restart")) { restart(); ret "Yo"; }
        if (eqic(s, "!theory")) ret "OK" with loadTheory();
        if (eqic(s, "!peep")) {
          runAndCleanUp(#1010980);
          ret "OK, got " + fileLength(ai_chatAnalysis_peepHoleFile()) + " bytes";
        }
      }
      
      if "unlearn * *"
        ret "OK, was: " + uniq(MatchLearner, pattern := $1).examples.put($2, 'rejected);
    }
    
    if "Are you online?" ret "Yes";
    if (eqic(s, "!question"))
      ret random_gac36k();
      
    if (swic_trim(s, "!word ", m)) {
      selectedWord = $1;
      save('selectedWord);
      ret "OK";
    }
      
    if (eqic(s, "!uptime"))
      ret n(secondsSinceSysTime(started), "second");
      
    if (swic(s, "!nodes ", m))
      ret lstr(indexedNodes($1));
      
    if (swic(s, "!splitAtBaseFormVerb ", m))
      ret sfu(splitAtBaseFormVerb($1));
      
    if (swic(s, "!maxRunlengthOfRepeatingChars ", m))
      ret str(maxRunlengthOfRepeatingChars($1));
      
    if (swic(s, "!collapseWord ", m))
      ret collapseWord($1);
      
    s = ai_dropLeadingAdditions(s);
  
    if "cache size"
      ret n(keys(cachedNodeIndex()), "different term")
        + ", " + n(web_countNodes(allWebs_cached()), "node")
        + ", " + n(allWebs_cached(), "web");
    
    if "give me subtypes of ..."
      ret ai_renderList(ai_subtypesOf(m.rest()));
      
    if "give me a third person verb"
      ret random(thirdPersonVerbs());
      
    if (learnedFlexMatch("give me some *", s, m)) {
      S query = singular($1);
      ret ai_renderNodesList(concatLists(
        webs_search_dollarX(webFromTriples("$X", "is a", query), indexedWebs(query)),
        webs_search_dollarX(webFromTriples("$X", "is", a(query)), indexedWebs(a(query)))));
    }
      
    if "authed?"
      ret authed ? "You are authed." : "You are not authed.";
      
    if "what is the singular of *"
      ret or2(getSingularFromWordHippo($1), singular($1));
      
    if (learnedFlexMatch("what is the relation between * and *", s, m)) {
      L<S> l = ai_getRelation($1, $2);
      //ret ai_renderList(l);
      if (nempty(l)) ret $1 + " " + first(l) + " " + $2;
    }
      
    if "what unix day is it"
      ret str(unixDay());
      
    if "show me the ..."
      ret "What " + $1 + "?";
      
    if (learnedFlexMatch("What do * have?", s, m))
      ret ai_renderNodesList(webs_search_dollarX(webFromTriples($1, "have", "$X"), indexedWebs($1)));
      
    if (learnedFlexMatch("What does * do?", s, m))
      ret ai_renderList(map(f web_nodePairToText, webs_search_dollarXY(webFromTriples($1, "$X", "$Y"), indexedWebs($1))));
      
    if (learnedFlexMatch("What is *", s, m))
      try answer ai_renderNodesList(ai_whatIs($1), "");
      
    S sf = web_text(first(webs_search_dollarX(webFromTriples("$X", "implements", quote(s)), indexedWebs(quote(s)))));
    if (startsWith(sf, "sf ", m))
      ret str(makeAndCall($1));
      
    if (learnedFlexMatch("* how many visitors *", s) || match("how many visitors", s))
      ret str(ai1_cookiesToday_int());
      
    // Once more with generated webs (replacing $ vars)
    
    if (learnedFlexMatch("What is *", s, m)) {
      L<Web> extendedWebs = indexedWebsAfterVariableSubstitution($1);
      print("Have " + n(extendedWebs, "extended web") + " for " + quote($1));
      ret ai_renderNodesList(webs_search_dollarX(webFromTriples($1, "is", "$X"), extendedWebs), "I don't know");
    }
    
    S match;
    if (learnedFlexMatch(match = "* is *", s, m)) {
      postSoftwareMadeWeb(webFromTriples($1, "is", $2),
        +match, input := s);
      ret "OK, stored.";
    }
    
    for (WebNode node : indexedNodes(s)) {
      S x = web_operandText(node, "replace with");
      if (x != null) {
        print("Replacing with " + x);
        s = x;
        continue replaceloop;
      }
    }
    break;
  }
  
  if (ai_isQuestion_1(s)) ret "No idea";
}

svoid loadBots(S... botIDs) {
  for (S id : botIDs) pcall {
    thoughtBots.add(runSubBot(id));
  }
}

// s = uri
static NanoHTTPD.Response html(S s) {
  if "thoughts"
    ret serveHTML(html_thoughts());
    
  if "log"
    ret serveText_direct(printLog());
  ret serveText_direct(renderConcepts(list(MatchLearner)));
}

sS html_thoughts() {
  S html = /*hrefresh(5) +*/ hGoogleFontOswald();
  if (theoryModule == null)
    ret html + "Loading theory module...";
  S thoughts = (S) call(theoryModule, 'html_thoughts);
  if (nempty(selectedWord))
    //ret html + hSingleRowTable(thoughts, wordThoughts());
    ret html + tag('table, tr(td_top(thoughts, style := "background: #CCC") + td_top(wordThoughts(), style := "padding-left: 20px")));
  ret html + thoughts;
}

sS wordThoughts() {
  try {
    if (empty(selectedWord)) ret "";
    L<WebNode> nodes = indexedNodes(selectedWord);
    L<WebNode> is = ai_whatIs(selectedWord);
    ret h3(htmlencode(selectedWord))
      + ul(map html_linkURLs(map htmlencode_noQuotes(allToString(flattenArray2(
        uniquify(map ai_renderNode(is)),
        "[" + n(nodes, "node") + "]",
      )))));
  } catch e {
    printStackTrace(e);
    ret "Erreur";
  }
}