{
  "aboutHtml": "<p>Uvod: sklepanje na podlagi dolgih dokumentov</p><p>QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje z dolgim kontekstom. Njegov namen je odgovarjati na vprašanja, katerih dokazi so razpršeni po dokumentu ali več dokumentih, namesto da bi preprosto ponovil bližnji odlomek. Zgrajen je iz DeepSeek-R1-Distill-Qwen-32B in dodatno učen za sklepanje, utemeljeno v dokumentih. Priložite besedilo in vprašanje; model ustvari besedilno zaporedje sklepanja in odgovor. Skenirane strani, zvok in video pred tem besedilnim delovnim potekom potrebujejo ustrezen ločen korak pretvorbe.</p><p>Kako deluje učenje dolgega konteksta</p><p>Ogrodje QwenLong-L1 najprej pripravi politiko sklepanja z nadzorovanim finim prilagajanjem, nato pa s kurikulumom spodbujevalnega učenja povečuje dolžino konteksta. Retrospektivno vzorčenje, ki upošteva težavnost, med napredovanjem učenja prilagaja izbiro ponovno obravnavanih primerov. Proizvajalec združuje binarne nagrade za izid na podlagi pravil in modela ter uporablja optimizacijo politike glede na skupino za spodbujanje odgovorov, ki ostanejo utemeljeni v obsežnih dokazih. To opisuje učni pristop kontrolne točke; ne pomeni, da zunanji presojevalec vsak odgovor samodejno preveri.</p><p>Izdana različica</p><p>To je izvirna izdaja QwenLong-L1-32B. Ločeno poimenovani QwenLong-L1-32B-AWQ je kvantizirana izdaja INT4 in mora ohraniti lastno identiteto. Objavljena konfiguracija tega modela uporablja arhitekturo vzročnega jezikovnega modela Qwen2 s 64 plastmi in utežmi bfloat16. Specializacija modela za dokumente je za izbiro pomembnejša od obravnave imena 32B kot dokaza, da bo vsaka splošnonamenska naloga izboljšana.</p><p>Priprava vprašanja o dokumentu</p><p>Proizvajalčev primer dokument loči od vprašanja z izrecnimi besedilnimi razmejevalniki in za sklepanjem zahteva prepoznavno frazo končnega odgovora. Sledite tej strukturi: priložite ustrezno telo dokumenta, ohranite berljive naslove in tabele ter zastavite eno konkretno vprašanje. Pri izračunu iz poročila ohranite enote, obdobja poročanja in oznake tabel, nato zahtevajte formulo, uporabljene vrednosti in končni rezultat. Pri primerjavi politik dokumenta označite z A in B ter zahtevajte tabelo ujemajočih se pravil, razlik in podpornega razdelka za vsako vrstico. To so avtorsko oblikovane uporabe dokumentiranih numeričnih in meddokumentnih zmožnosti.</p><p>Primer ločeno razčleni besedilo sklepanja in končnega odgovora. Uporablja proračun ustvarjanja 10.000 žetonov, parameter temperature z vrednostjo 0.7 in top_p 0.95; to so nastavitve primera, ne razglašena največja dolžina izhoda. Kartica prikazuje tudi izbirno sistemsko sporočilo za nastavitev identitete. Ohranite lastna navodila za pozive tega modela, namesto da priporočila druge kontrolne točke uvažate zgolj zato, ker je del njegovega izvora.</p><p>Obdelava dolgih dokumentov</p><p>Tongyi Lab preverja dolžine konteksta do 131.072 žetonov z YaRN in priporoča razširitev, kadar skupni vhod in izhod bistveno presegata 32.768 žetonov. Njegovi primeri opisujejo faktor štiri ali manjši faktor, na primer dva za obremenitev 65.536 žetonov. Statična razširitev lahko poslabša delovanje pri krajšem besedilu, zato kartica odsvetuje njeno omogočanje, kadar običajne zahteve ostanejo znotraj 32.768 žetonov. Objavljena konfiguracija navaja 131.072 položajev, vendar nima omogočenega polja rope_scaling; konfiguracijo in proizvajalčev pogojni postopek dolgega konteksta je zato treba preveriti skupaj.</p><p>Dolg vhod še vedno potrebuje prostor za sklepanje in odgovor. Začnite z odlomki, potrebnimi za vprašanje, odstranite ponavljajoče se glave in navigacijsko besedilo ter ohranite identifikatorje strani ali razdelkov. V rezultatu zahtevajte reference na dokaze, da lahko pregledovalec sledi sklepu nazaj do priloženega gradiva. Velika dodelitev konteksta pomaga vključiti več dokazov v eno zahtevo; ne zagotavlja popolnega priklica vsake podrobnosti.</p><p>Kaj zajema učenje na dokumentih</p><p>DocQA-RL-1.6K vsebuje 1.600 učnih problemov s treh področij sklepanja: 600 numeričnih vprašanj iz dolgih specializiranih dokumentov, kot so finančna poročila; 600 logičnih vprašanj z več izbirami o pravnih, finančnih, zavarovalniških in proizvodnih dokumentih; ter 400 večstopenjskih primerov, ki povezujejo dokaze med viri. Zato je model ustrezen kandidat za računanje iz poročil, razlago pravil in vprašanja, ki potrebujejo več podpornih odlomkov. Učna področja opisujejo izkušnje s temi nalogami, ne strokovne certifikacije ali zajamčenih sklepov.</p><p>Praktični izhod in omejitve</p><p>Izberite odgovor, ki ga je mogoče preveriti: izračunano vrednost z enotami, primerjavo pravil z referencami razdelkov ali kratek sklep z verigo podpornih dejstev. Če dokument ne vsebuje zahtevanega datuma ali definicije, zahtevajte, da model določi manjkajoče dokaze, namesto da jih izmisli. Gradiva ob izdaji se osredotočajo na odgovarjanje na vprašanja o dokumentih in ne določajo namenske pogodbe za klicanje orodij ali ločene stroge zgornje meje izhoda. Odgovore obravnavajte kot utemeljene osnutke ter izračune, reference in razlage preverite s priloženimi dokumenti.</p>",
  "aboutText": "Uvod: sklepanje na podlagi dolgih dokumentov\n\nQwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje z dolgim kontekstom. Njegov namen je odgovarjati na vprašanja, katerih dokazi so razpršeni po dokumentu ali več dokumentih, namesto da bi preprosto ponovil bližnji odlomek. Zgrajen je iz DeepSeek-R1-Distill-Qwen-32B in dodatno učen za sklepanje, utemeljeno v dokumentih. Priložite besedilo in vprašanje; model ustvari besedilno zaporedje sklepanja in odgovor. Skenirane strani, zvok in video pred tem besedilnim delovnim potekom potrebujejo ustrezen ločen korak pretvorbe.\n\nKako deluje učenje dolgega konteksta\n\nOgrodje QwenLong-L1 najprej pripravi politiko sklepanja z nadzorovanim finim prilagajanjem, nato pa s kurikulumom spodbujevalnega učenja povečuje dolžino konteksta. Retrospektivno vzorčenje, ki upošteva težavnost, med napredovanjem učenja prilagaja izbiro ponovno obravnavanih primerov. Proizvajalec združuje binarne nagrade za izid na podlagi pravil in modela ter uporablja optimizacijo politike glede na skupino za spodbujanje odgovorov, ki ostanejo utemeljeni v obsežnih dokazih. To opisuje učni pristop kontrolne točke; ne pomeni, da zunanji presojevalec vsak odgovor samodejno preveri.\n\nIzdana različica\n\nTo je izvirna izdaja QwenLong-L1-32B. Ločeno poimenovani QwenLong-L1-32B-AWQ je kvantizirana izdaja INT4 in mora ohraniti lastno identiteto. Objavljena konfiguracija tega modela uporablja arhitekturo vzročnega jezikovnega modela Qwen2 s 64 plastmi in utežmi bfloat16. Specializacija modela za dokumente je za izbiro pomembnejša od obravnave imena 32B kot dokaza, da bo vsaka splošnonamenska naloga izboljšana.\n\nPriprava vprašanja o dokumentu\n\nProizvajalčev primer dokument loči od vprašanja z izrecnimi besedilnimi razmejevalniki in za sklepanjem zahteva prepoznavno frazo končnega odgovora. Sledite tej strukturi: priložite ustrezno telo dokumenta, ohranite berljive naslove in tabele ter zastavite eno konkretno vprašanje. Pri izračunu iz poročila ohranite enote, obdobja poročanja in oznake tabel, nato zahtevajte formulo, uporabljene vrednosti in končni rezultat. Pri primerjavi politik dokumenta označite z A in B ter zahtevajte tabelo ujemajočih se pravil, razlik in podpornega razdelka za vsako vrstico. To so avtorsko oblikovane uporabe dokumentiranih numeričnih in meddokumentnih zmožnosti.\n\nPrimer ločeno razčleni besedilo sklepanja in končnega odgovora. Uporablja proračun ustvarjanja 10.000 žetonov, parameter temperature z vrednostjo 0.7 in top_p 0.95; to so nastavitve primera, ne razglašena največja dolžina izhoda. Kartica prikazuje tudi izbirno sistemsko sporočilo za nastavitev identitete. Ohranite lastna navodila za pozive tega modela, namesto da priporočila druge kontrolne točke uvažate zgolj zato, ker je del njegovega izvora.\n\nObdelava dolgih dokumentov\n\nTongyi Lab preverja dolžine konteksta do 131.072 žetonov z YaRN in priporoča razširitev, kadar skupni vhod in izhod bistveno presegata 32.768 žetonov. Njegovi primeri opisujejo faktor štiri ali manjši faktor, na primer dva za obremenitev 65.536 žetonov. Statična razširitev lahko poslabša delovanje pri krajšem besedilu, zato kartica odsvetuje njeno omogočanje, kadar običajne zahteve ostanejo znotraj 32.768 žetonov. Objavljena konfiguracija navaja 131.072 položajev, vendar nima omogočenega polja rope_scaling; konfiguracijo in proizvajalčev pogojni postopek dolgega konteksta je zato treba preveriti skupaj.\n\nDolg vhod še vedno potrebuje prostor za sklepanje in odgovor. Začnite z odlomki, potrebnimi za vprašanje, odstranite ponavljajoče se glave in navigacijsko besedilo ter ohranite identifikatorje strani ali razdelkov. V rezultatu zahtevajte reference na dokaze, da lahko pregledovalec sledi sklepu nazaj do priloženega gradiva. Velika dodelitev konteksta pomaga vključiti več dokazov v eno zahtevo; ne zagotavlja popolnega priklica vsake podrobnosti.\n\nKaj zajema učenje na dokumentih\n\nDocQA-RL-1.6K vsebuje 1.600 učnih problemov s treh področij sklepanja: 600 numeričnih vprašanj iz dolgih specializiranih dokumentov, kot so finančna poročila; 600 logičnih vprašanj z več izbirami o pravnih, finančnih, zavarovalniških in proizvodnih dokumentih; ter 400 večstopenjskih primerov, ki povezujejo dokaze med viri. Zato je model ustrezen kandidat za računanje iz poročil, razlago pravil in vprašanja, ki potrebujejo več podpornih odlomkov. Učna področja opisujejo izkušnje s temi nalogami, ne strokovne certifikacije ali zajamčenih sklepov.\n\nPraktični izhod in omejitve\n\nIzberite odgovor, ki ga je mogoče preveriti: izračunano vrednost z enotami, primerjavo pravil z referencami razdelkov ali kratek sklep z verigo podpornih dejstev. Če dokument ne vsebuje zahtevanega datuma ali definicije, zahtevajte, da model določi manjkajoče dokaze, namesto da jih izmisli. Gradiva ob izdaji se osredotočajo na odgovarjanje na vprašanja o dokumentih in ne določajo namenske pogodbe za klicanje orodij ali ločene stroge zgornje meje izhoda. Odgovore obravnavajte kot utemeljene osnutke ter izračune, reference in razlage preverite s priloženimi dokumenti.",
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      "practical_html": "<h3>Praktična naloga</h3><p>Tehnični primer v angleščini</p><pre><code>Connect evidence across report sections\n\nDocument section 1 says 240 units were shipped. Section 4 says 30 shipped units were returned before month end. Appendix A says net shipped units equal shipped minus returned units. Calculate net shipped units for the month, cite every section needed and state whether revenue can be calculated from these facts. End with a clearly labelled final answer.</code></pre><h4>Pričakovani rezultat</h4><pre><code>A source-linked formula and calculation, a revenue-information limit and a labelled final result.</code></pre><h4>Preverjanje rezultata</h4><pre><code>Check that all three source sections support the calculation and that a price or revenue value is not invented.</code></pre>"
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      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">QwenLong L1 32B</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Zapri\">×</button></div><div class=\"idline\"><span>Drugo /</span><code>Tongyi-Zhiwen/QwenLong-L1-32B</code><button type=\"button\" id=\"copy-id\">Kopiraj ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Razdelki kartice modela\"><button type=\"button\" data-card-jump=\"overview\">Začetek</button><button type=\"button\" data-card-jump=\"methods\">Vhodi in metode</button><button type=\"button\" data-card-jump=\"pricing\">Cenik</button><button type=\"button\" data-card-jump=\"examples\">Primeri</button><button type=\"button\" data-card-jump=\"results\">Rezultati</button><button type=\"button\" data-card-jump=\"aliases\">Druga imena</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Metode API\"><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-0\" data-card-method=\"Ultra|chat|/v1/chat/completions|Tongyi-Zhiwen%2FQwenLong-L1-32B\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|Tongyi-Zhiwen%2FQwenLong-L1-32B\">Messages</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-0\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Začetek</h3><p class=\"mdesc-full\">QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje pri vprašanjih, utemeljenih v dolgih dokumentih. Izhodišče DeepSeek-R1-Distill-Qwen-32B združuje s spodbujevalnim učenjem, osredotočenim na dokumente, za numerično, logično in meddokumentno sklepanje.</p><dl class=\"card-io\" data-card-io><div><dt>Dovoljeni vhodi</dt><dd>Besedilo</dd></div><div><dt>Rezultati</dt><dd>Besedilo</dd></div></dl><details class=\"card-about\"><summary>O modelu</summary><p class=\"note-s\" data-model-method-boundary>Ta opis zajema zmožnosti modela. Vhodi, izhodi in možnosti, ki so na voljo v Ailoot, so spodaj navedeni za izbrano metodo.</p><div class=\"mabout\" id=\"m-about\"><p>Uvod: sklepanje na podlagi dolgih dokumentov</p><p>QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje z dolgim kontekstom. Njegov namen je odgovarjati na vprašanja, katerih dokazi so razpršeni po dokumentu ali več dokumentih, namesto da bi preprosto ponovil bližnji odlomek. Zgrajen je iz DeepSeek-R1-Distill-Qwen-32B in dodatno učen za sklepanje, utemeljeno v dokumentih. Priložite besedilo in vprašanje; model ustvari besedilno zaporedje sklepanja in odgovor. Skenirane strani, zvok in video pred tem besedilnim delovnim potekom potrebujejo ustrezen ločen korak pretvorbe.</p><p>Kako deluje učenje dolgega konteksta</p><p>Ogrodje QwenLong-L1 najprej pripravi politiko sklepanja z nadzorovanim finim prilagajanjem, nato pa s kurikulumom spodbujevalnega učenja povečuje dolžino konteksta. Retrospektivno vzorčenje, ki upošteva težavnost, med napredovanjem učenja prilagaja izbiro ponovno obravnavanih primerov. Proizvajalec združuje binarne nagrade za izid na podlagi pravil in modela ter uporablja optimizacijo politike glede na skupino za spodbujanje odgovorov, ki ostanejo utemeljeni v obsežnih dokazih. To opisuje učni pristop kontrolne točke; ne pomeni, da zunanji presojevalec vsak odgovor samodejno preveri.</p><p>Izdana različica</p><p>To je izvirna izdaja QwenLong-L1-32B. Ločeno poimenovani QwenLong-L1-32B-AWQ je kvantizirana izdaja INT4 in mora ohraniti lastno identiteto. Objavljena konfiguracija tega modela uporablja arhitekturo vzročnega jezikovnega modela Qwen2 s 64 plastmi in utežmi bfloat16. Specializacija modela za dokumente je za izbiro pomembnejša od obravnave imena 32B kot dokaza, da bo vsaka splošnonamenska naloga izboljšana.</p><p>Priprava vprašanja o dokumentu</p><p>Proizvajalčev primer dokument loči od vprašanja z izrecnimi besedilnimi razmejevalniki in za sklepanjem zahteva prepoznavno frazo končnega odgovora. Sledite tej strukturi: priložite ustrezno telo dokumenta, ohranite berljive naslove in tabele ter zastavite eno konkretno vprašanje. Pri izračunu iz poročila ohranite enote, obdobja poročanja in oznake tabel, nato zahtevajte formulo, uporabljene vrednosti in končni rezultat. Pri primerjavi politik dokumenta označite z A in B ter zahtevajte tabelo ujemajočih se pravil, razlik in podpornega razdelka za vsako vrstico. To so avtorsko oblikovane uporabe dokumentiranih numeričnih in meddokumentnih zmožnosti.</p><p>Primer ločeno razčleni besedilo sklepanja in končnega odgovora. Uporablja proračun ustvarjanja 10.000 žetonov, parameter temperature z vrednostjo 0.7 in top_p 0.95; to so nastavitve primera, ne razglašena največja dolžina izhoda. Kartica prikazuje tudi izbirno sistemsko sporočilo za nastavitev identitete. Ohranite lastna navodila za pozive tega modela, namesto da priporočila druge kontrolne točke uvažate zgolj zato, ker je del njegovega izvora.</p><p>Obdelava dolgih dokumentov</p><p>Tongyi Lab preverja dolžine konteksta do 131.072 žetonov z YaRN in priporoča razširitev, kadar skupni vhod in izhod bistveno presegata 32.768 žetonov. Njegovi primeri opisujejo faktor štiri ali manjši faktor, na primer dva za obremenitev 65.536 žetonov. Statična razširitev lahko poslabša delovanje pri krajšem besedilu, zato kartica odsvetuje njeno omogočanje, kadar običajne zahteve ostanejo znotraj 32.768 žetonov. Objavljena konfiguracija navaja 131.072 položajev, vendar nima omogočenega polja rope_scaling; konfiguracijo in proizvajalčev pogojni postopek dolgega konteksta je zato treba preveriti skupaj.</p><p>Dolg vhod še vedno potrebuje prostor za sklepanje in odgovor. Začnite z odlomki, potrebnimi za vprašanje, odstranite ponavljajoče se glave in navigacijsko besedilo ter ohranite identifikatorje strani ali razdelkov. V rezultatu zahtevajte reference na dokaze, da lahko pregledovalec sledi sklepu nazaj do priloženega gradiva. Velika dodelitev konteksta pomaga vključiti več dokazov v eno zahtevo; ne zagotavlja popolnega priklica vsake podrobnosti.</p><p>Kaj zajema učenje na dokumentih</p><p>DocQA-RL-1.6K vsebuje 1.600 učnih problemov s treh področij sklepanja: 600 numeričnih vprašanj iz dolgih specializiranih dokumentov, kot so finančna poročila; 600 logičnih vprašanj z več izbirami o pravnih, finančnih, zavarovalniških in proizvodnih dokumentih; ter 400 večstopenjskih primerov, ki povezujejo dokaze med viri. Zato je model ustrezen kandidat za računanje iz poročil, razlago pravil in vprašanja, ki potrebujejo več podpornih odlomkov. Učna področja opisujejo izkušnje s temi nalogami, ne strokovne certifikacije ali zajamčenih sklepov.</p><p>Praktični izhod in omejitve</p><p>Izberite odgovor, ki ga je mogoče preveriti: izračunano vrednost z enotami, primerjavo pravil z referencami razdelkov ali kratek sklep z verigo podpornih dejstev. Če dokument ne vsebuje zahtevanega datuma ali definicije, zahtevajte, da model določi manjkajoče dokaze, namesto da jih izmisli. Gradiva ob izdaji se osredotočajo na odgovarjanje na vprašanja o dokumentih in ne določajo namenske pogodbe za klicanje orodij ali ločene stroge zgornje meje izhoda. Odgovore obravnavajte kot utemeljene osnutke ter izračune, reference in razlage preverite s priloženimi dokumenti.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Na voljo v Ailoot · vhodi in metode</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · OpenAI Chat</b> <code>POST /v1/chat/completions</code></summary><dl class=\"method-capabilities\"><div><dt>Vhod</dt><dd><code>text</code></dd></div><div><dt>Izhod</dt><dd><code>text</code></dd></div><div><dt>Izhodni format</dt><dd>json ali SSE</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Polje</th><th>Vrsta</th><th>Zahteva</th><th>Vrednosti in omejitve</th><th>Privzeto</th></tr></thead><tbody><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Tongyi-Zhiwen/QwenLong-L1-32B</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>message[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Najmanjše število elementov: 1</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].role</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Primeri: system, user, assistant, tool, function</div><div>Pogoji: Te vloge so izrecno predstavljene s tipi združljivosti v izvorni kodi; natančen nabor vlog ostaja odvisen od modela.</div><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].content</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string|content_part[]|null</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].tool_calls</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>tool_call[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].tool_call_id</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Velja, ko: role=tool; uporabite dejansko vrnjeni ID</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].name</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].reasoning_content</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Velja, ko: Pošljite nazaj dejansko vrnjeno sklepanje, kadar ga ta model uporablja</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].reasoning_details</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>object|array</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>integer</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Najmanj: 1</div><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">max_completion_tokens</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>integer</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Najmanj: 1</div><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>boolean</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"known\"><span class=\"card-cell-label\">Privzeto</span>false</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">stream_options.include_usage</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>boolean</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">temperature</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>number</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">top_p</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>number</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">stop</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string|string[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tools</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>function_tool[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tools[].type</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>function</div><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tools[].function.name</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Velja, ko: podano je funkcijsko orodje</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tools[].function.description</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tools[].function.parameters</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>JSON_schema</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">tool_choice</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string|object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">parallel_tool_calls</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>boolean</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">response_format</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">reasoning_effort</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">reasoning</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">service_tier</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_compatibility\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">instructions</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Polje združljivosti</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">functions</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>function[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">function_call</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string|object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"model_dependent\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">prompt_cache_options</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div class=\"note-s\">Odvisno od modela</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">modalities</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>text</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">provider</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>object</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Pogoji: provider.options je na tej besedilni poti Ultra zavrnjen</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">cache_control.ttl</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Pogoji: 1h je zavrnjen na dejanskih mestih za predpomnjenje pozivov</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr></tbody></table></div><details class=\"card-about\" data-material-combinations><summary>Kombinacije vhodnih gradiv</summary><p class=\"note-s\"><b>Besedilo</b> · Besedilo UTF8</p><p class=\"note-s\"><code>messages[].content</code></p></details><details class=\"note-s\" data-method-contract><summary>Parametri in življenjski cikel metode</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Specifikacija</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>model, messages</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>messages</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>polje sporočil s strukturo role/content</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>file_material</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>dejanski dokument UTF-8 je vstavljen kot dobesedno besedilo; ID datoteke se ne izpeljuje</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional_controls</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>stream, temperature, top_p, stop, max_tokens, max_completion_tokens, reasoning, response_format, tools, tool_choice</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>control_scope</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>odvisno od modela; uporabniška funkcijska orodja se razlikujejo od orodij, ki jih izvaja storitev</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>output_modalities</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>hosted_operations</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>false</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>multimodal_input_binding</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>null</td></tr></tbody></table></div><p>Življenjski cikel: <code>synchronous_or_streamed</code></p><p class=\"note-s\">Pošljite natančen ID modela skupaj z messages.</p><p class=\"note-s\">Dolžina konteksta ni zgornja meja izhoda.</p><p class=\"note-s\">Besedilna datoteka lahko poda dobesedno besedilo; slikovni, zvočni vhodi in vhodi z datotečnimi objekti potrebujejo natančno vezavo.</p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Cenik</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Tarifni podatki ne dodajajo možnosti zahteve. Podprti parametri so navedeni pri izbrani metodi.</p><dl data-price-conditions><dt>Hitri način</dt><dd>Ni navedeno <span class=\"note-s\">Ko je izbran hitri način</span></dd><dt>Način flex</dt><dd>Ni navedeno <span class=\"note-s\">Ko je izbran način flex</span></dd><dt>Najvišja raven razmišljanja</dt><dd>Ni navedeno <span class=\"note-s\">Ko najvišja raven razmišljanja uporablja privzeto prilagoditev (default)</span></dd></dl></div><div data-declared-tariff-pricing><h4>Cene Ailoot</h4><h4>Cene po nastavitvah</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Nastavitev</th><th>Cenovna lestvica</th><th>Strošek</th></tr></thead><tbody><tr><th data-cell-label=\"Nastavitev\" scope=\"row\"><span class=\"card-cell-label\">Nastavitev</span>Osnovne cene za žetone</th><td data-cell-label=\"Cenovna lestvica\"><span class=\"card-cell-label\">Cenovna lestvica</span>Osnovna cena</td><td data-cell-label=\"Strošek\"><span class=\"card-cell-label\">Strošek</span><div><span>Vhod · Vhodni žetoni</span> <b>$0.00028</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Izhod · Izhodni žetoni</span> <b>$0.0012</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Branje predpomnilnika</span> <b>$0</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Zapis v predpomnilnik</span> <b>$0</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Zapis v predpomnilnik, 1 ura</span> <b>—</b> <span class=\"price-unit\">/ 1K žetonov</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot pred zahtevo rezervira ocenjeni znesek. Po rezultatu obračuna končni strošek na podlagi izmerjene porabe. Obračun pretakanja uporablja končni zapis porabe. <a href=\"/docs/sl/billing/reserve/\">Kako delujeta rezervacija in obračun →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Primeri zahtev</h3><h4>Ailoot Ultra · OpenAI Chat</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Primeri kode\"><button class=\"cg-tab\" id=\"model-code-979-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-979-panel-0\" aria-selected=\"true\" tabindex=\"0\">curl</button><button class=\"cg-tab\" id=\"model-code-979-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-979-panel-1\" aria-selected=\"false\" tabindex=\"-1\">Python SDK</button><button class=\"cg-tab\" id=\"model-code-979-tab-2\" role=\"tab\" type=\"button\" aria-controls=\"model-code-979-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Tok Python</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Kopiraj kodo\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-979-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-979-tab-0\"><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json,os\nfrom pathlib import Path\np=json.loads(&#39;{&quot;model&quot;: &quot;Tongyi-Zhiwen/QwenLong-L1-32B&quot;, &quot;messages&quot;: [{&quot;role&quot;: &quot;user&quot;, &quot;content&quot;: &quot;Explain the difference between an observation and a hypothesis in three sentences.&quot;}]}&#39;)\n\nPath(&quot;request.json&quot;).write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H &quot;Authorization: Bearer $AILOOT_API_KEY&quot; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - &lt;&lt;&#39;PY_RESULT&#39;\nimport json\nfrom pathlib import Path\nr=json.loads(Path(&quot;result.json&quot;).read_text())\nfor x in r.get(&quot;choices&quot;,[]):\n    if x.get(&quot;message&quot;,{}).get(&quot;content&quot;): print(x[&quot;message&quot;][&quot;content&quot;])\nPY_RESULT\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-979-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-979-tab-1\" hidden><pre data-lang=\"python\"><code>from openai import OpenAI\nimport os\n\nif not os.environ.get(&quot;AILOOT_API_KEY&quot;, &quot;&quot;).strip(): raise SystemExit(&quot;Set AILOOT_API_KEY before making a request&quot;)\nclient=OpenAI(base_url=&quot;https://api.ailoot.ai/v1&quot;,api_key=os.environ[&quot;AILOOT_API_KEY&quot;],max_retries=0)\nresult=client.chat.completions.create(model=&#39;Tongyi-Zhiwen/QwenLong-L1-32B&#39;,messages=[{&quot;role&quot;:&quot;user&quot;,&quot;content&quot;:&quot;Explain observations and hypotheses in three sentences.&quot;}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=&quot;result&quot;):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + &quot;.json&quot;).write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=&quot;utf-8&quot;)\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b&quot;-_&quot;, validate=True)\n        ext = &quot;png&quot; if raw.startswith(b&quot;\\x89PNG\\r\\n\\x1a\\n&quot;) else &quot;jpg&quot; if raw.startswith(b&quot;\\xff\\xd8&quot;) else &quot;webp&quot; if raw[:4] == b&quot;RIFF&quot; and raw[8:12] == b&quot;WEBP&quot; else suffix\n        file = Path(stem + &quot;-&quot; + label + &quot;.&quot; + ext)\n        file.write_bytes(raw)\n        print(&quot;Saved&quot;, file)\n    for index, block in enumerate(data.get(&quot;content&quot;) or []):\n        print(&quot;Content&quot;, index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(&quot;choices&quot;) or []:\n        print(&quot;Choice&quot;, choice.get(&quot;index&quot;), json.dumps(choice.get(&quot;message&quot;, choice.get(&quot;delta&quot;, {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(&quot;output&quot;) or []):\n        print(&quot;Output&quot;, index, json.dumps(item, ensure_ascii=False))\n        if item.get(&quot;type&quot;) == &quot;image_generation_call&quot; and item.get(&quot;result&quot;):\n            save_blob(item[&quot;result&quot;], item.get(&quot;output_format&quot;) or &quot;bin&quot;, &quot;output-&quot; + str(index))\n    for ci, candidate in enumerate(data.get(&quot;candidates&quot;) or []):\n        for pi, part in enumerate((candidate.get(&quot;content&quot;) or {}).get(&quot;parts&quot;) or []):\n            print(&quot;Candidate/part&quot;, ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(&quot;inlineData&quot;) or part.get(&quot;inline_data&quot;)\n            if blob and blob.get(&quot;data&quot;):\n                mime = blob.get(&quot;mimeType&quot;) or blob.get(&quot;mime_type&quot;)\n                suffix = {&quot;image/png&quot;:&quot;png&quot;, &quot;image/jpeg&quot;:&quot;jpg&quot;, &quot;image/webp&quot;:&quot;webp&quot;, &quot;audio/wav&quot;:&quot;wav&quot;, &quot;audio/mpeg&quot;:&quot;mp3&quot;, &quot;video/mp4&quot;:&quot;mp4&quot;}.get(mime, &quot;bin&quot;)\n                save_blob(blob[&quot;data&quot;], suffix, &quot;candidate-&quot; + str(ci) + &quot;-part-&quot; + str(pi))\n\nsave_result(result.to_dict(mode=&quot;json&quot;))\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-979-panel-2\" role=\"tabpanel\" aria-labelledby=\"model-code-979-tab-2\" hidden><pre data-lang=\"python\"><code>from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(&quot;AILOOT_API_KEY&quot;, &quot;&quot;).strip(): raise SystemExit(&quot;Set AILOOT_API_KEY before making a request&quot;)\nclient=OpenAI(base_url=&quot;https://api.ailoot.ai/v1&quot;,api_key=os.environ[&quot;AILOOT_API_KEY&quot;],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=&quot;result&quot;):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + &quot;.json&quot;).write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=&quot;utf-8&quot;)\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b&quot;-_&quot;, validate=True)\n        ext = &quot;png&quot; if raw.startswith(b&quot;\\x89PNG\\r\\n\\x1a\\n&quot;) else &quot;jpg&quot; if raw.startswith(b&quot;\\xff\\xd8&quot;) else &quot;webp&quot; if raw[:4] == b&quot;RIFF&quot; and raw[8:12] == b&quot;WEBP&quot; else suffix\n        file = Path(stem + &quot;-&quot; + label + &quot;.&quot; + ext)\n        file.write_bytes(raw)\n        print(&quot;Saved&quot;, file)\n    for index, block in enumerate(data.get(&quot;content&quot;) or []):\n        print(&quot;Content&quot;, index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(&quot;choices&quot;) or []:\n        print(&quot;Choice&quot;, choice.get(&quot;index&quot;), json.dumps(choice.get(&quot;message&quot;, choice.get(&quot;delta&quot;, {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(&quot;output&quot;) or []):\n        print(&quot;Output&quot;, index, json.dumps(item, ensure_ascii=False))\n        if item.get(&quot;type&quot;) == &quot;image_generation_call&quot; and item.get(&quot;result&quot;):\n            save_blob(item[&quot;result&quot;], item.get(&quot;output_format&quot;) or &quot;bin&quot;, &quot;output-&quot; + str(index))\n    for ci, candidate in enumerate(data.get(&quot;candidates&quot;) or []):\n        for pi, part in enumerate((candidate.get(&quot;content&quot;) or {}).get(&quot;parts&quot;) or []):\n            print(&quot;Candidate/part&quot;, ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(&quot;inlineData&quot;) or part.get(&quot;inline_data&quot;)\n            if blob and blob.get(&quot;data&quot;):\n                mime = blob.get(&quot;mimeType&quot;) or blob.get(&quot;mime_type&quot;)\n                suffix = {&quot;image/png&quot;:&quot;png&quot;, &quot;image/jpeg&quot;:&quot;jpg&quot;, &quot;image/webp&quot;:&quot;webp&quot;, &quot;audio/wav&quot;:&quot;wav&quot;, &quot;audio/mpeg&quot;:&quot;mp3&quot;, &quot;video/mp4&quot;:&quot;mp4&quot;}.get(mime, &quot;bin&quot;)\n                save_blob(blob[&quot;data&quot;], suffix, &quot;candidate-&quot; + str(ci) + &quot;-part-&quot; + str(pi))\n\nwith client.chat.completions.stream(model=&#39;Tongyi-Zhiwen/QwenLong-L1-32B&#39;,messages=[{&quot;role&quot;:&quot;user&quot;,&quot;content&quot;:&quot;Explain observations and hypotheses in three sentences.&quot;}]) as stream:\n    with Path(&quot;stream-events.jsonl&quot;).open(&quot;w&quot;,encoding=&quot;utf-8&quot;) as log:\n        for event in stream:\n            payload=event.to_dict(mode=&quot;json&quot;)\n            log.write(json.dumps(payload,ensure_ascii=False)+&quot;\\n&quot;); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode=&quot;json&quot;),&quot;stream-result&quot;)\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Prejmi in shrani rezultate</h3><h4>Ailoot Ultra · OpenAI Chat</h4><p class=\"note-s\">json ali SSE</p><div class=\"card-result-process\" data-all-results><h5>Ohrani vse dokončane rezultate</h5><p class=\"note-s\">Shranite vsak v celoti vrnjen odgovor, datoteko in del vsebine.</p><p class=\"note-s\">Ohranite vsako možnost odgovora ter njeno vsebino, klice orodij in sklepanje. V SSE sestavite delne spremembe po indeksu možnosti/orodja ter ohranite končni razlog zaključka in podatke o porabi.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Če je treba preveriti izvirni odgovor</h5><p class=\"note-s\">Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan.</p></div><details class=\"card-about\" data-output-fields><summary>Polja odgovora</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Polje</th><th>Vrsta</th></tr></thead><tbody><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].index</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>integer</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].message.content</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string|null</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].message.tool_calls</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>tool_call[]</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].message.reasoning_content</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].message.reasoning_details</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>object|array</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">choices[].finish_reason</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string|null</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>object</td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>Napake in naslednji koraki</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>Odgovor</th><th>Pogoj</th><th>Naslednji korak</th></tr></thead><tbody><tr><th data-cell-label=\"Odgovor\" scope=\"row\"><span class=\"card-cell-label\">Odgovor</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"Pogoj\"><span class=\"card-cell-label\">Pogoj</span>Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra</td><td data-cell-label=\"Naslednji korak\"><span class=\"card-cell-label\">Naslednji korak</span>Pred novo zahtevo za ustvarjanje popravite navedena polja.</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Druga imena</h3><h4>Druga imena modelov</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;route=Ultra&amp;caller=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;fmt=chat\"><code>Tongyi-Zhiwen/QwenLong-L1-32B</code></a></span></p><h4>Druga imena poti metod</h4><p class=\"note-s\">Uporabite zgoraj navedene poti metod.</p><h4>Povezani ID-ji za klic</h4><p class=\"note-s\"><a href=\"#m=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;route=Ultra&amp;caller=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;fmt=chat\"><code>Tongyi-Zhiwen/QwenLong-L1-32B</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "fmt": "chat",
        "http": "POST",
        "path": "/v1/chat/completions",
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|chat|/v1/chat/completions|Tongyi-Zhiwen%2FQwenLong-L1-32B",
      "ordinal": 0,
      "rawMethod": {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "errors": [
              {
                "code": null,
                "condition": "Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra",
                "http_status": 400,
                "recovery": "Pred novo zahtevo za ustvarjanje popravite navedena polja.",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.",
              "Tool calls propose actions; the client application returns actual observations with the returned call ID.",
              "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "Besedilo UTF8"
              }
            ],
            "operation_modes": [
              "conversation",
              "function_tool_continuation",
              "streaming"
            ],
            "outputs": {
              "all_results": "Ohranite vsako možnost odgovora ter njeno vsebino, klice orodij in sklepanje. V SSE sestavite delne spremembe po indeksu možnosti/orodja ter ohranite končni razlog zaključka in podatke o porabi.",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "choices[].index",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "choices[].message.content",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "choices[].message.tool_calls",
                  "type": "tool_call[]"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_content",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_details",
                  "type": "object|array"
                },
                {
                  "description": null,
                  "name": "choices[].finish_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "json ali SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Tongyi-Zhiwen/QwenLong-L1-32B"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "model_dependent",
                "conditions": "Te vloge so izrecno predstavljene s tipi združljivosti v izvorni kodi; natančen nabor vlog ostaja odvisen od modela.",
                "default": null,
                "default_known": false,
                "enum": [
                  "system",
                  "user",
                  "assistant",
                  "tool",
                  "function"
                ],
                "enum_exhaustive": false,
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": false,
                "type": "string|content_part[]|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_calls",
                "required": false,
                "type": "tool_call[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_call_id",
                "required": false,
                "type": "string",
                "when": "role=tool; uporabite dejansko vrnjeni ID"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].name",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_content",
                "required": false,
                "type": "string",
                "when": "Pošljite nazaj dejansko vrnjeno sklepanje, kadar ga ta model uporablja"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_details",
                "required": false,
                "type": "object|array"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_completion_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stream_options.include_usage",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stop",
                "required": false,
                "type": "string|string[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools",
                "required": false,
                "type": "function_tool[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": [
                  "function"
                ],
                "enum_known": true,
                "name": "tools[].type",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.name",
                "required": true,
                "type": "string",
                "when": "podano je funkcijsko orodje"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.description",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.parameters",
                "required": false,
                "type": "JSON_schema"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tool_choice",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "parallel_tool_calls",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "response_format",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning_effort",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "service_tier",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_compatibility",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "instructions",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "functions",
                "required": false,
                "type": "function[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "function_call",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "prompt_cache_options",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "text"
                ],
                "enum_known": true,
                "name": "modalities",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "conditions": "provider.options je na tej besedilni poti Ultra zavrnjen",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "conditions": "1h je zavrnjen na dejanskih mestih za predpomnjenje pozivov",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "cache_control.ttl",
                "required": false,
                "type": "string"
              }
            ],
            "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.",
            "unsupported": [
              "additional models/models list",
              "plugins",
              "route",
              "hosted tools; ordinary client function tools remain separate",
              "non-text output modalities",
              "provider.options overrides",
              "one-hour prompt-cache TTL"
            ]
          },
          "hints": [
            "Pošljite natančen ID modela skupaj z messages.",
            "Dolžina konteksta ni zgornja meja izhoda.",
            "Besedilna datoteka lahko poda dobesedno besedilo; slikovni, zvočni vhodi in vhodi z datotečnimi objekti potrebujejo natančno vezavo."
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "odvisno od modela; uporabniška funkcijska orodja se razlikujejo od orodij, ki jih izvaja storitev",
            "file_material": "dejanski dokument UTF-8 je vstavljen kot dobesedno besedilo; ID datoteke se ne izpeljuje",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "polje sporočil s strukturo role/content",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream",
              "temperature",
              "top_p",
              "stop",
              "max_tokens",
              "max_completion_tokens",
              "reasoning",
              "response_format",
              "tools",
              "tool_choice"
            ],
            "output_modalities": [
              "text"
            ],
            "required": [
              "model",
              "messages"
            ]
          },
          "lifecycle": {
            "mode": "synchronous_or_streamed",
            "unknown": "preserve original request id; no generic chat job retrieval path"
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/chat/completions"
          },
          "method_aliases": [],
          "operation_modes": [
            "text_chat"
          ],
          "output": {
            "content": "choices[].message.content or stream delta",
            "family": "text",
            "format": "json or supported SSE",
            "tool_calls": "retain actual returned function calls"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Osnovne cene za žetone",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"Tongyi-Zhiwen/QwenLong-L1-32B\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n    if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n",
            "label": "curl · retained exact creation",
            "language": "bash"
          },
          {
            "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='Tongyi-Zhiwen/QwenLong-L1-32B',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n",
            "label": "Python SDK · all choices",
            "language": "python"
          },
          {
            "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='Tongyi-Zhiwen/QwenLong-L1-32B',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n    with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n        for event in stream:\n            payload=event.to_dict(mode=\"json\")\n            log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n",
            "label": "Python SDK streaming · all events",
            "language": "python"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "in": 0.28,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 1.2,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.00028000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.00000028",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0.0012000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000012",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
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    },
    {
      "html": "<div class=\"sheet-head\"><span class=\"mav\" aria-hidden=\"true\">•</span><h2 id=\"sheet-title\">QwenLong L1 32B</h2><button class=\"icon-btn\" type=\"button\" data-close-sheet aria-label=\"Zapri\">×</button></div><div class=\"idline\"><span>Drugo /</span><code>Tongyi-Zhiwen/QwenLong-L1-32B</code><button type=\"button\" id=\"copy-id\">Kopiraj ID</button></div><nav class=\"card-jump-nav\" aria-label=\"Razdelki kartice modela\"><button type=\"button\" data-card-jump=\"overview\">Začetek</button><button type=\"button\" data-card-jump=\"methods\">Vhodi in metode</button><button type=\"button\" data-card-jump=\"pricing\">Cenik</button><button type=\"button\" data-card-jump=\"examples\">Primeri</button><button type=\"button\" data-card-jump=\"results\">Rezultati</button><button type=\"button\" data-card-jump=\"aliases\">Druga imena</button></nav><div class=\"card-method-tabs\" role=\"tablist\" aria-label=\"Metode API\"><button type=\"button\" role=\"tab\" tabindex=\"-1\" aria-controls=\"card-method-content\" aria-selected=\"false\" id=\"card-method-tab-0\" data-card-method=\"Ultra|chat|/v1/chat/completions|Tongyi-Zhiwen%2FQwenLong-L1-32B\">Chat</button><button type=\"button\" role=\"tab\" tabindex=\"0\" aria-controls=\"card-method-content\" aria-selected=\"true\" id=\"card-method-tab-1\" data-card-method=\"Ultra|messages|/v1/messages|Tongyi-Zhiwen%2FQwenLong-L1-32B\">Messages</button></div><div id=\"card-method-content\" role=\"tabpanel\" aria-labelledby=\"card-method-tab-1\"><section class=\"card-section\" data-card-section=\"overview\"><h3 tabindex=\"-1\">Začetek</h3><p class=\"mdesc-full\">QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje pri vprašanjih, utemeljenih v dolgih dokumentih. Izhodišče DeepSeek-R1-Distill-Qwen-32B združuje s spodbujevalnim učenjem, osredotočenim na dokumente, za numerično, logično in meddokumentno sklepanje.</p><dl class=\"card-io\" data-card-io><div><dt>Dovoljeni vhodi</dt><dd>Besedilo</dd></div><div><dt>Rezultati</dt><dd>json · sse</dd></div></dl><details class=\"card-about\"><summary>O modelu</summary><p class=\"note-s\" data-model-method-boundary>Ta opis zajema zmožnosti modela. Vhodi, izhodi in možnosti, ki so na voljo v Ailoot, so spodaj navedeni za izbrano metodo.</p><div class=\"mabout\" id=\"m-about\"><p>Uvod: sklepanje na podlagi dolgih dokumentov</p><p>QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje z dolgim kontekstom. Njegov namen je odgovarjati na vprašanja, katerih dokazi so razpršeni po dokumentu ali več dokumentih, namesto da bi preprosto ponovil bližnji odlomek. Zgrajen je iz DeepSeek-R1-Distill-Qwen-32B in dodatno učen za sklepanje, utemeljeno v dokumentih. Priložite besedilo in vprašanje; model ustvari besedilno zaporedje sklepanja in odgovor. Skenirane strani, zvok in video pred tem besedilnim delovnim potekom potrebujejo ustrezen ločen korak pretvorbe.</p><p>Kako deluje učenje dolgega konteksta</p><p>Ogrodje QwenLong-L1 najprej pripravi politiko sklepanja z nadzorovanim finim prilagajanjem, nato pa s kurikulumom spodbujevalnega učenja povečuje dolžino konteksta. Retrospektivno vzorčenje, ki upošteva težavnost, med napredovanjem učenja prilagaja izbiro ponovno obravnavanih primerov. Proizvajalec združuje binarne nagrade za izid na podlagi pravil in modela ter uporablja optimizacijo politike glede na skupino za spodbujanje odgovorov, ki ostanejo utemeljeni v obsežnih dokazih. To opisuje učni pristop kontrolne točke; ne pomeni, da zunanji presojevalec vsak odgovor samodejno preveri.</p><p>Izdana različica</p><p>To je izvirna izdaja QwenLong-L1-32B. Ločeno poimenovani QwenLong-L1-32B-AWQ je kvantizirana izdaja INT4 in mora ohraniti lastno identiteto. Objavljena konfiguracija tega modela uporablja arhitekturo vzročnega jezikovnega modela Qwen2 s 64 plastmi in utežmi bfloat16. Specializacija modela za dokumente je za izbiro pomembnejša od obravnave imena 32B kot dokaza, da bo vsaka splošnonamenska naloga izboljšana.</p><p>Priprava vprašanja o dokumentu</p><p>Proizvajalčev primer dokument loči od vprašanja z izrecnimi besedilnimi razmejevalniki in za sklepanjem zahteva prepoznavno frazo končnega odgovora. Sledite tej strukturi: priložite ustrezno telo dokumenta, ohranite berljive naslove in tabele ter zastavite eno konkretno vprašanje. Pri izračunu iz poročila ohranite enote, obdobja poročanja in oznake tabel, nato zahtevajte formulo, uporabljene vrednosti in končni rezultat. Pri primerjavi politik dokumenta označite z A in B ter zahtevajte tabelo ujemajočih se pravil, razlik in podpornega razdelka za vsako vrstico. To so avtorsko oblikovane uporabe dokumentiranih numeričnih in meddokumentnih zmožnosti.</p><p>Primer ločeno razčleni besedilo sklepanja in končnega odgovora. Uporablja proračun ustvarjanja 10.000 žetonov, parameter temperature z vrednostjo 0.7 in top_p 0.95; to so nastavitve primera, ne razglašena največja dolžina izhoda. Kartica prikazuje tudi izbirno sistemsko sporočilo za nastavitev identitete. Ohranite lastna navodila za pozive tega modela, namesto da priporočila druge kontrolne točke uvažate zgolj zato, ker je del njegovega izvora.</p><p>Obdelava dolgih dokumentov</p><p>Tongyi Lab preverja dolžine konteksta do 131.072 žetonov z YaRN in priporoča razširitev, kadar skupni vhod in izhod bistveno presegata 32.768 žetonov. Njegovi primeri opisujejo faktor štiri ali manjši faktor, na primer dva za obremenitev 65.536 žetonov. Statična razširitev lahko poslabša delovanje pri krajšem besedilu, zato kartica odsvetuje njeno omogočanje, kadar običajne zahteve ostanejo znotraj 32.768 žetonov. Objavljena konfiguracija navaja 131.072 položajev, vendar nima omogočenega polja rope_scaling; konfiguracijo in proizvajalčev pogojni postopek dolgega konteksta je zato treba preveriti skupaj.</p><p>Dolg vhod še vedno potrebuje prostor za sklepanje in odgovor. Začnite z odlomki, potrebnimi za vprašanje, odstranite ponavljajoče se glave in navigacijsko besedilo ter ohranite identifikatorje strani ali razdelkov. V rezultatu zahtevajte reference na dokaze, da lahko pregledovalec sledi sklepu nazaj do priloženega gradiva. Velika dodelitev konteksta pomaga vključiti več dokazov v eno zahtevo; ne zagotavlja popolnega priklica vsake podrobnosti.</p><p>Kaj zajema učenje na dokumentih</p><p>DocQA-RL-1.6K vsebuje 1.600 učnih problemov s treh področij sklepanja: 600 numeričnih vprašanj iz dolgih specializiranih dokumentov, kot so finančna poročila; 600 logičnih vprašanj z več izbirami o pravnih, finančnih, zavarovalniških in proizvodnih dokumentih; ter 400 večstopenjskih primerov, ki povezujejo dokaze med viri. Zato je model ustrezen kandidat za računanje iz poročil, razlago pravil in vprašanja, ki potrebujejo več podpornih odlomkov. Učna področja opisujejo izkušnje s temi nalogami, ne strokovne certifikacije ali zajamčenih sklepov.</p><p>Praktični izhod in omejitve</p><p>Izberite odgovor, ki ga je mogoče preveriti: izračunano vrednost z enotami, primerjavo pravil z referencami razdelkov ali kratek sklep z verigo podpornih dejstev. Če dokument ne vsebuje zahtevanega datuma ali definicije, zahtevajte, da model določi manjkajoče dokaze, namesto da jih izmisli. Gradiva ob izdaji se osredotočajo na odgovarjanje na vprašanja o dokumentih in ne določajo namenske pogodbe za klicanje orodij ali ločene stroge zgornje meje izhoda. Odgovore obravnavajte kot utemeljene osnutke ter izračune, reference in razlage preverite s priloženimi dokumenti.</p></div></details></section><section class=\"card-section\" data-card-section=\"methods\"><h3 tabindex=\"-1\">Na voljo v Ailoot · vhodi in metode</h3><details class=\"card-method\" open><summary><b>Ailoot Ultra · Anthropic Messages</b> <code>POST /v1/messages</code></summary><dl class=\"method-capabilities\"><div><dt>Vhod</dt><dd><code>text</code></dd></div><div><dt>Izhod</dt><dd><code>json</code>, <code>sse</code></dd></div><div><dt>Izhodni format</dt><dd>JSON ali SSE</dd></div></dl><div class=\"tw\" data-card-parameters data-typed-parameters><table><thead><tr><th>Polje</th><th>Vrsta</th><th>Zahteva</th><th>Vrednosti in omejitve</th><th>Privzeto</th></tr></thead><tbody><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>Tongyi-Zhiwen/QwenLong-L1-32B</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>message[]</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].role</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span><div>user, assistant</div></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">messages[].content</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>string</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">max_tokens</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>integer</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Obvezno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"unspecified\"><span class=\"card-cell-label\">Privzeto</span>—</td></tr><tr data-parameter-availability=\"source_interface\"><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">stream</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span><code>boolean</code></td><td data-cell-label=\"Zahteva\"><span class=\"card-cell-label\">Zahteva</span>Izbirno</td><td data-cell-label=\"Vrednosti in omejitve\"><span class=\"card-cell-label\">Vrednosti in omejitve</span></td><td data-cell-label=\"Privzeto\" data-default=\"known\"><span class=\"card-cell-label\">Privzeto</span>false</td></tr></tbody></table></div><details class=\"card-about\" data-material-combinations><summary>Kombinacije vhodnih gradiv</summary><p class=\"note-s\"><b>Besedilo</b> · Besedilo UTF-8</p><p class=\"note-s\"><code>niz messages[].content</code></p></details><details class=\"note-s\" data-method-contract><summary>Parametri in življenjski cikel metode</summary><div class=\"tw\" data-card-table=\"contract\"><table><thead><tr><th>Parameter</th><th>Specifikacija</th></tr></thead><tbody><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>content_type</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>application/json</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>required</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>model, messages, max_tokens</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>optional_controls</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>stream</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>material_types</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>text</td></tr><tr><th data-cell-label=\"Parameter\" scope=\"row\"><span class=\"card-cell-label\">Parameter</span><code>text_file_material</code></th><td data-cell-label=\"Specifikacija\"><span class=\"card-cell-label\">Specifikacija</span>Preberite dejanski dokument UTF-8 in njegovo besedilo vstavite v navedeni vhodni niz ali niz vsebine sporočila.</td></tr></tbody></table></div><p>Življenjski cikel: <code>synchronous_or_streamed</code></p></details></details></section><section class=\"card-section\" data-card-section=\"pricing\"><h3 tabindex=\"-1\">Cenik</h3><div data-native-semantic-method=\"v1\" data-tariff-reference-only><p class=\"note-s\" data-rate-support-note>Tarifni podatki ne dodajajo možnosti zahteve. Podprti parametri so navedeni pri izbrani metodi.</p><dl data-price-conditions><dt>Hitri način</dt><dd>Ni navedeno <span class=\"note-s\">Ko je izbran hitri način</span></dd><dt>Način flex</dt><dd>Ni navedeno <span class=\"note-s\">Ko je izbran način flex</span></dd><dt>Najvišja raven razmišljanja</dt><dd>Ni navedeno <span class=\"note-s\">Ko najvišja raven razmišljanja uporablja privzeto prilagoditev (default)</span></dd></dl></div><div data-declared-tariff-pricing><h4>Cene Ailoot</h4><h4>Cene po nastavitvah</h4><div class=\"tw\" data-pricing-profiles><table><thead><tr><th>Nastavitev</th><th>Cenovna lestvica</th><th>Strošek</th></tr></thead><tbody><tr><th data-cell-label=\"Nastavitev\" scope=\"row\"><span class=\"card-cell-label\">Nastavitev</span>Osnovne cene za žetone</th><td data-cell-label=\"Cenovna lestvica\"><span class=\"card-cell-label\">Cenovna lestvica</span>Osnovna cena</td><td data-cell-label=\"Strošek\"><span class=\"card-cell-label\">Strošek</span><div><span>Vhod · Vhodni žetoni</span> <b>$0.00028</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Izhod · Izhodni žetoni</span> <b>$0.0012</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Branje predpomnilnika</span> <b>$0</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Zapis v predpomnilnik</span> <b>$0</b> <span class=\"price-unit\">/ 1K žetonov</span></div><div><span>Vhod · Zapis v predpomnilnik, 1 ura</span> <b>—</b> <span class=\"price-unit\">/ 1K žetonov</span></div></td></tr></tbody></table></div></div><p class=\"note-s\">Ailoot pred zahtevo rezervira ocenjeni znesek. Po rezultatu obračuna končni strošek na podlagi izmerjene porabe. Obračun pretakanja uporablja končni zapis porabe. <a href=\"/docs/sl/billing/reserve/\">Kako delujeta rezervacija in obračun →</a></p></section><section class=\"card-section\" data-card-section=\"examples\"><h3 tabindex=\"-1\">Primeri zahtev</h3><h4>Ailoot Ultra · Anthropic Messages</h4><div class=\"code-group\"><div class=\"cg-bar\"><div class=\"cg-tabs\" role=\"tablist\" aria-label=\"Primeri kode\"><button class=\"cg-tab\" id=\"model-code-980-tab-0\" role=\"tab\" type=\"button\" aria-controls=\"model-code-980-panel-0\" aria-selected=\"true\" tabindex=\"0\">Popolno minimalno telo zahteve JSON</button><button class=\"cg-tab\" id=\"model-code-980-tab-1\" role=\"tab\" type=\"button\" aria-controls=\"model-code-980-panel-1\" aria-selected=\"false\" tabindex=\"-1\">curl · uporabite svoj dokument UTF-8</button><button class=\"cg-tab\" id=\"model-code-980-tab-2\" role=\"tab\" type=\"button\" aria-controls=\"model-code-980-panel-2\" aria-selected=\"false\" tabindex=\"-1\">Python · shranite celoten rezultat</button></div><div class=\"cg-tools\"><button class=\"cg-btn cg-copy\" type=\"button\" aria-label=\"Kopiraj kodo\"><svg class=\"cp\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><rect x=\"5.25\" y=\"5.25\" width=\"8.5\" height=\"8.5\" rx=\"1.75\"/><path d=\"M10.75 5.25V3.5a1.25 1.25 0 0 0-1.25-1.25H3.5A1.25 1.25 0 0 0 2.25 3.5v6a1.25 1.25 0 0 0 1.25 1.25h1.75\"/></svg><svg class=\"ok\" viewBox=\"0 0 16 16\" fill=\"none\" stroke=\"currentColor\" stroke-width=\"1.4\"><path d=\"m3 8.5 3.25 3.25L13 5\"/></svg></button></div></div><div class=\"cg-body\"><div class=\"cg-pane\" id=\"model-code-980-panel-0\" role=\"tabpanel\" aria-labelledby=\"model-code-980-tab-0\"><pre data-lang=\"json\"><code>{\n  &quot;model&quot;: &quot;Tongyi-Zhiwen/QwenLong-L1-32B&quot;,\n  &quot;max_tokens&quot;: 128,\n  &quot;messages&quot;: [\n    {\n      &quot;role&quot;: &quot;user&quot;,\n      &quot;content&quot;: &quot;Summarize the incident report.&quot;\n    }\n  ],\n  &quot;stream&quot;: false\n}</code></pre></div><div class=\"cg-pane\" id=\"model-code-980-panel-1\" role=\"tabpanel\" aria-labelledby=\"model-code-980-tab-1\" hidden><pre data-lang=\"bash\"><code>set -eu\n: &quot;${AILOOT_API_KEY:?Set your Ailoot API key}&quot;\n: &quot;${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}&quot;\nexport AILOOT_TEXT_FILE\npython3 - &lt;&lt;&#39;PY_REQUEST&#39;\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ[&#39;AILOOT_TEXT_FILE&#39;])\nif not source_file.is_file():\n    raise SystemExit(&#39;Set AILOOT_TEXT_FILE to your actual UTF-8 document&#39;)\ntext = source_file.read_text(encoding=&#39;utf-8&#39;)\nif not text.strip():\n    raise SystemExit(&#39;Choose a document containing text&#39;)\npayload = {&#39;model&#39;: &#39;Tongyi-Zhiwen/QwenLong-L1-32B&#39;, &#39;max_tokens&#39;: 128, &#39;messages&#39;: [{&#39;role&#39;: &#39;user&#39;, &#39;content&#39;: &#39;Summarize the incident report.&#39;}]}\npayload[&#39;messages&#39;][0][&#39;content&#39;] = &#39;Summarize this material and quote supporting source passages.\\n\\n&#39; + text\nPath(&#39;request.json&#39;).write_text(json.dumps(payload, ensure_ascii=False), encoding=&#39;utf-8&#39;)\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H &quot;x-api-key: $AILOOT_API_KEY&quot; -H &#39;anthropic-version: 2023-06-01&#39; -H &#39;Content-Type: application/json&#39; \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - &lt;&lt;&#39;PY_RESULT&#39;\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path(&#39;result.json&#39;).read_text(encoding=&#39;utf-8&#39;))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n</code></pre></div><div class=\"cg-pane\" id=\"model-code-980-panel-2\" role=\"tabpanel\" aria-labelledby=\"model-code-980-tab-2\" hidden><pre data-lang=\"python\"><code>import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ[&#39;AILOOT_TEXT_FILE&#39;])\nif not source_file.is_file():\n    raise SystemExit(&#39;Set AILOOT_TEXT_FILE to your actual UTF-8 document&#39;)\ntext = source_file.read_text(encoding=&#39;utf-8&#39;)\nif not text.strip():\n    raise SystemExit(&#39;Choose a document containing text&#39;)\npayload = {&#39;model&#39;: &#39;Tongyi-Zhiwen/QwenLong-L1-32B&#39;, &#39;max_tokens&#39;: 128, &#39;messages&#39;: [{&#39;role&#39;: &#39;user&#39;, &#39;content&#39;: &#39;Summarize the incident report.&#39;}]}\npayload[&#39;messages&#39;][0][&#39;content&#39;] = &#39;Summarize this material and quote supporting source passages.\\n\\n&#39; + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ[&#39;AILOOT_API_KEY&#39;]\nif not api_key.strip():\n    raise SystemExit(&#39;Set AILOOT_API_KEY before making a request&#39;)\nheaders = {&#39;x-api-key&#39;: &#39;PLACEHOLDER_KEY&#39;, &#39;anthropic-version&#39;: &#39;2023-06-01&#39;, &#39;Content-Type&#39;: &#39;application/json&#39;}\nheaders[&#39;x-api-key&#39;] = api_key\nrequest = Request(&#39;https://api.ailoot.ai/v1/messages&#39;, data=json.dumps(payload, ensure_ascii=False).encode(&#39;utf-8&#39;), headers=headers, method=&#39;POST&#39;)\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path(&#39;response-headers.txt&#39;).write_text(str(response.headers), encoding=&#39;utf-8&#39;)\nexcept HTTPError as error:\n    Path(&#39;result.json&#39;).write_bytes(error.read())\n    Path(&#39;response-headers.txt&#39;).write_text(str(error.headers), encoding=&#39;utf-8&#39;)\n    raise\nPath(&#39;result.json&#39;).write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path(&#39;result.json&#39;).read_text(encoding=&#39;utf-8&#39;))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n</code></pre></div></div></div></section><section class=\"card-section\" data-card-section=\"results\"><h3 tabindex=\"-1\">Prejmi in shrani rezultate</h3><h4>Ailoot Ultra · Anthropic Messages</h4><p class=\"note-s\">JSON ali SSE</p><div class=\"card-result-process\" data-all-results><h5>Ohrani vse dokončane rezultate</h5><p class=\"note-s\">Shranite vsak v celoti vrnjen odgovor, datoteko in del vsebine.</p><p class=\"note-s\">Ohranite vse vsebinske bloke, podpise sklepanja in dejanske ID uporabe orodij. Sestavite vse delne spremembe blokov SSE; prvi besedilni blok ni celoten izhod.</p></div><div class=\"card-result-process\" data-unknown-recovery><h5>Če je treba preveriti izvirni odgovor</h5><p class=\"note-s\">Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan.</p></div><details class=\"card-about\" data-output-fields><summary>Polja odgovora</summary><div class=\"tw\" data-card-table=\"output\"><table><thead><tr><th>Polje</th><th>Vrsta</th></tr></thead><tbody><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">id</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">model</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">content[]</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>text|thinking|tool_use|other content block</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">stop_reason</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>string|null</td></tr><tr><th data-cell-label=\"Polje\" scope=\"row\"><span class=\"card-cell-label\">Polje</span><code class=\"card-field-name\">usage</code></th><td data-cell-label=\"Vrsta\" data-field-type><span class=\"card-cell-label\">Vrsta</span>object</td></tr></tbody></table></div></details><details class=\"card-about\" data-method-errors><summary>Napake in naslednji koraki</summary><div class=\"tw\" data-card-table=\"errors\"><table><thead><tr><th>Odgovor</th><th>Pogoj</th><th>Naslednji korak</th></tr></thead><tbody><tr><th data-cell-label=\"Odgovor\" scope=\"row\"><span class=\"card-cell-label\">Odgovor</span>400 · <code>invalid_request_error</code></th><td data-cell-label=\"Pogoj\"><span class=\"card-cell-label\">Pogoj</span>Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra</td><td data-cell-label=\"Naslednji korak\"><span class=\"card-cell-label\">Naslednji korak</span>Pred novo zahtevo za ustvarjanje popravite navedena polja.</td></tr></tbody></table></div></details></section><section class=\"card-section\" data-card-section=\"aliases\"><h3 tabindex=\"-1\">Druga imena</h3><h4>Druga imena modelov</h4><p class=\"note-s\"><span data-model-alias-route=\"Ultra\"><b>Ailoot Ultra</b> <a href=\"#m=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;route=Ultra&amp;caller=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;fmt=messages\"><code>Tongyi-Zhiwen/QwenLong-L1-32B</code></a></span></p><h4>Druga imena poti metod</h4><p class=\"note-s\">Uporabite zgoraj navedene poti metod.</p><h4>Povezani ID-ji za klic</h4><p class=\"note-s\"><a href=\"#m=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;route=Ultra&amp;caller=Tongyi-Zhiwen%2FQwenLong-L1-32B&amp;fmt=messages\"><code>Tongyi-Zhiwen/QwenLong-L1-32B</code></a></p></section></div>",
      "method_identity": {
        "effective_request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "fmt": "messages",
        "http": "POST",
        "path": "/v1/messages",
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra"
      },
      "method_key": "Ultra|messages|/v1/messages|Tongyi-Zhiwen%2FQwenLong-L1-32B",
      "ordinal": 1,
      "rawMethod": {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "headers": [
                "Authorization: Bearer",
                "x-api-key",
                "anthropic-version"
              ],
              "version_example": "2023-06-01"
            },
            "errors": [
              {
                "code": null,
                "condition": "Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra",
                "http_status": 400,
                "recovery": "Pred novo zahtevo za ustvarjanje popravite navedena polja.",
                "type": "invalid_request_error"
              }
            ],
            "example_body": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Tongyi-Zhiwen/QwenLong-L1-32B",
              "stream": false
            },
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "niz messages[].content",
                "required_material": "Besedilo UTF-8"
              }
            ],
            "operation_modes": [
              "synchronous_json",
              "streamed_SSE"
            ],
            "outputs": {
              "all_results": "Ohranite vse vsebinske bloke, podpise sklepanja in dejanske ID uporabe orodij. Sestavite vse delne spremembe blokov SSE; prvi besedilni blok ni celoten izhod.",
              "family": "protocol",
              "fields": [
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "content[]",
                  "type": "text|thinking|tool_use|other content block"
                },
                {
                  "description": null,
                  "name": "stop_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "JSON ali SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Tongyi-Zhiwen/QwenLong-L1-32B"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "user",
                  "assistant"
                ],
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.",
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "oneOf": [
                          {
                            "type": "string"
                          },
                          {
                            "items": {
                              "oneOf": [
                                {
                                  "properties": {
                                    "text": {
                                      "type": "string"
                                    },
                                    "type": {
                                      "const": "text"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "text"
                                  ],
                                  "type": "object"
                                },
                                {
                                  "properties": {
                                    "source": {
                                      "oneOf": [
                                        {
                                          "properties": {
                                            "type": {
                                              "const": "url"
                                            },
                                            "url": {
                                              "type": "string"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "url"
                                          ],
                                          "type": "object"
                                        },
                                        {
                                          "properties": {
                                            "data": {
                                              "type": "string"
                                            },
                                            "media_type": {
                                              "type": "string"
                                            },
                                            "type": {
                                              "const": "base64"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "media_type",
                                            "data"
                                          ],
                                          "type": "object"
                                        }
                                      ]
                                    },
                                    "type": {
                                      "const": "image"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "source"
                                  ],
                                  "type": "object"
                                }
                              ]
                            },
                            "type": "array"
                          }
                        ]
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "Tongyi-Zhiwen/QwenLong-L1-32B"
                  ],
                  "type": "string"
                },
                "stream": {
                  "default": false,
                  "type": "boolean"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Tongyi-Zhiwen/QwenLong-L1-32B",
              "stream": false
            },
            "unsupported": [
              "No query API key.",
              "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example."
            ]
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "stream"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ],
            "text_file_material": "Preberite dejanski dokument UTF-8 in njegovo besedilo vstavite v navedeni vhodni niz ali niz vsebine sporočila."
          },
          "lifecycle": {
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "job_read": null,
            "mode": "synchronous_or_streamed",
            "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/messages"
          },
          "output": {
            "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.",
            "family": "protocol",
            "format": "JSON or SSE"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Osnovne cene za žetone",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "{\n  \"model\": \"Tongyi-Zhiwen/QwenLong-L1-32B\",\n  \"max_tokens\": 128,\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"Summarize the incident report.\"\n    }\n  ],\n  \"stream\": false\n}",
            "label": "Complete minimal JSON body",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Tongyi-Zhiwen/QwenLong-L1-32B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n",
            "label": "curl · use your UTF-8 document",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Tongyi-Zhiwen/QwenLong-L1-32B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n",
            "label": "Python · save the complete result",
            "language": "python"
          }
        ],
        "family": "anthropic",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "messages",
        "http": "POST",
        "in": 0.28,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 1.2,
        "output": [
          "json",
          "sse"
        ],
        "path": "/v1/messages",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.00028000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.00000028",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0.0012000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000012",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          }
        ]
      }
    }
  ],
  "model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
  "nativeProvenance": {
    "input_facts_canonical_sha256": "aeacec120a3165988c301a6e79eebe48d7ccfe78fd4de09b7a12d8866c52fe90",
    "input_html_sha256": "2df9a1b65457fdd8212a0ff9f7ea36a01ac7dee7af3ec5bcc0366a36a3df060d",
    "private_audit_sha256": "71c03298639af42df0ff960349ab5e30a43325a4be1c758571ea78f9d0af94a7",
    "role": "historical-normalized-input-audit-hashes",
    "schema": "ailoot-native-model-provenance-v2"
  },
  "page": {
    "canonical": "https://ailoot.ai/models/sl/tongyi-zhiwen-qwenlong-l1-32b/",
    "description": "QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje pri vprašanjih, utemeljenih v dolgih dokumentih. Izhodišče DeepSeek-R1-Distill-Qwen-32B združuje s spodbujevalnim učenjem, osredotočenim na dokumente, za numerično, logično in meddokumentno sklepanje.",
    "locale": "sl",
    "md_url": "https://ailoot.ai/models/sl/tongyi-zhiwen-qwenlong-l1-32b/index.md",
    "title": "QwenLong L1 32B — Ailoot",
    "url": "https://ailoot.ai/models/sl/tongyi-zhiwen-qwenlong-l1-32b/"
  },
  "practicalHtml": "<h3>Praktična naloga</h3><p>Tehnični primer v angleščini</p><pre><code>Connect evidence across report sections\n\nDocument section 1 says 240 units were shipped. Section 4 says 30 shipped units were returned before month end. Appendix A says net shipped units equal shipped minus returned units. Calculate net shipped units for the month, cite every section needed and state whether revenue can be calculated from these facts. End with a clearly labelled final answer.</code></pre><h4>Pričakovani rezultat</h4><pre><code>A source-linked formula and calculation, a revenue-information limit and a labelled final result.</code></pre><h4>Preverjanje rezultata</h4><pre><code>Check that all three source sections support the calculation and that a price or revenue value is not invented.</code></pre>",
  "practicalText": "Praktična naloga Tehnični primer v angleščini Connect evidence across report sections Document section 1 says 240 units were shipped. Section 4 says 30 shipped units were returned before month end. Appendix A says net shipped units equal shipped minus returned units. Calculate net shipped units for the month, cite every section needed and state whether revenue can be calculated from these facts. End with a clearly labelled final answer. Pričakovani rezultat A source-linked formula and calculation, a revenue-information limit and a labelled final result. Preverjanje rezultata Check that all three source sections support the calculation and that a price or revenue value is not invented.",
  "rawModel": {
    "about": "Uvod: sklepanje na podlagi dolgih dokumentov\n\nQwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje z dolgim kontekstom. Njegov namen je odgovarjati na vprašanja, katerih dokazi so razpršeni po dokumentu ali več dokumentih, namesto da bi preprosto ponovil bližnji odlomek. Zgrajen je iz DeepSeek-R1-Distill-Qwen-32B in dodatno učen za sklepanje, utemeljeno v dokumentih. Priložite besedilo in vprašanje; model ustvari besedilno zaporedje sklepanja in odgovor. Skenirane strani, zvok in video pred tem besedilnim delovnim potekom potrebujejo ustrezen ločen korak pretvorbe.\n\nKako deluje učenje dolgega konteksta\n\nOgrodje QwenLong-L1 najprej pripravi politiko sklepanja z nadzorovanim finim prilagajanjem, nato pa s kurikulumom spodbujevalnega učenja povečuje dolžino konteksta. Retrospektivno vzorčenje, ki upošteva težavnost, med napredovanjem učenja prilagaja izbiro ponovno obravnavanih primerov. Proizvajalec združuje binarne nagrade za izid na podlagi pravil in modela ter uporablja optimizacijo politike glede na skupino za spodbujanje odgovorov, ki ostanejo utemeljeni v obsežnih dokazih. To opisuje učni pristop kontrolne točke; ne pomeni, da zunanji presojevalec vsak odgovor samodejno preveri.\n\nIzdana različica\n\nTo je izvirna izdaja QwenLong-L1-32B. Ločeno poimenovani QwenLong-L1-32B-AWQ je kvantizirana izdaja INT4 in mora ohraniti lastno identiteto. Objavljena konfiguracija tega modela uporablja arhitekturo vzročnega jezikovnega modela Qwen2 s 64 plastmi in utežmi bfloat16. Specializacija modela za dokumente je za izbiro pomembnejša od obravnave imena 32B kot dokaza, da bo vsaka splošnonamenska naloga izboljšana.\n\nPriprava vprašanja o dokumentu\n\nProizvajalčev primer dokument loči od vprašanja z izrecnimi besedilnimi razmejevalniki in za sklepanjem zahteva prepoznavno frazo končnega odgovora. Sledite tej strukturi: priložite ustrezno telo dokumenta, ohranite berljive naslove in tabele ter zastavite eno konkretno vprašanje. Pri izračunu iz poročila ohranite enote, obdobja poročanja in oznake tabel, nato zahtevajte formulo, uporabljene vrednosti in končni rezultat. Pri primerjavi politik dokumenta označite z A in B ter zahtevajte tabelo ujemajočih se pravil, razlik in podpornega razdelka za vsako vrstico. To so avtorsko oblikovane uporabe dokumentiranih numeričnih in meddokumentnih zmožnosti.\n\nPrimer ločeno razčleni besedilo sklepanja in končnega odgovora. Uporablja proračun ustvarjanja 10.000 žetonov, parameter temperature z vrednostjo 0.7 in top_p 0.95; to so nastavitve primera, ne razglašena največja dolžina izhoda. Kartica prikazuje tudi izbirno sistemsko sporočilo za nastavitev identitete. Ohranite lastna navodila za pozive tega modela, namesto da priporočila druge kontrolne točke uvažate zgolj zato, ker je del njegovega izvora.\n\nObdelava dolgih dokumentov\n\nTongyi Lab preverja dolžine konteksta do 131.072 žetonov z YaRN in priporoča razširitev, kadar skupni vhod in izhod bistveno presegata 32.768 žetonov. Njegovi primeri opisujejo faktor štiri ali manjši faktor, na primer dva za obremenitev 65.536 žetonov. Statična razširitev lahko poslabša delovanje pri krajšem besedilu, zato kartica odsvetuje njeno omogočanje, kadar običajne zahteve ostanejo znotraj 32.768 žetonov. Objavljena konfiguracija navaja 131.072 položajev, vendar nima omogočenega polja rope_scaling; konfiguracijo in proizvajalčev pogojni postopek dolgega konteksta je zato treba preveriti skupaj.\n\nDolg vhod še vedno potrebuje prostor za sklepanje in odgovor. Začnite z odlomki, potrebnimi za vprašanje, odstranite ponavljajoče se glave in navigacijsko besedilo ter ohranite identifikatorje strani ali razdelkov. V rezultatu zahtevajte reference na dokaze, da lahko pregledovalec sledi sklepu nazaj do priloženega gradiva. Velika dodelitev konteksta pomaga vključiti več dokazov v eno zahtevo; ne zagotavlja popolnega priklica vsake podrobnosti.\n\nKaj zajema učenje na dokumentih\n\nDocQA-RL-1.6K vsebuje 1.600 učnih problemov s treh področij sklepanja: 600 numeričnih vprašanj iz dolgih specializiranih dokumentov, kot so finančna poročila; 600 logičnih vprašanj z več izbirami o pravnih, finančnih, zavarovalniških in proizvodnih dokumentih; ter 400 večstopenjskih primerov, ki povezujejo dokaze med viri. Zato je model ustrezen kandidat za računanje iz poročil, razlago pravil in vprašanja, ki potrebujejo več podpornih odlomkov. Učna področja opisujejo izkušnje s temi nalogami, ne strokovne certifikacije ali zajamčenih sklepov.\n\nPraktični izhod in omejitve\n\nIzberite odgovor, ki ga je mogoče preveriti: izračunano vrednost z enotami, primerjavo pravil z referencami razdelkov ali kratek sklep z verigo podpornih dejstev. Če dokument ne vsebuje zahtevanega datuma ali definicije, zahtevajte, da model določi manjkajoče dokaze, namesto da jih izmisli. Gradiva ob izdaji se osredotočajo na odgovarjanje na vprašanja o dokumentih in ne določajo namenske pogodbe za klicanje orodij ali ločene stroge zgornje meje izhoda. Odgovore obravnavajte kot utemeljene osnutke ter izračune, reference in razlage preverite s priloženimi dokumenti.",
    "alias_of": null,
    "aliases": [],
    "author": "Other",
    "available": null,
    "canonical_model": "Tongyi-Zhiwen/QwenLong-L1-32B",
    "capabilities": {
      "context_length": 128000,
      "manufacturer_input": [],
      "manufacturer_output": []
    },
    "card_routes": [
      {
        "label": "Ultra",
        "rates": [
          {
            "amount": "0.00028000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.00000028",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0.0012000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000012",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          }
        ],
        "summary": "Celoten cenik konfiguracije je v podrobnostih."
      }
    ],
    "ctx": null,
    "display_name": "QwenLong L1 32B",
    "entity_type": "model",
    "formats": [
      "chat",
      "messages"
    ],
    "id": "Tongyi-Zhiwen/QwenLong-L1-32B",
    "input": [
      "text"
    ],
    "kind": "text",
    "max_out": null,
    "methods": [
      {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "all_results": "Keep every choice and its content/tool calls/reasoning. In SSE assemble deltas by choice/tool index, retain the final finish reason and usage.",
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "header": "Authorization: Bearer"
            },
            "errors": [
              {
                "code": null,
                "condition": "Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra",
                "http_status": 400,
                "recovery": "Pred novo zahtevo za ustvarjanje popravite navedena polja.",
                "type": "invalid_request_error"
              }
            ],
            "hints": [
              "Model context is not an output cap.",
              "A model-dependent field needs the exact published model profile; unspecified defaults/enums are not guessed.",
              "Tool calls propose actions; the client application returns actual observations with the returned call ID.",
              "Guarded canonical keys must occur once; duplicate or case-varied model/tools/cap fields are rejected."
            ],
            "ignored_fields": [],
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/chat/completions"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "messages[].content",
                "required_material": "Besedilo UTF8"
              }
            ],
            "operation_modes": [
              "conversation",
              "function_tool_continuation",
              "streaming"
            ],
            "outputs": {
              "all_results": "Ohranite vsako možnost odgovora ter njeno vsebino, klice orodij in sklepanje. V SSE sestavite delne spremembe po indeksu možnosti/orodja ter ohranite končni razlog zaključka in podatke o porabi.",
              "family": "text",
              "fields": [
                {
                  "description": null,
                  "name": "choices[].index",
                  "type": "integer"
                },
                {
                  "description": null,
                  "name": "choices[].message.content",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "choices[].message.tool_calls",
                  "type": "tool_call[]"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_content",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "choices[].message.reasoning_details",
                  "type": "object|array"
                },
                {
                  "description": null,
                  "name": "choices[].finish_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "json ali SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Tongyi-Zhiwen/QwenLong-L1-32B"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "min_items": 1,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "model_dependent",
                "conditions": "Te vloge so izrecno predstavljene s tipi združljivosti v izvorni kodi; natančen nabor vlog ostaja odvisen od modela.",
                "default": null,
                "default_known": false,
                "enum": [
                  "system",
                  "user",
                  "assistant",
                  "tool",
                  "function"
                ],
                "enum_exhaustive": false,
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": false,
                "type": "string|content_part[]|null"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_calls",
                "required": false,
                "type": "tool_call[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].tool_call_id",
                "required": false,
                "type": "string",
                "when": "role=tool; uporabite dejansko vrnjeni ID"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].name",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_content",
                "required": false,
                "type": "string",
                "when": "Pošljite nazaj dejansko vrnjeno sklepanje, kadar ga ta model uporablja"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].reasoning_details",
                "required": false,
                "type": "object|array"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "minimum": 1,
                "name": "max_completion_tokens",
                "required": false,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stream_options.include_usage",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "temperature",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "top_p",
                "required": false,
                "type": "number"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "stop",
                "required": false,
                "type": "string|string[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools",
                "required": false,
                "type": "function_tool[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": [
                  "function"
                ],
                "enum_known": true,
                "name": "tools[].type",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.name",
                "required": true,
                "type": "string",
                "when": "podano je funkcijsko orodje"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.description",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tools[].function.parameters",
                "required": false,
                "type": "JSON_schema"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "tool_choice",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "parallel_tool_calls",
                "required": false,
                "type": "boolean"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "response_format",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning_effort",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "reasoning",
                "required": false,
                "type": "object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "service_tier",
                "required": false,
                "type": "string"
              },
              {
                "availability": "source_compatibility",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "instructions",
                "required": false,
                "type": "string"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "functions",
                "required": false,
                "type": "function[]"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "function_call",
                "required": false,
                "type": "string|object"
              },
              {
                "availability": "model_dependent",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "prompt_cache_options",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "text"
                ],
                "enum_known": true,
                "name": "modalities",
                "required": false,
                "type": "string[]"
              },
              {
                "availability": "source_interface",
                "conditions": "provider.options je na tej besedilni poti Ultra zavrnjen",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "provider",
                "required": false,
                "type": "object"
              },
              {
                "availability": "source_interface",
                "conditions": "1h je zavrnjen na dejanskih mestih za predpomnjenje pozivov",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "cache_control.ttl",
                "required": false,
                "type": "string"
              }
            ],
            "profile_binding": "Exact existing Ailoot model and method; interface constraints below do not assert provider qualification.",
            "unsupported": [
              "additional models/models list",
              "plugins",
              "route",
              "hosted tools; ordinary client function tools remain separate",
              "non-text output modalities",
              "provider.options overrides",
              "one-hour prompt-cache TTL"
            ]
          },
          "hints": [
            "Pošljite natančen ID modela skupaj z messages.",
            "Dolžina konteksta ni zgornja meja izhoda.",
            "Besedilna datoteka lahko poda dobesedno besedilo; slikovni, zvočni vhodi in vhodi z datotečnimi objekti potrebujejo natančno vezavo."
          ],
          "input": {
            "content_type": "application/json",
            "control_scope": "odvisno od modela; uporabniška funkcijska orodja se razlikujejo od orodij, ki jih izvaja storitev",
            "file_material": "dejanski dokument UTF-8 je vstavljen kot dobesedno besedilo; ID datoteke se ne izpeljuje",
            "hosted_operations": false,
            "material_types": [
              "text"
            ],
            "messages": "polje sporočil s strukturo role/content",
            "multimodal_input_binding": null,
            "optional_controls": [
              "stream",
              "temperature",
              "top_p",
              "stop",
              "max_tokens",
              "max_completion_tokens",
              "reasoning",
              "response_format",
              "tools",
              "tool_choice"
            ],
            "output_modalities": [
              "text"
            ],
            "required": [
              "model",
              "messages"
            ]
          },
          "lifecycle": {
            "mode": "synchronous_or_streamed",
            "unknown": "preserve original request id; no generic chat job retrieval path"
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/chat/completions"
          },
          "method_aliases": [],
          "operation_modes": [
            "text_chat"
          ],
          "output": {
            "content": "choices[].message.content or stream delta",
            "family": "text",
            "format": "json or supported SSE",
            "tool_calls": "retain actual returned function calls"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Osnovne cene za žetone",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\npython3 - <<'PY_REQUEST'\nimport json,os\nfrom pathlib import Path\np=json.loads('{\"model\": \"Tongyi-Zhiwen/QwenLong-L1-32B\", \"messages\": [{\"role\": \"user\", \"content\": \"Explain the difference between an observation and a hypothesis in three sentences.\"}]}')\n\nPath(\"request.json\").write_text(json.dumps(p,ensure_ascii=False))\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/chat/completions \\\n  -H \"Authorization: Bearer $AILOOT_API_KEY\" -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\nr=json.loads(Path(\"result.json\").read_text())\nfor x in r.get(\"choices\",[]):\n    if x.get(\"message\",{}).get(\"content\"): print(x[\"message\"][\"content\"])\nPY_RESULT\n",
            "label": "curl · retained exact creation",
            "language": "bash"
          },
          {
            "code": "from openai import OpenAI\nimport os\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nresult=client.chat.completions.create(model='Tongyi-Zhiwen/QwenLong-L1-32B',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}])\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nsave_result(result.to_dict(mode=\"json\"))\n",
            "label": "Python SDK · all choices",
            "language": "python"
          },
          {
            "code": "from openai import OpenAI\nimport os\nfrom pathlib import Path\n\nif not os.environ.get(\"AILOOT_API_KEY\", \"\").strip(): raise SystemExit(\"Set AILOOT_API_KEY before making a request\")\nclient=OpenAI(base_url=\"https://api.ailoot.ai/v1\",api_key=os.environ[\"AILOOT_API_KEY\"],max_retries=0)\nimport base64, json\nfrom pathlib import Path\n\ndef save_result(data, stem=\"result\"):\n    # Keep every field, including usage, IDs, reasoning and tool requests.\n    Path(stem + \".json\").write_text(json.dumps(data, ensure_ascii=False, indent=2), encoding=\"utf-8\")\n    print(json.dumps(data, ensure_ascii=False, indent=2))\n    def save_blob(encoded, suffix, label):\n        raw = base64.b64decode(encoded, altchars=b\"-_\", validate=True)\n        ext = \"png\" if raw.startswith(b\"\\x89PNG\\r\\n\\x1a\\n\") else \"jpg\" if raw.startswith(b\"\\xff\\xd8\") else \"webp\" if raw[:4] == b\"RIFF\" and raw[8:12] == b\"WEBP\" else suffix\n        file = Path(stem + \"-\" + label + \".\" + ext)\n        file.write_bytes(raw)\n        print(\"Saved\", file)\n    for index, block in enumerate(data.get(\"content\") or []):\n        print(\"Content\", index, json.dumps(block, ensure_ascii=False))\n    for choice in data.get(\"choices\") or []:\n        print(\"Choice\", choice.get(\"index\"), json.dumps(choice.get(\"message\", choice.get(\"delta\", {})), ensure_ascii=False))\n    for index, item in enumerate(data.get(\"output\") or []):\n        print(\"Output\", index, json.dumps(item, ensure_ascii=False))\n        if item.get(\"type\") == \"image_generation_call\" and item.get(\"result\"):\n            save_blob(item[\"result\"], item.get(\"output_format\") or \"bin\", \"output-\" + str(index))\n    for ci, candidate in enumerate(data.get(\"candidates\") or []):\n        for pi, part in enumerate((candidate.get(\"content\") or {}).get(\"parts\") or []):\n            print(\"Candidate/part\", ci, pi, json.dumps(part, ensure_ascii=False))\n            blob = part.get(\"inlineData\") or part.get(\"inline_data\")\n            if blob and blob.get(\"data\"):\n                mime = blob.get(\"mimeType\") or blob.get(\"mime_type\")\n                suffix = {\"image/png\":\"png\", \"image/jpeg\":\"jpg\", \"image/webp\":\"webp\", \"audio/wav\":\"wav\", \"audio/mpeg\":\"mp3\", \"video/mp4\":\"mp4\"}.get(mime, \"bin\")\n                save_blob(blob[\"data\"], suffix, \"candidate-\" + str(ci) + \"-part-\" + str(pi))\n\nwith client.chat.completions.stream(model='Tongyi-Zhiwen/QwenLong-L1-32B',messages=[{\"role\":\"user\",\"content\":\"Explain observations and hypotheses in three sentences.\"}]) as stream:\n    with Path(\"stream-events.jsonl\").open(\"w\",encoding=\"utf-8\") as log:\n        for event in stream:\n            payload=event.to_dict(mode=\"json\")\n            log.write(json.dumps(payload,ensure_ascii=False)+\"\\n\"); log.flush()\n            print(json.dumps(payload,ensure_ascii=False))\n    final=stream.get_final_completion()\n    save_result(final.to_dict(mode=\"json\"),\"stream-result\")\n",
            "label": "Python SDK streaming · all events",
            "language": "python"
          }
        ],
        "family": "openai",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "chat",
        "hints": [
          "Send exact model ID with messages.",
          "Context length is not an output cap.",
          "A text file may supply literal text; image/audio/file-object inputs need exact binding."
        ],
        "http": "POST",
        "in": 0.28,
        "input": [
          "text"
        ],
        "label": "OpenAI Chat",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 1.2,
        "output": [
          "text"
        ],
        "path": "/v1/chat/completions",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.00028000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.00000028",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0.0012000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000012",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          }
        ]
      },
      {
        "available": null,
        "cache_read": 0,
        "cache_write": 0,
        "cache_write_1h": null,
        "contract": {
          "data": {
            "authentication": {
              "api_key_source": "AILOOT_API_KEY",
              "headers": [
                "Authorization: Bearer",
                "x-api-key",
                "anthropic-version"
              ],
              "version_example": "2023-06-01"
            },
            "errors": [
              {
                "code": null,
                "condition": "Neveljavna obvezna polja, predstavitev gradiva ali vrednost parametra",
                "http_status": 400,
                "recovery": "Pred novo zahtevo za ustvarjanje popravite navedena polja.",
                "type": "invalid_request_error"
              }
            ],
            "example_body": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Tongyi-Zhiwen/QwenLong-L1-32B",
              "stream": false
            },
            "lifecycle": {
              "create": {
                "http": "POST",
                "path": "/v1/messages"
              },
              "job_read": null,
              "mode": "synchronous_or_streamed",
              "unknown": "Ohranite ID zahtev/odgovorov in glave. Splošni URL za pridobivanje besedilne naloge ni podan."
            },
            "material_combinations": [
              {
                "mode": "text",
                "representation": "niz messages[].content",
                "required_material": "Besedilo UTF-8"
              }
            ],
            "operation_modes": [
              "synchronous_json",
              "streamed_SSE"
            ],
            "outputs": {
              "all_results": "Ohranite vse vsebinske bloke, podpise sklepanja in dejanske ID uporabe orodij. Sestavite vse delne spremembe blokov SSE; prvi besedilni blok ni celoten izhod.",
              "family": "protocol",
              "fields": [
                {
                  "description": null,
                  "name": "id",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "model",
                  "type": "string"
                },
                {
                  "description": null,
                  "name": "content[]",
                  "type": "text|thinking|tool_use|other content block"
                },
                {
                  "description": null,
                  "name": "stop_reason",
                  "type": "string|null"
                },
                {
                  "description": null,
                  "name": "usage",
                  "type": "object"
                }
              ],
              "format": "JSON ali SSE"
            },
            "parameters": [
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "Tongyi-Zhiwen/QwenLong-L1-32B"
                ],
                "enum_known": true,
                "name": "model",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages",
                "required": true,
                "type": "message[]"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": [
                  "user",
                  "assistant"
                ],
                "enum_known": true,
                "name": "messages[].role",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "messages[].content",
                "required": true,
                "type": "string"
              },
              {
                "availability": "source_interface",
                "default": null,
                "default_known": false,
                "enum": null,
                "enum_known": false,
                "name": "max_tokens",
                "required": true,
                "type": "integer"
              },
              {
                "availability": "source_interface",
                "default": false,
                "default_known": true,
                "enum": null,
                "enum_known": false,
                "name": "stream",
                "required": false,
                "type": "boolean"
              }
            ],
            "profile_binding": "Documented current stock Messages bridge; optional model capabilities are separate from this minimal text request.",
            "request_schema": {
              "additionalProperties": false,
              "properties": {
                "max_tokens": {
                  "minimum": 1,
                  "type": "integer"
                },
                "messages": {
                  "items": {
                    "additionalProperties": false,
                    "properties": {
                      "content": {
                        "oneOf": [
                          {
                            "type": "string"
                          },
                          {
                            "items": {
                              "oneOf": [
                                {
                                  "properties": {
                                    "text": {
                                      "type": "string"
                                    },
                                    "type": {
                                      "const": "text"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "text"
                                  ],
                                  "type": "object"
                                },
                                {
                                  "properties": {
                                    "source": {
                                      "oneOf": [
                                        {
                                          "properties": {
                                            "type": {
                                              "const": "url"
                                            },
                                            "url": {
                                              "type": "string"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "url"
                                          ],
                                          "type": "object"
                                        },
                                        {
                                          "properties": {
                                            "data": {
                                              "type": "string"
                                            },
                                            "media_type": {
                                              "type": "string"
                                            },
                                            "type": {
                                              "const": "base64"
                                            }
                                          },
                                          "required": [
                                            "type",
                                            "media_type",
                                            "data"
                                          ],
                                          "type": "object"
                                        }
                                      ]
                                    },
                                    "type": {
                                      "const": "image"
                                    }
                                  },
                                  "required": [
                                    "type",
                                    "source"
                                  ],
                                  "type": "object"
                                }
                              ]
                            },
                            "type": "array"
                          }
                        ]
                      },
                      "role": {
                        "enum": [
                          "user",
                          "assistant"
                        ],
                        "type": "string"
                      }
                    },
                    "required": [
                      "role",
                      "content"
                    ],
                    "type": "object"
                  },
                  "minItems": 1,
                  "type": "array"
                },
                "model": {
                  "enum": [
                    "Tongyi-Zhiwen/QwenLong-L1-32B"
                  ],
                  "type": "string"
                },
                "stream": {
                  "default": false,
                  "type": "boolean"
                }
              },
              "required": [
                "model",
                "messages",
                "max_tokens"
              ],
              "type": "object"
            },
            "schema_template": {
              "max_tokens": 128,
              "messages": [
                {
                  "content": "Summarize the incident report.",
                  "role": "user"
                }
              ],
              "model": "Tongyi-Zhiwen/QwenLong-L1-32B",
              "stream": false
            },
            "unsupported": [
              "No query API key.",
              "Hosted/server-side tools and model-specific optional controls are not part of this minimal family example."
            ]
          },
          "input": {
            "content_type": "application/json",
            "material_types": [
              "text"
            ],
            "optional_controls": [
              "stream"
            ],
            "required": [
              "model",
              "messages",
              "max_tokens"
            ],
            "text_file_material": "Preberite dejanski dokument UTF-8 in njegovo besedilo vstavite v navedeni vhodni niz ali niz vsebine sporočila."
          },
          "lifecycle": {
            "create": {
              "http": "POST",
              "path": "/v1/messages"
            },
            "job_read": null,
            "mode": "synchronous_or_streamed",
            "unknown": "Keep request/response IDs and headers. No generic text job retrieval URL is supplied."
          },
          "manufacturer_capability": null,
          "method": {
            "http": "POST",
            "path": "/v1/messages"
          },
          "output": {
            "all_results": "Keep all content blocks, thinking signatures and actual tool-use IDs. Assemble all SSE block deltas; a first text block is not the complete output.",
            "family": "protocol",
            "format": "JSON or SSE"
          }
        },
        "ctx": null,
        "declared_pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Osnovne cene za žetone",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "examples": [
          {
            "code": "{\n  \"model\": \"Tongyi-Zhiwen/QwenLong-L1-32B\",\n  \"max_tokens\": 128,\n  \"messages\": [\n    {\n      \"role\": \"user\",\n      \"content\": \"Summarize the incident report.\"\n    }\n  ],\n  \"stream\": false\n}",
            "label": "Complete minimal JSON body",
            "language": "json"
          },
          {
            "code": "set -eu\n: \"${AILOOT_API_KEY:?Set your Ailoot API key}\"\n: \"${AILOOT_TEXT_FILE:?Set your actual UTF-8 document}\"\nexport AILOOT_TEXT_FILE\npython3 - <<'PY_REQUEST'\nimport json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Tongyi-Zhiwen/QwenLong-L1-32B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nPath('request.json').write_text(json.dumps(payload, ensure_ascii=False), encoding='utf-8')\nPY_REQUEST\ncurl --fail-with-body --silent --show-error https://api.ailoot.ai/v1/messages \\\n  -H \"x-api-key: $AILOOT_API_KEY\" -H 'anthropic-version: 2023-06-01' -H 'Content-Type: application/json' \\\n  --data-binary @request.json -D response-headers.txt -o result.json\npython3 - <<'PY_RESULT'\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\nPY_RESULT\n",
            "label": "curl · use your UTF-8 document",
            "language": "bash"
          },
          {
            "code": "import json, os\nfrom pathlib import Path\n\nsource_file = Path(os.environ['AILOOT_TEXT_FILE'])\nif not source_file.is_file():\n    raise SystemExit('Set AILOOT_TEXT_FILE to your actual UTF-8 document')\ntext = source_file.read_text(encoding='utf-8')\nif not text.strip():\n    raise SystemExit('Choose a document containing text')\npayload = {'model': 'Tongyi-Zhiwen/QwenLong-L1-32B', 'max_tokens': 128, 'messages': [{'role': 'user', 'content': 'Summarize the incident report.'}]}\npayload['messages'][0]['content'] = 'Summarize this material and quote supporting source passages.\\n\\n' + text\nfrom urllib.request import Request, urlopen\nfrom urllib.error import HTTPError\n\napi_key = os.environ['AILOOT_API_KEY']\nif not api_key.strip():\n    raise SystemExit('Set AILOOT_API_KEY before making a request')\nheaders = {'x-api-key': 'PLACEHOLDER_KEY', 'anthropic-version': '2023-06-01', 'Content-Type': 'application/json'}\nheaders['x-api-key'] = api_key\nrequest = Request('https://api.ailoot.ai/v1/messages', data=json.dumps(payload, ensure_ascii=False).encode('utf-8'), headers=headers, method='POST')\ntry:\n    with urlopen(request, timeout=120) as response:\n        raw = response.read()\n        Path('response-headers.txt').write_text(str(response.headers), encoding='utf-8')\nexcept HTTPError as error:\n    Path('result.json').write_bytes(error.read())\n    Path('response-headers.txt').write_text(str(error.headers), encoding='utf-8')\n    raise\nPath('result.json').write_bytes(raw)\nimport json\nfrom pathlib import Path\n\nresult = json.loads(Path('result.json').read_text(encoding='utf-8'))\nprint(json.dumps(result, ensure_ascii=False, indent=2))\n",
            "label": "Python · save the complete result",
            "language": "python"
          }
        ],
        "family": "anthropic",
        "fast_multiplier": null,
        "flex_multiplier": null,
        "fmt": "messages",
        "http": "POST",
        "in": 0.28,
        "input": [
          "text"
        ],
        "label": "Anthropic Messages",
        "max_out": null,
        "max_reasoning_effort_multiplier": null,
        "method_aliases": [],
        "out": 1.2,
        "output": [
          "json",
          "sse"
        ],
        "path": "/v1/messages",
        "price_conditions": [
          {
            "label": "Fast mode",
            "value": "Not specified",
            "when": "When fast mode is selected"
          },
          {
            "label": "Flex mode",
            "value": "Not specified",
            "when": "When flex mode is selected"
          },
          {
            "label": "Maximum reasoning effort",
            "value": "Not specified",
            "when": "When maximum reasoning effort uses the default adjustment"
          }
        ],
        "pricing": {
          "billing_mode": "token",
          "image_input_price": null,
          "image_output_price": null,
          "per_request_price": null
        },
        "pricing_profiles": [
          {
            "dimensions": {
              "regime": "base"
            },
            "label": "Base token rates",
            "units": [
              {
                "amount": "0.00028000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "input_price",
                "label": "Input tokens",
                "native_amount_usd_per_unit": "0.00000028",
                "native_quantity": 1,
                "native_unit": "input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "input_token"
              },
              {
                "amount": "0.0012000",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "output_price",
                "label": "Output tokens",
                "native_amount_usd_per_unit": "0.0000012",
                "native_quantity": 1,
                "native_unit": "output_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "out",
                "unit": "output_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_read_price",
                "label": "Cache read",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "cached_input_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "cached_input_token"
              },
              {
                "amount": "0",
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_price",
                "label": "Cache write",
                "native_amount_usd_per_unit": "0",
                "native_quantity": 1,
                "native_unit": "generic_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "generic_cache_creation_token"
              },
              {
                "amount": null,
                "amount_unit": "usd_per_thousand_tokens",
                "billing_input": true,
                "estimate_only": false,
                "key": "cache_write_1h_price",
                "label": "Cache write, 1 hour",
                "native_amount_usd_per_unit": null,
                "native_quantity": 1,
                "native_unit": "one_hour_cache_creation_token",
                "public_unit_label": "/ 1K tokens",
                "quantity": 1000,
                "quantity_is_estimate": false,
                "rate_role": "typed_native_retail_rate",
                "side": "in",
                "unit": "one_hour_cache_creation_token"
              }
            ]
          }
        ],
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra",
        "status_reads": [],
        "tiers": [],
        "units": [
          {
            "amount": "0.00028000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "input_price",
            "label": "Input tokens",
            "native_amount_usd_per_unit": "0.00000028",
            "native_quantity": 1,
            "native_unit": "input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "input_token"
          },
          {
            "amount": "0.0012000",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "output_price",
            "label": "Output tokens",
            "native_amount_usd_per_unit": "0.0000012",
            "native_quantity": 1,
            "native_unit": "output_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "out",
            "unit": "output_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_read_price",
            "label": "Cache read",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "cached_input_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "cached_input_token"
          },
          {
            "amount": "0",
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_price",
            "label": "Cache write",
            "native_amount_usd_per_unit": "0",
            "native_quantity": 1,
            "native_unit": "generic_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "generic_cache_creation_token"
          },
          {
            "amount": null,
            "amount_unit": "usd_per_thousand_tokens",
            "billing_input": true,
            "estimate_only": false,
            "key": "cache_write_1h_price",
            "label": "Cache write, 1 hour",
            "native_amount_usd_per_unit": null,
            "native_quantity": 1,
            "native_unit": "one_hour_cache_creation_token",
            "public_unit_label": "/ 1K tokens",
            "quantity": 1000,
            "quantity_is_estimate": false,
            "rate_role": "typed_native_retail_rate",
            "side": "in",
            "unit": "one_hour_cache_creation_token"
          }
        ]
      }
    ],
    "model_aliases": [
      {
        "canonical_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "request_model_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
        "route_label": "Ultra"
      }
    ],
    "name": "Tongyi-Zhiwen/QwenLong-L1-32B",
    "price": {
      "in": 0.28,
      "in_label": null,
      "out": 1.2,
      "out_label": null,
      "scope_label": "Token rates",
      "sort_in": 0.28,
      "sort_out": 1.2,
      "varies": false
    },
    "public_id": "Tongyi-Zhiwen/QwenLong-L1-32B",
    "short": "QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje pri vprašanjih, utemeljenih v dolgih dokumentih. Izhodišče DeepSeek-R1-Distill-Qwen-32B združuje s spodbujevalnim učenjem, osredotočenim na dokumente, za numerično, logično in meddokumentno sklepanje."
  },
  "renderer_schema": {
    "method_order": "Original DTO methods order; every exact route/format/path/caller survives.",
    "prices": "Original public DTO fields and original native display HTML; no flattened or normalized offers."
  },
  "representation": "exact-public-dto-and-native-renderer-html",
  "representationNotes": {
    "current_reference": {
      "about_json_pointer": "/aboutHtml",
      "methods": [
        {
          "contract_json_pointer": "/methods/0/rawMethod/contract",
          "html_json_pointer": "/methods/0/html",
          "method_ordinal": 0
        },
        {
          "contract_json_pointer": "/methods/1/rawMethod/contract",
          "html_json_pointer": "/methods/1/html",
          "method_ordinal": 1
        }
      ],
      "role": "current-semantic-reference"
    },
    "raw_input": {
      "examples_role": "historical-input-not-current-ready-examples",
      "json_pointers": [
        "/rawModel",
        "/methods/0/rawMethod",
        "/methods/1/rawMethod"
      ],
      "role": "historical-owner-input"
    },
    "schema": "ailoot-native-model-representations-v1"
  },
  "schema": "ailoot-static-model-facts-v1",
  "schema_version": 1,
  "shortText": "QwenLong-L1-32B je model podjetja Tongyi Lab za besedilno sklepanje pri vprašanjih, utemeljenih v dolgih dokumentih. Izhodišče DeepSeek-R1-Distill-Qwen-32B združuje s spodbujevalnim učenjem, osredotočenim na dokumente, za numerično, logično in meddokumentno sklepanje.",
  "source": {
    "audit_sha256": "2e00086bcbfc28e64d0cebe97aa47c17d8d5618963027f8ffb9dc6123d7d25b1",
    "bridge_map_sha256": "1125275768b9636fc8461bc7da5061239a81ddfe508e2557843ca42c58ab0036",
    "raw_model_json_sha256": "b5dc1c4f9016ba2a64269da01465713af742d6810efb3361e0b0dc546d1cc101",
    "renderer_sha256": "dcba2271c18b0f9570a8b166e8d1e3166f121e096a58609c3a46da31562a1bf2"
  },
  "sourceRevision": "12ae8550d9a08583ced846585bb40ce0f60e3293b9dcfe2d9ef3c1054c591785"
}