Katta til modellari (LLM) bilan bog'liq doimiy muammo bu ularning oldindan aytib bo'lmaydigan mahsulot ishlab chiqarish tendentsiyasidir. Ehtiyotkorlik bilan ishlab chiqilgan ko'rsatmalarga qaramay, LLMlar ko'pincha kutilganidan chetga chiqadi, bu esa o'z mahsulotlarini qayta ishlatish yoki ish oqimlariga integratsiya qilishni qiyinlashtiradi. Bundan ham yomoni, natijalar ko'pincha takrorlanmaydi, bu esa quyida ishlov berishni murakkablashtiradi. Ushbu blog postida biz vazifalarni bajarishdan oldin yechimlar uchun JSON sxemalarini dinamik ravishda yaratadigan o'rganamiz. Bu ko'proq qayta foydalanish mumkin, ishonchli va bashorat qilinadigan takliflarni yaratishga yordam beradi. tizimli meta-so'rovni Fon Ko'pgina zamonaviy LLMlar endi JSON chiqish rejimini taklif qiladi, ammo natijalar har doim ham kutilgan sxemaga mos kelmaydi. Ishlab chiquvchilar ko'pincha vaqt talab qiluvchi, qimmat va foydalanuvchi tajribasini buzishga moyil bo'lgan tekshirish va qayta urinish mexanizmlariga murojaat qilishadi. yordamida OpenAI tizimli chiqishlarni taqdim etdi, bu esa chiqish foydalanuvchi tomonidan taqdim etilgan JSON sxemasiga mos kelishini kafolatlaydi. Garchi aniq tafsilotlar oshkor etilmagan bo'lsa-da, bunga cheklangan dekodlash va namunadan oldingi logitni yo'naltirish kombinatsiyasi erishilgan bo'lishi mumkin. Shunga o'xshash imkoniyatlar yo'l-yo'riq, konturlar, inversiya, CommandR, SGLang kabi boshqa vositalar tomonidan taqdim etiladi. Ushbu yondashuvlar ishlab chiquvchilarga natijalarni JSON sxemalariga yo'naltirish imkoniyatini beradi, ularning har biri o'ziga xos o'zgarishlarga ega. gpt4o Strukturaviy meta-so'rov nima? Strukturaviy meta-so'rov - bu yechim ishlab chiqarishdan oldin muammoning tuzilgan tavsifini dinamik ravishda yaratish uchun LLMdan foydalanadigan har qanday usul. Ushbu usul to'g'ridan-to'g'ri so'rashga nisbatan bir qator afzalliklarga ega: : Chiqish tuzilmalari modelga qattiq kodlangan yoki nozik sozlangan emas, balki vazifa tavsiflari asosida ish vaqtida yaratiladi. Dinamik : Yaratilgan sxema odamlar tomonidan o'qilishi mumkin va uni odamlar yoki boshqa LLMlar tekshirishi, tekshirishi yoki o'zgartirishi mumkin. Moslashuvchan : Sxema bir nechta vazifalar, ishga tushirish va mashinalarda saqlanishi va qayta ishlatilishi mumkin. Qayta foydalanish mumkin : Yechimlar aniq belgilangan tuzilishga mos keladi va ularni quyi oqimdagi hisoblash uchun mos qiladi. Bashorat qilinadigan Kod Keling, yangi ko'p sotilgan ayg'oqchi triller romanining konturini yaratish uchun tuzilgan meta-so'rovdan foydalanayotgan misolni ko'rib chiqaylik. Ushbu blog postining barcha kodlari ushbu mavjud. Colab daftarida kodingizni Colab Secrets-da o‘rnatganingizga ishonch hosil qiling OPENAI_API_KEY 1. Strukturani yaratish dBirinchi qadam kerakli natijani tavsiflovchi JSON sxemasini aniqlashdir. Buni amalga oshirish uchun biz JSON sxemasi uchun JSON sxemasini yaratamiz — samarali, ! Bu spetsifikatsiyaning bir qismi sifatida taqdim etilgan, ammo biz ba'zi o'zgartirishlar kiritishimiz kerak. meta-sxema 1.1 Meta-sxemani o'zgartirish OpenAI va Cohere-ning tuzilgan chiqish API-lari standart JSON sxemalariga qo'yadi. Bu juda achinarli, ammo hozircha hal qilishimiz mumkin bo'lgan narsa. Mosligini ta'minlash uchun biz meta-sxemani o'zgartiramiz: bir nechta cheklovlarni from jsonschema import Draft202012Validator def openai_compatible_metaschema(schema: Dict[str, object]): schema["type"] = "object" del schema["allOf"] return schema openai_json_metaschema = openai_compatible_metaschema( copy.deepcopy(Draft202012Validator.META_SCHEMA) ) *: Ko'rinishidan* Eslatma inversiyada bunday cheklovlar yo'q va o'zboshimchalik bilan JSON sxemalarini qo'llab-quvvatlaydi... lekin hali ommaviy kirish imkoni yo'q! 1.2 Meta-so'rovimizga cheklovlar qo'shish Keyinchalik, natijada olingan JSON sxemasi OpenAI cheklovlariga mos kelishini ta'minlash uchun ko'rsatmalarni taklifga kiritamiz. Masalan; misol uchun: Barcha maydonlar talab qilinishi kerak. Ob'ektlarning chuqurligi va hajmi bo'yicha cheklovlar mavjud. Qo'shimcha xususiyatlarga ruxsat berilmasligi kerak ( ). "additionalProperties": false system_guidelines = "\n".join( [ "All fields must be required - To use Structured Outputs, all fields or function parameters must be specified as required. NOTE: Although all fields must be required (and the model will return a value for each parameter), it is possible to emulate an optional parameter by using a union type with null." "Objects have limitations on nesting depth and size - A schema may have up to 100 object properties total, with up to 5 levels of nesting.", "Limitations on total string size - In a schema, total string length of all property names, definition names, enum values, and const values cannot exceed 15,000 characters.", "Limitations on enum size - A schema may have up to 500 enum values across all enum properties. For a single enum property with string values, the total string length of all enum values cannot exceed 7,500 characters when there are more than 250 enum values.", "additionalProperties: false must always be set in objects - additionalProperties controls whether it is allowable for an object to contain additional keys / values that were not defined in the JSON Schema. Structured Outputs only supports generating specified keys / values, so we require developers to set additionalProperties: false to opt into Structured Outputs.", "Some type-specific keywords are not yet supported - Notable keywords not supported include: For strings: minLength, maxLength, pattern, format; For numbers: minimum, maximum, multipleOf; For objects: patternProperties, unevaluatedProperties, propertyNames, minProperties, maxProperties; For arrays: unevaluatedItems, contains, minContains, maxContains, minItems, maxItems, uniqueItems", "For anyOf, the nested schemas must each be a valid JSON Schema per this subset", "Definitions are supported - You can use definitions to define subschemas which are referenced throughout your schema. The following is a simple example.", "Recursive schemas are supported - Sample recursive schema using # to indicate root recursion.", ] ) 1.3 Meta-so'rovni o'rnatish Endi biz ayg'oqchi triller konturi uchun JSON sxemasini yaratish uchun meta-so'rovni aniqlaymiz from langchain.prompts import ChatPromptTemplate task_description = "Write an outline for a bestselling spy thriller novel" task_guidelines = """ - You must follow one of the six basic story arcs: Rags to riches, Riches to rags, Icarus, Oedipus, Cinderella, Man in a hole - Outputs must include characters, plot points (including exposition, rising action, climax, falling action, and resolution), central conflict, setting, major turning points or "beats," character arcs, and a synopsis of the story; essentially, a detailed breakdown of the key elements that will drive the narrative throughout the novel. """ prompt_messages = ChatPromptTemplate.from_messages( [ ( "system", "You are an expert in creating JSON schemas. You have been asked to generate a detailed JSON schema for the output of a given task based based on a task desciption and some guidelines.", ), ( "system", "Your JSON schema must always adhere to the following system system guidelines for JSON schemas:\n<system_guidelines>\n{system_guidelines}\n</system_guidelines>", ), ( "user", "Use the task description and guidelines below to generate an output JSON schema for the following task based on the guidelines provided.\n\n<task_description>\n{task_description}\n</task_description>\n\n<guidelines>\n{task_guidelines}\n</guidelines>", ), ] ) 1.4 Strukturani yaratish Biz sxemani yaratish uchun LLMni chaqiramiz: messages = prompt_messages.format_messages( system_guidelines=system_guidelines, task_description=task_description, task_guidelines=task_guidelines ) ## Make sure to set up OPENAI_API_KEY in your Colab Secrets ## https://x.com/GoogleColab/status/1719798406195867814 client = OpenAI(api_key=userdata.get('OPENAI_API_KEY')) model = "gpt-4o" metaprompt_completion = client.beta.chat.completions.parse( model=model, messages=convert_to_penai_messages(messages), response_format={ "type": "json_schema", "json_schema": JSONSchema( name="JsonMetaschema", description="JSON Metaschema for the 2020-12 Draft of the JSON Schema specification that can be used to validate JSON data", schema=openai_json_metaschema, strict=False, ) } ) task_output_schema = json.loads(metaprompt_completion.choices[0].message.content) print(json.dumps(task_output_schema, indent=2)) { "$schema": "https://json-schema.org/draft/2020-12/schema", "title": "Outline for a Bestselling Spy Thriller Novel", "type": "object", "properties": { "storyArc": { "type": "string", "enum": [ "Rags to riches", "Riches to rags", "Icarus", "Oedipus", "Cinderella", "Man in a hole" ] }, "characters": { "type": "array", "items": { "type": "object", "properties": { "name": { "type": "string" }, "role": { "type": "string" }, "description": { "type": "string" }, "arc": { "type": "string" } }, "required": ["name", "role", "description", "arc"], "additionalProperties": false }, "minItems": 1 }, "plotPoints": { "type": "object", "properties": { "exposition": { "type": "string" }, "risingAction": { "type": "string" }, "climax": { "type": "string" }, "fallingAction": { "type": "string" }, "resolution": { "type": "string" } }, "required": [ "exposition", "risingAction", "climax", "fallingAction", "resolution" ], "additionalProperties": false }, "centralConflict": { "type": "string" }, "setting": { "type": "string" }, "majorTurningPoints": { "type": "array", "items": { "type": "string" }, "minItems": 1 }, "characterArcs": { "type": "object", "properties": { "protagonistArc": { "type": "string" }, "antagonistArc": { "type": "string" }, "supportingCharactersArcs": { "type": "array", "items": { "type": "string" }, "minItems": 0 } }, "required": [ "protagonistArc", "antagonistArc", "supportingCharactersArcs" ], "additionalProperties": false }, "synopsis": { "type": "string" } }, "required": [ "storyArc", "characters", "plotPoints", "centralConflict", "setting", "majorTurningPoints", "characterArcs", "synopsis" ], "additionalProperties": false } Endi bizda ayg'oqchi triller romanimiz konturini tavsiflovchi sxema mavjud. Bu faylda yoki ma'lumotlar bazasida saqlanib qolishi mumkin. 2. Yechim ishlab chiqarish 2.1 Tezkor sozlash Sxemadan foydalanib, biz roman konturi uchun taklifni aniqlaymiz. Biz ba'zi asosiy rolli o'yinni taklif qilish va ko'rsatmalardan foydalanamiz: user_requirements = "Tell a story about counter-intelligence operative working against the clock. The novel should be extremely realistic, slow burn." task_prompt = ChatPromptTemplate.from_messages( [ ( "system", "You are a world-renowned author that has written dozens of bestselling thriller novels. Your task is to create an outline for a new novel based on the user's requirements.", ), ( "user", "Please write a novel outline based strictly on the following requirements <requirements>{requirements}</requirements>", ), ] ) task_completion = client.beta.chat.completions.parse( model=model, messages=convert_to_openai_messages(task_prompt.format_messages(requirements=user_requirements)), response_format={ "type": "json_schema", "json_schema": JSONSchema( ## TODO: You can change this depending your task name="ThrillerNovelOutlineSchema", description="A schema for outlining a new novel", schema=task_output_schema, strict=False, ) } ) task_result = json.loads(task_completion.choices[0].message.content) Mana bizning navbatdagi ayg‘oqchi trillerimiz rejasi: { "storyArc": "Cinderella", "synopsis": "In 'The Clockwork Veil', Ethan Cross, a savvy counter-intelligence operative, is thrust into a high-pressure scenario where leaked documents threaten national integrity. As he races against time to unmask a mole within the agency, Ethan confronts his personal fears and the boundaries of the meticulous strategies he's known for. This slow-burn thriller follows Ethan's transformation in a world where every second could spell disaster, culminating in a showdown with Lena Grey\u2014a former ally who has turned the clockwork of espionage into her personal vendetta. Through grit and cunning, Ethan must adapt his methods, realizing that in the world of espionage, the most powerful weapon is a well-timed intuition.", "characters": [ { "name": "Ethan Cross", "role": "Protagonist", "description": "A meticulous and resourceful counter-intelligence operative known for his analytical mind and calm demeanor under pressure.", "arc": "Ethan transforms from a methodical planner to a decisive action-taker as he confronts his personal fears and realizes the importance of instinct." }, { "name": "Lena Grey", "role": "Antagonist", "description": "A brilliant but disillusioned former operative now turned mole, seeking vengeance against the agency she believes wronged her.", "arc": "Lena starts with a single-minded focus on revenge but gradually becomes conflicted as old loyalties resurface." }, { "name": "Dr. Julia Ward", "role": "Supporting Character", "description": "An astute psychologist who helps Ethan manage the stress of his demanding role and assists in profiling Lena's psychological state.", "arc": "Julia grows from a secondary advisory role to a key player in helping Ethan unearth Lena's motivations." }, { "name": "Michael Garner", "role": "Supporting Character", "description": "Ethan's trusted field partner and an expert in electronic surveillance, providing vital technical support.", "arc": "Michael's experience is tested as he learns to adapt to unpredictable situations, becoming more versatile in his approach." } ], "plotPoints": { "exposition": "Ethan Cross is tasked with investigating a series of leaked documents that could compromise national security. The leaks point to an insider within the agency.", "risingAction": "As Ethan dives deeper, he uncovers a trail leading to Lena Grey, a former colleague presumed dead. Evidence mounts as Ethan closes in, forcing him to question his long-standing methodologies.", "climax": "Ethan finally confronts Lena, who has rigged a trap to destroy critical evidence. In a tense standoff, Ethan must choose between following protocol or taking a risk to stop her.", "fallingAction": "With quick thinking and a new reliance on intuition, Ethan manages to disarm the trap. Lena, deflated, questions her own motives as old memories of camaraderie surface.", "resolution": "Lena is apprehended, the mole hunt ends, and Ethan reflects on his journey, acknowledging the balance between calculated strategy and spontaneity." }, "centralConflict": "Ethan Cross must identify and capture a mole within the agency who is leaking classified information, while dealing with his own rigid attachment to protocol in a dynamically evolving threat landscape.", "setting": "The story unfolds across various global locations including the bustling intelligence hub of Langley, a remote cabin in the Swiss Alps, and the teeming streets of Berlin, lending an authentic and international scope to the narrative.", "majorTurningPoints": [ "Ethan discovers the identity of the mole as his former colleague Lena Grey.", "Lena executes a series of diversions leading to a crisis within the agency.", "Ethan's adherence to protocol nearly costs him a critical breakthrough.", "Ethan's confrontation with Lena culminates in an uncharacteristic display of intuition that saves the mission." ], "characterArcs": { "protagonistArc": "Ethan evolves from strictly adhering to procedures to embracing a balance between strategy and instinctive decision-making, essential in high-stakes situations.", "antagonistArc": "Lena's journey from spite-fueled revenge to questioning her own motivations reflects a shift from isolation to an internal struggle with her past loyalties.", "supportingCharactersArcs": [ "Julia grows from providing psychological insights to playing an active role in strategizing the final approach to Lena.", "Michael transitions from a technical support role to becoming a crucial element in executing Ethan\u2019s plans, emphasizing adaptability." ] } } d Endi biz ushbu sxemadan mahsulot tarkibidagi maydonlar haqida kuchli kafolatlar bilan quvur liniyasida bir nechta yechimlarni yaratish uchun qayta foydalanishimiz mumkin. Xulosa Strukturaviy meta-so'rov sizga tuzilmani tezda aniqlash imkonini beradi, bu esa LLM natijalarini quyi oqim jarayonlari uchun yanada ishonchli qiladi. Keyingi postni kuzatib boring, u yerda biz tuzilgan meta-so‘rovni boshqa usullar bilan birlashtirishni o‘rganamiz.
