PageSourceSearch

https://www.promptingguide.ai/_next/static/chunks/pages/applications/generating.en-f5da4bd82dc00043.js

js promptingguide.ai collected 2026-10-01 08:38:54 UTC 25,072 bytes, 1 lines download raw bytes

1(self.webpackChunk_N_E=self.webpackChunk_N_E||[]).push([[74003],{28539:function(e,n,a){(window.__NEXT_P=window.__NEXT_P||[]).push(["/applications/generating.en",function(){return a(89338)}])},89338:function(e,n,a){"use strict";a.r(n),a.d(n,{__toc:function(){return c}});var i=a(52676),t=a(45118),o=a(23742),s=a(40241);a(21729),a(29814);var l=a(41619),r=a(70754);let c=[];function _createMdxContent(e){let n=Object.assign({h1:"h1",p:"p",em:"em",pre:"pre",code:"code",span:"span",a:"a"},(0,l.a)(),e.components);return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.h1,{children:"Generating Data"}),"\n","\n",(0,i.jsx)(n.p,{children:"LLMs have strong capabilities to generate coherent text. Using effective prompt strategies can steer the model to produce better, consistent, and more factual responses. LLMs can also be especially useful for generating data which is really useful to run all sorts of experiments and evaluations. For example, we can use it to generate quick samples for a sentiment classifier like so:"}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.em,{children:"Prompt:"})}),"\n",(0,i.jsx)(n.pre,{"data-language":"text","data-theme":"default",children:(0,i.jsxs)(n.code,{"data-language":"text","data-theme":"default",children:[(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Produce 10 exemplars for sentiment analysis. Examples are categorized as either positive or negative. Produce 2 negative examples and 8 positive examples. Use this format for the examples:"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: <sentence>"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: <sentiment>"})})]})}),"\n",(0,i.jsx)(n.p,{children:(0,i.jsx)(n.em,{children:"Output:"})}),"\n",(0,i.jsx)(n.pre,{"data-language":"text","data-theme":"default",children:(0,i.jsxs)(n.code,{"data-language":"text","data-theme":"default",children:[(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I just got the best news ever!"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: We just got a raise at work!"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I'm so proud of what I accomplished today."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I'm having the best day ever!"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I'm really looking forward to the weekend."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I just got the best present ever!"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I'm so happy right now."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I'm so blessed to have such an amazing family."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Positive"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: The weather outside is so gloomy."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Negative"})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"}})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"Q: I just got some terrible news."})}),"\n",(0,i.jsx)(n.span,{className:"line",children:(0,i.jsx)(n.span,{style:{color:"var(--shiki-color-text)"},children:"A: Negative"})})]})}),"\n",(0,i.jsx)(n.p,{children:"This is very useful. We actually use this example for a different test in another section of the guides."}),"\n",(0,i.jsx)(r.UW,{type:"info",emoji:"\uD83C\uDF93",children:(0,i.jsxs)(n.p,{children:["Learn more about advanced prompting methods in our new AI courses. ",(0,i.jsx)(n.a,{href:"https://academy.dair.ai/",children:"Join now!"}),"\nUse code PROMPTING20 to get an extra 20% off."]})})]})}let d={MDXContent:function(){let e=arguments.length>0&&void 0!==arguments[0]?arguments[0]:{},{wrapper:n}=Object.assign({},(0,l.a)(),e.components);return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(_createMdxContent,{...e})}):_createMdxContent(e)},pageOpts:{filePath:"pages/applications/generating.en.mdx",route:"/applications/generating",timestamp:1769980197e3,pageMap:[{kind:"Meta",locale:"en",data:{index:"Prompt Engineering",introduction:"Introduction",techniques:"Prompting Techniques",agents:"AI Agents",guides:"Guides",applications:"Applications",prompts:"Prompt Hub",models:"Models",risks:"Risks & Misuses",research:"LLM Research Findings",papers:"Papers",tools:"Tools",notebooks:"Notebooks",datasets:"Datasets",readings:"Additional Readings",courses:{title:"\uD83C\uDF93 Courses",type:"menu",items:{"intro-prompt-engineering":{title:"Intro to Prompt Engineering",href:"https://academy.dair.ai/courses/introduction-prompt-engineering"},"advanced-prompt-engineering":{title:"Advanced Prompt Engineering",href:"https://academy.dair.ai/courses/advanced-prompt-engineering"},"intro-ai-agents":{title:"Intro to AI Agents",href:"https://academy.dair.ai/courses/introduction-ai-agents"}
1,"agents-with-n8n":{title:"Building Effective AI Agents with n8n",href:"https://academy.dair.ai/courses/building-effective-ai-agents"},"rag-systems":{title:"Build RAG Systems",href:"https://academy.dair.ai/courses/introduction-to-rag"},"advanced-agents":{title:"Building Advanced AI Agents",href:"https://academy.dair.ai/courses/advanced-ai-agents"},"all-courses":{title:"See all →",href:"https://academy.dair.ai/courses"}}},about:{title:"About",type:"page"},services:"Services"}},{kind:"MdxPage",name:"about",route:"/about",locale:"en"},{kind:"Folder",name:"agents",route:"/agents",children:[{kind:"Meta",locale:"en",data:{introduction:"Introduction to Agents",components:"Agent Components","ai-workflows-vs-ai-agents":"AI Workflows vs AI Agents","context-engineering":"Context Engineering for AI Agents","context-engineering-deep-dive":"Context Engineering Deep Dive","function-calling":"Function Calling","deep-agents":"Deep Agents"}},{kind:"MdxPage",name:"ai-workflows-vs-ai-agents",route:"/agents/ai-workflows-vs-ai-agents",locale:"en"},{kind:"MdxPage",name:"components",route:"/agents/components",locale:"en"},{kind:"MdxPage",name:"context-engineering-deep-dive",route:"/agents/context-engineering-deep-dive",locale:"en"},{kind:"MdxPage",name:"context-engineering",route:"/agents/context-engineering",locale:"en"},{kind:"MdxPage",name:"deep-agents",route:"/agents/deep-agents",locale:"en"},{kind:"MdxPage",name:"function-calling",route:"/agents/function-calling",locale:"en"},{kind:"MdxPage",name:"introduction",route:"/agents/introduction",locale:"en"}]},{kind:"MdxPage",name:"agents",route:"/agents",locale:"en"},{kind:"Folder",name:"applications",route:"/applications",children:[{kind:"Meta",locale:"en",data:{"finetuning-gpt4o":"Fine-tuning GPT-4o",function_calling:"Function Calling","context-caching":"Context Caching with LLMs",generating:"Generating Data",synthetic_rag:"Generating Synthetic Dataset for RAG",generating_textbooks:"Tackling Generated Datasets Diversity",coding:"Generating Code",workplace_casestudy:"Graduate Job Classification Case Study",pf:"Prompt Function"}},{kind:"MdxPage",name:"coding",route:"/applications/coding",locale:"en"},{kind:"MdxPage",name:"context-caching",route:"/applications/context-caching",locale:"en"},{kind:"MdxPage",name:"finetuning-gpt4o",route:"/applications/finetuning-gpt4o",locale:"en"},{kind:"MdxPage",name:"function_calling",route:"/applications/function_calling",locale:"en"},{kind:"MdxPage",name:"generating",route:"/applications/generating",locale:"en"},{kind:"MdxPage",name:"generating_textbooks",route:"/applications/generating_textbooks",locale:"en"},{kind:"MdxPage",name:"pf",route:"/applications/pf",locale:"en"},{kind:"MdxPage",name:"synthetic_rag",route:"/applications/synthetic_rag",locale:"en"},{kind:"MdxPage",name:"workplace_casestudy",route:"/applications/workplace_casestudy",locale:"en"}]},{kind:"MdxPage",name:"applications",route:"/applications",locale:"en"},{kind:"MdxPage",name:"courses",route:"/courses",locale:"en"},{kind:"MdxPage",name:"datasets",route:"/datasets",locale:"en"},{kind:"Folder",name:"guides",route:"/guides",children:[{kind:"MdxPage",name:"4o-image-generation",route:"/guides/4o-image-generation",locale:"en"},{kind:"Meta",locale:"en",data:{"optimizing-prompts":"Optimizing Prompts","deep-research":"OpenAI Deep Research","reasoning-llms":"Reasoning LLMs","4o-image-generation":"4o Image Generation","context-engineering-guide":"Context Engineering Guide"}},{kind:"MdxPage",name:"context-engineering-guide",route:"/guides/context-engineering-guide",locale:"en"},{kind:"MdxPage",name:"deep-research",route:"/guides/deep-research",locale:"en"},{kind:"MdxPage",name:"optimizing-prompts",route:"/guides/optimizing-prompts",locale:"en"},{kind:"MdxPage",name:"reasoning-llms",route:"/guides/reasoning-llms",locale:"en"}]},{kind:"MdxPage",name:"index",route:"/",locale:"en"},{kind:"Folder",name:"introduction",route:"/introduction",children:[{kind:"Meta",locale:"en",data:{settings:"LLM Settings",basics:"Basics of Prompting",elements:"Prompt Elements",tips:"General Tips for Designing Prompts",examples:"Examples of Prompts"}},{kind:"MdxPage",name:"basics",route:"/introduction/basics",locale:"en"},{kind:"MdxPage",name:"elements",route:"/introduction/elements",locale:"en"},{kind:"MdxPage",name:"examples",route:"/introduction/examples",locale:"en"},{kind:"MdxPage",name:"settings",route:"/introduction/settings",locale:"en"},{kind:"MdxPage",name:"tips",route:"/introduction/tips",locale:"en"}]},{kind:"MdxPage",name:"introduction",route:"/introduction",locale:"en"},{kind:"Folder",name:"models",route:"/models",children:[{kind:"Meta",locale:"en",data:{chatgpt:"ChatGPT","claude-3":"Claude 3","code-llama":"Code Llama",flan:"Flan",gemini:"Gemini","gemini-advanced":"Gemini Advanced","gemini-pro":"Gemini 1.5 Pro",gemma:"Gemma","gpt-4":"GPT-4","grok-1":"Grok-1","kimi-k2.5":"Kimi K2.5",llama:"LLaMA","llama-3":"Llama 3","mistral-7b":"Mistral 7B","mistral-large":"Mistral Large",mixtral:"Mixtral","mixtral-8x22b":"Mixtral 8x22B",olmo:"OLMo","phi-2":"Phi-2",sora:"Sora",collection:"LLM Collection"}},{kind:"MdxPage",name:"chatgpt",route:"/models/chatgpt",locale:"en"},{kind:"MdxPage",name:"claude-3",route:"/models/claude-3",locale:"en"},{kind:"MdxPage",name:"code-llama",route:"/models/code-llama",locale:"en"},{kind:"MdxPage",name:"collection",route:"/models/collection",locale:"en"},{kind:"MdxPage",name:"flan",route:"/models/flan",locale:"en"},{kind:"MdxPage",name:"gemini-advanced",route:"/models/gemini-advanced",locale:"en"},{kind:"MdxPage",name:"gemini-pro",route:"/models/gemini-pro",locale:"en"},{kind:"MdxPage",name:"gemini",route:"/models/gemini",locale:"en"},{kind:"MdxPage",name:"gemma",route:"/models/gemma",locale:"en"},{kind:"MdxPage",name:"gpt-4",route:"/models/gpt-4",locale:"en"},{kind:"MdxPage",name:"grok-1",route:"/models/grok-1",locale:"en"},{kind:"MdxPage",name:"kimi-k2.5",route:"/models/kimi-k2.5",locale:"en"},{kind:"MdxPage",name:"llama-3",route:"/models/llama-3",locale:"en"},{kind:"MdxPage",name:"llama",route:"/models/llama",locale:"en"},{kind:"MdxPage",name:"mistral-7b",route:"/models/mistral-7b",locale:"en"},{kind:"MdxPage",name:"mistral-large",route:"/models/mistral-large",locale:"en"},{kind:"MdxPage",name:"mixtral-8x22b",route:"/models/mixtral-8x22b",locale:"en"},{kind:"MdxPage",name:"mixtral",route:"/models/mixtral",locale:"en"},{kind:"MdxPage",name:"olmo",route:"/models/olmo",locale:"en"},{kind:"MdxPage",name:"phi-2",route:"/models/phi-2",locale:"en"},{kind:"MdxPage",name:"sora",route:"/models/sora",locale:"en"}]},{kind:"MdxPage",name:"models",route:"/models",locale:"en"},{kind:"MdxPage",name:"notebooks",route:"/notebooks",locale:"en"},{kind:"MdxPage",name:"papers",route:"/papers",locale:"en"},{kind:"Folder",name:"prompts",route:"/prompts",children:[{kind:"Meta",locale:"en",data:{classification:"Classification",coding:"Coding",creativity:"Creativity",evaluation:"Evaluation","information-extraction":"Information Extraction","image-generation":"Image Generation",mathematics:"Mathematics","question-answering":"Question Answering",reasoning:"Reasoning","text-summarization":"Text Summarization",truthfulness:"Truthfulness","adversarial-prompting":"Adversarial Prompting"}},{kind:"Folder",name:"adversarial-prompting",route:"/prompts/adversarial-prompting",children:[{kind:"Meta",locale:"en",data:{"prompt-injection":"Prompt Injection","prompt-leaking":"Prompt Leaking","jailbreaking-llms":"Jailbreaking"}},{kind:"MdxPage",name:"jailbreaking-llms",route:"/prompts/adversarial-prompting/jailbreaking-llms",locale:"en"},{kind:"MdxPage",name:"prompt-injection",route:"/prompts/adversarial-prompting/prompt-injection",locale:"en"},{kind:"MdxPage",name:"prompt-leaking",route:"/prompts/adversarial-prompting/prompt-leaking",locale:"en"}]},{kind:"MdxPage",name:"adversarial-prompting",route:"/prompts/adversarial-prompting",locale:"en"},{kind:"Folder",name:"classification",route:"/prompts/classification",children:[{kind:"Meta",locale:"en",data:{sentiment:"Sentiment Classification","sentiment-fewsh
1ot":"Few-Shot Sentiment Classification"}},{kind:"MdxPage",name:"sentiment-fewshot",route:"/prompts/classification/sentiment-fewshot",locale:"en"},{kind:"MdxPage",name:"sentiment",route:"/prompts/classification/sentiment",locale:"en"}]},{kind:"MdxPage",name:"classification",route:"/prompts/classification",locale:"en"},{kind:"Folder",name:"coding",route:"/prompts/coding",children:[{kind:"Meta",locale:"en",data:{"code-snippet":"Generate Code Snippet","mysql-query":"Generate MySQL Query",tikz:"Draw TiKZ Diagram"}},{kind:"MdxPage",name:"code-snippet",route:"/prompts/coding/code-snippet",locale:"en"},{kind:"MdxPage",name:"mysql-query",route:"/prompts/coding/mysql-query",locale:"en"},{kind:"MdxPage",name:"tikz",route:"/prompts/coding/tikz",locale:"en"}]},{kind:"MdxPage",name:"coding",route:"/prompts/coding",locale:"en"},{kind:"Folder",name:"creativity",route:"/prompts/creativity",children:[{kind:"Meta",locale:"en",data:{rhymes:"Rhymes","infinite-primes":"Infinite Primes",interdisciplinary:"Interdisciplinary","new-words":"Inventing New Words"}},{kind:"MdxPage",name:"infinite-primes",route:"/prompts/creativity/infinite-primes",locale:"en"},{kind:"MdxPage",name:"interdisciplinary",route:"/prompts/creativity/interdisciplinary",locale:"en"},{kind:"MdxPage",name:"new-words",route:"/prompts/creativity/new-words",locale:"en"},{kind:"MdxPage",name:"rhymes",route:"/prompts/creativity/rhymes",locale:"en"}]},{kind:"MdxPage",name:"creativity",route:"/prompts/creativity",locale:"en"},{kind:"Folder",name:"evaluation",route:"/prompts/evaluation",children:[{kind:"Meta",locale:"en",data:{"plato-dialogue":"Evaluate Plato's Dialogue"}},{kind:"MdxPage",name:"plato-dialogue",route:"/prompts/evaluation/plato-dialogue",locale:"en"}]},{kind:"MdxPage",name:"evaluation",route:"/prompts/evaluation",locale:"en"},{kind:"Folder",name:"image-generation",route:"/prompts/image-generation",children:[{kind:"Meta",locale:"en",data:{"alphabet-person":"Draw a Person Using Alphabet"}},{kind:"MdxPage",name:"alphabet-person",route:"/prompts/image-generation/alphabet-person",locale:"en"}]},{kind:"MdxPage",name:"image-generation",route:"/prompts/image-generation",locale:"en"},{kind:"Folder",name:"information-extraction",route:"/prompts/information-extraction",children:[{kind:"Meta",locale:"en",data:{"extract-models":"Extract Model Names"}},{kind:"MdxPage",name:"extract-models",route:"/prompts/information-extraction/extract-models",locale:"en"}]},{kind:"MdxPage",name:"information-extraction",route:"/prompts/information-extraction",locale:"en"},{kind:"Folder",name:"mathematics",route:"/prompts/mathematics",children:[{kind:"Meta",locale:"en",data:{"composite-functions":"Evaluating Composite Functions","odd-numbers":"Adding Odd Numbers"}},{kind:"MdxPage",name:"composite-functions",route:"/prompts/mathematics/composite-functions",locale:"en"},{kind:"MdxPage",name:"odd-numbers",route:"/prompts/mathematics/odd-numbers",locale:"en"}]},{kind:"MdxPage",name:"mathematics",route:"/prompts/mathematics",locale:"en"},{kind:"Folder",name:"question-answering",route:"/prompts/question-answering",children:[{kind:"Meta",locale:"en",data:{"closed-domain":"Closed Domain Question Answering","open-domain":"Open Domain Question Answering","science-qa":"Science Question Answering"}},{kind:"MdxPage",name:"closed-domain",route:"/prompts/question-answering/closed-domain",locale:"en"},{kind:"MdxPage",name:"open-domain",route:"/prompts/question-answering/open-domain",locale:"en"},{kind:"MdxPage",name:"science-qa",route:"/prompts/question-answering/science-qa",locale:"en"}]},{kind:"MdxPage",name:"question-answering",route:"/prompts/question-answering",locale:"en"},{kind:"Folder",name:"reasoning",route:"/prompts/reasoning",children:[{kind:"Meta",locale:"en",data:{"indirect-reasoning":"Indirect Reasoning","physical-reasoning":"Physical Reasoning"}},{kind:"MdxPage",name:"indirect-reasoning",route:"/prompts/reasoning/indirect-reasoning",locale:"en"},{kind:"MdxPage",name:"physical-reasoning",route:"/prompts/reasoning/physical-reasoning",locale:"en"}]},{kind:"MdxPage",name:"reasoning",route:"/prompts/reasoning",locale:"en"},{kind:"Folder",name:"text-summarization",route:"/prompts/text-summarization",children:[{kind:"Meta",locale:"en",data:{"explain-concept":"Explain A Concept"}},{kind:"MdxPage",name:"explain-concept",route:"/prompts/text-summarization/explain-concept",locale:"en"}]},{kind:"MdxPage",name:"text-summarization",route:"/prompts/text-summarization",locale:"en"},{kind:"Folder",name:"truthfulness",route:"/prompts/truthfulness",children:[{kind:"Meta",locale:"en",data:{"identify-hallucination":"Hallucination Identification"}},{kind:"MdxPage",name:"identify-hallucination",route:"/prompts/truthfulness/identify-hallucination",locale:"en"}]},{kind:"MdxPage",name:"truthfulness",route:"/prompts/truthfulness",locale:"en"}]},{kind:"MdxPage",name:"prompts",route:"/prompts",locale:"en"},{kind:"MdxPage",name:"readings",route:"/readings",locale:"en"},{kind:"Folder",name:"research",route:"/research",children:[{kind:"Meta",locale:"en",data:{"llm-agents":"LLM Agents",rag:"RAG for LLMs","llm-reasoning":"LLM Reasoning","rag-faithfulness":"RAG Faithfulness","llm-recall":"LLM In-Context Recall",rag_hallucinations:"RAG Reduces Hallucination",synthetic_data:"Synthetic Data",thoughtsculpt:"ThoughtSculpt","infini-attention":"Infini-Attention","guided-cot":"LM-Guided CoT","trustworthiness-in-llms":"Trustworthiness in LLMs","llm-tokenization":"LLM Tokenization",groq:"What is Groq?"}},{kind:"MdxPage",name:"groq",route:"/research/groq",locale:"en"},{kind:"MdxPage",name:"guided-cot",route:"/research/guided-cot",locale:"en"},{kind:"MdxPage",name:"infini-attention",route:"/research/infini-attention",locale:"en"},{kind:"MdxPage",name:"llm-agents",route:"/research/llm-agents",locale:"en"},{kind:"MdxPage",name:"llm-reasoning",route:"/research/llm-reasoning",locale:"en"},{kind:"MdxPage",name:"llm-recall",route:"/research/llm-recall",locale:"en"},{kind:"MdxPage",name:"llm-tokenization",route:"/research/llm-tokenization",locale:"en"},{kind:"MdxPage",name:"rag-faithfulness",route:"/research/rag-faithfulness",locale:"en"},{kind:"MdxPage",name:"rag",route:"/research/rag",locale:"en"},{kind:"MdxPage",name:"rag_hallucinations",route:"/research/rag_hallucinations",locale:"en"},{kind:"MdxPage",name:"synthetic_data",route:"/research/synthetic_data",locale:"en"},{kind:"MdxPage",name:"thoughtsculpt",route:"/research/thoughtsculpt",locale:"en"},{kind:"MdxPage",name:"trustworthiness-in-llms",route:"/research/trustworthiness-in-llms",locale:"en"}]},{kind:"MdxPage",name:"research",route:"/research",locale:"en"},{kind:"Folder",name:"risks",route:"/risks",children:[{kind:"Meta",locale:"en",data:{adversarial:"Adversarial Prompting",factuality:"Factuality",biases:"Biases"}},{kind:"MdxPage",name:"adversarial",route:"/risks/adversarial",locale:"en"},{kind:"MdxPage",name:"biases",route:"/risks/biases",locale:"en"},{kind:"MdxPage",name:"factuality",route:"/risks/factuality",locale:"en"}]},{kind:"MdxPage",name:"risks",route:"/risks",locale:"en"},{kind:"MdxPage",name:"services",route:"/services",locale:"en"},{kind:"Folder",name:"techniques",route:"/techniques",children:[{kind:"Meta",locale:"en",data:{zeroshot:"Zero-shot Prompting",fewshot:"Few-shot Prompting",cot:"Chain-of-Thought Prompting","meta-prompting":"Meta Prompting",consistency:"Self-Consistency",knowledge:"Generate Knowledge Prompting",prompt_chaining:"Prompt Chaining",tot:"Tree of Thoughts",rag:"Retrieval Augmented Generation",art:"Automatic Reasoning and Tool-use",ape:"Automatic Prompt Engineer",activeprompt:"Active-Prompt",dsp:"Directional Stimulus Prompting",pal:"Program-Aided Language Models",react:"ReAct",reflexion:"Reflexion",multimodalcot:"Multimodal CoT",graph:"Graph Prompting"}},{kind:"MdxPage",name:"activeprompt",route:"/techniques/activeprompt",locale:"en"},{kind:"MdxPage",name:"ape",route:"/techniques/ape",locale:"en"},{kind:"MdxPage",name:"art",route:"/techniques/art",locale:"en"},{kind:"MdxPage",name:"consistency",route:"/techniques/consistency",locale:"en"},{kind:"MdxPage",name:"cot",route:"/techniques/cot",locale:"en"},{kind:"MdxPage",name:"dsp",route:"/techniques/dsp",locale:"en"},{kind:"MdxPage",name:"fewshot",route:"/techniques/fewshot",locale:"en"},{kind:"MdxPage",name:"graph",route:"/techniques/graph",locale:"en"},{kind:"MdxPage",name:"knowledge",route:"/techniques/knowledge",locale:"en"},{kind:"MdxPage",name:"meta-prompting",route:"/techniques/meta-prompting",locale:"en"},{kind:"MdxPage",name:"multimodalcot",route:"/techniques/multimodalcot",locale:"en"},{kind:"MdxPage",name:"pal",route:"/techniques/pal",locale:"en"},{kind:"MdxPage",name:"prompt_chaining",route:"/techniques/prompt_chaining",locale:"en"},{kind:"MdxPage",name:"rag",route:"/techniques/rag",locale:"en"},{kind:"MdxPage",name:"react",route:"/techniques/react",locale:"en"},{kind:"MdxPage",name:"reflexion",route:"/techniques/reflexion",locale:"en"},{kind:"MdxPage",name:"tot",route:"/techniques/tot",locale:"en"},{kind:"MdxPage",name:"zeroshot",route:"/techniques/zeroshot",locale:"en"}]},{kind:"MdxPage",name:"techniques",route:"/techniques",locale:"en"},{kind:"MdxPage",name:"tools",route:"/tools",locale:"en"}],flexsearch:{codeblocks:!0},title:"Generating Data",headings:c},pageNextRoute:"/applications/generating.en",nextraLayout:o.ZP,themeConfig:s.Z};
1n.default=(0,t.j)(d)}},function(e){e.O(0,[57914,26494,49774,92888,40179],function(){return e(e.s=28539)}),_N_E=e.O()}]);

Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.