[{"data":1,"prerenderedAt":2343},["ShallowReactive",2],{"blog-article-/hi-in/blog/zero-hallucination-qa":3,"blog-list-hi-in":1430},{"id":4,"title":5,"body":6,"config":1414,"date":1415,"description":1416,"draft":1417,"extension":1418,"image":1414,"meta":1419,"navigation":1420,"path":1421,"seo":1422,"stem":1423,"tags":1424,"toolbar":1414,"translationKey":1428,"updated":1415,"__hash__":1429},"blog/hi-in/blog/zero-hallucination-qa.md","मैंने रीडर में «शून्य मतिभ्रम» Q&A कैसे बनाया",{"type":7,"value":8,"toc":1378},"minimark",[9,17,32,35,40,47,52,57,75,80,93,98,132,135,139,157,164,168,183,188,226,233,237,250,275,280,398,416,423,425,429,436,451,458,478,484,486,490,493,499,501,505,528,538,599,602,613,623,630,632,636,647,653,660,664,671,679,686,690,700,741,752,758,760,764,779,787,793,796,835,845,853,859,866,870,878,884,895,897,901,907,911,918,922,944,951,953,957,963,1020,1025,1027,1031,1038,1056,1060,1080,1091,1093,1097,1108,1111,1133,1144,1150,1152,1156,1171,1182,1184,1188,1209,1220,1222,1226,1244,1250,1252,1256,1344,1351,1362],[10,11,12],"p",{},[13,14],"img",{"alt":15,"src":16},"कवर: शून्य-मतिभ्रम Q&A","https://cdn.linghuxiong.com/resources/snapshots/ai-chat-cover.png",[18,19,20],"blockquote",{},[10,21,22,23,27,28,31],{},"यह लेख हमारे AI रीडर में ",[24,25,26],"strong",{},"शून्य-मतिभ्रम Q&A"," की इंजीनियरिंग साझा करता है: उत्तर सख्ती से आपके खुले पुस्तक के पाठ पर आधारित हैं, और मुख्य दावों को ",[24,29,30],{},"एक क्लिक"," में सटीक अंश तक ट्रेस किया जा सकता है। यदि आप AI पढ़ना, दस्तावेज़ Q&A या RAG-शैली ऐप बना रहे हैं, तो तीन पुनरावृत्तियों के सबक और अंतिम आर्किटेक्चर उपयोगी हों।",[33,34],"hr",{},[36,37,39],"h2",{"id":38},"i-तीन-चरणों-में-विकास","I. तीन चरणों में विकास",[10,41,42,43,46],{},"शून्य-मतिभ्रम Q&A पहले दिन से पूर्ण नहीं था। यह ",[24,44,45],{},"लागत, विलंबता और सटीकता"," के तनाव में विकसित हुआ। नीचे तीन चरणों का कालानुक्रमिक दृश्य—वर्तमान आर्किटेक्चर क्यों ऐसा दिखता है, इसके लिए संदर्भ।",[48,49],"mermaid",{":config":50,"code":51},"config","flowchart%20LR%0A%20%20%20%20P1%5B%E0%A4%9A%E0%A4%B0%E0%A4%A3%201%3A%20%E0%A4%AA%E0%A5%82%E0%A4%B0%E0%A5%8D%E0%A4%A3%20%E0%A4%AA%E0%A4%BE%E0%A4%A0%20context%20%E0%A4%AE%E0%A5%87%E0%A4%82%5D%20--%3E%20P2%5B%E0%A4%9A%E0%A4%B0%E0%A4%A3%202%3A%20LLM%20%E0%A4%AE%E0%A5%81%E0%A4%96%E0%A5%8D%E0%A4%AF%20%E0%A4%B5%E0%A4%BE%E0%A4%95%E0%A5%8D%E0%A4%AF%20%E0%A4%A8%E0%A4%BF%E0%A4%95%E0%A4%BE%E0%A4%B2%E0%A4%A8%E0%A4%BE%5D%0A%20%20%20%20P2%20--%3E%20P3%5B%E0%A4%9A%E0%A4%B0%E0%A4%A3%203%3A%20Segment%20index%20%2B%20Tool%20retrieval%5D%0A%20%20%20%20P1%20-.-%3E%7C%E0%A4%A7%E0%A5%80%E0%A4%AE%E0%A4%BE%2C%20%E0%A4%AE%E0%A4%B9%E0%A4%81%E0%A4%97%E0%A4%BE%2C%20%E0%A4%B2%E0%A4%82%E0%A4%AC%E0%A5%80%20%E0%A4%AA%E0%A5%81%E0%A4%B8%E0%A5%8D%E0%A4%A4%E0%A4%95%E0%A5%8B%E0%A4%82%20%E0%A4%AA%E0%A4%B0%20%E0%A4%97%E0%A4%B2%E0%A4%A4%7C%20X1%5B%E0%A4%A4%E0%A5%8D%E0%A4%AF%E0%A4%BE%E0%A4%97%5D%0A%20%20%20%20P2%20-.-%3E%7C%E0%A4%B5%E0%A4%BF%E0%A4%B5%E0%A4%B0%E0%A4%A3%20%E0%A4%96%E0%A5%8B%E0%A4%A8%E0%A4%BE%2C%20%E0%A4%85%E0%A4%AD%E0%A5%80%20%E0%A4%AD%E0%A5%80%20%E0%A4%A7%E0%A5%80%E0%A4%AE%E0%A4%BE%7C%20X2%5B%E0%A4%A4%E0%A5%8D%E0%A4%AF%E0%A4%BE%E0%A4%97%5D%0A%20%20%20%20P3%20--%3E%7C%E0%A4%B5%E0%A4%B0%E0%A5%8D%E0%A4%A4%E0%A4%AE%E0%A4%BE%E0%A4%A8%7C%20OK%5B%E0%A4%B6%E0%A5%82%E0%A4%A8%E0%A5%8D%E0%A4%AF%20%E0%A4%AE%E0%A4%A4%E0%A4%BF%E0%A4%AD%E0%A5%8D%E0%A4%B0%E0%A4%AE%20%2B%20%E0%A4%9F%E0%A5%8D%E0%A4%B0%E0%A5%87%E0%A4%B8%20%E0%A4%AF%E0%A5%8B%E0%A4%97%E0%A5%8D%E0%A4%AF%5D",[53,54,56],"h3",{"id":55},"चरण-1-पूरी-किताब-context-में-डालना-सबसे-सरलऔर-सबसे-पहले-टूटा","चरण 1: पूरी किताब context में डालना (सबसे सरल—और सबसे पहले टूटा)",[10,58,59,62,63,66,67,70,71,74],{},[24,60,61],{},"दृष्टिकोण:"," उपयोगकर्ता किताब खोलकर प्रश्न पूछे तो ",[24,64,65],{},"सारा निकाला गया मुख्य पाठ"," System Prompt या उपयोगकर्ता संदेश में रखें और चैट मॉडल से उत्तर लें। पुस्तक लगभग ",[24,68,69],{},"4 लाख वर्ण"," से अधिक हो तो ",[24,72,73],{},"कठोर काट","—केवल शुरुआत रहती है; बाद के अध्याय मॉडल के लिए अदृश्य।",[10,76,77],{},[24,78,79],{},"फायदे:",[81,82,83,87,90],"ul",{},[84,85,86],"li",{},"बहुत कम कार्यान्वयन लागत; लगभग कोई पूर्व-प्रसंस्करण नहीं;",[84,88,89],{},"छोटी पुस्तकों और सरल दस्तावेज़ों पर ठीक—मॉडल ने वास्तव में «पूरी किताब देखी»;",[84,91,92],{},"सरल UX: पूछें और उत्तर, «विश्लेषण की प्रतीक्षा» स्थिति नहीं।",[10,94,95],{},[24,96,97],{},"नुकसान (जल्दी अस्वीकार्य):",[81,99,100,106,112,122],{},[84,101,102,105],{},[24,103,104],{},"धीमे उत्तर:"," हर प्रश्न पर विशाल payload फिर भेजा जाता है; पहले token तक का समय और कुल विलंबता पुस्तक लंबाई के साथ बढ़ती है;",[84,107,108,111],{},[24,109,110],{},"उच्च token लागत:"," हर प्रश्न पर पूरी किताब का input भुगतान;",[84,113,114,117,118,121],{},[24,115,116],{},"लंबी पुस्तकें बुरी तरह विकृत:"," 4 लाख वर्ण के बाद दूसरा आधा, परिशिष्ट, निष्कर्ष मानो नहीं—और UI अक्सर ",[24,119,120],{},"स्पष्ट नहीं बताता"," कि काट हुआ;",[84,123,124,127,128,131],{},[24,125,126],{},"शून्य retrieval granularity:"," मॉडल को लाखों वर्णों में «सूई ढूँढनी»—विवरण छूटना आसान, ",[24,129,130],{},"आधारहीन लेकिन विश्वसनीय लगने वाले सार"," आसान—पढ़ने वाले ऐप को बचना चाहिए।",[10,133,134],{},"चरण 1 MVP के लिए ठीक, उत्पाद-स्तर के लिए नहीं।",[53,136,138],{"id":137},"चरण-2-हल्का-llm-मुख्य-वाक्य-निकाले-context-संकुचितपर-बहुत-अधिक","चरण 2: हल्का LLM मुख्य वाक्य निकाले (context संकुचित—पर बहुत अधिक)",[10,140,141,143,144,147,148,151,152,156],{},[24,142,61],{}," Q&A से पहले (या पहली बार खोलने पर) ",[24,145,146],{},"सस्ता मॉडल"," मुख्य पाठ पर: Spine अध्याय से विभाजित (या पूरी पुस्तक chunk), ",[24,149,150],{},"मुख्य वाक्य"," निकालें, ",[153,154,155],"code",{},"[fफ़ाइल-शुरू-अंत]"," जैसे स्थिति टैग रखें, फिर संक्षिप्त context में जोड़कर बाद के Q&A के लिए।",[10,158,159,160,163],{},"सामान्य pipeline: ",[24,161,162],{},"Extract → Cache → Chat",". एक बार निकालें (offline या माँग पर), «मुख्य वाक्य बंडल» संग्रहित, हर प्रश्न पर पुन: उपयोग—कई दस्तावेज़ Q&A प्रोटोटाइप जैसा।",[10,165,166],{},[24,167,79],{},[81,169,170,177,180],{},[84,171,172,173,176],{},"हर प्रश्न ",[24,174,175],{},"बहुत कम पाठ"," भेजता है; प्रति अनुरोध token चरण 1 से कम;",[84,178,179],{},"पूर्व-प्रसंस्करण cache हो सकता है; उसी पुस्तक पर हर प्रश्न पर पुन: निकालना नहीं;",[84,181,182],{},"स्थिति टैग उद्धरण की नींव।",[10,184,185],{},[24,186,187],{},"नुकसान (लंबी पुस्तकों पर अभी भी विफल):",[81,189,190,196,206,216],{},[84,191,192,195],{},[24,193,194],{},"भारी विवरण हानि:"," «मुख्य वाक्य» मॉडल चुनता है; सीमक, प्रतिवाद, तर्क श्रृंखला अक्सर गिरती है—उत्तर «सही पर एकतरफा»;",[84,197,198,201,202,205],{},[24,199,200],{},"लंबी पुस्तकों पर context अभी भी बड़ा:"," बड़े ग्रंथों के मुख्य वाक्य बंडल भी भारी—विलंबता और लागत ",[24,203,204],{},"कम हुई, हल नहीं",";",[84,207,208,211,212,215],{},[24,209,210],{},"दोहरा LLM त्रुटि:"," निष्कर्षण छूट सकता है; Q&A अंश गलत पढ़ सकता है—त्रुटियाँ ",[24,213,214],{},"जुड़ती"," हैं;",[84,217,218,221,222,225],{},[24,219,220],{},"स्थिर context:"," उपयोगकर्ता एक अध्याय या पूरी संरचना पूछे, मॉडल को हमेशा ",[24,223,224],{},"वही पूर्व-निकाला blob","—प्रश्न से गतिशील संकुचन नहीं।",[10,227,228,229,232],{},"सबक: मुद्दा «संकुचित करें या नहीं» नहीं, ",[24,230,231],{},"«संकुचन माँग पर है और क्या स्रोत पाठ पर लौट सकते हैं»","।",[53,234,236],{"id":235},"चरण-3-segment-index-tool-retrieval-माँग-पर-स्रोत-पाठ-वापस-वर्तमान","चरण 3: Segment index + Tool retrieval माँग पर + स्रोत पाठ वापस (वर्तमान)",[10,238,239,241,242,249],{},[24,240,61],{}," ",[243,244,248],"a",{"href":245,"rel":246},"https://github.com/VectifyAI/PageIndex",[247],"nofollow","PageIndex"," से प्रेरित। चरण 2 की तुलना में तीन मुख्य बदलाव:",[251,252,253,259,269],"ol",{},[84,254,255,258],{},[24,256,257],{},"पूर्व-प्रसंस्करण संरचित index"," (TOC-स्तर सार + सटीक वर्ण span), सीधे Q&A context के रूप में अंश नहीं;",[84,260,261,264,265,268],{},[24,262,263],{},"हर प्रश्न Tool Calling से माँग पर retrieval",", फिर ",[24,266,267],{},"स्थिति टैग के साथ स्रोत पाठ"," खींचकर उत्तर;",[84,270,271,274],{},[24,272,273],{},"System Prompt + frontend"," उद्धरण प्रारूप लागू, क्लिक से कूद और रीडर में हाइलाइट।",[10,276,277],{},[24,278,279],{},"तीन चरण तुलना:",[281,282,283,302],"table",{},[284,285,286],"thead",{},[287,288,289,293,296,299],"tr",{},[290,291,292],"th",{},"आयाम",[290,294,295],{},"चरण 1 (पूर्ण dump)",[290,297,298],{},"चरण 2 (मुख्य वाक्य)",[290,300,301],{},"चरण 3 (वर्तमान)",[303,304,305,324,338,352,366,384],"tbody",{},[287,306,307,311,314,317],{},[308,309,310],"td",{},"प्रति प्रश्न context",[308,312,313],{},"पूरी पुस्तक (या काटा पहला आधा)",[308,315,316],{},"पूर्व-निकाले मुख्य वाक्य",[308,318,319,320,323],{},"केवल प्रश्न से संबंधित ",[24,321,322],{},"स्रोत"," अंश",[287,325,326,329,332,335],{},[308,327,328],{},"लंबी पुस्तक सटीकता",[308,330,331],{},"~400k वर्ण के बाद गिरावट",[308,333,334],{},"निष्कर्षण पर निर्भर; विवरण खोना",[308,336,337],{},"TOC/span से retrieve; पूरी पुस्तक कठोर काट नहीं",[287,339,340,343,346,349],{},[308,341,342],{},"उत्तर गति",[308,344,345],{},"धीमा",[308,347,348],{},"थोड़ा बेहतर; लंबी पुस्तक अभी धीमी",[308,350,351],{},"Retrieve + छोटा context—स्पष्ट तेज",[287,353,354,357,360,363],{},[308,355,356],{},"Token लागत",[308,358,359],{},"बहुत उच्च",[308,361,362],{},"मध्यम-उच्च",[308,364,365],{},"परिशोधित पूर्व-प्रसंस्करण + आवश्यकतानुसार भुगतान",[287,367,368,371,374,377],{},[308,369,370],{},"ट्रेस योग्यता",[308,372,373],{},"कमजोर",[308,375,376],{},"टैग हैं पर सामग्री पहले से छनी",[308,378,379,380,383],{},"फ़ुटनोट ",[24,381,382],{},"वास्तविक स्रोत span"," से मेल",[287,385,386,389,392,395],{},[308,387,388],{},"इंजीनियरिंग जटिलता",[308,390,391],{},"कम",[308,393,394],{},"मध्यम",[308,396,397],{},"उच्च",[10,399,400,403,404,407,408,411,412,415],{},[24,401,402],{},"चरण 3 पर क्यों रुके:"," पढ़ने में शून्य मतिभ्रम «मॉडल को ज़्यादा से ज़्यादा पाठ दिखाना» नहीं, ",[24,405,406],{},"«उत्तर से पहले प्रश्न के लिए स्रोत साक्ष्य लाना»","। चरण 1–2 ने ",[24,409,410],{},"context आकार"," पर लड़ाई की; चरण 3 pipeline विभाजित: ",[24,413,414],{},"index (पूर्व-प्रसंस्करण) → retrieve (Tool) → साक्ष्य (स्रोत) → उत्तर (बंधित जनरेशन)","—सटीकता, लागत, ट्रेस योग्यता संतुलन।",[10,417,418,419,422],{},"नीचे ",[24,420,421],{},"चरण 3"," विवरण।",[33,424],{},[36,426,428],{"id":427},"ii-समस्या-परिभाषा-पुस्तक-qa-में-मतिभ्रम-सामान्य-चैट-से-अधिक-हानिकारक","II. समस्या परिभाषा: पुस्तक Q&A में मतिभ्रम सामान्य चैट से अधिक हानिकारक",[10,430,431,432,435],{},"सामान्य चैटबॉट में उपयोगकर्ता कभी-कभार त्रुटि क्षमा करते हैं। ",[24,433,434],{},"पुस्तक Q&A"," में लागत अधिक:",[81,437,438,445,448],{},[84,439,440,441,444],{},"वे पूछते हैं ",[24,442,443],{},"यह पुस्तक"," क्या कहती है—मॉडल की parametric memory नहीं;",[84,446,447],{},"विश्वसनीय लगने वाला «पुस्तक का विचार» नोट, उद्धरण, पुन: साझा करने में भ्रमित कर सकता है;",[84,449,450],{},"स्रोत के बिना सत्यापन नहीं—विश्वास बनाना कठिन।",[10,452,453,454,457],{},"अतः «शून्य मतिभ्रम» तीन ",[24,455,456],{},"कार्यान्वयन योग्य"," नियम:",[251,459,460,466,472],{},[84,461,462,465],{},[24,463,464],{},"पुस्तक प्रश्न पहले पुस्तक से पूछें:"," खुली पुस्तक से संबंधित कुछ भी retrieval (Tool) से गुजरना चाहिए;",[84,467,468,471],{},[24,469,470],{},"उत्तर ट्रेस योग्य:"," मुख्य दावों में स्थिति टैग जिन्हें UI पार्स और कूद सके;",[84,473,474,477],{},[24,475,476],{},"न मिले तो कहें:"," पुस्तक में न हो तो कहें—सामान्य ज्ञान को «पुस्तक कहती है» न बनाएँ।",[10,479,480,481,483],{},"शेष ",[24,482,421],{}," डेटा प्रवाह और नियम कार्यान्वयन।",[33,485],{},[36,487,489],{"id":488},"iii-आर्किटेक्चर-पूर्व-प्रसंस्करण-tool-retrieval-बंधित-जनरेशन-क्लिक-योग्य-उद्धरण","III. आर्किटेक्चर: पूर्व-प्रसंस्करण → Tool retrieval → बंधित जनरेशन → क्लिक योग्य उद्धरण",[48,491],{":config":50,"code":492},"flowchart%20TB%0A%20%20%20%20subgraph%20prep%20%5BOffline%20%2F%20%E0%A4%AA%E0%A4%B9%E0%A4%B2%E0%A5%80%20%E0%A4%AC%E0%A4%BE%E0%A4%B0%20%E0%A4%AA%E0%A5%82%E0%A4%B0%E0%A5%8D%E0%A4%B5-%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%B8%E0%A4%82%E0%A4%B8%E0%A5%8D%E0%A4%95%E0%A4%B0%E0%A4%A3%5D%0A%20%20%20%20%20%20%20%20A%5BTOC%20%E0%A4%AF%E0%A4%BE%20%E0%A4%B2%E0%A4%82%E0%A4%AC%E0%A4%BE%E0%A4%88%20%E0%A4%B8%E0%A5%87%20%E0%A4%AA%E0%A5%81%E0%A4%B8%E0%A5%8D%E0%A4%A4%E0%A4%95%20%E0%A4%B5%E0%A4%BF%E0%A4%AD%E0%A4%BE%E0%A4%9C%E0%A4%BF%E0%A4%A4%5D%20--%3E%20B%5BLLM%20Segment%20%E0%A4%B8%E0%A4%BE%E0%A4%B0%5D%0A%20%20%20%20%20%20%20%20B%20--%3E%20C%5B%E0%A4%B8%E0%A5%8D%E0%A4%A5%E0%A4%BE%E0%A4%A8%E0%A5%80%E0%A4%AF%20Segment%20cache%20persist%5D%0A%20%20%20%20end%0A%0A%20%20%20%20subgraph%20ask%20%5B%E0%A4%89%E0%A4%AA%E0%A4%AF%E0%A5%8B%E0%A4%97%E0%A4%95%E0%A4%B0%E0%A5%8D%E0%A4%A4%E0%A4%BE%20%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%B6%E0%A5%8D%E0%A4%A8%5D%0A%20%20%20%20%20%20%20%20D%5B%E0%A4%89%E0%A4%AA%E0%A4%AF%E0%A5%8B%E0%A4%97%E0%A4%95%E0%A4%B0%E0%A5%8D%E0%A4%A4%E0%A4%BE%20input%5D%20--%3E%20E%7BSegment%20cache%20%E0%A4%B9%E0%A5%88%3F%7D%0A%20%20%20%20%20%20%20%20E%20--%3E%7C%E0%A4%A8%E0%A4%B9%E0%A5%80%E0%A4%82%7C%20F%5B%E0%A4%AA%E0%A5%82%E0%A4%B0%E0%A5%8D%E0%A4%A3%20%E0%A4%AA%E0%A4%BE%E0%A4%A0%20%E0%A4%A8%E0%A4%BF%E0%A4%95%E0%A4%BE%E0%A4%B2%E0%A5%87%E0%A4%82%20%2F%20%E0%A4%AA%E0%A5%82%E0%A4%B0%E0%A5%8D%E0%A4%B5-%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%B8%E0%A4%82%E0%A4%B8%E0%A5%8D%E0%A4%95%E0%A4%B0%E0%A4%A3%20%E0%A4%AA%E0%A5%82%E0%A4%9B%E0%A5%87%E0%A4%82%5D%0A%20%20%20%20%20%20%20%20F%20--%3E%20prep%0A%20%20%20%20%20%20%20%20E%20--%3E%7C%E0%A4%B9%E0%A4%BE%E0%A4%81%7C%20G%5BTool%20Calling%20%E0%A4%AA%E0%A4%82%E0%A4%9C%E0%A5%80%E0%A4%95%E0%A5%83%E0%A4%A4%5D%0A%20%20%20%20end%0A%0A%20%20%20%20subgraph%20retrieve%20%5BTool%20retrieval%5D%0A%20%20%20%20%20%20%20%20G%20--%3E%20H%7B%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%B6%E0%A5%8D%E0%A4%A8%20%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%95%E0%A4%BE%E0%A4%B0%7D%0A%20%20%20%20%20%20%20%20H%20--%3E%7C%E0%A4%85%E0%A4%B5%E0%A4%B2%E0%A5%8B%E0%A4%95%E0%A4%A8%20%2F%20%E0%A4%B8%E0%A4%AE%E0%A5%80%E0%A4%95%E0%A5%8D%E0%A4%B7%E0%A4%BE%7C%20I%5Bget_full_book_segment_summaries%5D%0A%20%20%20%20%20%20%20%20H%20--%3E%7C%E0%A4%A4%E0%A4%A5%E0%A5%8D%E0%A4%AF%20%2F%20%E0%A4%B5%E0%A5%8D%E0%A4%AF%E0%A4%95%E0%A5%8D%E0%A4%A4%E0%A4%BF%20%2F%20%E0%A4%85%E0%A4%A7%E0%A5%8D%E0%A4%AF%E0%A4%BE%E0%A4%AF%7C%20J%5Bget_related_segment_summaries%5D%0A%20%20%20%20%20%20%20%20J%20--%3E%20K%5BLLM%20%E0%A4%B8%E0%A4%BE%E0%A4%B0%20%E0%A4%95%E0%A5%88%E0%A4%9F%E0%A4%B2%E0%A5%89%E0%A4%97%20%E0%A4%B8%E0%A5%87%20Segment%20ID%20%E0%A4%9A%E0%A5%81%E0%A4%A8%E0%A4%A4%E0%A4%BE%5D%0A%20%20%20%20%20%20%20%20K%20--%3E%20L%5Bspan%20%E0%A4%B8%E0%A5%87%20%E0%A4%B8%E0%A5%8D%E0%A4%B0%E0%A5%8B%E0%A4%A4%20%2B%20%E0%A4%B8%E0%A5%8D%E0%A4%A5%E0%A4%BF%E0%A4%A4%E0%A4%BF%20%E0%A4%9F%E0%A5%88%E0%A4%97%5D%0A%20%20%20%20%20%20%20%20I%20--%3E%20M%5B%E0%A4%B8%E0%A4%AD%E0%A5%80%20Segment%20%E0%A4%B8%E0%A4%BE%E0%A4%B0%20%E0%A4%9C%E0%A5%8B%E0%A4%A1%E0%A4%BC%E0%A5%87%E0%A4%82%5D%0A%20%20%20%20end%0A%0A%20%20%20%20subgraph%20answer%20%5B%E0%A4%9C%E0%A4%A8%E0%A4%B0%E0%A5%87%E0%A4%9F%20%E0%A4%94%E0%A4%B0%20%E0%A4%AA%E0%A5%8D%E0%A4%B0%E0%A4%A6%E0%A4%B0%E0%A5%8D%E0%A4%B6%E0%A4%A8%5D%0A%20%20%20%20%20%20%20%20L%20--%3E%20N%5BTool%20%E0%A4%AA%E0%A4%B0%E0%A4%BF%E0%A4%A3%E0%A4%BE%E0%A4%AE%20%E0%A4%AE%E0%A5%89%E0%A4%A1%E0%A4%B2%20%E0%A4%95%E0%A5%8B%5D%0A%20%20%20%20%20%20%20%20M%20--%3E%20N%0A%20%20%20%20%20%20%20%20N%20--%3E%20O%5BSystem%20Prompt%20%E0%A4%89%E0%A4%A6%E0%A5%8D%E0%A4%A7%E0%A4%B0%E0%A4%A3%20%E0%A4%A8%E0%A4%BF%E0%A4%AF%E0%A4%AE%5D%0A%20%20%20%20%20%20%20%20O%20--%3E%20P%5B%E0%A4%B8%E0%A5%8D%E0%A4%9F%E0%A5%8D%E0%A4%B0%E0%A5%80%E0%A4%AE%20%E0%A4%89%E0%A4%A4%E0%A5%8D%E0%A4%A4%E0%A4%B0%20%2B%20%E0%A4%B8%E0%A5%8D%E0%A4%A5%E0%A4%BF%E0%A4%A4%E0%A4%BF%20%E0%A4%AB%E0%A4%BC%E0%A5%81%E0%A4%9F%E0%A4%A8%E0%A5%8B%E0%A4%9F%5D%0A%20%20%20%20%20%20%20%20P%20--%3E%20Q%5B%E0%A4%95%E0%A5%8D%E0%A4%B2%E0%A4%BF%E0%A4%95%20%E0%A4%AF%E0%A5%8B%E0%A4%97%E0%A5%8D%E0%A4%AF%20%E0%A4%AB%E0%A4%BC%E0%A5%81%E0%A4%9F%E0%A4%A8%E0%A5%8B%E0%A4%9F%20render%5D%0A%20%20%20%20%20%20%20%20Q%20--%3E%20R%5B%E0%A4%95%E0%A5%8D%E0%A4%B2%E0%A4%BF%E0%A4%95%20%E2%86%92%20%E0%A4%AA%E0%A5%82%E0%A4%B0%E0%A5%8D%E0%A4%B5%E0%A4%BE%E0%A4%B5%E0%A4%B2%E0%A5%8B%E0%A4%95%E0%A4%A8%20%E2%86%92%20%E0%A4%95%E0%A5%82%E0%A4%A6%20%E0%A4%94%E0%A4%B0%20%E0%A4%B9%E0%A4%BE%E0%A4%87%E0%A4%B2%E0%A4%BE%E0%A4%87%E0%A4%9F%5D%0A%20%20%20%20end",[10,494,495,496],{},"मुख्य विचार: ",[24,497,498],{},"मॉडल को «स्मृति से उत्तर» न दें—«साक्ष्य इकट्ठा करें, उत्तर दें, स्रोत चिह्नित करें»।",[33,500],{},[36,502,504],{"id":503},"iv-पूर्व-प्रसंस्करण-पूरी-पुस्तक-को-खोज-योग्य-segment-index-बनाना","IV. पूर्व-प्रसंस्करण: पूरी पुस्तक को खोज योग्य Segment index बनाना",[10,506,507,508,511,512,515,516,519,520,523,524,527],{},"यदि हर प्रश्न ",[24,509,510],{},"चरण 1"," पूर्ण-पुस्तक context उपयोग करे, लंबी पुस्तकें token बजट फोड़ दें। चरण 3: किसी पुस्तक पर पहला AI चैट पर पृष्ठभूमि में ",[24,513,514],{},"Segment सार कार्य","—",[24,517,518],{},"TOC"," या ",[24,521,522],{},"पाठ लंबाई"," से ",[153,525,526],{},"Segment"," में विभाजित, प्रत्येक का सार, स्थानीय IndexedDB में persist।",[10,529,530,531,533,534,537],{},"प्रत्येक ",[153,532,526],{}," में सार और ",[24,535,536],{},"मुख्य पाठ में भौतिक स्थिति",":",[281,539,540,550],{},[284,541,542],{},[287,543,544,547],{},[290,545,546],{},"फ़ील्ड",[290,548,549],{},"अर्थ",[303,551,552,566,579,589],{},[287,553,554,563],{},[308,555,556,559,560],{},[153,557,558],{},"startFileIndex"," / ",[153,561,562],{},"endFileIndex",[308,564,565],{},"Spine फ़ाइल index (PDF: प्रति पृष्ठ एक फ़ाइल)",[287,567,568,576],{},[308,569,570,559,573],{},[153,571,572],{},"startOffset",[153,574,575],{},"endOffset",[308,577,578],{},"वर्ण प्रारंभ/अंत",[287,580,581,586],{},[308,582,583],{},[153,584,585],{},"sequence",[308,587,588],{},"रैखिक पढ़ने क्रम",[287,590,591,596],{},[308,592,593],{},[153,594,595],{},"title",[308,597,598],{},"TOC शीर्षक",[10,600,601],{},"विभाजन सटीकता और लागत संतुलित: TOC नोड का मुख्य पाठ ~20KB से कम हो तो केवल वह नोड; sibling 15–20KB बैच में मिल सकते हैं LLM से पहले; असंरचित लंबे ब्लॉक ~30–40k वर्ण अंतराल में।",[10,603,604,605,608,609,612],{},"सार System Prompt ",[24,606,607],{},"inline स्थिति टैग"," (",[153,610,611],{},"[fसंख्या-संख्या-संख्या]",") माँगता है ताकि Tool-स्रोत Spine offset से मेल खाए। मुख्य बाधा:",[614,615,621],"pre",{"className":616,"code":618,"language":619,"meta":620},[617],"language-text","यदि सार किसी अंश से संबंधित हो, अंत में स्थिति टैग [fसंख्या-संख्या-संख्या] रखें (जैसे [f1-90-109])।\nटैग परमाणु हैं—कोई वर्ण या अंक न बदलें, मिलाएँ या छोड़ें।\n","text","",[153,622,618],{"__ignoreMap":620},[10,624,625,626,629],{},"पूर्व-प्रसंस्करण के बाद Q&A ",[24,627,628],{},"संरचित Segment index"," पर निर्भर, पूर्ण-पुस्तक context नहीं—लंबी पुस्तकों पर शून्य मतिभ्रम की इंजीनियरिंग पूर्वापेक्षा।",[33,631],{},[36,633,635],{"id":634},"v-स्थिति-टैग-प्रणाली-पाठ-में-कहाँ-एन्कोड","V. स्थिति टैग प्रणाली: पाठ में «कहाँ» एन्कोड",[10,637,638,639,642,643,646],{},"शून्य मतिभ्रम को स्रोत से सामग्री ",[24,640,641],{},"और"," मशीन-पार्स, UI-कूद योग्य ",[24,644,645],{},"उत्पत्ति"," चाहिए। हम inline टैग:",[614,648,651],{"className":649,"code":650,"language":619},[617],"[f{fileIndex}-{startChar}-{endChar}]\n",[153,652,650],{"__ignoreMap":620},[10,654,655,656,659],{},"उदाहरण: ",[153,657,658],{},"[f5-123-165]"," = Spine फ़ाइल 5 (0-आधारित), वर्ण 123–165।",[53,661,663],{"id":662},"_51-टैग-मुख्य-पाठ-में-कैसे-लिखे-जाते-हैं","5.1 टैग मुख्य पाठ में कैसे लिखे जाते हैं",[10,665,666,667,670],{},"निष्कर्षण परत Segment अंत में ",[153,668,669],{},"[f{fileIndex}-{start}-{end}]"," जोड़ती है:",[614,672,677],{"className":673,"code":675,"language":676,"meta":620},[674],"language-typescript","const position = `[f${fileIndex}-${absOffset}-${absOffset + segment.length}]`;\nfileLines.push(segment.text.trim() + position);\n","typescript",[153,678,675],{"__ignoreMap":620},[10,680,681,682,685],{},"पूर्व-प्रसंस्करण सार या Tool अंश, स्थिति ",[24,683,684],{},"Spine वर्ण offset"," से मेल—मॉडल अनुमानित पृष्ठ संख्या नहीं।",[53,687,689],{"id":688},"_52-मॉडल-आउटपुट-पर-बाधाएँ","5.2 मॉडल आउटपुट पर बाधाएँ",[10,691,692,693,699],{},"System Prompt में ",[24,694,695],{},[696,697,698],"span",{},"Position Citation Rules","—पाँच मुख्य बिंदु:",[251,701,702,711,720,726,735],{},[84,703,704,241,707,710],{},[24,705,706],{},"मानक प्रारूप:",[153,708,709],{},"[f_fileIndex-startChar-endChar]"," अनिवार्य; तीन संख्यात्मक भाग;",[84,712,713,716,717,205],{},[24,714,715],{},"केवल वर्तमान स्रोत से कॉपी:"," फ़ुटनोट इस turn के system/user या Tool से ",[24,718,719],{},"शब्दशः",[84,721,722,725],{},[24,723,724],{},"निर्माण नहीं:"," स्थिति गणना, संपादन, आविष्कार नहीं;",[84,727,728,731,732,205],{},[24,729,730],{},"छोड़ना प्राथमिक:"," context में वैध टैग नहीं तो सामान्य उत्तर—",[24,733,734],{},"कोई स्थिति टैग नहीं",[84,736,737,740],{},[24,738,739],{},"दावे के साथ inline:"," टैग प्रासंगिक वाक्य के बाद; अंत में उद्धरण सूची नहीं।",[10,742,743,744,747,748,751],{},"UI कभी-कभार ",[24,745,746],{},"दो-भाग"," अवैध टैग (जैसे ",[153,749,750],{},"[f1-293]",") render से पहले फ़िल्टर करता है।",[10,753,754],{},[13,755],{"alt":756,"src":757},"उद्धरण ट्रेस पॉपअप","https://cdn.linghuxiong.com/resources/snapshots/ai-chat.png",[33,759],{},[36,761,763],{"id":762},"vi-tool-calling-पहले-retrieve-फिर-उत्तर","VI. Tool Calling: पहले retrieve, फिर उत्तर",[10,765,766,767,770,771,774,775,778],{},"जब चैट पुस्तक से बँधा (",[153,768,769],{},"resourceId"," मौजूद, ",[153,772,773],{},"chatType === 'chat'","), हर जनरेशन से पहले दो Tools executors के साथ—मानक OpenAI ",[24,776,777],{},"function calling"," लूप।",[53,780,782,783,786],{"id":781},"_61-get_related_segment_summaries-लक्षित-segment-खोज","6.1 ",[153,784,785],{},"get_related_segment_summaries"," — लक्षित Segment खोज",[10,788,789,790,232],{},"के लिए: अवधारणा, पात्र, कथानक, अध्याय विवरण—",[24,791,792],{},"स्पष्ट retrieval इरादा",[10,794,795],{},"प्रवाह:",[251,797,798,805,811,818,828],{},[84,799,800,801,804],{},"मॉडल उपयोगकर्ता शब्दों को ",[24,802,803],{},"पुस्तक में संभावित शब्दों"," में बदलता है (System Prompt में «Optimize Search Queries»);",[84,806,807,810],{},[153,808,809],{},"question"," के साथ Tool;",[84,812,813,814,817],{},"सभी Segment सार token बजट से ",[24,815,816],{},"बैच"," (~30k tokens प्रति बैच, अधिकतम 5);",[84,819,820,821,824,825,205],{},"प्रत्येक बैच: अलग LLM अनुरोध ",[153,822,823],{},"{ id, title, summary }"," से प्रासंगिक Segment ID (अधिकतम 5), JSON जैसे ",[153,826,827],{},"{\"Thinking\":\"...\",\"answer\":[\"1\",\"3\"]}",[84,829,830,831,834],{},"चुने Segment के लिए Spine से ",[24,832,833],{},"टैग युक्त स्रोत पाठ","—सार नहीं—Tool परिणाम।",[10,836,837,840,841,844],{},[24,838,839],{},"मुख्य डिज़ाइन: Tool स्रोत लौटाता है, सार नहीं।"," मॉडल वास्तविक अनुच्छेदों से inline ",[153,842,843],{},"[f…]"," के साथ उत्तर, «सार → पुन: सार» विचलन से बचाव।",[53,846,848,849,852],{"id":847},"_62-get_full_book_segment_summaries-पूर्ण-पुस्तक-अवलोकन","6.2 ",[153,850,851],{},"get_full_book_segment_summaries"," — पूर्ण-पुस्तक अवलोकन",[10,854,855,856,232],{},"के लिए: «पुस्तक सारांश», «समीक्षा», «समग्र संरचना/विषय»—",[24,857,858],{},"वैश्विक दृश्य",[10,860,861,862,865],{},"सभी Segment ",[153,863,864],{},"summary"," पढ़ने क्रम में जोड़ें—केवल chunk प्रासंगिकता से मुख्य अध्याय न छूटें।",[53,867,869],{"id":868},"_63-system-prompt-पुस्तक-पहले-tools-पहले","6.3 System Prompt: पुस्तक पहले, tools पहले",[10,871,872,873,537],{},"बँधी पुस्तक पर ",[24,874,875],{},[696,876,877],{},"Core Principles for Reading Assistant",[614,879,882],{"className":880,"code":881,"language":619},[617],"1. Book First, Tool First\n   - पुस्तक से संबंधित कोई भी प्रश्न पहले tools;\n   - उत्तर मुख्यतः retrieval पर—बिना retrieval «पुस्तक सामग्री» न बनाएँ।\n\n2. General Knowledge as Fallback Only\n   - केवल: आम बातचीत / उपयोगकर्ता स्पष्ट रूप से पुस्तक छोड़े / tools खाली;\n   - पुस्तक में न हो तो «इस पुस्तक में उल्लेख नहीं» सामान्य ज्ञान से पहले।\n\n3. Direct Style\n   - सीधे मुद्दे पर—«प्रदत्त सामग्री के आधार पर…» जैसी भराव नहीं।\n",[153,883,881],{"__ignoreMap":620},[10,885,886,887,890,891,894],{},"जनरेशन tool लूप: ",[153,888,889],{},"tool_calls"," → execute → ",[153,892,893],{},"role: tool"," → अंतिम पाठ तक। tools सक्षम पर thinking चैनल बंद, protocol संघर्ष से बचाव।",[33,896],{},[36,898,900],{"id":899},"vii-frontend-ट्रेस-फ़ुटनोट-से-हाइलाइट","VII. Frontend ट्रेस: फ़ुटनोट से हाइलाइट",[10,902,903,904,906],{},"मॉडल ",[153,905,658],{}," कच्चा नहीं दिखता; render परत क्लिक योग्य उद्धरण।",[53,908,910],{"id":909},"_71-फ़ुटनोट-render","7.1 फ़ुटनोट render",[10,912,913,914,917],{},"टैग Markdown लिंक ",[153,915,916],{},"[1]([f5-123-165])"," में, क्रमांकित फ़ुटनोट; समान स्थिति dedupe।",[53,919,921],{"id":920},"_72-क्लिक-इंटरैक्शन","7.2 क्लिक इंटरैक्शन",[251,923,924,932,938],{},[84,925,926,241,929,931],{},[24,927,928],{},"पहला क्लिक:",[153,930,843],{}," पार्स → fileIndex + offsets → Spine पाठ → पूर्वावलोकन (वैकल्पिक TOC शीर्षक);",[84,933,934,937],{},[24,935,936],{},"वही फ़ुटनोट फिर:"," पूर्वावलोकन बंद;",[84,939,940,943],{},[24,941,942],{},"कूद पुष्टि:"," रीडर दृश्य, वर्ण अंतराल हाइलाइट।",[10,945,946,947,950],{},"मॉडल टैग से उपयोगकर्ता-दृश्य स्रोत तक श्रृंखला ",[24,948,949],{},"कभी दूसरे LLM से नहीं","—नियतात्मक, पुनरुत्पादनीय।",[33,952],{},[36,954,956],{"id":955},"viii-सीमा-मामले-और-ईमानदार-अवनति","VIII. सीमा मामले और ईमानदार अवनति",[10,958,959,960,537],{},"शून्य मतिभ्रम ≠ «हमेशा उत्तर»—",[24,961,962],{},"साक्ष्य नहीं तो निर्माण नहीं",[281,964,965,975],{},[284,966,967],{},[287,968,969,972],{},[290,970,971],{},"परिदृश्य",[290,973,974],{},"व्यवहार",[303,976,977,985,996,1004,1012],{},[287,978,979,982],{},[308,980,981],{},"Segment सार तैयार नहीं",[308,983,984],{},"पहले पूर्ण पाठ निकालें और सार",[287,986,987,990],{},[308,988,989],{},"Tool कुछ नहीं",[308,991,992,995],{},[153,993,994],{},"(No relevant segment excerpts found…)","; मॉडल पुस्तक में नहीं कहे",[287,997,998,1001],{},[308,999,1000],{},"मॉडल से अवैध दो-भाग टैग",[308,1002,1003],{},"Frontend फ़िल्टर",[287,1005,1006,1009],{},[308,1007,1008],{},"आम बातचीत",[308,1010,1011],{},"System Prompt पुस्तक से बाहर सामान्य ज्ञान",[287,1013,1014,1017],{},[308,1015,1016],{},"चैट निर्यात",[308,1018,1019],{},"फ़ुटनोट रीडर deep link बन सकते हैं",[10,1021,1022],{},[13,1023],{"alt":1016,"src":1024},"https://cdn.linghuxiong.com/resources/snapshots/ai-chat-export.png",[33,1026],{},[36,1028,1030],{"id":1029},"ix-डिज़ाइन-समझौता-vector-rag-क्यों-नहीं","IX. डिज़ाइन समझौता: «vector RAG» क्यों नहीं?",[10,1032,1033,1034,1037],{},"दस्तावेज़ Q&A सहकर्मी पूछते: retrieval-augmented generation हो तो ",[24,1035,1036],{},"Embedding + vector DB Top-K"," क्यों नहीं?",[10,1039,1040,1041,1044,1045,1048,1049,515,1052,1055],{},"हम ",[24,1042,1043],{},"RAG कर रहे हैं","—जनरेट से पहले retrieve। अंतर: समुदाय में «RAG» अक्सर ",[24,1046,1047],{},"vector समानता","; हमारा चरण 3 ",[24,1050,1051],{},"Segment index + Tool माँग पर स्रोत pull",[24,1053,1054],{},"जानबूझकर vector परत नहीं","। नीचे आर्किटेक्चर कारण, vector RAG का मूल्य नकार नहीं।",[53,1057,1059],{"id":1058},"दायरा-कोई-retrieval-नहीं-नहीं-vector-retrieval-नहीं","दायरा: «कोई retrieval नहीं» नहीं, «vector retrieval नहीं»",[81,1061,1062,1071],{},[84,1063,1064,1067,1068,205],{},[24,1065,1066],{},"व्यापक RAG:"," retrieve → generate → ",[24,1069,1070],{},"हम करते हैं",[84,1072,1073,1076,1077,232],{},[24,1074,1075],{},"Vector RAG:"," embedding समानता से recall → ",[24,1078,1079],{},"इस संस्करण में नहीं",[10,1081,1082,1083,1086,1087,1090],{},"पूर्व-प्रसंस्करण ",[24,1084,1085],{},"Segment सार index","; मॉडल Tools से Segment चुनता, ",[24,1088,1089],{},"स्रोत पाठ"," पाता है। Retrieval बिना अलग embedding मॉडल और vector index रख-रखाव।",[33,1092],{},[53,1094,1096],{"id":1095},"कारण-1-कस्टम-llm-providersएकीकरण-सतह-छोटी","कारण 1: कस्टम LLM providers—एकीकरण सतह छोटी",[10,1098,1099,1100,1103,1104,1107],{},"उपयोगकर्ता ",[24,1101,1102],{},"अपनी API keys",", कस्टम base URL, या ",[24,1105,1106],{},"स्थानीय Ollama","—चैट मॉडल उनकी पसंद।",[10,1109,1110],{},"सामान्य vector RAG एकीकरण विस्तार:",[81,1112,1113,1123,1126],{},[84,1114,1115,1118,1119,1122],{},[24,1116,1117],{},"चैट मॉडल"," के अलावा अक्सर ",[24,1120,1121],{},"embedding मॉडल"," (दूसरा नाम, कभी दूसरा endpoint);",[84,1124,1125],{},"स्थानीय Ollama को अलग embedding और आयाम/API अनुकूलता;",[84,1127,1128,1129,1132],{},"अधिक विफलता: चैट ठीक पर ",[24,1130,1131],{},"खाली retrieval","—embedding, index, आयाम असंगति; एक provider end-to-end से कठिन debug।",[10,1134,1135,1136,1139,1140,1143],{},"यहाँ ",[24,1137,1138],{},"Segment चयन और उत्तर एक provider config साझा","—«चैट A, index B» नहीं। ",[24,1141,1142],{},"प्लग योग्य LLM"," ऐप के लिए अक्सर कुछ recall अंक से महत्वपूर्ण।",[10,1145,1146],{},[13,1147],{"alt":1148,"src":1149},"कस्टम AI providers","https://cdn.linghuxiong.com/resources/snapshots/ai-customize-providers.png",[33,1151],{},[53,1153,1155],{"id":1154},"कारण-2-embeddings-index-से-बँधेprovider-बदलना-महँगा","कारण 2: Embeddings index से बँधे—provider बदलना महँगा",[10,1157,1158,1159,1162,1163,1166,1167,1170],{},"Vector RAG में ",[24,1160,1161],{},"वेक्टर सार्वभौमिक मध्य प्रारूप नहीं","—एक embedding मॉडल के निर्देशांक। A से index, B से query: समानता ",[24,1164,1165],{},"तुलनीय नहीं","—अक्सर ",[24,1168,1169],{},"पूर्ण re-embedding",", आयाम (768 / 1024 / 1536 …) storage schema लॉक।",[10,1172,1173,1174,1177,1178,1181],{},"चरण 3 ",[24,1175,1176],{},"संरचित सार + वर्ण span"," persist, वेक्टर नहीं; चैट मॉडल बदलने पर ",[24,1179,1180],{},"index पुनर्निर्माण नहीं","; साक्ष्य श्रृंखला (स्रोत स्थिति) वही—«कभी भी अलग LLM आज़माएँ» से मेल।",[33,1183],{},[53,1185,1187],{"id":1186},"कारण-3-toc-भारी-लंबे-दस्तावेज़ों-पर-संरचित-रूटिंग-अक्सर-पर्याप्त","कारण 3: TOC-भारी लंबे दस्तावेज़ों पर संरचित रूटिंग अक्सर पर्याप्त",[10,1189,1190,1191,1194,1195,1198,1199,1202,1203,1208],{},"ई-पुस्तक, PDF में ",[24,1192,1193],{},"अध्याय संरचना","; पूर्व-प्रसंस्करण ",[24,1196,1197],{},"Segment शीर्षक + सार","। «अध्याय X क्या कहता है» या «पुस्तक Y कैसे परिभाषित» के लिए कैटलॉग से चुनकर ",[24,1200,1201],{},"स्रोत खींचना"," व्यवहार में स्थिर; Tool ",[24,1204,1205,1207],{},[153,1206,843],{}," स्रोत"," लौटाता, शून्य मतिभ्रम वर्ण span पर।",[10,1210,1211,1212,1215,1216,1219],{},"वेक्टर धुंधली अर्थ, बहुभाषा, लंबे अंतराल literal mismatch में मदद; ",[24,1213,1214],{},"TOC + पूर्व-प्रसंस्करण + मजबूत ट्रेस"," रीडर में ",[24,1217,1218],{},"Tool + स्रोत वापसी + उद्धरण नियम"," में ROI अक्सर अधिक।",[33,1221],{},[53,1223,1225],{"id":1224},"भविष्य-संकर-recall-पुनर्लेखन-नहीं","भविष्य: संकर recall, पुनर्लेखन नहीं",[10,1227,1228,1231,1232,1235,1236,1239,1240,1243],{},[24,1229,1230],{},"vector मोटा recall"," (embedding केवल Top-N अध्याय उम्मीदवार) जोड़ सकते हैं, अंत ",[24,1233,1234],{},"Segment चुनें → स्रोत → क्लिक ट्रेस","—शून्य-मतिभ्रम नियम वही। यदि जोड़ें: embedding ",[24,1237,1238],{},"वैकल्पिक",", मॉडल बदलने पर ",[24,1241,1242],{},"स्पष्ट re-index"," संकेत—मूक गलत retrieval नहीं।",[10,1245,1246,1247],{},"तब तक: ",[24,1248,1249],{},"कोई भी OpenAI-संगत चैट API; चैट मॉडल बदलने पर स्थानीय index पुनर्निर्माण नहीं।",[33,1251],{},[36,1253,1255],{"id":1254},"x-सारांश","X. सारांश",[281,1257,1258,1271],{},[284,1259,1260],{},[287,1261,1262,1265,1268],{},[290,1263,1264],{},"चरण",[290,1266,1267],{},"विधि",[290,1269,1270],{},"भूमिका",[303,1272,1273,1284,1297,1311,1322,1333],{},[287,1274,1275,1278,1281],{},[308,1276,1277],{},"पूर्व-प्रसंस्करण",[308,1279,1280],{},"TOC/लंबाई विभाजन + Segment सार cache",[308,1282,1283],{},"लंबी पुस्तकें खोज योग्य",[287,1285,1286,1289,1294],{},[308,1287,1288],{},"स्थिति टैग",[308,1290,1291,1292],{},"स्रोत में ",[153,1293,155],{},[308,1295,1296],{},"मशीन-पार्स उत्पत्ति",[287,1298,1299,1302,1308],{},[308,1300,1301],{},"Tool retrieval",[308,1303,1304,1305,1307],{},"प्रति प्रश्न Segment / पूर्ण-पुस्तक सार, ",[24,1306,322],{}," लौटाएँ",[308,1309,1310],{},"उत्तर से पहले साक्ष्य",[287,1312,1313,1316,1319],{},[308,1314,1315],{},"System Prompt",[308,1317,1318],{},"पुस्तक पहले, नकली टैग नहीं, न मिले तो कहें",[308,1320,1321],{},"जनरेशन बाधा",[287,1323,1324,1327,1330],{},[308,1325,1326],{},"Frontend",[308,1328,1329],{},"फ़ुटनोट → पूर्वावलोकन → कूद और हाइलाइट",[308,1331,1332],{},"उपयोगकर्ता साक्ष्य सत्यापित",[287,1334,1335,1338,1341],{},[308,1336,1337],{},"vector retrieval नहीं",[308,1339,1340],{},"एक provider; चैट बदलें बिना re-index",[308,1342,1343],{},"कम एकीकरण लागत",[10,1345,1346,1347,1350],{},"«शून्य मतिभ्रम» मॉडल कभी नहीं गलती नहीं—",[24,1348,1349],{},"आउटपुट साक्ष्य श्रृंखला से बँधा",": retrieval नहीं → पुस्तक सामग्री का दिखावा नहीं; retrieval है → सत्यापन योग्य स्रोत स्थिति।",[10,1352,1353,1354,1357,1358,1361],{},"यदि आप AI पढ़ना या दस्तावेज़ Q&A बनाते हैं, ",[24,1355,1356],{},"पूर्ण dump → मुख्य वाक्य → Tool-first माँग पर"," पथ और ",[24,1359,1360],{},"inline स्थिति टैग + स्रोत वापसी"," संदर्भ कार्यान्वयन हो सकता है।",[18,1363,1364],{},[10,1365,1366,1367,1372,1373,1377],{},"ये ",[243,1368,1371],{"href":1369,"rel":1370},"https://reader.linghuxiong.com",[247],"Foxycape"," AI रीडर निर्माण के सबक हैं—केवल संदर्भ। रीडर ",[243,1374,1376],{"href":1375},"/hi-in#download","डाउनलोड पृष्ठ"," पर आज़माएँ।",{"title":620,"searchDepth":1379,"depth":1379,"links":1380},2,[1381,1387,1388,1389,1390,1394,1401,1405,1406,1413],{"id":38,"depth":1379,"text":39,"children":1382},[1383,1385,1386],{"id":55,"depth":1384,"text":56},3,{"id":137,"depth":1384,"text":138},{"id":235,"depth":1384,"text":236},{"id":427,"depth":1379,"text":428},{"id":488,"depth":1379,"text":489},{"id":503,"depth":1379,"text":504},{"id":634,"depth":1379,"text":635,"children":1391},[1392,1393],{"id":662,"depth":1384,"text":663},{"id":688,"depth":1384,"text":689},{"id":762,"depth":1379,"text":763,"children":1395},[1396,1398,1400],{"id":781,"depth":1384,"text":1397},"6.1 get_related_segment_summaries — लक्षित Segment खोज",{"id":847,"depth":1384,"text":1399},"6.2 get_full_book_segment_summaries — पूर्ण-पुस्तक 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