{"passport":{"unfragile":{"@version":"1.0","version":"2026-05","artifact":{"id":"tool_b7labs","slug":"b7labs","name":"B7Labs","type":"product","url":"https://b7labs.co","page_url":"https://unfragile.ai/b7labs","categories":["text-writing"],"tags":[],"pricing":{"model":"free","free":true,"starting_price":null},"status":"active","verified":false},"capabilities":[{"id":"tool_b7labs__cap_0","uri":"capability://text.generation.language.automatic.document.summarization.with.ai","name":"automatic-document-summarization-with-ai","description":"Generates concise AI-powered summaries of uploaded documents by processing full text through a language model backend, extracting key points and condensing content into digestible overviews. The system likely uses extractive or abstractive summarization techniques to identify salient information while maintaining semantic coherence, enabling users to quickly grasp document essence without reading entire texts.","intents":["I need to quickly understand the main points of a 50-page research paper without reading it all","I want to extract key takeaways from multiple documents to compare their core arguments","I need a summary I can share with colleagues who don't have time to read the full document"],"best_for":["students processing large reading lists for courses","researchers synthesizing literature across multiple papers","knowledge workers triaging incoming documents for relevance"],"limitations":["Summarization quality depends on underlying model tier; free tier likely uses smaller models prone to oversimplification of nuanced arguments","May struggle with domain-specific jargon or highly technical content requiring specialized knowledge","No control over summary length or detail level — fixed output format may not suit all use cases","Cannot preserve complex structural relationships or hierarchical information from original documents"],"requires":["Document upload capability (likely PDF, DOCX, or TXT support)","Active internet connection to reach backend AI service","No authentication mentioned, suggesting anonymous/free tier access"],"input_types":["PDF documents","text files","potentially DOCX or other office formats"],"output_types":["text summary","structured bullet points or paragraphs"],"categories":["text-generation-language","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_b7labs__cap_1","uri":"capability://text.generation.language.interactive.document.question.answering.chat","name":"interactive-document-question-answering-chat","description":"Enables conversational Q&A with uploaded documents through a chat interface that retrieves relevant passages and generates contextual answers. The system likely implements a retrieval-augmented generation (RAG) pipeline where user queries are matched against document embeddings or semantic search indices, then passed to an LLM with retrieved context to generate grounded answers, allowing multi-turn dialogue about document content.","intents":["I want to ask specific questions about a document and get answers without re-reading sections","I need to clarify ambiguous points in a paper by asking follow-up questions interactively","I want to cross-reference information across multiple documents through natural language queries"],"best_for":["researchers exploring document content through exploratory questioning","students verifying understanding by asking clarification questions","professionals extracting specific data points from lengthy contracts or reports"],"limitations":["Answer accuracy depends on document retrieval quality — poor semantic matching may cause missed relevant passages or hallucinated answers","No explicit context window limits documented; may struggle with very long documents or complex multi-document queries","Free tier likely has rate limiting or session duration constraints not publicly disclosed","Cannot handle questions requiring synthesis across many documents or external knowledge beyond uploaded content"],"requires":["Document must be uploaded first before chat becomes available","Active session/connection to backend chat service","Support for multi-turn conversation state management"],"input_types":["natural language questions","follow-up queries in conversational format"],"output_types":["natural language answers","potentially with source citations or passage references"],"categories":["text-generation-language","memory-knowledge"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_b7labs__cap_2","uri":"capability://memory.knowledge.multi.document.content.aggregation.and.comparison","name":"multi-document-content-aggregation-and-comparison","description":"Allows users to upload and process multiple documents simultaneously, enabling comparative analysis and cross-document insights through unified chat and summary interfaces. The system likely maintains separate embeddings or indices per document while providing a unified query interface that can retrieve and synthesize information across all uploaded files, facilitating literature review and comparative research workflows.","intents":["I need to compare arguments across 10 research papers on the same topic","I want to find contradictions or agreements between multiple sources","I need to extract similar concepts from different documents to identify patterns"],"best_for":["literature review researchers comparing multiple papers","policy analysts synthesizing information from multiple reports","students conducting comparative analysis across assigned readings"],"limitations":["No documented limits on number of documents that can be uploaded simultaneously; likely has practical constraints on free tier","Cross-document queries may suffer from context dilution — LLM may struggle to synthesize insights from many sources within token limits","No explicit deduplication or conflict resolution when documents contain contradictory information","Unclear whether summaries are generated per-document or as unified synthesis across all documents"],"requires":["Multiple document uploads (format support same as single-document capability)","Sufficient backend storage/processing capacity for multi-document indexing","Session management to track which documents are active in current analysis"],"input_types":["multiple PDF documents","multiple text files","mixed document formats"],"output_types":["comparative summaries","cross-document Q&A answers","synthesis of information across sources"],"categories":["memory-knowledge","data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_b7labs__cap_3","uri":"capability://data.processing.analysis.document.upload.and.parsing.with.format.support","name":"document-upload-and-parsing-with-format-support","description":"Handles ingestion of various document formats (PDF, DOCX, TXT, potentially others) through a web upload interface, performing format-specific parsing to extract text content and structure. The system likely uses libraries like PyPDF2, pdfplumber, or python-docx to extract text while preserving document structure where possible, then stores parsed content for downstream summarization and retrieval tasks.","intents":["I want to upload a PDF research paper and immediately start analyzing it","I need to process a Word document without converting it manually first","I want to batch-upload multiple documents in different formats"],"best_for":["users with documents in standard office formats who want frictionless upload","researchers working with mixed document sources","anyone avoiding manual format conversion steps"],"limitations":["No documented support for scanned PDFs or OCR — image-based PDFs likely fail or produce poor text extraction","File size limits not publicly disclosed; free tier likely has restrictive caps (possibly 5-50MB per document)","Parsing may lose formatting, tables, or complex layouts — extracted text may be linearized or poorly structured","No support for encrypted PDFs or documents requiring passwords"],"requires":["Web browser with file upload capability","Document file in supported format (PDF, DOCX, TXT minimum)","File size within undocumented limits"],"input_types":["PDF files","DOCX files","TXT files","potentially PPTX, ODT, or other formats"],"output_types":["extracted plain text","parsed document structure","indexed content ready for summarization/retrieval"],"categories":["data-processing-analysis","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"tool_b7labs__cap_4","uri":"capability://memory.knowledge.session.based.document.context.persistence","name":"session-based-document-context-persistence","description":"Maintains document context and chat history within user sessions, allowing continuous interaction with uploaded documents across multiple queries without re-uploading. The system likely stores parsed document embeddings and conversation state in temporary session storage (possibly Redis or in-memory cache), enabling stateful multi-turn conversations while keeping documents available for the duration of a session.","intents":["I want to ask multiple questions about a document in one session without re-uploading","I need to maintain context across several follow-up questions to the same document","I want to switch between documents in my current session without losing previous work"],"best_for":["users conducting extended research sessions with multiple documents","students working through documents over time within a single sitting","researchers iteratively refining questions based on previous answers"],"limitations":["Session persistence likely has time limits (possibly 30 minutes to 24 hours) before automatic cleanup","No documented ability to save sessions or export conversation history — work may be lost after session expires","Free tier likely has strict session limits (possibly 1-3 concurrent sessions or daily session count caps)","No cross-device session sync — starting a session on mobile and continuing on desktop likely not supported"],"requires":["Active browser session or app session","Cookies or session tokens enabled","Continuous connection to backend service"],"input_types":["uploaded documents (stored in session)","user queries and follow-ups"],"output_types":["conversation history","persistent document references","session state metadata"],"categories":["memory-knowledge","automation-workflow"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":39,"verified":false,"data_access_risk":"low","permissions":["Document upload capability (likely PDF, DOCX, or TXT support)","Active internet connection to reach backend AI service","No authentication mentioned, suggesting anonymous/free tier access","Document must be uploaded first before chat becomes available","Active session/connection to backend chat service","Support for multi-turn conversation state management","Multiple document uploads (format support same as single-document capability)","Sufficient backend storage/processing capacity for multi-document indexing","Session management to track which documents are active in current analysis","Web browser with file upload capability"],"failure_modes":["Summarization quality depends on underlying model tier; free tier likely uses smaller models prone to oversimplification of nuanced arguments","May struggle with domain-specific jargon or highly technical content requiring specialized knowledge","No control over summary length or detail level — fixed output format may not suit all use cases","Cannot preserve complex structural relationships or hierarchical information from original documents","Answer accuracy depends on document retrieval quality — poor semantic matching may cause missed relevant passages or hallucinated answers","No explicit context window limits documented; may struggle with very long documents or complex multi-document queries","Free tier likely has rate limiting or session duration constraints not publicly disclosed","Cannot handle questions requiring synthesis across many documents or external knowledge beyond uploaded content","No documented limits on number of documents that can be uploaded simultaneously; likely has practical constraints on free tier","Cross-document queries may suffer from context dilution — LLM may struggle to synthesize insights from many sources within token limits","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.31666666666666665,"quality":0.67,"ecosystem":0.15000000000000002,"match_graph":0.25,"freshness":0.75,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.1,"match_graph":0.35,"freshness":0.05}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-05-24T12:16:29.134Z","last_scraped_at":"2026-04-05T13:23:42.561Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=b7labs","compare_url":"https://unfragile.ai/compare?artifact=b7labs"}},"signature":"ABsCglzUeq47JQ4az9ppd36gjKbXbugG5r4XbOet1iD0P9Kv5jozpjxWilLZvQJhAYP+Wgn7ak4TGjm9KHQwBQ==","signedAt":"2026-06-21T09:02:40.432Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/b7labs","artifact":"https://unfragile.ai/b7labs","verify":"https://unfragile.ai/api/v1/verify?slug=b7labs","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}