📄 Parse de Documentos — Extraindo Texto de PDFs, DOCX e CSV
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PortuguêsO que é?
O Document Parsing é a skill que permite ao agente TacFlow extrair texto estruturado de arquivos. É a porta de entrada para processar documentos complexos sem sair do chat!
Formatos suportados
Formato Extensão Uso típico
PDF.pdf Contratos, relatórios, artigos acadêmicos
DOCX.docx Documentos do Microsoft Word
CSV.csv Planilhas, dados tabulares, exports
TXT.txt Texto puro, logs, configurações Como usar?
Basta enviar o arquivo no chat e pedir:
- Envie o arquivo — arraste o PDF, DOCX, CSV ou TXT para o chat
- Peça a extração — "Extraia o texto deste PDF" ou "Leia esta planilha para mim"
- Receba o resultado — o agente devolve o texto em markdown estruturado
Exemplos práticos
Contrato em PDF: "Extraia as cláusulas principais deste contrato"
Planilha CSV: "Quais são as colunas e os 5 primeiros registros?"
Relatório DOCX: "Resuma este relatório técnico"
Log TXT: "Encontre erros neste arquivo de log"
Fluxo recomendado
📄 Arquivo → Parse-document → Análise/Summary → Memory-storeExtraia o texto, analise com o agente e salve o resultado na memória para consultar depois!
Limitações
️ Formatação complexa — tabelas aninhadas ou layouts multi-coluna podem perder a estrutura original
️ PDF escaneado — PDFs que são imagens (não texto nativo) precisam ser processados via OCR primeiro
️ Arquivos muito grandes — documentos com centenas de páginas podem ser truncados
EnglishWhat is it?
Document Parsing is the skill that lets your TacFlow agent extract structured text from files. It is the gateway to processing complex documents without leaving the chat!
Supported Formats
Format Extension Typical Use
PDF.pdf Contracts, reports, academic papers
DOCX.docx Microsoft Word documents
CSV.csv Spreadsheets, tabular data, exports
TXT.txt Plain text, logs, configs How to use?
Just upload the file to chat and ask:
- Upload the file — drag & drop your PDF, DOCX, CSV, or TXT into the chat
- Ask for extraction — "Extract the text from this PDF" or "Read this spreadsheet for me"
- Get the result — the agent returns the text as structured markdown
Practical Examples
PDF Contract: "Extract the main clauses from this contract"
CSV Spreadsheet: "What are the columns and the first 5 rows?"
DOCX Report: "Summarize this technical report"
TXT Log: "Find errors in this log file"
Recommended Workflow
📄 File → Parse-document → Analysis/Summary → Memory-storeExtract the text, analyze with the agent, and save the result to memory for later reference!
Limitations
️ Complex formatting — nested tables or multi-column layouts may lose their original structure
️ Scanned PDFs — image-based PDFs (not native text) need OCR processing first
️ Large files — documents with hundreds of pages may be truncated -
R Rodrigo Serpa moved this topic from Getting Started on
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R Rodrigo Serpa moved this topic from Copy & Paste on
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