Actualizar Home

Miguel 2025-02-05 08:17:05 -03:00
parent 13861e7613
commit a26538036e
1 changed files with 77 additions and 1 deletions

78
Home.md

@ -1 +1,77 @@
# Email to Chronological Markdown Converter ## Overview This script processes email files (.eml) into a chronological narrative in Markdown format, optimized for processing with Large Language Models (LLMs). It extracts essential information from emails while removing unnecessary metadata, creating a clean, temporal narrative that can be easily analyzed. ## Purpose The main goal is to convert email threads and nested communications into a simple, chronological text format that LLMs can effectively process to: - Analyze communication patterns - Extract key information - Track project development - Identify important decisions and their timeline - Understand relationships and interactions between participants ## Core Functionality ### Input Processing - Reads .eml files from the current directory - Handles nested .eml files found as attachments - Supports multiple languages (English, Italian) - Extracts sender name and timestamp as primary identifiers ### Content Management - Maintains a single chronological file (cronologia.md) - Removes redundant metadata and formatting - Preserves essential content in plain text - Converts tables to markdown format - Links to non-email attachments - Eliminates duplicate entries ### Format Structure ```markdown ## YYYYMMDDhhmmss|Sender Name Message content in plain text... Tables converted to markdown format... ### Attachments - [[document1.pdf]] - [[image1.jpg]] --- ``` ### Key Features 1. Chronological Organization - All messages sorted by date - Consistent timestamp format - Clear sender identification 2. Content Cleaning - Removes email headers - Eliminates signatures - Strips formatting - Preserves table structure 3. Attachment Handling - Creates 'attachments' folder - Maintains file references - Processes nested emails - Prevents duplicates ## LLM Processing Considerations The output is structured to facilitate: 1. Temporal analysis 2. Relationship mapping 3. Topic tracking 4. Decision point identification 5. Project timeline reconstruction The consistent formatting and cleaned content allow LLMs to focus on: - Message content analysis - Temporal relationships - Communication patterns - Project development tracking - Key information extraction This format enables LLMs to effectively process email communications while maintaining the contextual and temporal relationships essential for understanding the narrative flow of information.
# Email to Chronological Markdown Converter
## Overview
This script processes email files (.eml) into a chronological narrative in Markdown format, optimized for processing with Large Language Models (LLMs). It extracts essential information from emails while removing unnecessary metadata, creating a clean, temporal narrative that can be easily analyzed.
## Purpose
The main goal is to convert email threads and nested communications into a simple, chronological text format that LLMs can effectively process to:
- Analyze communication patterns
- Extract key information
- Track project development
- Identify important decisions and their timeline
- Understand relationships and interactions between participants
## Core Functionality
### Input Processing
- Reads .eml files from the current directory
- Handles nested .eml files found as attachments
- Supports multiple languages (English, Italian)
- Extracts sender name and timestamp as primary identifiers
### Content Management
- Maintains a single chronological file (cronologia.md)
- Removes redundant metadata and formatting
- Preserves essential content in plain text
- Converts tables to markdown format
- Links to non-email attachments
- Eliminates duplicate entries
### Format Structure
```markdown
## YYYYMMDDhhmmss|Sender Name
Message content in plain text...
Tables converted to markdown format...
### Attachments
- [[document1.pdf]]
- [[image1.jpg]]
---
```
### Key Features
1. Chronological Organization
- All messages sorted by date
- Consistent timestamp format
- Clear sender identification
2. Content Cleaning
- Removes email headers
- Eliminates signatures
- Strips formatting
- Preserves table structure
3. Attachment Handling
- Creates 'attachments' folder
- Maintains file references
- Processes nested emails
- Prevents duplicates
## LLM Processing Considerations
The output is structured to facilitate:
1. Temporal analysis
2. Relationship mapping
3. Topic tracking
4. Decision point identification
5. Project timeline reconstruction
The consistent formatting and cleaned content allow LLMs to focus on:
- Message content analysis
- Temporal relationships
- Communication patterns
- Project development tracking
- Key information extraction
This format enables LLMs to effectively process email communications while maintaining the contextual and temporal relationships essential for understanding the narrative flow of information.