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