docs: Add comprehensive LLM-friendly documentation

[askdevai-bot]

📚 Add Comprehensive LLM-Friendly Documentation

Overview

This PR adds a comprehensive LLM.md file that provides detailed, LLM-friendly documentation for the PandasAI library. The documentation is structured to be easily consumable by both LLMs and developers, significantly improving the developer experience.

What's Included

🔧 Complete API Reference

• Agent Class: Main interaction interface with all methods and properties
• DataFrame Class: Enhanced pandas DataFrame with natural language querying
• Config Class: Comprehensive configuration management
• VirtualDataFrame: Database connection handling
• Connectors: SQL and NoSQL database integrations

💡 Practical Examples

• Code snippets for all major use cases
• Database connector examples (MySQL, PostgreSQL, SQLite, MongoDB)
• LLM integration patterns (OpenAI, Anthropic, Google, Azure)
• Configuration examples and best practices

🎯 Key Features

• Structured Format: Easy navigation and reference
• Code Examples: Practical usage patterns
• Parameter Details: Complete parameter documentation
• Best Practices: Recommended usage patterns
• Error Handling: Common pitfalls and solutions

Benefits

1. Improved Developer Experience: Developers can quickly understand and implement PandasAI features
2. LLM-Friendly: Structured format allows LLMs to provide better assistance
3. Comprehensive Coverage: All major classes and methods documented
4. Practical Focus: Real-world examples and use cases
5. Maintainable: Clear structure for future updates

Changes Made

• ✅ Enhanced existing LLM.md with comprehensive API documentation
• ✅ Added practical code examples for all major features
• ✅ Structured content for optimal LLM consumption
• ✅ Included database connector examples
• ✅ Added configuration best practices

Testing

The documentation has been:

• ✅ Reviewed for accuracy against the current codebase
• ✅ Structured for optimal readability
• ✅ Tested with LLM consumption patterns

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Note: This contribution follows the project's contribution guidelines and aims to improve the overall developer experience with PandasAI.

A developer on Askdev.AI requested this update

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Important

Adds LLM.md with comprehensive, LLM-friendly documentation for PandasAI, including API references, examples, and best practices.

• Documentation:
  • Adds LLM.md with comprehensive API documentation for PandasAI.
  • Includes detailed descriptions of Agent, DataFrame, Config, VirtualDataFrame, and Connectors.
  • Provides practical examples for database connectors, LLM integration, and custom functions.
• Features:
  • Structured format for easy navigation and LLM consumption.
  • Includes code snippets, parameter details, and best practices.
  • Covers error handling, memory management, and security features.
• Testing:
  • Documentation reviewed for accuracy and structured for readability.
  • Tested with LLM consumption patterns.

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[ellipsis-dev]

Caution

Changes requested ❌

Reviewed everything up to 43cd485 in 1 minute and 49 seconds. Click for details.

• Reviewed 460 lines of code in 1 files
• Skipped 0 files when reviewing.
• Skipped posting 2 draft comments. View those below.
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1. LLM.md:4

• Draft comment:
  Consider capitalizing 'MongoDB' and 'NoSQL' for consistency.
• Reason this comment was not posted:
  Marked as duplicate.

2. LLM.md:364

• Draft comment:
  In the Custom Response Parser example, 'processed_response' is returned but not defined. Clarify that this is a placeholder.
• Reason this comment was not posted:
  Decided after close inspection that this draft comment was likely wrong and/or not actionable: usefulness confidence = 20% vs. threshold = 50% This is a documentation example showing how to create a custom parser. The code is clearly an example template, with "Custom parsing logic" as a comment placeholder. The variable processed_response being undefined is part of the template nature of the example. Adding "# placeholder variable" doesn't add meaningful value since it's already clear this is example code. The comment is technically correct that processed_response is undefined. Documentation should be clear and not confuse readers. The example's nature as a template is already clear from context - it has a "Custom parsing logic" comment placeholder and is in a documentation example section. Adding "# placeholder" is redundant and makes the example more cluttered. Delete the comment. The example code's template nature is already clear from context and adding a "placeholder" comment would just add noise to a documentation example.

Workflow ID: wflow_yYMIwHLMuJpSXbpm

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[ellipsis-dev]

Add a trailing newline at the end of the file.

[ellipsis-dev]

Typographical suggestion: In the description on line 4, consider using consistent casing for database types. Instead of "mongodb, noSQL", it might be clearer as "MongoDB, NoSQL".

Suggested change

	**Description:** Chat with your database (SQL, CSV, pandas, mongodb, noSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.
	**Description:** Chat with your database (SQL, CSV, pandas, MongoDB, NoSQL, etc). PandasAI makes data analysis conversational using LLMs (GPT 3.5 / 4, Anthropic, VertexAI) and RAG.

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