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Token Visualizer
Optimize your LLM prompts effortlessly with advanced token analysis.
Pitch

Token Visualizer serves as a vital tool for developers managing costs associated with large language model prompts. Offering deep token analysis and visual insights, it helps identify inefficiencies and optimize prompts, leading to significant savings. Improve prompt effectiveness while reducing costs with precise token metrics and AI-powered suggestions.

Description

Token Visualizer is an essential tool designed for developers who work with Large Language Models (LLMs). This software enables comprehensive analysis, visualization, and optimization of prompts to help minimize token usage, which directly impacts cost efficiency. Token Visualizer addresses common pain points by eliminating the guesswork associated with token usage and providing actionable insights to enhance prompt quality.


Why Choose Token Visualizer?

In the landscape of LLM interactions, token counts translate to monetary cost. Many developers find themselves navigating this complex system without visibility into their prompt efficiency. Common challenges include:

  • Manually copying prompts to tokenizers for analysis.
  • Lacking insights into inefficient prompt structures.
  • Incurring unnecessary expenses due to verbose text.
  • Missing systematic strategies for prompt compression.

Token Visualizer resolves these issues with ease.

Key Benefits

With the usage of Token Visualizer, significant savings can be achieved:

Original prompt: 847 tokens → $0.0254 per request
Optimized prompt: 623 tokens → $0.0187 per request
Savings: 26% cost reduction → $67/month saved at 10K requests

Features

Deep Token Analysis

  • Multi-tokenizer support: Supports various models including GPT-4, GPT-3.5, Claude, and LLaMA.
  • Precise counting: Utilizes tiktoken and transformers for exact token counts.
  • Line-by-line breakdown: Provides insights into token allocation.
  • Efficiency metrics: Tracks characters per token ratios to identify redundancy.

Visual Intelligence

  • Color-coded output: Visual cues to identify costly sections:
    • 🔴 Red: Lines with high costs (>50 tokens)
    • 🟡 Yellow: Areas for potential optimization (25-50 tokens)
    • 🟢 Green: Efficient lines (<25 tokens)
  • Token grid view: Detailed visualization of text tokenization.
  • Progress indicators: Visual feedback during analysis.

AI-Powered Compression Suggestions

  • Pattern detection: Identifies verbose phrases and recommends smarter replacements.
  • Repetition analysis: Highlights commonly used words and phrases.
  • Whitespace optimization: Streamlines text by removing extra spaces.
  • Efficiency scoring: Provides quantified recommendations for enhancements.
  • Cost impact: Displays potential savings in tokens and dollars.

Developer Experience

  • Multiple input modes: Engage with the tool interactively, through files, or programmatically.
  • Cross-platform compatibility: Runs seamlessly on Windows, macOS, and Linux.
  • Zero-configuration setup: Ready to use without complex setups or dependencies.
  • Terminal-friendly output: Generates aesthetically pleasing output with automatic color detection.

Usage Examples

Interactive Mode: Quickly analyze text prompts for efficiency.

python token_visualizer.py

File Analysis Mode: Supports single or batch file analysis.

# Analyze a single file
python token_visualizer.py my_prompt.txt

Programmatic Integration: Easily integrate with other tools using the provided API.

from token_visualizer import TokenVisualizer
visualizer = TokenVisualizer("gpt-4")
text = "Your prompt here..."
stats = visualizer.tokenize(text)

Future Development

Token Visualizer is actively evolving with planned features like:

  • A web interface for easier accessibility.
  • Batch processing capabilities for multiple files.
  • An API endpoint for seamless integrations.
  • Enhanced AI-powered optimization features.

Community and Contributions

Token Visualizer thrives on community input. Developers can contribute by enhancing tokenizer support, adding new visualization methods, or developing additional compression algorithms. Join the community and start contributing to a project that is making a difference in LLM prompt optimization.


For more information and in-depth exploration of the functionalities, check out the repository's full API reference. Token Visualizer is geared towards providing developers with the essential tools needed to fine-tune prompts and optimize their interactions with Large Language Models.

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