Helicone
Helicone has an llms.txt. Do you?
Helicone is revolutionizing the way companies harness the power of large language models. This open-source observability platform offers insights into usage, latency, and costs, helping developers optimize their AI applications and reduce expenses. Say goodbye to guesswork and hello to data-driven decisions!
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Helicone's llms.txt Insights
Short and sweet
3 sections. Minimalist, but hey — at least they showed up.
What's inside Helicone's llms.txt
Helicone's llms.txt contains 4 sections:
- Helicone
- Docs
- Examples
- Optional
How does Helicone's llms.txt compare?
| Helicone | Directory Avg | Top Performer | |
|---|---|---|---|
| Lines | 31 | 1029 | 163,447 |
| Sections | 3 | 17 | 3207 |
Cool table. Now the real question — where do you land? Find out →
Helicone's llms.txt preview
First 31 of 31 lines
# Helicone
> Helicone is an open-source observability platform for LLM users. It helps companies monitor usage, latency, and costs for AI models like GPT-3, enabling optimization of AI applications and reduction of OpenAI bills. Helicone provides key insights into spend, performance, and usage patterns.
Helicone offers tools for developers to monitor, analyze, and optimize their use of large language models (LLMs). Key features include:
- Usage and cost tracking across multiple AI models
- Latency monitoring and performance optimization
- Request caching and model-swapping capabilities
- Custom property tracking for detailed analytics
- Integration with popular AI frameworks and platforms
Helicone is designed to be easily integrated into existing AI workflows, with support for self-hosted deployments and cloud-based solutions.
## Docs
- [Quick Start Guide](https://docs.helicone.ai/getting-started/quick-start): Introduction to setting up and using Helicone
- [Gateway Integration](https://docs.helicone.ai/getting-started/integration-method/gateway): Guide to integrating Helicone as a proxy for AI model requests
- [Custom Properties](https://docs.helicone.ai/features/advanced-usage/custom-properties): Advanced usage for tracking custom metrics and properties
- [Self-Hosted Deployment](https://docs.helicone.ai/getting-started/self-deploy): Instructions for deploying Helicone on your own infrastructure
- [Authentication](https://docs.helicone.ai/helicone-headers/helicone-auth): Details on authenticating requests with Helicone
## Examples
- [First AI App with Helicone](https://www.helicone.ai/blog/first-ai-app-with-helicone): Tutorial on building an AI app with Helicone integration
- [Product Hunt Launch Automation](https://www.helicone.ai/blog/product-hunt-automate): Case study on using Helicone for automating a product launch
- [Helicone vs Competitors](https://www.helicone.ai/blog/portkey-vs-helicone): Comparison of Helicone with other LLM observability tools
## Optional
- [GitHub Repository](https://github.com/Helicone/helicone): Source code and open-source contributions
- [Y Combinator Profile](https://www.ycombinator.com/companies/helicone): Information about Helicone's participation in Y Combinator
- [Company Blog](https://www.helicone.ai/blog): Latest updates, tutorials, and insights from the Helicone team
- [API Reference](https://docs.helicone.ai/getting-started/quick-start): Detailed API documentation for advanced integrations
What is llms.txt?
llms.txt is an open standard that helps AI language models understand your website. By placing a structured markdown file at /llms.txt, websites provide AI search engines like ChatGPT, Claude, and Perplexity with a clear map of their content, services, and documentation. Companies like Helicone use it to ensure AI accurately represents their brand when answering user queries. Read the spec.
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