Helicone Changelog | Latest Updates & New Features

November 26, 2025

Claude Sonnet 4 and Sonnet 4.5 now support 1M context window

Claude Sonnet 4 and Claude Sonnet 4.5 models on the AI Gateway now support 1M context window by default.

What’s Changed

No configuration changes are needed - requests to Sonnet 4 models will automatically use the extended context window.

August 13, 2025

Control Reasoning Effort in Playground and better feedback on thinking models

You can now fine-tune how models think and respond with the reasoning effort parameter.

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What’s New

Try the new reasoning controls in the Playground to see how different settings affect model responses.

Coming Soon

August 7, 2025

OpenAI GPT-5 Models Pricing and Playground Support

You can now use GPT-5 models in the Playground with full cost tracking.

What’s New (Models)

Teams can now track GPT-5 costs and also use them in the Playground.

August 5, 2025

OpenAI GPT OSS Models Pricing

Cost tracking is now available for GPT-OSS models across multiple providers.

What’s New

With this update, teams using GPT-OSS models can track their spending across Fireworks, Groq, and OpenRouter providers and compare costs with other AI models.

August 5, 2025

Claude Opus 4.1 Pricing

Cost tracking is now available for Anthropic’s Claude Opus 4.1 model.

What’s New

With this update, teams using Anthropic’s Claude Opus 4.1 model can track their spending and compare costs across different AI providers.

July 22, 2025

Prompt Management V2

Iterate on prompts without code deployments. Our new Prompt Management system brings powerful composability, version control, and instant deployment to your LLM workflows.

Features

How It Works

Save prompts in our Playground with variables like {{hc:customer_name:string}}. Test them with different inputs and models. When ready, reference the prompt ID in your API calls through the AI Gateway:

const response = await openai.chat.completions.create({
  model: "openai/gpt-4o-mini",
  prompt_id: "abc123",
  inputs: {
    customer_name: "John Doe",
    product: "AI Gateway"
  }
});

The AI Gateway compiles your saved prompt with runtime inputs and sends it to your chosen model. Update prompts in the dashboard and changes take effect immediately - no code changes or deployments needed.

Get Started

Visit the Prompts page in your dashboard to create your first prompt, or check out our documentation for detailed examples and best practices.

July 16, 2025

Improved Timezone Display for Requests

We’ve improved how timestamps are displayed throughout the Helicone dashboard to provide a better user experience for teams working across different timezones.

What’s New

This update makes it easier for distributed teams to collaborate and analyze their LLM usage patterns without timezone confusion.

July 15, 2025

Country-Based Request Filtering

Analyze your LLM usage patterns by geographic location with our new country-based filtering feature.

Features

How It Works

The country code is determined by the Cloudflare edge server that receives your request. Since Helicone runs on Cloudflare’s global network, we can identify which region processed each request, giving you insights into where your users are located.

How to Use

In the requests dashboard, you can now:

  1. Use the new country filter in the advanced filters section
  2. Add country_code:US (or any ISO country code) to your search queries
  3. View geographic distribution in the analytics dashboard

This helps you understand your global usage patterns and user distribution. Country data is automatically collected for all new requests going forward.

July 14, 2025

GPT-4o Search Model Pricing

We’ve added pricing support for OpenAI’s new GPT-4o Search model, which includes built-in web search capabilities.

What’s New

The GPT-4o Search model combines GPT-4o’s capabilities with real-time web search. With this update, you can accurately track costs for search-enhanced conversations and compare them with standard GPT-4o usage.

July 12, 2025

Mistral Model Pricing Updates

We’ve updated pricing for all Mistral models to reflect their current rates and added support for new model variants.

What’s Updated

This ensures your cost tracking stays accurate as Mistral’s model offerings and pricing evolve.

July 11, 2025

Grok 4 Model Pricing

Cost tracking is now available for xAI’s Grok 4 model.

What’s New

With this update, teams using xAI’s Grok models can track their spending and compare costs across different AI providers.

June 19, 2025

Helicone AI Gateway - Now Available!

We’re thrilled to announce the launch of Helicone AI Gateway - a powerful open-source solution for routing, caching, and managing your LLM traffic at scale.

🚀 What is Helicone AI Gateway?

The AI Gateway is a high-performance proxy that sits between your application and LLM providers, offering enterprise-grade features:

💻 Get Started

The AI Gateway is available as a separate open-source project:

GitHub Repository: github.com/helicone/ai-gateway

Quick start with Docker:

docker run -p 8080:8080 helicone/ai-gateway

📚 Learn More

🔧 Key Features

Start using the AI Gateway today to take control of your LLM infrastructure!

May 28, 2025

Introducing Go Helicone Helpers Package

We’re thrilled to announce that we now have a Go SDK for Helicone’s Helpers Package. You can now integrate any custom LLM with Helicone using the Go Manual Logger. Install it now with:

go get github.com/helicone/go-helicone-helpers

Refer to our docs on how to use it.

May 6, 2025

[Introducing Smarter Sessions Design

We’ve introduced a new design for Sessions, now with session-level metrics, smarter filters, and a cleaner UI.

The new Sessions include average latency, total cost, and improved time filtering, making it easier to debug multi-step LLM workflows. The UI has also been refined for a cleaner and more intuitive experience.

Try it out in Sessions, we’d love to hear your feedback!

Refer to our docs on how to set up Sessions to start tracing your LLM workflows.

May 5, 2025

[Introducing Helicone Self-Hosting

We’re excited to re-introduce Helicone self-hosting! Now you can deploy our powerful observability platform directly within your own infrastructure with a single Docker command.

This update addresses the needs of organizations with strict security and compliance requirements, allowing you to leverage Helicone’s insights into your LLM usage without sending sensitive data to third-party servers.

Why self-host?

Get started with a single Docker command:

git clone https://github.com/Helicone/helicone.git

# See your Helicone dashboard in localhost:3000!
cd docker
docker compose up -d

Read more about our self-hosting offering in our blog.

April 23, 2025

[Added support for OpenAI's new Responses API

Helicone now supports OpenAI’s new Responses API, allowing you to monitor and analyze your model’s responses seamlessly.

What is the OpenAI Responses API?

The OpenAI Responses API enables you to provide text or image inputs to generate text or JSON outputs by calling your own custom code or using built-in tools like web search or file search.

Integrating with Helicone

  1. Create a Helicone account and API key.
  2. Set environment variables
  3. Install the OpenAI SDK:
npm install openai
  1. Configure your OpenAI client to use the Helicone proxy:
import OpenAI from "openai";

const openai = new OpenAI({
     apiKey: process.env.OPENAI_API_KEY,
     baseURL: "https://oai.helicone.ai/v1", // Route requests through Helicone
     defaultHeaders: {
       "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`, // Authenticate with Helicone
     },
});

With this setup, any calls to the OpenAI Responses API will be automatically logged and monitored by Helicone.

For more examples, including file search, streaming, function calling, and reasoning, please refer to our documentation.

April 22, 2025

[Introducing Open WebUI Integration

Today, you can start monitoring your local LLM interactions with Open WebUI in Helicone!

With the integration, you can:

We’ve just published a comprehensive guide on how to integrate Helicone with Open WebUI (formerly Ollama WebUI). This will show you how to gain comprehensive observability across all your LLM interactions, whether you’re using local Ollama models or cloud LLM APIs.

Get started: Open WebUI x Helicone docs.

April 18, 2025

April 2025 Changelog

Helicone is the first observability platform to support OpenAI’s Realtime API, the 4.1 model family, and more.

What’s New?

Improvements

Bug Fixes

April 7, 2025

[Helicone Now Supports OpenAI's Realtime API

We’re thrilled to announce that Helicone now supports logging of OpenAI’s Realtime API, enabling low-latency, multi-modal conversational experiences.

Seamless Integration with Helicone

Integrating OpenAI’s Realtime API with Helicone is as simple as ever. Following our standard one-line integration approach, you can immediately start monitoring performance, analyzing interactions, and gaining valuable insights into your real-time conversations.

How it Works

Connect to the Realtime API through Helicone using your preferred provider (OpenAI or Azure). Helicone acts as a proxy, allowing you to leverage our observability features without changing your core application logic.

Example: Connecting via WebSocket (OpenAI Provider)

// Simply swap with the following url:
const url =
  "wss://api.helicone.ai/v1/gateway/oai/realtime?model=gpt-4o-realtime-preview-2024-12-17";

const ws = new WebSocket(url, {
  headers: {
    // Your OpenAI Key
    Authorization: `Bearer ${process.env.OPENAI_API_KEY}`,
    // Your Helicone Key
    "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`,
    // Optional Helicone properties for enhanced analytics
    "Helicone-Session-Id": `session_123`,
    "Helicone-User-Id": "user_123",
  },
});

Key Benefits

Get started today by updating your WebSocket connection URL and adding your Helicone API key header. For more details, check out the full OpenAI Realtime Integration documentation.

March 29, 2025

[Filter UI Update: A New Look with Enhanced Features

A fresh new look for our filtering system brings enhanced performance and usability to your data exploration experience. The redesigned filter interface is now more intuitive and powerful than ever, making it easier to analyze your LLM usage data.

What’s new

Try it out

Experience the new filtering system across all main pages:

We’re excited to hear your feedback on these improvements! Let us know what you think about the new filtering experience.

March 28, 2025

[Online Evaluators New UI

We’ve completely redesigned the online evaluators creation and editing experience, making it more intuitive and powerful than ever. The new interface guides developers through the process with real-time feedback and advanced configuration options.

What’s new

Getting started

  1. Navigate to the Evaluators tab in Helicone
  2. Click “Create New Evaluator” or edit an existing one
  3. Create/edit an evaluator with the new interface with real-time feedback

We’re continuously working to make Helicone’s features more accessible and powerful. Share your thoughts on the new evaluators interface - we’d love to hear your feedback!

March 27, 2025

Vertex AI Gemini Support

We just added support for Vertex AI Gemini integration with Helicone logging framework, including stream handling and logging capabilities for both Python and TypeScript SDKs.

There are two ways to integrate Helicone with Vertex AI’s Python SDK, Proxy and Manual Logger. The manual logger provides more granular control over logging the LLM’s responses.

Manual Logger Key Capabilities

  1. Log both request parameters and responses with full context.
  2. Handle streaming responses with proper chunk logging.
  3. Built-in error tracking and logging.
  4. Add custom metadata to your logs
  5. Explicitly specify which model is being used for better analytics.
  6. Automatic tracking of streaming response timing.

For integration guide and advanced configuration options, please refer to our Vertex AI documentation.

March 26, 2025

Groq Streaming Support: Enhanced Token Tracking

We’re excited to announce support for Groq streaming tokens in Helicone! This update enhances our integration with Groq’s API, providing better token tracking and usage monitoring for streaming responses.

What’s new

Getting started

To use Groq streaming with Helicone:

  1. Configure your Helicone proxy settings for Groq
  2. Make streaming requests as usual through the Helicone proxy
  3. Monitor your token usage in the Helicone dashboard

March 23, 2025

Introducing LangGraph Integration: Monitor Your AI Agent Workflows

Helicone now integrates seamlessly with LangGraph, providing comprehensive observability for your graph-based AI agents and tools. With minimal configuration, you can get full visibility into your LangGraph workflows, from basic chains to complex multi-agent systems.

Capabilties

LangGraph has emerged as a powerful framework for building stateful, multi-agent LLM applications. Our integration gives you:

Supported models

The integration works with all major LLM providers supported by LangChain, including:

For implementation details, check out our LangGraph integration guide.

March 5, 2025

New HeliconeLogBuilder for Improved Stream Handling

We’re excited to introduce the HeliconeLogBuilder, a new approach to handling streaming responses with better error handling and a simplified workflow.

Introducing HeliconeLogBuilder

The new HeliconeLogBuilder class provides a simplified way to handle streaming LLM responses with improved error handling and async support. This new approach makes it easier to:

Example Usage with Next.js App Router

import { HeliconeManualLogger } from "@helicone/helpers";
import { after } from "next/server";
import Together from "together-ai";

const together = new Together();
const helicone = new HeliconeManualLogger({
  apiKey: process.env.HELICONE_API_KEY!,
});

export async function POST(request: Request) {
  const { question } = await request.json();
  const body = {
    model: "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
    messages: [{ role: "user", content: question }],
    stream: true,
  };

const heliconeLogBuilder = helicone.logBuilder(body, {
    "Helicone-Property-Environment": "dev",
  });

try {
    const response = await together.chat.completions.create(body);
    return new Response(heliconeLogBuilder.toReadableStream(response));
  } catch (error) {
    heliconeLogBuilder.setError(error);
    throw error;
  } finally {
    after(async () => {
      // This will be executed after the response is sent to the client
      await heliconeLogBuilder.sendLog();
    });
  }
}

Benefits Over Previous Methods

The logBuilder approach offers several advantages over the previous streaming methods:

This new approach is now the recommended way to handle streaming responses with Helicone. For more information, check out our Manual Logger with Streaming guide.

March 4, 2025

[Property Page Enhancements: Average Prompt Tokens & Sorting

We’ve enhanced the Properties pages with new metrics and improved user experience:

These enhancements make it easier to analyze property data by providing more metrics and a smoother, more responsive user interface. The skeleton loading states significantly reduce the perception of loading time and prevent jarring layout shifts when data loads.

The backend sorting implementation ensures that sorting large datasets is efficient and performant, as the sorting happens at the database level rather than in the browser.

March 2, 2025

Webhook Enhancement: Combined Request/Response URL

We’ve enhanced our webhook functionality to improve integration with external systems:

These changes make webhook integration more efficient while maintaining backward compatibility with existing implementations.

For details, see our updated documentation.

February 27, 2025

Improved Streaming Support and Async Stream Parser

Improved Streaming Support and Async Stream Parser

We’ve made significant improvements to our streaming functionality with two key updates:

Stream Fixes

We’ve resolved several issues with stream handling across different LLM providers, ensuring more reliable and consistent streaming experiences. These fixes address edge cases and improve compatibility with various streaming implementations, including:

New Streaming Methods

The HeliconeManualLogger class now includes enhanced methods for working with streams:

Example Usage with Together AI

import Together from "together-ai";
import { HeliconeManualLogger } from "@helicone/helpers";

// Initialize with properties
const helicone = new HeliconeManualLogger({
  apiKey: process.env.HELICONE_API_KEY!,
  loggingEndpoint: "https://api.worker.helicone.ai/oai/v1/log",
  headers: {
    "Helicone-Property-Environment": "production",
  },
});

export async function POST(request: Request) {
  const { question } = await request.json();

const body = {
    model: "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
    messages: [{ role: "user", content: question }],
    stream: true,
  } as Together.Chat.CompletionCreateParamsStreaming & { stream: true };

const response = await together.chat.completions.create(body);
  const [stream1, stream2] = response.tee();
  helicone.logStream(
    body,
    async (resultRecorder) => {
      resultRecorder.attachStream(stream2.toReadableStream());
    },
    {
      "Helicone-User-Id": "123",
    }
  );

return new Response(stream1.toReadableStream());
}

These improvements make working with streaming LLMs more reliable and efficient, especially for applications that require real-time responses.

February 26, 2025

Complete Logging Control for Async Integration

We’ve enhanced our Python Asynchronous Logging integration with new methods to completely disable all logging to Helicone. This feature allows you to temporarily or permanently stop sending any data to our backend while maintaining your integration setup.

New Methods

This is different from the existing disable_content_tracing() which only omits request and response content but still sends other metrics. The new functionality gives you complete control over your data privacy and is only available when using Helicone’s async integration mode.

# Example usage
from helicone_async import HeliconeAsyncLogger
from openai import OpenAI

logger = HeliconeAsyncLogger(api_key=HELICONE_API_KEY)
logger.init()

# Completely disable all logging
logger.disable_logging()

# Your OpenAI calls here - no data sent to Helicone

# Later, re-enable logging if needed
logger.enable_logging()

February 25, 2025

Enhanced Cost Sorting and Data Organization

Improved sorting capabilities across the platform, particularly for cost request pages. This update ( #3326) makes it easier to organize and analyze your data with more intuitive sorting controls.

February 24, 2025

[New Claude 3.7 Sonnet Support: Full Cost Tracking and Integration

Immediate Support for Claude 3.7 Sonnet

We’re excited to announce full support for Anthropic’s latest Claude 3.7 Sonnet model (claude-3-7-sonnet-20250219), including comprehensive cost tracking and monitoring capabilities.

What’s New in Claude 3.7?

Claude 3.7 Sonnet represents Anthropic’s latest advancement in language AI, introducing groundbreaking hybrid reasoning capabilities. As announced by Anthropic, this model offers:

Core Capabilities

Enhanced Performance

Real-world Applications

The model has demonstrated exceptional performance across:

Cost Tracking and Integration

Our platform provides comprehensive monitoring with:

Usage Analytics

Integration Features

How to Use

To start using Claude 3.7 Sonnet with Helicone:

  1. Update your model parameter to claude-3-7-sonnet-20250219
  2. Refer to our Anthropic Integration Guide for implementation details
  3. Monitor costs and usage through your Helicone dashboard

Supported Features

Learn More About Claude 3.7 Sonnet

February 14, 2025

Introducing Auto-Improve for Prompts

We’re excited to launch Auto-Improve, an intelligent prompt optimization tool that helps you write more effective LLM prompts. While traditional prompt engineering requires extensive trial and error, Auto-Improve analyzes your prompts and suggests improvements instantly.

How it Works

  1. Click the Auto-Improve button in the Helicone Prompt Editor
  2. Our AI analyzes each sentence of your prompt to understand:
  1. Get a new suggested optimized version of your prompt

Key Benefits

Auto-Improve is now available in beta for all Helicone users. Try it today with one of your prompts!

February 14, 2025

Anthropic Prompt Caching Support

We now support Anthropic’s Prompt Caching feature! Monitor and analyze cached prompt tokens and costs alongside regular requests through Helicone’s observability tools. Enable prompt caching through your existing Anthropic integration with Helicone - no additional configuration needed.

January 31, 2025

[Perplexity AI + Helicone

We’re excited to announce our integration with Perplexity AI, bringing powerful observability tools to your Perplexity model implementations! Get started with just two simple steps:

  1. Generate a write-only API key in your Helicone account.
  2. Update your Perplexity AI base URL to:
https://perplexity.helicone.ai

That’s all it takes! Now you can monitor, analyze, and optimize your Perplexity AI models with Helicone’s comprehensive insights.

For more details, check out our Perplexity AI integration guide.

January 30, 2025

[Nebius Token Factory + Helicone

We’re excited to announce our integration with Nebius Token Factory, bringing powerful observability tools to your Nebius model implementations! Get started with just two simple steps:

  1. Generate a write-only API key in your Helicone account.
  2. Update your Nebius Token Factory base URL to:
https://nebius.helicone.ai

That’s all it takes! Now you can monitor, analyze, and optimize your Nebius Token Factory models with Helicone’s comprehensive insights.

For more details, check out our Nebius Token Factory integration guide.

January 24, 2025

Helicone Prompt Editor: Your Ultimate AI Prompt Workspace

Elevate your prompt development with our new best-in-the-world editor, designed for peak efficiency and creativity. Now Live for all Prompts & Experiments users!

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Smart Editing Capabilities

Comprehensive Control & Flexibility

January 16, 2025

[DeepSeek AI + Helicone

We’re excited to announce our integration with DeepSeek AI, bringing powerful observability tools to your DeepSeek model implementations! Get started with just two simple steps:

  1. Generate a write-only API key in your Helicone account.
  2. Update your DeepSeek AI base URL to:
https://deepseek.helicone.ai

That’s all it takes! Now you can monitor, analyze, and optimize your DeepSeek AI models with Helicone’s comprehensive insights.

For more details, check out our DeepSeek AI integration guide.

December 19, 2024

[User Histograms: Analyze LLM Usage Patterns

We’re excited to introduce User Histograms, a powerful new visualization tool that helps you understand user behavior patterns across your LLM applications.

Key Features

Use Cases

  1. Usage Pattern Analysis
    • Identify usage clusters and understand how different user segments interact with your LLM applications
    • Spot outliers and investigate unusual usage patterns
  2. Cost Optimization
    • Understand cost distribution across your user base
    • Make informed decisions about pricing tiers and usage limits
  3. Capacity Planning
    • Analyze token usage patterns to better predict and plan for scaling
    • Understand peak usage patterns across your user base

To access User Histograms, navigate to the Users tab in your Helicone dashboard and click on the Histograms view.

December 10, 2024

[🎉 Experiments is here!

We are thrilled to announce that Experiments is out of beta.

Experiments is designed to help you tune your LLM prompt, test it on production data, and verify your iterations with quantifiable data.

Main use cases

1. Continuous Improvement

Analyze production edge cases to refine your application’s performance.

2. Pre-deployment Testing

Benchmark new releases rigorously before rolling out to production environments.

3. Structured Testing

Implement LLM-as-a-judge or custom evaluation metrics, then compare prompt variations side-by-side with quick, actionable feedback loop.

4. Prompt Optimization

Determine the best prompt for production by running evaluators to prevent performance regressions.

For detailed documentation, refer to our updated docs.

December 6, 2024

Support for AWS Bedrock Models

We’re excited to announce support for tracking AWS Bedrock models requests through Helicone

How to track your requests?

To track your Bedrock requests through Helicone, you can set the Bedrock client’s endpoint to use the Helicone Proxy.

endpoint="https://bedrock.helicone.ai/v1/<region>"

For detailed API documentation, please refer to our updated docs.

November 12, 2024

Cerebras: New Model Provider Integration

Cerebras Integration

We’re excited to announce the addition of Cerebras as a new model provider on our platform. This integration expands our suite of available AI models and provides more options for our users.

Getting Started

To start using Cerebras models, create an account on Cerebras and then create a new API key. Once you have your API key, you can add it to your Helicone configuration as a base_url.

base_url="https://cerebras.helicone.ai/v1"

For detailed API documentation, please refer to our updated docs.

October 24, 2024

[Webhooks: Real-Time Integration and Automation

We are excited to announce the addition of webhooks to our platform, enhancing real-time integration and automation capabilities. With this update, you can:

For detailed instructions, please refer to our Webhooks Setup Guide.

October 23, 2024

[Prompt UI Refresh

We’ve refreshed the Prompts interface to align with our new UI style — now simpler, more productive, and consistent throughout. Key improvements include:

Check it out in the Prompts tab in Helicone!

October 23, 2024

[New Claude 3.5 Sonnet (claude-3-5-sonnet-20241022-v2): Full Cost Support and Tracking

We’re excited to announce immediate support for Anthropic’s latest Claude 3.5 Sonnet model (claude-3-5-sonnet-20241022-v2), released in October 2024.

What’s New in This Version?

Performance Tracking and Cost Management

Our platform now offers:

How to Use

Refer to our Anthropic Integration Guide for details on how to use the new model with Helicone

Learn More About Claude 3.5 Sonnet

October 4, 2024

🎉 Prompt Experiments V2 Launch! 🎉

Discover Helicone’s experiments, a new spreadsheet-like interface designed for efficient LLM prompt experimentation. Easily manage multiple prompt variations, run flexible experiments, and gain data-driven insights to optimize your AI prompts.

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Get early access now 👉 helicone.ai/experiments

October 3, 2024

[Redesigned Requests Page for Enhanced LLM Observability

We’re excited to announce a major redesign of our Requests page, enhancing the user experience and efficiency for AI LLM observability.

Key Improvements

Benefits for LLM Developers and Data Scientists

This redesign reflects our commitment to providing the best tools for AI LLM observability. We’ve focused on enhancing the core features that matter most to our users, making it easier than ever to gain insights from your LLM application data.

We encourage you to explore the new Requests page and experience the improvements firsthand. Your feedback is valuable as we continue to refine and enhance Helicone’s observability platform.

October 2, 2024

Introducing new NPM packages for Helicone

We are thrilled to announce the addition of two essential npm packages: @helicone/async and @helicone/helpers. Additionally, we are also deprecating the @helicone/helicone package.

Why These Changes?

Detailed Changes

September 23, 2024

[Summary Reports

Get weekly summary reports of your LLM usage

We’ve launched a new feature that keeps you updated on your LLM usage with detailed weekly reports delivered directly to your inbox every Monday at 10 AM UTC. These reports provide a comprehensive overview of key metrics, including total usage, cost analysis, number of requests, error rate, active users, threats, number of sessions, and average session costs.

With these automated reports, you can easily monitor your AI performance, optimize your usage, and make data-driven decisions for your projects. Ensure you’re staying on top of your LLM utilization and maximizing the value of your resources.

Ready to get started? Configure your weekly summaries now.

September 16, 2024

[O1 Models: Support Added with Token and Cost Tracking

Immediate Support for OpenAI’s o1 Models

We’re excited to announce support for OpenAI’s new o1 models, along with comprehensive tracking of token counts and spending.

What Are o1 Models?

OpenAI’s o1 models represent a significant advancement in language AI. They use reinforcement learning to perform complex reasoning tasks, generating an internal chain of thought before producing a final response. This leads to enhanced performance and new capabilities for your applications.

Accurate Cost Tracking

Our platform now fully supports cost tracking for o1 model usage. Due to the unique way these models process information, it’s important to provide token counts for both input and output to ensure accurate cost calculations.

How to Ensure Accurate Tracking

Learn More About o1 Models

September 12, 2024

Datasets

Streamline your AI data organization and analysis with Helicone’s new Datasets feature. Designed for LLM developers and data scientists, this tool simplifies data handling for improved AI model performance.

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Key Features of Helicone Datasets:

  1. Dataset Creation: Quickly set up and organize your AI training data within the requests page.
  2. Export: Easily export your data as JSONL for training or finetuning.
  3. Edit: Edit your dataset and save it as a new version.

Benefits for AI Development:

To begin using the Datasets feature:

  1. Navigate to the Requests page in your Helicone dashboard.
  2. Enter select mode by clicking the select icon in the top right corner.
  3. Select the data points you want to include in your dataset.
  4. Click on “Create Dataset” and give it a name.
  5. Access your datasets from the new Datasets tab to export or edit as needed.

September 11, 2024

[Collapsible Sidebar

Enhance your workflow with our new collapsible sidebar feature. Users can now easily toggle the sidebar visibility, maximizing screen real estate and improving focus. This update offers:

Optimize your productivity by customizing your interface on demand. Experience a cleaner, more adaptable workspace with our latest sidebar enhancement.

September 10, 2024

[Slack Alerts

Real-Time Alerts Now Available in Slack for Faster Issue Resolution

Stay on top of critical issues with Helicone’s latest update: Slack Integration for Alerts. In addition to email notifications, you can now receive real-time alerts directly in your Slack workspace for faster action when something goes wrong.

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To get started, visit the Alerts page to create or edit an alert. Enhance your team’s productivity by responding to key notifications without delay.

August 29, 2024

[#1 Product of the Day on Product Hunt

Helicone Reaches #1 on Product Hunt!

This achievement reflects our team’s hard work and the incredible support from our community. We’re thrilled about the boost in visibility for our platform!

Highlights:

A huge thank you to everyone who upvoted, commented, and shared Helicone. Your support motivates us to keep improving!

For more on our Product Hunt journey, check out our blog posts:

Links:

Product Hunt: Helicone on Product Hunt

August 25, 2024

[Docker images on Docker Hub

Docker images now available on Docker Hub We’ve started publishing Docker images on Docker Hub.

This update simplifies Helicone deployment on platforms that don’t natively support the Google Container Registry. For detailed instructions, please refer to our updated self-hosting guide.

Links:

Docker Hub: helicone

August 12, 2024

[New hpstatic Function for Static Prompts in LLM Applications

We’ve added a new hpstatic function to our Helicone Prompt Formatter (HPF) package. This function allows users to create static prompts that don’t change between requests, which is particularly useful for system prompts or other constant text. The hpstatic function wraps the text in <helicone-prompt-static> tags, indicating to Helicone that this part of the prompt should not be treated as variable input.

Here’s a quick example of how to use hpstatic:

import { hpf, hpstatic } from "@helicone/prompts";

const systemPrompt = hpstatic`You are a helpful assistant.`;
const userPrompt = hpf`Write a story about ${{ character }}`;

const chatCompletion = await openai.chat.completions.create(
  {
    messages: [\
      { role: "system", content: systemPrompt },\
      { role: "user", content: userPrompt },\
    ],
    model: "gpt-3.5-turbo",
  },
  {
    headers: {
      "Helicone-Prompt-Id": "prompt_story",
    },
  }
);

This new feature enhances our prompt management capabilities, allowing for more flexible and efficient prompt structuring in your applications.

Start Using Static Prompts 🚀

August 9, 2024

[Ragas Integration for RAG System Evaluation

We’re excited to announce our integration with Ragas, an open-source framework for evaluating Retrieval-Augmented Generation (RAG) systems. This integration allows you to:

Check out this quick video overview of the Ragas integration:

Observability for Ragas - Evaluation Framework - YouTube

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hello my name is Justin and I am superexcited to show you how to integratehelicone

Observability for Ragas - Evaluation Framework Helicone AI

Helicone AI145 subscribers

0:03Time elapsed 3 seconds/2:10Time duration 2 minutes, 10 seconds

More videos

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Doctor Warns These 9 Medications May Cause Memory Loss After 60 - Dr. William Li \ 2 days ago

To get started with the Ragas integration, visit our documentation for step-by-step instructions and code examples.

August 6, 2024

[Optimistic Updates & Asynchronous Loading in Requests Page

We’ve improved data loading in the Requests page of the Helicone platform. By fetching metadata and request bodies separately and loading data asynchronously we’ve reduced the time it takes to render large tables by almost 6x, improving speed and UX.

July 26, 2024

[New Assistants UI Playground

We’re thrilled to announce a major update to our Assistants UI Playground! Head to the Playground and click the “Try New Playground” button to explore the latest improvements:

Coming soon:

Try out the new Playground today and elevate your LLM testing experience!

July 24, 2024

[Fireworks AI + Helicone

We’re excited to announce our integration with Fireworks AI, the high-performance LLM platform! Enhance your AI applications with Helicone’s powerful observability tools in just two easy steps:

  1. Generate a write-only API key in your Helicone account.
  2. Update your Fireworks AI base URL to:
https://fireworks.helicone.ai

That’s all it takes! Now you can monitor, analyze, and optimize your Fireworks AI models with Helicone’s comprehensive insights.

For more details, check out our Fireworks AI integration guide.

July 23, 2024

[Dify + Helicone

We’re thrilled to announce our integration with Dify, the open-source LLM app development platform! Now you can easily add Helicone’s powerful observability features to your Dify projects in just two simple steps:

  1. Generate a write-only API key in your Helicone account.
  2. Set your API base URL in Dify to:
https://oai.helicone.ai/<API_KEY>

That’s it! Enjoy comprehensive logs and insights for your Dify LLM applications.

Check out our integration guide for more details.

July 22, 2024

[Prompts package

We’re excited to announce the release of our new @helicone/prompts package! This lightweight library simplifies prompt formatting for Large Language Models, offering features like:

Check it out on GitHub and enhance your LLM workflow today!