OpenPipe AI

OpenPipe AI is a platform that helps enterprises and developers build, fine-tune, and deploy custom AI models for production applications. It specializes in streamlining the process of replacing expensive, slow prompts with smaller, cheaper, and more efficient fine-tuned models.

OpenPipe performs several key functions including data capture, which automatically records LLM requests and responses for future use; fine-tuning, which enables easy fine-tuning of open-source models like GPT-3.5, Mistral, and Llama 2 on your own data; model hosting, where your fine-tuned models are hosted on managed endpoints that scale to millions of requests; evaluation, allowing you to compare your models against each other and base models like OpenAI’s for performance; and integration, offering SDKs for Python and TypeScript with OpenAI-compatible endpoints for seamless integration.

To get started with OpenPipe, you need to create an account by signing up, then retrieve your project API key from the settings. Next, capture data by integrating the OpenPipe SDK or using the OpenPipe Proxy to log your LLM requests and responses. After preparing a dataset, either by uploading your own in OpenAI-compatible JSONL format or by using the captured logs, you can then use the platform to start a fine-tuning job on your dataset. Finally, deploy your model and compare its performance against other models.

OpenPipe supports fine-tuning of popular open-source models such as GPT-3.5, Mistral, and Llama 2. You can host these models on OpenPipe or download the weights for deployment elsewhere.

OpenPipe ensures data security and compliance by offering SOC 2 Type 2 compliance, HIPAA compliance for healthcare data, and GDPR compliance for data privacy.

ART is OpenPipe’s reinforcement learning framework for training AI agents. It allows for easy training of LLM-based agents using techniques like GRPO, with integrations for observability and debugging.

Yes, you can upload your own datasets in OpenAI-compatible JSONL format, or use the data captured by OpenPipe’s logging features.

To integrate OpenPipe with your existing application, you need to update your SDK import statement and add an OpenPipe API key, then replace your current LLM provider’s model name with your OpenPipe model name. No changes to your response parsing are needed, as OpenPipe models are OpenAI-compatible.

The benefits of using OpenPipe include cost savings, as fine-tuned models can be up to 50x cheaper to run than base models; improved performance, since custom models often outperform general-purpose models for specific tasks; ease of use, due to simple integration, automated data capture, and streamlined fine-tuning; and scalability, with managed endpoints that can handle millions of requests.

For general inquiries, you can contact founders@openpipe.ai, and for technical support, reach out to support@openpipe.ai.

More documentation can be found on the OpenPipe Documentation page and their OpenPipe GitHub repository.

OpenPipe offers a per-token pricing model with enterprise plans that include additional features like HIPAA/SOC 2/GDPR compliance, custom relabeling, active learning, and discounted token rates.