OpenPipe

# OpenPipe ## Docs - [OpenPipe Documentation](https://docs.openpipe.ai/introduction.md): Software engineers and data scientists use OpenPipe's intuitive fine-tuning and monitoring services to decrease the cost and latency of their LLM operations. You can use OpenPipe to collect and analyze LLM logs, create fine-tuned models, and compare output from multiple models given the same input. - [Overview](https://docs.openpipe.ai/overview.md): OpenPipe is a streamlined platform designed to help product-focused teams train specialized LLM models as replacements for slow and expensive prompts. - [Base Models](https://docs.openpipe.ai/base-models.md): Train and compare across a range of the most powerful base models. - [Quick Start](https://docs.openpipe.ai/getting-started/quick-start.md): Get started with OpenPipe in a few quick steps. - [Installing the SDK](https://docs.openpipe.ai/getting-started/openpipe-sdk.md) - [Logging Requests](https://docs.openpipe.ai/features/request-logs/logging-requests.md): Record production data to train and improve your models' performance. - [Logging Anthropic Requests](https://docs.openpipe.ai/features/request-logs/reporting-anthropic.md) - [Exporting Logs](https://docs.openpipe.ai/features/request-logs/exporting-logs.md): Export your past requests as a JSONL file in their raw form. - [Datasets](https://docs.openpipe.ai/features/datasets/overview.md): Collect, evaluate, and refine your training data. - [Datasets Quick Start](https://docs.openpipe.a […gekürzt]