PromptDesk
The easiest and fastest way to build prompt-based applications.
Top 4 features:
Collaborative GUI Prompt Builder: Featuring a user-friendly and sophisticated interface, this builder streamlines the creation of complex prompts, enabling users to craft intricate prompt structures with ease.
100% LLM Support: PromptDesk offers seamless integration with all large language models without restriction, limit or wait.
Fine-Tuning and Data Management: Users have access to detailed logs and histories, facilitating the fine-tuning of datasets and prompts for optimized performance and tailored application responses.
Python SDK: Accelerate prompt-to-code which allows for effortless integration of prompts created in the GUI with Python source code.
LiteLLM
Call 100+ LLM models using the OpenAI format.
Top 4 features:
Unified API Format: It allows calling various LLM APIs using the OpenAI format, simplifying integration with multiple providers like Azure, Cohere, Anthropic, etc.
Consistent Output and Exception Mapping: Guarantees consistent output format and maps common exceptions across different providers to OpenAI exception types.
Load Balancing and Proxy Management: Supports load balancing across multiple deployments and manages calling 100+ LLMs in OpenAI format.
Logging and Observability: Provides predefined callbacks for integration with various logging and monitoring tools.
LLMClient
A caching and debugging proxy server for LLM users.
Top 4 features:
Multi-LLM Support: It supports various language models, including OpenAI's GPT models, Anthropic's Claude, Azure's AI models, Google's AI Text models, and more.
Function (API) Calling with Reasoning (CoT): Enables language models to reason through tasks and interact with external data via API calls. This includes built-in functions like a code interpreter.
Detailed Debug Logs and Troubleshooting Support: Provides tools for debugging, including comprehensive logs and a Web UI for tracing and metrics.
Long Term Memory and Vector DB Support (Built-in RAG): Supports long-term memory for maintaining context in conversations and retrieval-augmented generation (RAG) with vector database support for enhanced query responses.
GPTCache
A semantic cache for LLMs that fully integrates with LangChain and llama_index.
Top 4 features:
Semantic Caching: Utilizes semantic analysis to cache similar queries, enhancing efficiency and reducing redundant API calls to language models.
Modular Design: Offers flexibility in integrating various components like LLM adapters, multimodal adapters, and embedding generators for customized caching solutions.
Support for Multiple LLMs and Multimodal Models: Compatible with a range of large language models and multimodal models, facilitating broad application scenarios.
Diverse Storage and Vector Store Options: Supports a variety of cache storage systems and vector stores, allowing for scalable and adaptable cache management.
Top comments (1)
I would add agenta (github.com/agenta-ai/agenta). It's open-source, provides a playground for comparison of models and prompts, prompt versioning, automatic evaluation, and human evaluation feedback.