#python #datasets #evaluation #metrics #natural_language_processing #nlp #numpy #pandas #pytorch #tensorflow

https://github.com/huggingface/nlp

#typescript #agent_monitoring #analytics #evaluation #gpt #langchain #large_language_models #llama_index #llm #llm_cost #llm_evaluation #llm_observability #llmops #monitoring #open_source #openai #playground #prompt_engineering #prompt_management #ycombinator

Helicone is an all-in-one, open-source platform for developing and managing Large Language Models (LLMs). It allows you to integrate with various LLM providers like OpenAI, Anthropic, and more with just one line of code. You can observe and debug your model's performance, analyze metrics such as cost and latency, and fine-tune your models easily. The platform also offers a playground to test and iterate on prompts and sessions, and it supports prompt management and automatic evaluations. Helicone is enterprise-ready, compliant with SOC 2 and GDPR, and offers a generous free tier of 100k requests per month. This makes it easier to manage and optimize your LLM projects efficiently.

https://github.com/Helicone/helicone

#python #agent #agentops #agents_sdk #ai #anthropic #autogen #cost_estimation #crewai #evals #evaluation_metrics #groq #langchain #llm #mistral #ollama #openai #openai_agents

AgentOps is a tool that helps developers monitor and improve AI agents. It provides features like session replays, cost management for Large Language Models (LLMs), and security checks to prevent data leaks. This platform allows you to track how your agents perform, interact with users, and use external tools. By using AgentOps, you can quickly identify problems, optimize agent performance, and ensure compliance with safety standards. It integrates well with popular platforms like OpenAI and AutoGen, making it easy to set up and use[1][3][5].

https://github.com/AgentOps-AI/agentops

#typescript #ai #analytics #datasets #dspy #evaluation #gpt #llm #llmops #low_code #observability #openai #prompt_engineering

LangWatch helps you monitor, test, and improve AI applications by tracking performance, comparing different setups, and optimizing prompts automatically. It works with any AI tool or framework, keeps your data secure, and lets you collaborate with experts to fix issues quickly, making your AI more reliable and efficient.

https://github.com/langwatch/langwatch

#typescript #ci #ci_cd #cicd #evaluation #evaluation_framework #llm #llm_eval #llm_evaluation #llm_evaluation_framework #llmops #pentesting #prompt_engineering #prompt_testing #prompts #rag #red_teaming #testing #vulnerability_scanners

Promptfoo is a tool that helps developers test and improve AI applications using Large Language Models (LLMs). It allows you to **test prompts and models** automatically, **secure your apps** by finding vulnerabilities, and **compare different models** side-by-side. You can use it on your computer or integrate it into your development workflow. This tool helps you make sure your AI apps work well and are secure before you release them. It saves time and ensures quality by using data instead of guessing.

https://github.com/promptfoo/promptfoo

#python #agents #document_search #evaluation #guardrails #llms #optimization #prompts #rag #vector_stores

Ragbits is a tool that helps build and deploy GenAI applications quickly. It offers features like swapping between many language models, ensuring safe interactions with these models, and connecting to various data storage systems. Ragbits also includes tools for managing data and testing prompts, making it easier to develop reliable AI applications. This helps users create more accurate and efficient AI systems by integrating the latest data and reducing errors. Overall, Ragbits makes it faster and more efficient to develop and deploy AI applications.

https://github.com/deepsense-ai/ragbits

#python #evaluation_framework #evaluation_metrics #llm_evaluation #llm_evaluation_framework #llm_evaluation_metrics

DeepEval is an open-source tool that makes it easy to test and improve large language model (LLM) applications, much like how Pytest works for regular software, but focused on LLM outputs. It offers over 30 ready-to-use metrics—such as answer relevancy, faithfulness, and hallucination—to check if your LLM is accurate, safe, and reliable. You can test your whole application or just parts of it, and even generate synthetic data for better testing. DeepEval works locally or in the cloud, letting you compare results, share reports, and keep improving your models. This helps you build better, safer, and more trustworthy LLM apps with less effort[1][2][3].

https://github.com/confident-ai/deepeval

#go #agent #agentic #ai #chatbot #chatbots #embeddings #evaluation #generative_ai #golang #knowledge_base #llm #multi_tenant #multimodel #ollama #openai #question_answering #rag #reranking #semantic_search #vector_search

WeKnora is a powerful tool that helps you understand and find answers in complex documents like PDFs and Word files. It uses advanced AI to read documents, understand what they mean, and answer your questions in a simple way. This tool is useful for businesses and researchers because it can quickly find information from many documents, making it easier to manage knowledge and make decisions. It also supports multiple languages and can be used privately, ensuring your data stays safe.

https://github.com/Tencent/WeKnora