#rust #agent #ai #artificial_intelligence #automation #generative_ai #large_language_model #llm #llmops #rust #scalable_ai

Rig is a Rust library that helps you build apps using Large Language Models (LLMs) like OpenAI and Cohere. It makes it easy to integrate these models into your application with minimal code. Rig supports various vector stores like MongoDB and Neo4j, and it provides simple but powerful tools to work with LLMs. To get started, you can add Rig to your project using `cargo add rig-core` and follow the examples provided. This library is constantly improving, so your feedback is valuable. Using Rig can save you time and effort by providing a straightforward way to use LLMs in your projects.

https://github.com/0xPlaygrounds/rig

#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

#other #chatbot #hugging_face #llm #llm_local #llm_prompting #llm_security #llmops #machine_learning #open_ai #pathway #rag #real_time #retrieval_augmented_generation #vector_database #vector_index

Pathway's AI Pipelines help you quickly create and deploy AI applications with high accuracy. These pipelines use the latest knowledge from your data sources and offer ready-to-deploy templates for large language models. You can test these apps on your own machine and deploy them on cloud services like GCP, AWS, or Azure, or on-premises. The apps connect to various data sources such as file systems, Google Drive, and databases, and they include built-in data indexing for efficient searches. This makes it easy to extract and organize data from documents in real-time, reducing the need for separate infrastructure setups. This simplifies the process of building and maintaining AI applications, saving you time and effort.

https://github.com/pathwaycom/llm-app

#python #cloud_native #cncf #deep_learning #docker #fastapi #framework #generative_ai #grpc #jaeger #kubernetes #llmops #machine_learning #microservice #mlops #multimodal #neural_search #opentelemetry #orchestration #pipeline #prometheus

Jina-serve is a tool that helps you build and deploy AI services easily. It supports major machine learning frameworks and allows you to scale your services from local development to production quickly. You can use it to create AI services that communicate via gRPC, HTTP, and WebSockets. It has features like built-in Docker integration, one-click cloud deployment, and support for Kubernetes and Docker Compose, making it easy to manage and scale your AI applications. This makes it simpler for you to focus on the core logic of your AI projects without worrying about the technical details of deployment and scaling.

https://github.com/jina-ai/serve

#python #agents #ai #ai_agents #aiagents #developer_tools #function_calling #gpt_4 #gpt_4o #hacktoberfest #hacktoberfest2024 #javascript #js #llm #llmops #python #typescript

Composio is a powerful tool that helps AI agents work with many different apps and services. It supports over 250 tools, including popular ones like GitHub, Gmail, and Salesforce. Composio makes it easy to manage authentication across multiple accounts, which means you can securely connect your AI agents to various platforms without worrying about security issues. This integration enhances productivity by automating tasks and streamlining workflows, making it easier for developers and users to get more out of their AI tools.

https://github.com/ComposioHQ/composio

#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

#rust #ai #ai_engineering #anthropic #artificial_intelligence #deep_learning #genai #generative_ai #gpt #large_language_models #llama #llm #llmops #llms #machine_learning #ml #ml_engineering #mlops #openai #python #rust

TensorZero is a free, open-source tool that helps you build and improve large language model (LLM) applications by using real-world data and feedback. It gives you one simple API to connect with all major LLM providers, collects data from your app’s use, and lets you easily test and improve prompts, models, and strategies. You can see how your LLMs perform, compare different options, and make them smarter, faster, and cheaper over time—all while keeping your data private and under your control. This means you get better results with less effort and cost, and your apps keep improving as you use them[1][2][3].

https://github.com/tensorzero/tensorzero

#typescript #ai_gateway #gateway #generative_ai #hacktoberfest #langchain #llama_index #llmops #llms #openai #prompt_engineering #router

The AI Gateway by Portkey lets you connect to over 1600 AI models quickly and securely through one simple API, making it easy to integrate any language, vision, or audio AI model in under two minutes. It ensures fast responses with less than 1ms latency, automatic retries, load balancing, and fallback options to keep your AI apps reliable and scalable. It also offers strong security with role-based access, guardrails, and compliance with standards like SOC2 and GDPR. You can save costs with smart caching and optimize usage without changing your code. This helps you build powerful, cost-effective, and secure AI applications faster and with less hassle.

https://github.com/Portkey-AI/gateway

#python #agents #gcp #gemini #genai_agents #generative_ai #llmops #mlops #observability

You can quickly create and deploy AI agents using the Agent Starter Pack, a Python package with ready-made templates and full infrastructure on Google Cloud. It handles everything except your agent’s logic, including deployment, monitoring, security, and CI/CD pipelines. You can start a project in just one minute, customize agents for tasks like document search or real-time chat, and extend them as needed. This saves you time and effort by providing production-ready tools and integration with Google Cloud services, letting you focus on building smart AI agents without worrying about backend setup or deployment details.

https://github.com/GoogleCloudPlatform/agent-starter-pack