I have handpicked 7 tools that solve the real challenges in AI development. Forget about prompt engineering - these tools handle everything from state management to production scaling, letting you focus on building actual features.
From production-ready AI infrastructure to performance optimization, these tools transform how developers build with AI. They're not just libraries; they're the foundation for properly engineered AI applications.
1. Julep - Platform to build and manage AI agent workflows
If you've built AI features, you know the pain: managing conversation state, handling long-running tasks, dealing with retries when LLMs fail, and praying your prompt chains work in production. Julep tackles all the infrastructure headaches that usually fall on your shoulders.
What makes Julep super valuable for a dev is:
All the hard stuff like state management, parallel processing with proper handling, long-running background tasks and automatic retries come out of the box.
It gives you the ability to write workflows like GitHub actions - so no need to manage complex chains of prompts or trying to handle concurrent LLM calls yourself.
It's production ready from Day 1 - and you can use the hosted version or run it locally. It automatically scales as you grow.
Give Julep a try and star it to stay updated. ⭐ -
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🌟 Call for Contributors!
We're excited to welcome new contributors to the Julep project! We've created several "good first issues" to help you get started. Here's how you can contribute:
- Check out our CONTRIBUTING.md file for guidelines on how to contribute.
- Browse our good first issues to find a task that interests you.
- If you have any questions or need help, don't hesitate to reach out on our Discord channel.
Your contributions, big or small, are valuable to us. Let's build something amazing together! 🚀
🎉 DevFest.AI October 2024
Exciting news! We're participating in DevFest.AI throughout October 2024! 🗓️
- Contribute to Julep during this…
2. Composio - Build and Ship AI Integrations
Composio is a framework that helps us to build scalable AI applications equipped with AI Agents to automate the workflow involving external applications.
This framework lets you augment your AI agents with robust tools and integrations to accomplish AI workflows.
It comes with over 100+ popular tools covering a wide range of domains such as Productivity, HR, Dev, CRM, etc to automate your complex workflows.
Check out their documentation to know more.
3. Portkey - Optimize your GenAI Apps
Portkey is a full stack LLM Ops platform. Helping you build and ship your GenAI apps to production faster and with confidence. It offers tools to manage models, LLM gateway, fine-tune, and privacy.
It simplifies the process of integrating AI models into applications by acting as a gateway between LLM apps and their providers.
Supports 250+ models including those from Google Vertex AI, and offers features like semantic caching, which can reduce API costs and improve response times.
Check out their documentation to know more.
4. Hamming - Improve your AI Agents
Hamming is an AI-driven platform that gives deep insights into the performance of AI applications & helps to improve the prompts, RAG & AI Agents.
It is designed to help engineering teams build and improve AI products, particularly focusing on voice and multi-step AI agents.
Instead of manually testing tweaks to prompts or models, Hamming can test hundreds of variations in minutes, significantly speeding up the development process.
Hamming aims to make building reliable and effective AI products easier and faster.
Check out their documentation to know more.
5. Cloudcode - Seamless Software Testing
CloudCode is an AI-powered tool designed to streamline and enhance various aspects of software development and deployment.
It offers intelligent QA assistance to automate code reviews, detect bugs, and generate tests.
The platform, known as Kaizen, supports pre-deployment smart code reviews, end-to-end testing, and unit test generation.
Kaizen integrates seamlessly with popular development environments and CI/CD pipelines, ensuring early detection of errors and optimized code quality.
Check out their documentation to know more.
6. Pieces - Your Workflow Copilot
Pieces is an AI-driven tool designed to simplify your coding workflow through intelligent snippet management, context-aware copilot interactions, and proactive surfacing of relevant materials.
Enhances your entire development experience while ensuring the privacy and security of your work with a fully offline AI approach.
Pieces offers a wealth of productivity-enhancing features, including AI-driven code snippet organization, contextual copilot interactions, and intelligent recommendations of valuable resources.
Check out their documentation to know more.
7. Gooey.AI - Low code platform to build AI workflows
Gooey is an open-source, low-code AI platform with the best of private and public AI.
Gooey helps increase worker productivity with discoverable, low-code AI workflows.
We help global organizations build AI that changes lives and improves our planet's Sustainable Development Goals in agriculture, health, education, climate and livelihoods.
Built for developers who code fast, teams that prove ROI and people that change the world.
These tools represent the cutting edge of AI development infrastructure, each addressing crucial aspects of the development lifecycle. From streamlining workflows to optimizing performance and ensuring production readiness, these solutions provide the foundation needed for building sophisticated AI applications.
Know of other tools making waves in the AI development space? Share your experiences and recommendations in the comments below!
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