AI development frameworks and platforms senior IT professionals must know
Problem - Where to find the latest AI papers and code?
Solution:
Papers with code (by Meta AI) -
Problem - How can we easily make LLM pipelines?
Solution:
VEXT
Problem - How can we run open-sourced LLMs on a laptop?
Solution:
Ollama
Problem - Where to find open-source models and datasets
Solution:
Hugging Face
Kaggle
Problem - How to quickly deploy AI/ LLM applications and share?
Solution:
Gradio
Streamlit
Problem - LLM Application Development Frameworks
Solution:
LangChain
LlamaIndex
Problem - How can we use open-sourced LLM models already deployed on the cloud?
Solution:
Amazon Web Services (AWS) Bedrock
NVIDIA NIM
Problem - Platform/ Frameworks for making AI Agents
Solution:
crewAI
AutogenAI
LangGraph -
Problem - How to evaluate LLMs and measure hallucination?
Solution:
Giskard
Vectara
MLflow
Problem - How to fine-tune LLMs faster?
Solution:
Unsloth AI
Problem - Can fine-tuning be done using web UI?
Solution:
Llama factory -
Problem - How to monitor latency, cost, token usage for LLM applications
Solution:
Langsmith -
Weights & Biases
Problem - How to deploy LLM applications as a REST API
Solution:
Langserve -
Problem - Can we build AI Agents without writing complex codes
Solution: Building AI Agents as a service
Dify
Problem - Can we build RAG pipelines without writing complex codes
Solution:
Dify
Google Cloud Platform's Search & Conversation
Problem - How can we test and monitor AI Agents?
Solution:
AgentOps AI
Problem - How to deploy AI/ LLM models and applications easily and faster?
Solution:
Deep Infra
Replicate
RunPod
Problem - How to evaluate RAG and Fine Tuning
Solution:
Arize AI
Problem - Can we have a vector database for edge devices?
Solution:
ObjectBox
Problem - How can we track model-building experiments and store unstructured data?
Solution:
DagsHub
If you are aware of any other great AI developer frameworks and platforms then please share and I will try to make it a comprehensive list