All chat API models are supported, this is a example, let me know if you run into issues
LLMS
-
Fastest Way to Build Web Apps with Anthropic API
By
–
awesome, also here is the fastest way to build web apps with anthropic API:
-
LangGraph with Instructor: Building AI Without LangChain
By
–
Cool example of using LangGraph with @jxnlco
's instructor Don't need to use LangChain to use LangGraph! -

Production AI Engineering Starts with Evals: LLM Ops Deep Dive
By
–
Production AI Engineering starts with Evals https://
latent.space/p/braintrust A 2 hour deep dive on the state of the LLM Ops industry with @ankrgyl following the @braintrustdata Series A! We discuss: why @HamelHusain was right: Evals are at the center of the production AI -

anthropic-gradio: Easy ML Apps with Anthropic API
By
–
anthropic-gradio a Python package that makes it very easy for developers to create machine learning apps that are powered by @AnthropicAI API
-

o1-mini Struggles to Prove Matrix Multiplication Distributive Property
By
–
I tried to get o1-mini to prove distributive property for matmul and it tried like 3 times before basically saying "ok I can't get this but like trust me it holds"
-

Lightning-Fast AI Inference with Llama 3.2 at SambaNova
By
–
POV: You're trying out lightning-fast #AI #inference on @AIatMeta
's #Llama 3.2 Experience high speeds, all running at full-precision. 2470 tokens/sec on 1B 1566 tokens/sec on 3B Start developing https://
cloud.sambanova.ai -
Agentic AI Transforms Enterprise LLM Deployment at Scale
By
–
With agentic AI playing a key role in shaping the future of LLMs, businesses are now able to build more dynamic, self-directed AI systems. See DataRobot featured in @SiliconANGLE as an AI innovator helping organizations deploy AI solutions securely and at scale:
-
LeanAgent: Lifelong Learning Agent for Formal Theorem Proving
By
–
Announcing LeanAgent: the first life-long learning agent for formal theorem proving in Lean. LLMs have been integrated with interactive proof assistants like Lean for theorem proving with 100% accuracy. So far, these LLMs are static, cannot learn new knowledge online, and
