optillm and LLMstudio

These two tools are complements: OptiLLM focuses on optimizing inference for deployed LLMs, while LLMstudio provides a framework to bring LLM applications to production, including potentially integrating and leveraging such optimization proxies.

optillm
62
Established
LLMstudio
61
Established
Maintenance 17/25
Adoption 10/25
Maturity 16/25
Community 19/25
Maintenance 10/25
Adoption 10/25
Maturity 25/25
Community 16/25
Stars: 3,377
Forks: 265
Downloads:
Commits (30d): 6
Language: Python
License: Apache-2.0
Stars: 371
Forks: 39
Downloads:
Commits (30d): 0
Language: Python
License: MPL-2.0
No Package No Dependents
No risk flags

About optillm

algorithmicsuperintelligence/optillm

Optimizing inference proxy for LLMs

This tool acts as a smart go-between for your existing Large Language Model (LLM) services, such as OpenAI. It takes your standard LLM requests and processes them using advanced reasoning techniques to produce significantly more accurate answers, especially for complex tasks like math, coding, and logical problems. Anyone using LLMs for critical reasoning, problem-solving, or content generation would find this beneficial, including researchers, data scientists, and developers building LLM applications.

LLM application development AI research reasoning automation problem solving code generation

About LLMstudio

TensorOpsAI/LLMstudio

Framework to bring LLM applications to production

This framework helps AI/ML engineers and developers quickly build and deploy applications that use large language models (LLMs). It provides a user-friendly interface to test and refine prompts, integrating seamlessly with various LLMs (OpenAI, Anthropic, Google, custom, or local models). You input your desired prompts and model configurations, and it outputs production-ready LLM applications with built-in monitoring and reliability features.

AI application development LLM deployment prompt engineering machine learning operations API integration

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