Transforms complex documents like PDFs and Office docs into LLM-ready markdown/JSON for your Agentic workflows.
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Get your documents ready for gen AI
Structured Outputs
- generative-ai
- llms
- prompt-engineering
- symbolic-ai
RWKV (pronounced RwaKuv) is an RNN with great LLM performance, which can also be directly trained like a GPT transformer (parallelizable). We are at RWKV-7 "Goose". So it's combining the best of RNN and transformer - great performance, linear time, constant space (no kv-cache), fast training, infinite ctx_len, and free sentence embedding.
- attention-mechanism
- deep-learning
- gpt
- gpt-2
💡 All-in-one AI framework for semantic search, LLM orchestration and language model workflows
- python
- search
- nlp
- semantic-search
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
CASSIA: A Multi-Agent LLM-Based Single-Cell Cell Type Annotation Framework
- ai4science
- llm
- multiagent-systems
- prompt-engineering
Autonomous multi-agent framework to optimize scientific software
- acceleration
- agentic-ai
- ai-agents
- bioinformatics
Turn any Java, Kotlin or Python project into an AI-ready context file in one command.