I am using llm to generate the application according to my requirements, this process highly depends on the code generation ability and agent ability to finish some complex tasks. I did a lot of research on it and make a collection for the reference. Hope it can also help you.
- MetaGPT https://github.com/geekan/MetaGPT/tree/main/examples/di
- Devika https://github.com/stitionai/devika
- OpenDevin https://github.com/OpenDevin/OpenDevin
- Maestro https://twitter.com/skirano/status/1770221447606104154
- gpt-engineer https://github.com/gpt-engineer-org/gpt-engineer
- SWE-agent https://github.com/princeton-nlp/SWE-agent
- auto-coder https://github.com/allwefantasy/auto-coder
- machine learning agent https://github.com/WecoAI/aideml
- CodeHalu https://github.com/yuchen814/CodeHalu
- trove https://github.com/zorazrw/trove
- ChatDev https://github.com/OpenBMB/ChatDev
- Devon https://github.com/entropy-research/Devon
- r2e https://github.com/r2e-project/r2e
- crewAI https://github.com/joaomdmoura/crewAI
- autogen https://www.microsoft.com/en-us/research/project/autogen/
- AgentLite https://github.com/SalesforceAIResearch/AgentLite
- AgentVerse https://github.com/OpenBMB/AgentVerse
- OneTwo https://github.com/google-deepmind/onetwo
- agentkit https://github.com/holmeswww/AgentKit
- Xagent https://github.com/OpenBMB/XAgent
- llm-reasoners https://github.com/maitrix-org/llm-reasoners/
- OSWorld https://github.com/xlang-ai/OSWorld
- agent design pattern https://twitter.com/shao__meng/status/1784474864113570027
- task-decompose https://github.com/zgimszhd61/task-decompose-quickstart
- JARVIS https://github.com/microsoft/JARVIS
- agent search tree https://github.com/andyz245/LanguageAgentTreeSearch
- stream of search https://github.com/kanishkg/stream-of-search
- ambigdocs https://ambigdocs.github.io/
- USACO https://github.com/princeton-nlp/USACO
- Logic-LLM https://github.com/teacherpeterpan/Logic-LLM
- chain of abstraction https://twitter.com/jerryjliu0/status/1778855608202277156
- graph cot https://github.com/PeterGriffinJin/Graph-CoT
- Multiplex https://github.com/LCS2-IIITD/Language_Model_Multiplex
- RoT https://github.com/huiwy/reflection-on-trees
- LanguageModelsasCompilers https://github.com/kyle8581/LanguageModelsasCompilers
- lumos https://github.com/allenai/lumos
- ReaLMistake https://github.com/psunlpgroup/ReaLMistake
- eclair https://github.com/HazyResearch/eclair-agents
- agentscope https://github.com/modelscope/agentscope
- Dspy https://github.com/stanfordnlp/dspy
- Tool use https://twitter.com/omarsar0/status/1770497515898433896
- Strong types https://github.com/bananaml/fructose
- Phidata https://github.com/phidatahq/phidata/tree/main/cookbook/claude
- RepoToTextForLLMs https://github.com/Doriandarko/RepoToTextForLLMs
- storm https://github.com/stanford-oval/storm
- storm claude https://github.com/angelina-yang/Claude_API_Contest/tree/main
- MathVC https://github.com/MurongYue/MathVC
- AIOS https://github.com/agiresearch/AIOS
- cohere-terrarium https://github.com/cohere-ai/cohere-terrarium
- data labeling https://github.com/HumanSignal/Adala
- data to paper https://github.com/Technion-Kishony-lab/data-to-paper
- gpt-prompt-engineer https://github.com/mshumer/gpt-prompt-engineer
- Claude-ception https://twitter.com/LangChainAI/status/1770124528322318522
- Enhancing Few-shot Text-to-SQL Capabilities https://twitter.com/emelia_seles/status/1767797228398342244
- prompt optimization https://twitter.com/hi_pondai/status/1769445700977221769
- advprompter https://github.com/facebookresearch/advprompter
- PromptReps https://github.com/ielab/PromptReps
- PromptAgent https://github.com/XinyuanWangCS/PromptAgent
- promptbench https://github.com/microsoft/promptbench
- coding prompt https://twitter.com/seclink/status/1776408191557075052
- Prompt Engineer https://twitter.com/JagersbergKnut/status/1776230873525788903
- ADaPT https://allenai.github.io/adaptllm/
- Step-by-Step Comparisons https://twitter.com/omarsar0/status/1770492690129359135
- Flow Adhering Planning https://twitter.com/ShamiikRoy/status/1768007927342969281
- CoT improves performance for code generation https://twitter.com/ellev3n11/status/1769574342206038201
- Implicit CoT https://twitter.com/Euclaise_/status/1769424716568072641
- RAT https://twitter.com/AndyLin2001/status/1767075865127719101
- Self discover https://twitter.com/hi_pondai/status/1769445700977221769
- Self-Correct Their Reasoning https://twitter.com/jefffhj/status/1709634179594703187
- Dspy optimization https://twitter.com/CShorten30/status/1768780338715623907
- fillerTokens https://github.com/JacobPfau/fillerTokens
- Claude's responses superior https://twitter.com/IntuitMachine/status/1770513600689410534
- Claude 3 Opus https://twitter.com/alexalbert__/status/1767258557039378511
- Microfot AutoDev https://twitter.com/Marktechpost/status/1770294548629189071
- Coding preference https://twitter.com/MWeyssow/status/1768623185107550295
- Livecodebench https://twitter.com/StringChaos/status/1768264053879873668
- AgentCoder https://twitter.com/debarghya_das/status/1768468420058902536
- 10 agent paper https://twitter.com/GptMaestro/status/1780605438092013797
- OpenChatML https://twitter.com/erhartford/status/1780027791641391489