Enable MetaGPT to self-evolve, accomplishing self-training, fine-tuning, optimization, utilization, and updates.
- Become the multi-agent framework with the highest ROI.
- Support fully automatic implementation of medium-sized projects (around 2000 lines of code).
- Implement most identified tasks, reaching version 0.5.
To reach version v0.5, approximately 70% of the following tasks need to be completed.
- Usability
Release v0.01 pip package to try to solve issues like npm installation (though not necessarily successfully)(v0.3.0)- Support for overall save and recovery of software companies
Support human confirmation and modification during the process(v0.3.0) New: Support human confirmation and modification with fewer constrainsts and a more user-friendly interface- Support process caching: Consider carefully whether to add server caching mechanism
Resolve occasional failure to follow instruction under current prompts, causing code parsing errors, through stricter system prompts(v0.4.0, with function call)- Write documentation, describing the current features and usage at all levels (ongoing, continuously adding contents to documentation site)
Support Docker
- Features
- Support a more standard and stable parser (need to analyze the format that the current LLM is better at)
Establish a separate output queue, differentiated from the message queue- Attempt to atomize all role work, but this may significantly increase token overhead
- Complete the design and implementation of module breakdown
- Support various modes of memory: clearly distinguish between long-term and short-term memory
- Perfect the test role, and carry out necessary interactions with humans
- Allowing natural communication between roles (expected v0.5.0)
- Implement SkillManager and the process of incremental Skill learning (experimentation done with game agents)
- Automatically get RPM and configure it by calling the corresponding openai page, so that each key does not need to be manually configured
- IMPORTANT: Support incremental development (expected v0.5.0)
- Strategies
- Support ReAct strategy (experimentation done with game agents)
- Support CoT strategy (experimentation done with game agents)
- Support ToT strategy
- Support Reflection strategy (experimentation done with game agents)
- Support planning
- Actions
Implementation: Search(v0.2.1)- Implementation: Knowledge search, supporting 10+ data formats
- Implementation: Data EDA (expected v0.6.0)
- Implementation: Review
- Implementation: Add Document (expected v0.5.0)
- Implementation: Delete Document (expected v0.5.0)
- Implementation: Self-training
Implementation: DebugError(v0.2.1)- Implementation: Generate reliable unit tests based on YAPI
- Implementation: Self-evaluation
- Implementation: AI Invocation
- Implementation: Learning and using third-party standard libraries
- Implementation: Data collection
- Implementation: AI training
Implementation: Run code(v0.2.1)Implementation: Web access(v0.2.1)
- Plugins: Compatibility with plugin system
- Tools
Support SERPER apiSupport Selenium apisSupport Playwright apis
- Roles
- Perfect the action pool/skill pool for each role
- Red Book blogger
- E-commerce seller
- Data analyst (expected v0.6.0)
- News observer
Institutional researcher(v0.2.1)
- Evaluation
- Support an evaluation on a game dataset (experimentation done with game agents)
- Reproduce papers, implement full skill acquisition for a single game role, achieving SOTA results (experimentation done with game agents)
- Support an evaluation on a math dataset (expected v0.6.0)
- Reproduce papers, achieving SOTA results for current mathematical problem solving process
- LLM
- Support Claude underlying API
Support Azure asynchronous API- Support streaming version of all APIs
Make gpt-3.5-turbo available (HARD)
- Other
- Clean up existing unused code
- Unify all code styles and establish contribution standards
- Multi-language support
- Multi-programming-language support