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+
+## Roadmap
+
+### Long-term Objective
+
+Enable MetaGPT to self-evolve, accomplishing self-training, fine-tuning, optimization, utilization, and updates.
+
+### Short-term Objective
+
+1. Become the multi-agent framework with the highest ROI.
+2. Support fully automatic implementation of medium-sized projects (around 2000 lines of code).
+3. Implement most identified tasks, reaching version 0.5.
+
+### Tasks
+
+To reach version v0.5, approximately 70% of the following tasks need to be completed.
+
+1. Usability
+   1. Release v0.01 pip package to try to solve issues like npm installation (though not necessarily successfully)
+   2. Support for overall save and recovery of software companies
+   3. Support human confirmation and modification during the process
+   4. Support process caching: Consider carefully whether to add server caching mechanism
+   5. Resolve occasional failure to follow instruction under current prompts, causing code parsing errors, through stricter system prompts
+   6. Write documentation, describing the current features and usage at all levels
+2. Features
+   1. Support a more standard and stable parser (need to analyze the format that the current LLM is better at)
+   2. Establish a separate output queue, differentiated from the message queue
+   3. Attempt to atomize all role work, but this may significantly increase token overhead
+   4. Complete the design and implementation of module breakdown
+   5. Support various modes of memory: clearly distinguish between long-term and short-term memory
+   6. Perfect the test role, and carry out necessary interactions with humans
+   7. Provide full mode instead of the current fast mode, allowing natural communication between roles
+   8. Implement SkillManager and the process of incremental Skill learning
+   9. Automatically get RPM and configure it by calling the corresponding openai page, so that each key does not need to be manually configured
+3. Strategies
+   1. Support ReAct strategy
+   2. Support CoT strategy
+   3. Support ToT strategy
+   4. Support Reflection strategy
+4. Actions
+   1. Implementation: Search
+   2. Implementation: Knowledge search, supporting 10+ data formats
+   3. Implementation: Data EDA
+   4. Implementation: Review
+   5. Implementation: Add Document
+   6. Implementation: Delete Document
+   7. Implementation: Self-training
+   8. Implementation: DebugError
+   9. Implementation: Generate reliable unit tests based on YAPI
+   10. Implementation: Self-evaluation
+   11. Implementation: AI Invocation
+   12. Implementation: Learning and using third-party standard libraries
+   13. Implementation: Data collection
+   14. Implementation: AI training
+   15. Implementation: Run code
+   16. Implementation: Web access
+5. Plugins: Compatibility with plugin system
+6. Roles
+   1. Perfect the action pool/skill pool for each role
+   2. Red Book blogger
+   3. E-commerce seller
+   4. Data analyst
+   5. News observer
+   6. Institutional researcher
+7. Evaluation
+   1. Support an evaluation on a game dataset
+   2. Reproduce papers, implement full skill acquisition for a single game role, achieving SOTA results
+   3. Support an evaluation on a math dataset
+   4. Reproduce papers, achieving SOTA results for current mathematical problem solving process
+8. LLM
+   1. Support Claude underlying API
+   2. Support Azure asynchronous API
+   3. Support streaming version of all APIs
+9. Other
+   1. Clean up existing unused code
+   2. Unify all code styles and establish contribution standards
+   3. Multi-language support