🚀 AutoGPT Roadmap - Empowering Agent Builders 👷 #6970
Pwuts
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Objectives 🎯
Background 💡
Turning research into practical applications
We want to enable straightforward building of (experimental) agents. Since the initial publication of AutoGPT, various agent and reasoning paradigms have emerged from experimentation and research. However, few have made it into PoCs with AutoGPT due to integration complexities. By improving the architecture, we can simplify experimentation (through modularity) and speed up building (through reusability of components).
Library code
AutoGPT contains a lot of library code - code that is not specific to our use case but essential for the system’s overall functionality. Whenever feasible, we try to import such code from third-party libraries. If suitable components are not available, it’s sensible to publish our own when we build a custom solution.
Vision 👉🏼
To make the above happen, each subproject in the AutoGPT project will have its own role:
SWOT 🧭
Strengths 💪
Weaknesses 🚧
Opportunities 🚀
Threats⚠️
Related 👪
Actionables
forge.models.config
intoforge.models.config
andforge.models.state
#7000autogpt.core.utils.json_schema
from AutoGPT to Forge #7002autogpt.core.resource.model_provider
from AutoGPT to Forge #7001autogpt.file_storage
functionality from AutoGPT to Forge #7004autogpt.agents.utils.exceptions
autogpt.core.prompting
autogpt.commands
autogpt.logs
autogpt
toforge
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