Flowith
About this Agent
A next-generation AI productivity tool with a two-dimensional canvas interface. Flowith enables multi-threaded, non-linear interaction with multiple AI agents and models in one workspace, aiming to help users achieve a “flow state” for deep work.
Use Case
Complex, multi-step problem solving and knowledge work. Flowith is used for research, brainstorming, learning, or any task where you might want to engage multiple lines of thought. For example, one can use it to gather and organize information (with an AI helping to fetch and summarize content), while another agent writes code or analyzes data – all concurrently on a canvas. It’s like an AI-powered sandbox for projects that involve text, code, and notes together.
Feature
- Canvas UI: Instead of a single chat, you have an infinite canvas where you can spawn multiple chat nodes. This visual layout lets you run parallel conversations or workflows (e.g. one agent writing an essay outline while another debugs code) , and you can see and connect different threads.
- Oracle Mode (Agent): A powerful autonomous agent, “Flowith Oracle,” can plan and execute multi-step tasks automatically
- It does task decomposition, uses tools, self-optimizes, and presents a reasoning chain, much like AutoGPT but more stable. You can give it a complex goal and watch it break it down and solve sub-tasks one by one.
- Knowledge Garden: An integrated knowledge base that users can build. It ingests your files, notes, and URLs, breaks them into “Seeds” of info, and connects them. The AI uses this to give context-aware answers using your data. This is essentially a personal Second Brain for contextual retrieval during chats.
- Multi-Model Support: You can utilize different AI models in different nodes (for instance, use GPT-4 in one conversation and another model in a different thread). Flowith can intelligently select the best model for a task or let you run models concurrently (via tool selection, as hinted in product materials).
- Tool Integrations: Supports using external tools (web search, calculators, etc.) within conversations – the Oracle agent has unlimited tool invocation capability , so it can, for example, call APIs or run Python code if set up.
- Non-linear Workflow: Because of its multi-threaded design, you can organize thoughts, to-dos, and outputs spatially. This makes it easier to handle elaborate projects (e.g. writing a research paper with sections in different nodes, or managing a coding project with separate agents for different functions).
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