Tencent / Tencent/WeSmartFlow

Local small models need a lighter agent mode

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Dominant language
Python
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Description

I tried running with a smaller local model. Normal chat was okay, but multi-step ReAct/tool calling became fragile pretty quickly. A lightweight mode that uses fewer tool rounds and falls back to plain explanation when parsing fails would make local deployment much more practical.

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Research direction

No files or tests are identified in the issue. Start by locating the agent and tool-calling entry points, then trace how parsing failures are handled. Done should mean a lightweight mode limits tool rounds and falls back to a plain explanation when parsing fails.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
ai
Issue type
Feature
Difficulty
4/5
Estimated time
3-5 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
45/100

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