CommandCodeAI / CommandCodeAI/command-code
muse spark 1.3 contributor usage bug
还没有人认领这个 Issue。
- 主要语言
- 没有语言数据
- 星标
- 4k
- 派生
- 350
- PR 合并指标
- 30 天内没有已合并 PR
描述
Summary
I've used muse spark 1.2 contributor and it it'd been the cheapest model to use at command-code, today was charged my go plan and
started to solve some bugs on a project with 1.3 contributor, only with 54.1m tokens I hit my limits, it means I spent 3 credits on only 54m
tokens. The last month I did 1.2b tokens with 10 credits, doing some numbers it means the performance on my go plan is 666% worst. I hope I
get a reset or part of my credits back.
Expected Behavior
with 300k of cache input I was supposed to get 1 billion tokens on muse spark with 3 credits, I only got 55m.
Actual Behavior
Most of the conversation wasn't cached.
Steps to reproduce the issue
Just coding with muse spark 1.3 contributor
Command Code Version
1.46.0
Operating System
Windows
Terminal/IDE
Unknown
Shell
cmd.exe
Session file (optional)
6a9ce306-af51-4823-b044-d6e85a1eabc7.meta.json
command-code-session-6a9ce306.md
I couldn't upload the session as jsonl.
Fix prompt (optional)
No response
Additional context
No response
贡献指南
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从这里开始
- 先读完整个 Issue,再读项目的贡献指南。
- 在 Issue 下留言说明你要接手 —— 这能避免两个人做同样的事。
- Fork 仓库,在一个分支上完成修改。
- 提交 Pull Request,并在描述里引用这个 Issue 编号。
调研方向
首先检查随附的会话元数据和会话记录,然后使用 Command Code 1.46.0、Muse Spark 1.3 Contributor 以及所述的 Windows cmd.exe 环境重现报告的使用情况。将缓存计费、令牌使用量和额度消耗与预期行为进行比较;完成标准是识别出可复现的产品缺陷,或记录说明报告的使用情况为何符合预期。
由索引模型根据 Issue 内容生成。
评估
- 领域
- ai, cli
- Issue 类型
- 缺陷
- 难度
- 4/5
- 预计耗时
- 3-5 天
- 活跃度
- 活跃
- 描述清晰度
- 需要澄清
- 新手友好度
- 28/100