PaperBanana-CN

io.github.mituan-ai由 GitHub 账号 mituan-ai 发布v2.0.1更新于 Nov 3, 2026

Generate and evaluate academic diagrams and plots with independent model connections.

已验证STDIO仅桌面数据与分析媒体与设计

概览

AI 生成的概览

根据研究描述生成学术方法示意图,并根据 CSV 或 JSON 数据生成统计图,VLM 与图像生成服务可分别配置。

可以做什么
  • 根据方法文本与图注生成方法示意图,可选择宽高比、分辨率和输出格式
  • 根据 CSV 或 JSON 数据生成统计图
  • 评估生成图的质量,并继续已保存的运行
  • 执行整篇论文编排、批量生成与参数扫描
  • 无需任何模型连接即可进行多面板拼图与历史运行浏览
适用场景
适合在撰写论文或报告时,让助手起草架构/方法示意图或数据图表,或批量生成并评估多个图版本。它偏向桌面使用,更适合本地研究工作流而非无头服务器环境。
运行要求
通过 uvx 以 stdio 在本地运行,需要 Python 3.10-3.12 与 uv;Studio 界面需要桌面浏览器。统计图与质量评估需要 VLM 连接,方法示意图还需图像生成连接;每个连接需单独填写协议、Base URL、API key、模型名和超时。清单未声明任何凭据。
安装前请注意
需要自行提供外部模型服务的 API key,密钥保存在连接配置中,方法文本、图注和数据会发送给这些服务商;生成会消耗付费额度。修改已保存的连接不会自动启用,API key 留空则沿用已存密钥。该项目为非官方社区实现,与上游作者无隶属关系。

安装

在 SourceWeft 中

  1. 打开 控制台中的 PaperBanana-CN,将其添加到工作区。
  2. 为需要使用其工具的对话启用该服务。

Desktop only,通过 STDIO。 STDIO 服务会启动本地进程,因此需要 SourceWeft 桌面宿主。

其他 MCP 客户端

参照 仓库 中的启动说明。

README

English · 简体中文

[PaperBanana-CN scientific figure workbench with a generated multimodal fault-diagnosis figure]

PaperBanana-CN generates methodology diagrams from research descriptions and statistical plots from CSV or JSON data. It uses the PaperBanana scientific workflow and adds separate VLM and image-service connections, a Chinese Studio interface, and explicit aspect-ratio and resolution controls.

[Launch Studio] [Install from PyPI]

[CI status] [Package version 2.0.1] [MIT License]

One run from input to figure

[A PaperBanana-CN Studio run progressing from configured inputs to a completed scientific figure]

The recording follows a methodology-diagram run from submitted inputs to the completed result.

Before you start

You need Python 3.10-3.12, uv, and a desktop browser.

TaskRequired model connections
Methodology diagramVLM and image generation
Statistical plotVLM only
Multi-panel composition and run browsingNone

Each connection specifies its own protocol, Base URL, API key, model name, and timeout. The VLM and image roles may use the same service or two different services.

Quick start

1. Launch Studio

bash
uvx paperbanana-cn studio

Open http://127.0.0.1:7860. uvx runs the package in an isolated environment and does not modify Debian or Ubuntu's system Python.

2. Add the model connections

Open Settings → VLM connection, fill in the service fields, and select Save and use. Repeat under Image connection before generating a methodology diagram.

Editing a saved connection does not activate it. An empty API-key field keeps the stored key. Studio does not fill stored keys back into the browser.

Connection manager screenshot and protocol notes

[PaperBanana-CN connection manager with separate fields for a VLM service]

The connection guide lists the supported protocols, credential storage rules, connection tests, and legacy mode.

3. Generate a figure

Open Methodology diagram, provide the method content and figure caption, then choose an aspect ratio, resolution, and output format.

The same task from the CLI:

bash
paperbanana-cn generate \  --input method.txt \  --caption "Overview of the proposed architecture" \  --aspect-ratio 16:9 \  --resolution 2K \  --format png

What PaperBanana-CN adds

Separate VLM and image connections

The two model roles have independent protocol, Base URL, API key, model, and timeout settings. Studio, CLI, and MCP resolve the same saved connections. Saved profiles contain credential references; API keys remain outside the repository and run metadata.

Official APIs, OpenAI-compatible services, and Gemini-compatible services are supported. Provider specifics stay in the adapters rather than the scientific workflow.

Chinese and English Studio

The Studio interface, help text, validation, progress messages, and errors are available in Chinese and English. Changing the interface language does not rewrite prompts, paper text, or labels inside the generated figure.

Aspect ratios and resolution

Supported aspect ratios:

1:1 · 4:3 · 3:2 · 5:4 · 16:9 · 21:9 · 4:5 · 3:4 · 2:3 · 9:16

Resolution tiers:

1K · 2K · 4K

Studio shows the request size or provider-native tier before generation. If an adapter cannot produce the selected combination, validation stops the request and reports the unsupported option.

Studio workflows

AreaWorkflowModel connections
CreateMethodology diagramVLM and image
CreateStatistical plotVLM
ImproveContinue a saved runDepends on the saved run
ImproveQuality evaluationVLM
AutomateFull-paper orchestrationVLM and image
AutomateBatch generationDepends on the task type
AutomateParameter sweepVLM and image
ToolsMulti-panel compositionNone
ToolsRun browserNone

[PaperBanana-CN methodology-diagram workspace with task inputs and a completed result]

Methodology-diagram workspace

[PaperBanana-CN statistical-plot workspace with CSV input and a completed line chart]

Statistical-plot workspace using synthetic demonstration data

CLI, MCP, Docker, and Colab

Entry pointCommand or link
Studiopaperbanana-cn studio
CLIpaperbanana-cn generate --help
MCP serverpaperbanana-cn mcp
GitHub ActionAction reference
Dockerghcr.io/mituan-ai/paperbanana-cn:2.0.1
ColabQuickstart notebook
MCP client configuration
json
{  "mcpServers": {    "paperbanana-cn": {      "command": "uvx",      "args": ["paperbanana-cn", "mcp"]    }  }}

The server provides 11 tools and reads the same active connections as Studio and CLI. See the MCP guide for the tool list and arguments.

Docker
bash
docker run --rm -p 7860:7860 \  -v paperbanana-cn-config:/home/paperbanana/.config/paperbanana-cn \  -v paperbanana-cn-data:/home/paperbanana/.local/share/paperbanana-cn \  -v paperbanana-cn-outputs:/work/outputs \  ghcr.io/mituan-ai/paperbanana-cn:2.0.1 \  studio --host 0.0.0.0
Permanent install, source setup, and optional providers

Install the command in a uv-managed environment:

bash
uv tool install paperbanana-cnpaperbanana-cn studio

Run the current source checkout:

bash
git clone https://github.com/mituan-ai/PaperBanana-CN.gitcd PaperBanana-CNuv syncuv run paperbanana-cn studio

The default package includes Studio, MCP, PDF input, OpenAI-compatible services, and Gemini.

Optional adapterInstall
AWS Bedrockuv tool install "paperbanana-cn[bedrock]"
Anthropicuv tool install "paperbanana-cn[anthropic]"
LiteLLMuv tool install "paperbanana-cn[litellm]"
All optional providersuv tool install "paperbanana-cn[all-providers]"

For CI, use paperbanana-cn connections add --api-key-env ENV_VAR so the key is read from an environment variable instead of a command-line value.

V1 and upstream

V2 is maintained on main as the paperbanana-cn distribution, the paperbanana_cn Python module, and the paperbanana-cn command.

The scientific figure-generation core is based on llmsresearch/paperbanana. PaperBanana-CN is an unofficial community implementation and is not affiliated with or endorsed by the upstream authors.

Community

PaperBanana-CN is maintained by mituan under the MIT License.

Development checks
bash
git clone https://github.com/mituan-ai/PaperBanana-CN.gitcd PaperBanana-CNuv sync --extra devuv run pytest tests/ -quv run ruff check paperbanana_cn/ mcp_server/ tests/ scripts/

Do not upload API keys, private relay URLs, unpublished papers, private datasets, local connection stores, or generated run directories.

Star history

[Star History Chart]

来源:README.md,提交 5f701ec

工具

0
SourceWeft 尚未在沙箱中启动过该软件包,因此其工具未知。

版本历史

1
  1. v2.0.1最新Sep 16, 2026

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