PaperBanana-CN

io.github.mituan-ai由 GitHub 帳號 mituan-ai 發布v2.0.1更新於 Nov 3, 2026

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

已驗證STDIO僅桌面資料與分析媒體與設計

概覽

AI 產生的概覽

依研究描述產生學術方法示意圖,並依 CSV 或 JSON 資料產生統計圖,VLM 與影像生成服務可分開設定。

可以做什麼
  • 依方法文字與圖說產生方法示意圖,可選擇長寬比、解析度與輸出格式
  • 依 CSV 或 JSON 資料產生統計圖
  • 評估生成圖表的品質,並接續已儲存的執行
  • 執行整篇論文編排、批次產生與參數掃描
  • 不需任何模型連線即可進行多面板拼圖與瀏覽歷史執行
適用情境
適合在撰寫論文或報告時,讓助理草擬架構/方法示意圖或資料圖表,或批次產生並評估多個圖表版本。它偏向桌面使用,較適合本機研究工作流程,而非無介面的伺服器環境。
執行需求
透過 uvx 以 stdio 在本機執行,需要 Python 3.10-3.12 與 uv;Studio 介面需要桌面瀏覽器。統計圖與品質評估需要 VLM 連線,方法示意圖還需要影像生成連線;每個連線需分別填寫協定、Base URL、API key、模型名稱與逾時。清單未宣告任何憑證。
安裝前請注意
需自行提供外部模型服務的 API key,金鑰會存在連線設定中,方法文字、圖說與資料會傳送給這些服務商;生成會消耗付費額度。修改已儲存的連線不會自動啟用,API key 留空則沿用已存金鑰。本專案為非官方社群實作,與上游作者無隸屬關係。

安裝

在 SourceWeft 中

  1. 開啟 儀表板中的 PaperBanana-CN,將其新增到工作區。
  2. 為需要使用其工具的對話啟用該服務。

Desktop only,透過 STDIO。 STDIO 服務會啟動本機處理程序,因此需要 SourceWeft 桌面主機。

其他 MCP 客戶端

參照 儲存庫 中的啟動說明。

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]

來源:README.md,提交 5f701ec

工具

0
SourceWeft 尚未在沙箱中啟動過該軟體包,因此其工具未知。

版本歷史

1
  1. v2.0.1最新Sep 16, 2026

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