Skip to main content

Bart.dIAs is an assistant for the WebGRIPP environment, focused on parallel programming analysis.

Project description

Bart.dIAs - WebGRIPP AI Assistant

Bart.dIAs is an assistant for the WebGRIPP environment. Currently, it is solely an assistant for parallel programming that analyzes sequential code to identify bottlenecks and suggest parallelization strategies. It combines critical path analysis with pattern recognition to provide targeted recommendations for improving application performance.

Features

  • Bottleneck Analysis: Identifies sequential bottlenecks in Python code.
  • 🔄 Parallelization Strategies: Suggests strategies to parallelize code using recognized patterns.
  • 🎯 Critical Path Analysis: Combines CPA with pattern recognition for targeted recommendations.
  • 🤖 LLM Chat: Conversational interface to discuss code optimizations.
  • 📎 Code Context: Analyze open files directly from JupyterLab.

Prerequisites

  • JupyterLab 4.x
  • Node.js 18+
  • Ollama running locally (default: http://localhost:11434)
  • Bart.dIAs MCP Server (for deep code analysis)

Installation

1. Install Dependencies

cd bart_dias_jupyter_extension
jlpm install

2. Build Extension

jlpm build

3. Install in JupyterLab

jupyter labextension install .

Usage

  1. Open the Bart.dIAs extension from the right sidebar.
  2. Open a Python file you want to analyze.
  3. Click the attach button (📎) to send the code to the assistant.
  4. Ask for parallelization suggestions or performance analysis.

Project Structure

bart_dias_jupyter_extension/
├── src/                    # Frontend (React/TypeScript)
│   ├── index.ts            # Extension entry point
│   ├── components/         # UI Components
│   ├── services/           # API & MCP logic
│   └── hooks/              # State management
├── style/                  # CSS Styles
└── pyproject.toml          # Python Packaging

Technology Stack

  • Frontend: React 18, TypeScript, Lumino
  • Analysis: LangChain, MCP Adapters
  • AI: Ollama (Local LLMs)

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

bart_dias_jupyter_extension-0.1.6.tar.gz (2.2 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

bart_dias_jupyter_extension-0.1.6-py3-none-any.whl (1.5 MB view details)

Uploaded Python 3

File details

Details for the file bart_dias_jupyter_extension-0.1.6.tar.gz.

File metadata

File hashes

Hashes for bart_dias_jupyter_extension-0.1.6.tar.gz
Algorithm Hash digest
SHA256 eb06abf791566a3360b923370dcc647ed14420875c0183f57525d421978c01ae
MD5 2a644c4a89125f5ff9db69cfdac420d3
BLAKE2b-256 6bd04132a2a1470a4dbc6a7a55151d30b860cad0fc2243a396708357649d3975

See more details on using hashes here.

File details

Details for the file bart_dias_jupyter_extension-0.1.6-py3-none-any.whl.

File metadata

File hashes

Hashes for bart_dias_jupyter_extension-0.1.6-py3-none-any.whl
Algorithm Hash digest
SHA256 9a34b816834d47264c659723a99fccc5378a07f824c7eb27bfc66d14337aeb54
MD5 8fd95cb654f8937482bbac09cb6c8ac3
BLAKE2b-256 b7bc99623c3d2b82a5272b16104627ac50fd54bb12e8f6a81db1665f34895928

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page