<2-3 sentences summarising what the project addresses and solves, the target audience, and the benefit.> OpenPlexity Pages offers an open-source, privacy-focused alternative to Perplexity Pages, designed to transform research into visually appealing, comprehensive articles. It targets educators, researchers, hobbyists, and content creators, enabling them to produce well-structured, up-to-date content while maintaining full data control and customization.

How It Works

This project leverages real-time search results, ensuring content remains current, unlike static embedding-based tools. It facilitates seamless content creation by transforming research into formatted articles, with planned support for local LLMs (Llama3, Mixtral via Ollama). Users can customize content tone and article structure, and integrate AI-generated or custom images, offering a flexible and private research-to-content pipeline.

Quick Start & Requirements

• Requirements: Groq API Key, Serper API Key.
• Installation: Install Poetry (pip install poetry), then run poetry install in the project directory.
• Configuration: Create a .env file in the root with GROQ_API_KEY=<your-groq-api-key>, BASE_URL=https://rentry.co, and SERPER_API_KEY=<your-serper-api-key>.
• Running: Execute poetry run streamlit run openplexity_pages/app.py.
• Documentation: Primary documentation is within the repository's README.

Highlighted Details

• Fully open-source and privacy-focused, running locally.
• Utilizes real-time search results for up-to-date information.
• Supports customizable content tone and article structure.
• Features AI-generated or user-integrated visuals.
• Planned integration for local LLMs (Ollama, Llama3, Mixtral).

Maintenance & Community

The project actively encourages community contributions, with guidelines available in CONTRIBUTING.md. Key contributors include @alxfazio, @mutatedmindcom, and @breezeight. Support the project by starring it on GitHub. No direct links to community channels like Discord or Slack are provided in the README.

Licensing & Compatibility

Licensed under the MIT license, which permits broad use, including commercial applications and integration into closed-source projects.

Limitations & Caveats

The system is not designed for producing publication-ready articles without significant revisions. Local LLM support is a future feature, currently pending. The roadmap indicates ongoing development for image features and document export modalities, suggesting potential incompleteness in these areas.