🚀 Litter Spark - AI Research Ideation Enhanced: An Open-Source Framework for Research Idea Generation with Visualized Interface 🌟

News

• Online demo available：spark.simplaj.fun

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Are you ready to revolutionize your research process? Introducing AI Researcher Spark, an upgraded and enhanced version of the research ideation pipeline inspired by Stanford NLP's groundbreaking work. Designed to empower researchers, educators, and students alike, our open-source project seamlessly integrates domestic large language models (compatible with OpenAPI-like platforms) and features a user-friendly, fully visualized interface for effortless use.

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🧠 What is AI Researcher Spark?

AI Researcher Spark takes the research ideation process to a whole new level, building on the original "Research Ideation Agent" pipeline. Whether you're a student brainstorming for your next project or an expert refining innovative ideas, our framework is tailored to provide detailed project proposals that are groundbreaking, executable, and ranked for quality.

💡 Key Features:

• Fully compatible with domestic large language models (e.g., qwen and Doubao) for enhanced accessibility in diverse environments.
• Visualized Interface: A Gradio-powered, easy-to-use GUI that simplifies every step of the research ideation process.
• Seamless integration with OpenAI-like APIs and domestic models for global and local accessibility.
• Modular pipeline design: Use end-to-end or customize each module as standalone tools.
• Comprehensive documentation and ready-to-use scripts to get you started in minutes.

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🔍 What Can You Do with AI Researcher Spark?

🔗 1. Related Paper Search

Effortlessly search for and rank relevant academic papers using advanced retrieval techniques, grounded in your input topic.

💡 2. Grounded Idea Generation

Generate detailed, novel research ideas—grounded in existing literature—with the option to use retrieval-augmented generation (RAG).

✨ 3. Idea Deduplication

Remove redundancy and refine your ideas by leveraging sentence similarity embeddings, ensuring only the most unique ideas make it forward.

📋 4. Project Proposal Generation

Transform research ideas into detailed project proposals, complete with step-by-step plans for implementation.

📊 5. Project Proposal Ranking

Rank your project proposals based on their quality, novelty, and feasibility using state-of-the-art ranking models.

✅ 6. Project Proposal Filtering

Automatically filter proposals for novelty and feasibility to ensure you're working on truly innovative projects.

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🌐 Why Choose AI Researcher Spark?

• Enhanced Compatibility: Fully adapted for domestic large language models, making it suitable for users in regions with limited access to OpenAI APIs.
• Budget-Friendly: Generate high-quality ideas and proposals while optimizing costs for API usage.
• Visualized & Intuitive: No need to navigate complex scripts—our interactive visual interface makes the entire workflow accessible to everyone.
• Research-Driven: Backed by rigorous evaluation with expert reviewers, ensuring ideas generated are novel and actionable.

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💻 Get Started in Minutes

Setting up AI Researcher Spark is simple! Follow these steps to unleash your research potential:

1. Clone the repo and set up the environment:

   git clone https://github.com/YourRepo/AI-Researcher-Spark.git
   cd AI-Researcher-Spark
   conda create -n ai-researcher python=3.10
   conda activate ai-researcher
   pip install -r requirements.txt

2. Configure your API keys in keys.json for seamless integration with models and APIs.

   {
      "api_key": "Your OpenAI-Like API Key",
      "base_url": "Your Base URL (Optional)",
      "organization_id": "Your OpenAI Organization ID (Optional)",
      "s2_key": "Your Semantic Scholar API Key (Optional)",
      "anthropic_key": "Your Anthropic API Key"
   }

3. Launch the visualized interface:

   python app.py

4. Explore, ideate, and innovate!

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🎉 What’s New in AI Researcher Spark?

• Domestic Model Support: Use cutting-edge local models for paper search, idea generation, ranking, and more.
• Visualized Workflow: Fully interactive, easy-to-use Gradio interface for running the entire pipeline or individual modules.
• Optimized for Feasibility: Lower inference costs while ensuring superior output quality.

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📝 Call to Action

⭐ Star this repo to support our open-source initiative!
📢 Spread the word by sharing this project with your peers, teams, and collaborators.
🛠️ Contribute: Got ideas for improvement? We welcome pull requests and feedback!

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📌 Citation

If you find this project useful in your research or workflow, please cite the original paper:

@article{si2024llmideas,
      title={Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers}, 
      author={Chenglei Si and Diyi Yang and Tatsunori Hashimoto},
      year={2024},
      journal={arXiv}
}

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Unlock the next level of research ideation with AI Researcher Spark. Your journey to groundbreaking research starts here. 🚀