What is BettaFish
BettaFish (Weiyu) is an open-source multi-agent public opinion analysis system that helps users quickly understand public views on events, brands, or products. The system is driven by natural language; users only need to state their needs as if chatting, and the system can automatically complete the collection, analysis, and prediction of public opinion across the entire internet. The system covers 30+ mainstream social media platforms domestically and internationally, features multi-agent collaboration, multimodal parsing, and public-private data fusion, and supports one-click deployment. The project is fully open source and suitable for scenarios such as brand public relations, market analysis, and scientific research.
Main features of BettaFish
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Natural language driven: Users input their needs in a chat-like manner, and the system can automatically complete collection, analysis, and prediction without complex operations.
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Multi-source collection across the entire internet: Covers 30+ mainstream social media platforms domestically and internationally, enabling comprehensive acquisition of public opinion information.
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Multi-agent collaboration: Multiple agents divide work and collaborate, simulating a "forum" for the collision of ideas to improve analysis quality.
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Prediction and decision-making: Predicts public opinion trends based on semantic analysis and popularity indices, and generates professional reports to assist decision-making.
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Multimodal capabilities: Deeply parses multimodal content such as images, text, and videos, accurately extracts information, and comprehensively grasps public opinion dynamics.
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Public-private data fusion: Supports seamless integration of internal business databases with public opinion data, providing a more comprehensive analytical perspective.
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Lightweight and highly extensible: Based on a pure Python modular design, supports one-click deployment, and is easy to extend and customize.
How to use BettaFish
- Clone the project and create an environment: From the GitHub repository https://github.com/666ghj/BettaFish clone the BettaFish project locally, create a new Python environment, and install the project dependencies.
- Install dependencies: In the project directory, install the required Python dependency packages, and install the Playwright browser driver to support the crawler functionality.
- Configure the system: Copy
config.py.examplefile asconfig.py, and fill in information such as database configuration and the API key for the LLM (e.g., OpenAI). - Initialize the database: When choosing to use a local database, run the database initialization script; if using a cloud database service, contact the project team to apply for access permission.
- Start the system: After activating the Python environment, start the main BettaFish application and access it through the browser at
http://localhost:5000to use the system.
BettaFish project address
- GitHub repository：https://github.com/666ghj/BettaFish
BettaFish application scenarios
- Brand public relations teams: Brand public relations teams use BettaFish to track feedback across the internet after a new product launch, promptly identify potential negative public opinion, and formulate response strategies in advance.
- Media and research institutions: Media and research institutions can use BettaFish to analyze the dissemination mechanisms of social hot events, gain an in-depth understanding of the dynamic changes in public opinion, and provide data support for reporting and research.
- Product managers/market analysts: Product managers and market analysts use BettaFish to understand users' real needs and pain points, optimize product design and market strategies, and enhance product competitiveness.
- Educational or scientific research purposes: Educators and researchers use BettaFish to study the evolution patterns of social public opinion, changes in language sentiment, etc., providing rich data and analytical tools for academic research in related fields.