
trendFinder
Stay on top of trending topics on social media and the web with AI
Stars: 2152

Trend Finder is a tool designed to help users stay updated on trending topics on social media by collecting and analyzing posts from key influencers. It sends Slack notifications when new trends or product launches are detected, saving time, keeping users informed, and enabling quick responses to emerging opportunities. The tool features AI-powered trend analysis, social media and website monitoring, instant Slack notifications, and scheduled monitoring using cron jobs. Built with Node.js and Express.js, Trend Finder integrates with Together AI, Twitter/X API, Firecrawl, and Slack Webhooks for notifications.
README:
Stay on top of trending topics on social media — all in one place.
Trend Finder collects and analyzes posts from key influencers, then sends a Slack notification when it detects new trends or product launches. This has been a complete game-changer for the Firecrawl marketing team by:
- Saving time normally spent manually searching social channels
- Keeping you informed of relevant, real-time conversations
- Enabling rapid response to new opportunities or emerging industry shifts
Spend less time hunting for trends and more time creating impactful campaigns.
-
Data Collection 📥
- Monitors selected influencers' posts on Twitter/X using the X API (Warning: the X API free plan is rate limited to only monitor 1 X account every 15 min)
- Monitors websites for new releases and news with Firecrawl's /extract
- Runs on a scheduled basis using cron jobs
-
AI Analysis 🧠
- Processes collected content through Together AI
- Identifies emerging trends, releases, and news.
- Analyzes sentiment and relevance
-
Notification System 📢
- When significant trends are detected, sends Slack notifications based on cron job setup
- Provides context about the trend and its sources
- Enables quick response to emerging opportunities
- 🤖 AI-powered trend analysis using Together AI
- 📱 Social media monitoring (Twitter/X integration)
- 🔍 Website monitoring with Firecrawl
- 💬 Instant Slack notifications
- ⏱️ Scheduled monitoring using cron jobs
- Runtime: Node.js with TypeScript
- Framework: Express.js
- AI/ML: Together AI
-
Data Sources:
- Twitter/X API
- Firecrawl
- Notifications: Slack Webhooks
- Scheduling: node-cron
-
Development:
- nodemon for hot reloading
- TypeScript for type safety
- Express async handler for error management
- Node.js (v14 or higher)
- npm or yarn
- Docker
- Docker Compose
- Slack workspace with webhook permissions
- API keys for required services
Copy .env.example
to .env
and configure the following variables:
# Required: API key from Together AI for trend analysis (https://www.together.ai/)
TOGETHER_API_KEY=your_together_api_key_here
# Required if monitoring web pages (https://www.firecrawl.dev/)
FIRECRAWL_API_KEY=your_firecrawl_api_key_here
# Required if monitoring Twitter/X trends (https://developer.x.com/)
X_API_BEARER_TOKEN=your_twitter_api_bearer_token_here
# Required: Incoming Webhook URL from Slack for notifications
SLACK_WEBHOOK_URL=https://hooks.slack.com/services/YOUR/WEBHOOK/URL
-
Clone the repository:
git clone [repository-url] cd trend-finder
-
Install dependencies:
npm install
-
Configure environment variables:
cp .env.example .env # Edit .env with your configuration
-
Run the application:
# Development mode with hot reloading npm run start # Build for production npm run build
-
Build the Docker image:
docker build -t trend-finder .
-
Run the Docker container:
docker run -d -p 3000:3000 --env-file .env trend-finder
-
Start the application with Docker Compose:
docker-compose up --build -d
-
Stop the application with Docker Compose:
docker-compose down
trend-finder/
├── src/
│ ├── controllers/ # Request handlers
│ ├── services/ # Business logic
│ └── index.ts # Application entry point
├── .env.example # Environment variables template
├── package.json # Dependencies and scripts
└── tsconfig.json # TypeScript configuration
- Fork the repository
- Create your feature branch (
git checkout -b feature/amazing-feature
) - Commit your changes (
git commit -m 'Add some amazing feature'
) - Push to the branch (
git push origin feature/amazing-feature
) - Open a Pull Request
For Tasks:
Click tags to check more tools for each tasksFor Jobs:
Alternative AI tools for trendFinder
Similar Open Source Tools

trendFinder
Trend Finder is a tool designed to help users stay updated on trending topics on social media by collecting and analyzing posts from key influencers. It sends Slack notifications when new trends or product launches are detected, saving time, keeping users informed, and enabling quick responses to emerging opportunities. The tool features AI-powered trend analysis, social media and website monitoring, instant Slack notifications, and scheduled monitoring using cron jobs. Built with Node.js and Express.js, Trend Finder integrates with Together AI, Twitter/X API, Firecrawl, and Slack Webhooks for notifications.

WatermarkRemover-AI
WatermarkRemover-AI is an advanced application that utilizes AI models for precise watermark detection and seamless removal. It leverages Florence-2 for watermark identification and LaMA for inpainting. The tool offers both a command-line interface (CLI) and a PyQt6-based graphical user interface (GUI), making it accessible to users of all levels. It supports dual modes for processing images, advanced watermark detection, seamless inpainting, customizable output settings, real-time progress tracking, dark mode support, and efficient GPU acceleration using CUDA.

minefield
BitBom Minefield is a tool that uses roaring bit maps to graph Software Bill of Materials (SBOMs) with a focus on speed, air-gapped operation, scalability, and customizability. It is optimized for rapid data processing, operates securely in isolated environments, supports millions of nodes effortlessly, and allows users to extend the project without relying on upstream changes. The tool enables users to manage and explore software dependencies within isolated environments by offline processing and analyzing SBOMs.

meeting-minutes
An open-source AI assistant for taking meeting notes that captures live meeting audio, transcribes it in real-time, and generates summaries while ensuring user privacy. Perfect for teams to focus on discussions while automatically capturing and organizing meeting content without external servers or complex infrastructure. Features include modern UI, real-time audio capture, speaker diarization, local processing for privacy, and more. The tool also offers a Rust-based implementation for better performance and native integration, with features like live transcription, speaker diarization, and a rich text editor for notes. Future plans include database connection for saving meeting minutes, improving summarization quality, and adding download options for meeting transcriptions and summaries. The backend supports multiple LLM providers through a unified interface, with configurations for Anthropic, Groq, and Ollama models. System architecture includes core components like audio capture service, transcription engine, LLM orchestrator, data services, and API layer. Prerequisites for setup include Node.js, Python, FFmpeg, and Rust. Development guidelines emphasize project structure, testing, documentation, type hints, and ESLint configuration. Contributions are welcome under the MIT License.

miner-release
Heurist Miner is a tool that allows users to contribute their GPU for AI inference tasks on the Heurist network. It supports dual mining capabilities for image generation models and Large Language Models, offers flexible setup on Windows or Linux with multiple GPUs, ensures secure rewards through a dual-wallet system, and is fully open source. Users can earn rewards by hosting AI models and supporting applications in the Heurist ecosystem.

CortexON
CortexON is an open-source, multi-agent AI system designed to automate and simplify everyday tasks. It integrates specialized agents like Web Agent, File Agent, Coder Agent, Executor Agent, and API Agent to accomplish user-defined objectives. CortexON excels at executing complex workflows, research tasks, technical operations, and business process automations by dynamically coordinating the agents' unique capabilities. It offers advanced research automation, multi-agent orchestration, integration with third-party APIs, code generation and execution, efficient file and data management, and personalized task execution for travel planning, market analysis, educational content creation, and business intelligence.

Groqqle
Groqqle 2.1 is a revolutionary, free AI web search and API that instantly returns ORIGINAL content derived from source articles, websites, videos, and even foreign language sources, for ANY target market of ANY reading comprehension level! It combines the power of large language models with advanced web and news search capabilities, offering a user-friendly web interface, a robust API, and now a powerful Groqqle_web_tool for seamless integration into your projects. Developers can instantly incorporate Groqqle into their applications, providing a powerful tool for content generation, research, and analysis across various domains and languages.

CrewAI-Studio
CrewAI Studio is an application with a user-friendly interface for interacting with CrewAI, offering support for multiple platforms and various backend providers. It allows users to run crews in the background, export single-page apps, and use custom tools for APIs and file writing. The roadmap includes features like better import/export, human input, chat functionality, automatic crew creation, and multiuser environment support.

SynthLang
SynthLang is a tool designed to optimize AI prompts by reducing costs and improving processing speed. It brings academic rigor to prompt engineering, creating precise and powerful AI interactions. The tool includes core components like a Translator Engine, Performance Optimization, Testing Framework, and Technical Architecture. It offers mathematical precision, academic rigor, enhanced security, a modern interface, and instant testing. Users can integrate mathematical frameworks, model complex relationships, and apply structured prompts to various domains. Security features include API key management and data privacy. The tool also provides a CLI for prompt engineering and optimization capabilities.

web-ui
WebUI is a user-friendly tool built on Gradio that enhances website accessibility for AI agents. It supports various Large Language Models (LLMs) and allows custom browser integration for seamless interaction. The tool eliminates the need for re-login and authentication challenges, offering high-definition screen recording capabilities.

Visionatrix
Visionatrix is a project aimed at providing easy use of ComfyUI workflows. It offers simplified setup and update processes, a minimalistic UI for daily workflow use, stable workflows with versioning and update support, scalability for multiple instances and task workers, multiple user support with integration of different user backends, LLM power for integration with Ollama/Gemini, and seamless integration as a service with backend endpoints and webhook support. The project is approaching version 1.0 release and welcomes new ideas for further implementation.

Vodalus-Expert-LLM-Forge
Vodalus Expert LLM Forge is a tool designed for crafting datasets and efficiently fine-tuning models using free open-source tools. It includes components for data generation, LLM interaction, RAG engine integration, model training, fine-tuning, and quantization. The tool is suitable for users at all levels and is accompanied by comprehensive documentation. Users can generate synthetic data, interact with LLMs, train models, and optimize performance for local execution. The tool provides detailed guides and instructions for setup, usage, and customization.

probe
Probe is an AI-friendly, fully local, semantic code search tool designed to power the next generation of AI coding assistants. It combines the speed of ripgrep with the code-aware parsing of tree-sitter to deliver precise results with complete code blocks, making it perfect for large codebases and AI-driven development workflows. Probe is fully local, keeping code on the user's machine without relying on external APIs. It supports multiple languages, offers various search options, and can be used in CLI mode, MCP server mode, AI chat mode, and web interface. The tool is designed to be flexible, fast, and accurate, providing developers and AI models with full context and relevant code blocks for efficient code exploration and understanding.

ai-flow
AI Flow is an open-source, user-friendly UI application that empowers you to seamlessly connect multiple AI models together, specifically leveraging the capabilities of multiples AI APIs such as OpenAI, StabilityAI and Replicate. In a nutshell, AI Flow provides a visual platform for crafting and managing AI-driven workflows, thereby facilitating diverse and dynamic AI interactions.

swift-chat
SwiftChat is a fast and responsive AI chat application developed with React Native and powered by Amazon Bedrock. It offers real-time streaming conversations, AI image generation, multimodal support, conversation history management, and cross-platform compatibility across Android, iOS, and macOS. The app supports multiple AI models like Amazon Bedrock, Ollama, DeepSeek, and OpenAI, and features a customizable system prompt assistant. With a minimalist design philosophy and robust privacy protection, SwiftChat delivers a seamless chat experience with various features like rich Markdown support, comprehensive multimodal analysis, creative image suite, and quick access tools. The app prioritizes speed in launch, request, render, and storage, ensuring a fast and efficient user experience. SwiftChat also emphasizes app privacy and security by encrypting API key storage, minimal permission requirements, local-only data storage, and a privacy-first approach.
For similar tasks

nlp-llms-resources
The 'nlp-llms-resources' repository is a comprehensive resource list for Natural Language Processing (NLP) and Large Language Models (LLMs). It covers a wide range of topics including traditional NLP datasets, data acquisition, libraries for NLP, neural networks, sentiment analysis, optical character recognition, information extraction, semantics, topic modeling, multilingual NLP, domain-specific LLMs, vector databases, ethics, costing, books, courses, surveys, aggregators, newsletters, papers, conferences, and societies. The repository provides valuable information and resources for individuals interested in NLP and LLMs.

adata
AData is a free and open-source A-share database that focuses on transaction-related data. It provides comprehensive data on stocks, including basic information, market data, and sentiment analysis. AData is designed to be easy to use and integrate with other applications, making it a valuable tool for quantitative trading and AI training.

PIXIU
PIXIU is a project designed to support the development, fine-tuning, and evaluation of Large Language Models (LLMs) in the financial domain. It includes components like FinBen, a Financial Language Understanding and Prediction Evaluation Benchmark, FIT, a Financial Instruction Dataset, and FinMA, a Financial Large Language Model. The project provides open resources, multi-task and multi-modal financial data, and diverse financial tasks for training and evaluation. It aims to encourage open research and transparency in the financial NLP field.

hezar
Hezar is an all-in-one AI library designed specifically for the Persian community. It brings together various AI models and tools, making it easy to use AI with just a few lines of code. The library seamlessly integrates with Hugging Face Hub, offering a developer-friendly interface and task-based model interface. In addition to models, Hezar provides tools like word embeddings, tokenizers, feature extractors, and more. It also includes supplementary ML tools for deployment, benchmarking, and optimization.

text-embeddings-inference
Text Embeddings Inference (TEI) is a toolkit for deploying and serving open source text embeddings and sequence classification models. TEI enables high-performance extraction for popular models like FlagEmbedding, Ember, GTE, and E5. It implements features such as no model graph compilation step, Metal support for local execution on Macs, small docker images with fast boot times, token-based dynamic batching, optimized transformers code for inference using Flash Attention, Candle, and cuBLASLt, Safetensors weight loading, and production-ready features like distributed tracing with Open Telemetry and Prometheus metrics.

CodeProject.AI-Server
CodeProject.AI Server is a standalone, self-hosted, fast, free, and open-source Artificial Intelligence microserver designed for any platform and language. It can be installed locally without the need for off-device or out-of-network data transfer, providing an easy-to-use solution for developers interested in AI programming. The server includes a HTTP REST API server, backend analysis services, and the source code, enabling users to perform various AI tasks locally without relying on external services or cloud computing. Current capabilities include object detection, face detection, scene recognition, sentiment analysis, and more, with ongoing feature expansions planned. The project aims to promote AI development, simplify AI implementation, focus on core use-cases, and leverage the expertise of the developer community.

spark-nlp
Spark NLP is a state-of-the-art Natural Language Processing library built on top of Apache Spark. It provides simple, performant, and accurate NLP annotations for machine learning pipelines that scale easily in a distributed environment. Spark NLP comes with 36000+ pretrained pipelines and models in more than 200+ languages. It offers tasks such as Tokenization, Word Segmentation, Part-of-Speech Tagging, Named Entity Recognition, Dependency Parsing, Spell Checking, Text Classification, Sentiment Analysis, Token Classification, Machine Translation, Summarization, Question Answering, Table Question Answering, Text Generation, Image Classification, Image to Text (captioning), Automatic Speech Recognition, Zero-Shot Learning, and many more NLP tasks. Spark NLP is the only open-source NLP library in production that offers state-of-the-art transformers such as BERT, CamemBERT, ALBERT, ELECTRA, XLNet, DistilBERT, RoBERTa, DeBERTa, XLM-RoBERTa, Longformer, ELMO, Universal Sentence Encoder, Llama-2, M2M100, BART, Instructor, E5, Google T5, MarianMT, OpenAI GPT2, Vision Transformers (ViT), OpenAI Whisper, and many more not only to Python and R, but also to JVM ecosystem (Java, Scala, and Kotlin) at scale by extending Apache Spark natively.

scikit-llm
Scikit-LLM is a tool that seamlessly integrates powerful language models like ChatGPT into scikit-learn for enhanced text analysis tasks. It allows users to leverage large language models for various text analysis applications within the familiar scikit-learn framework. The tool simplifies the process of incorporating advanced language processing capabilities into machine learning pipelines, enabling users to benefit from the latest advancements in natural language processing.
For similar jobs

Twitter Personality is a web application that analyzes Twitter handles to create personalized personality profiles using Wordware AI Agent. It leverages cutting-edge AI technologies to provide unique insights into Twitter personas. The project allows users to explore the AI agent and prompts through a web interface.

trendFinder
Trend Finder is a tool designed to help users stay updated on trending topics on social media by collecting and analyzing posts from key influencers. It sends Slack notifications when new trends or product launches are detected, saving time, keeping users informed, and enabling quick responses to emerging opportunities. The tool features AI-powered trend analysis, social media and website monitoring, instant Slack notifications, and scheduled monitoring using cron jobs. Built with Node.js and Express.js, Trend Finder integrates with Together AI, Twitter/X API, Firecrawl, and Slack Webhooks for notifications.

hyperfy
Hyperfy is a powerful tool for automating social media marketing tasks. It provides a user-friendly interface to schedule posts, analyze performance metrics, and engage with followers across multiple platforms. With Hyperfy, users can save time and effort by streamlining their social media management processes in one centralized platform.

LLMStack
LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots. It allows users to connect their own data, internal tools, and GPT-powered models without any coding experience. LLMStack can be deployed to the cloud or on-premise and can be accessed via HTTP API or triggered from Slack or Discord.

daily-poetry-image
Daily Chinese ancient poetry and AI-generated images powered by Bing DALL-E-3. GitHub Action triggers the process automatically. Poetry is provided by Today's Poem API. The website is built with Astro.

exif-photo-blog
EXIF Photo Blog is a full-stack photo blog application built with Next.js, Vercel, and Postgres. It features built-in authentication, photo upload with EXIF extraction, photo organization by tag, infinite scroll, light/dark mode, automatic OG image generation, a CMD-K menu with photo search, experimental support for AI-generated descriptions, and support for Fujifilm simulations. The application is easy to deploy to Vercel with just a few clicks and can be customized with a variety of environment variables.

SillyTavern
SillyTavern is a user interface you can install on your computer (and Android phones) that allows you to interact with text generation AIs and chat/roleplay with characters you or the community create. SillyTavern is a fork of TavernAI 1.2.8 which is under more active development and has added many major features. At this point, they can be thought of as completely independent programs.

Twitter-Insight-LLM
This project enables you to fetch liked tweets from Twitter (using Selenium), save it to JSON and Excel files, and perform initial data analysis and image captions. This is part of the initial steps for a larger personal project involving Large Language Models (LLMs).