{"id":24352153,"url":"https://github.com/cris-m/langgraph_examples","last_synced_at":"2026-02-11T10:01:30.106Z","repository":{"id":273025399,"uuid":"916433801","full_name":"cris-m/langgraph_examples","owner":"cris-m","description":"This repository contains a collection of examples demonstrating the usage of LangGraph in various applications. 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LangGraph is a powerful framework for building dynamic, decision-making workflows with natural language processing capabilities.\n\n---\n\n### **Overview**  \nLangGraph provides a way to model complex conversational flows, manage state, and integrate external tools and APIs seamlessly. The examples in this repository aim to showcase the versatility of LangGraph for different real-world use cases, from personal assistants to privacy-focused agents.  \n\nEach folder represents a different project or example that demonstrates how LangGraph can be combined with various technologies like OpenAI models, audio-based input/output, and external web services.\n\n---\n\n### **Featured Examples**\n\n1. **Voice Agent**  \n   This project demonstrates a voice-based agent that uses:  \n   - **Llama 3.2 (3B)** for natural language understanding (via [Ollama](https://ollama.com/library/llama3.2))  \n   - **[Whisper](https://github.com/openai/whisper)** for local audio transcription  \n   - **[Kokoro](https://huggingface.co/hexgrad/Kokoro-82M)** for local text-to-speech (TTS)  \n   - **DuckDuckGo** for privacy-focused web searches.  \n\n   **Note**: This project runs 100% locally, using open-source models to ensure privacy and control over data.  \n   [Link to Voice Agent Project](https://github.com/cris-m/langraph_examples/blob/main/voice_agent/voice_agent.ipynb)\n\n2. **Vision Agent**  \n   This project showcases a vision-based agent capable of analyzing both text and images. It uses:  \n   - **Llama 3.2 Vision (11B)** via [Ollama](https://ollama.com/library/llama3.2-vision) for multimodal understanding.  \n   - **LangGraph** to dynamically handle workflows and integrate visual and textual data.  \n   - Built-in **image preprocessing**, where images are converted to Base64 strings for seamless compatibility.  \n   - Advanced vision capabilities, including:  \n     - Object detection and scene understanding.  \n     - OCR for extracting text from images.  \n     - Multimodal question answering combining text and visual inputs.  \n\n   **Note**: This project ensures privacy by running all computations locally and leveraging cutting-edge models for visual analysis.  \n   [Link to Vision Agent Project](https://github.com/cris-m/langraph_examples/blob/main/vision_agent/vision_agent.ipynb)\n\n3. **Web Browsing Agent**  \n   This project highlights a web browsing agent capable of navigating websites based on user input. It uses:  \n   - **Llama 3.2 (via [Ollama](https://ollama.com/library/llama3.2))** for natural language understanding and decision-making. \n   - **[Helium](https://github.com/mherrmann/helium)** for lighter web automation with Python.  \n   - **[Selenium](https://selenium-python.readthedocs.io/)** for browser automation.  \n\n   The agent can:\n   - Open a web browser and navigate to specified URLs.  \n   - Perform searches and interact with web elements dynamically.  \n   - Execute tasks entirely on a local machine, ensuring privacy and security.\n\n   **Note**: This project runs 100% locally, leveraging powerful tools for automated web interaction.  \n   [Link to Web Browsing Agent Project](https://github.com/cris-m/langraph_examples/blob/main/web_browsing_agent/web_browsing_agent.ipynb)\n\n4. **Customer Support Call Agent**  \n   A voice-based customer support system that handles incoming phone calls and can transfer to human operators when needed. It uses:  \n   - **LangGraph** for conversation workflow management  \n   - **Twilio** for voice communication platform  \n   - **Anthropic Claude** as the default language model (configurable)  \n   - **HuggingFace** for text embeddings and memory search  \n\n   The agent can:\n   - Process voice calls in real-time and understand customer speech  \n   - Remember previous conversations with the same caller  \n   - Route calls based on customer needs and complexity  \n   - Transfer complex issues to human operators  \n   - Manage call queuing and hold functionality  \n\n   **Note**: This project integrates telephony services with AI to create an intelligent call center system.  \n   [Link to Call Support Agent Project](https://github.com/cris-m/langraph_examples/blob/main/call_support_agent/)\n\n---\n\n### **Future Updates**  \nThis repository will be gradually updated with more examples showcasing the diverse applications of LangGraph. Stay tuned for new projects and enhancements!\n\n---\n\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcris-m%2Flanggraph_examples","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcris-m%2Flanggraph_examples","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcris-m%2Flanggraph_examples/lists"}