Join David Jones-Gilardi as he guides you through using local Ollama models in your agents. Ollama empowers you to run models locally on your machine, offering a secure alternative to public providers like OpenAI. In this tutorial, discover how to set up and use Alibaba's Qwen 2.5 model with Langflow, enabling seamless integration with your applications while ensuring data privacy. Perfect for developers looking to enhance their AI workflows securely!
Resources
Langflow (Open Source): http://www.langflow.org
Ollama (local models): https://ollama.com
Additional Resources:
- DataStax Developer Hub: https://dtsx.io/devhub
- DataStax Blog: https://dtsx.io/howto
- Try Langflow: https://dtsx.io/trylangflow
- Try Astra DB: https://dtsx.io/40kQpI6
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Stay in touch:
- Join our Discord Community: https://discord.gg/datastax
- Follow us on X: https://x.com/DataStaxDevs
Chapters:
00:00:00 | 👋Introduction to Tool Calling with Ollama
00:00:12 | 🤔 Why Use Ollama?
00:00:39 | 🔧Setting Up Qwen 2.5 Model
00:01:54 | 🌐Using Langflow with Ollama
00:03:12 | 🔄 Converting OpenAI to Ollama
00:03:25 | ⚙️Configuring Custom Model in Langflow
00:05:18 | 🚀 Running Queries with Qwen 2.5
00:05:57 | ⏱️ Performance Considerations for Local Models
00:07:12 | 🔑 Final Tips and API Integration
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#Ollama #LocalModels #Langflow #AI #DataPrivacy #ToolCalling #QwenModel #DeveloperTutorial #SecureAI
