https://github.com/sangeetagarwal/ai-agents-langgraph
Become an expert in constructing and refining AI agents. Explore how to create flow-driven applications, employ agentic search methods, and integrate human-in-the-loop systems using the robust components of LangGraph.
https://github.com/sangeetagarwal/ai-agents-langgraph
agent-accuracy agent-components agent-development agentic-search ai-agents ai-enhancements essay-writing-agent flow-based-applications human-in-the-loop langchain langgraph state-management task-division
Last synced: about 2 months ago
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Become an expert in constructing and refining AI agents. Explore how to create flow-driven applications, employ agentic search methods, and integrate human-in-the-loop systems using the robust components of LangGraph.
- Host: GitHub
- URL: https://github.com/sangeetagarwal/ai-agents-langgraph
- Owner: SangeetAgarwal
- Created: 2025-02-02T19:41:47.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-02T19:55:13.000Z (over 1 year ago)
- Last Synced: 2025-03-27T02:51:25.207Z (about 1 year ago)
- Topics: agent-accuracy, agent-components, agent-development, agentic-search, ai-agents, ai-enhancements, essay-writing-agent, flow-based-applications, human-in-the-loop, langchain, langgraph, state-management, task-division
- Language: Python
- Homepage: https://www.deeplearning.ai/short-courses/ai-agents-in-langgraph/
- Size: 3.91 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# [AI Agents in LangGraph](https://www.deeplearning.ai/short-courses/ai-agents-in-langgraph/)
4. **Persistence**: Implement persistence in agents, enabling state management across multiple threads, conversation switching, and the ability to reload previous states.
**Note:** `SqliteSaver.from_conn_string()` is being used as a checkpointer in the course but that is now a context manager so per [github issue](https://github.com/langchain-ai/langgraph/discussions/1696#discussioncomment-10626265) the code has been updated as
```python
with SqliteSaver.from_conn_string(":memory:") as memory:
abot = Agent(model, [tool], system=prompt, checkpointer=memory)
messages = HumanMessage(content="who won the second last soccer world cup?")
...
```
## Credits
**Harrison Chase** is the Co-Founder and CEO of LangChain, bringing extensive expertise in AI and agent systems to guide you through this course.
**Rotem Weiss** is the Co-founder and CEO of Tavily, specializing in AI agent design and implementation, to help you master the use of LangGraph.
🔗 To enroll in the course or for further information, visit [deeplearning.ai](https://www.deeplearning.ai/short-courses/).