Reasoning Engine (LangChain on Vertex AI) is a managed service that helps you to build and deploy an agent reasoning framework. It gives you the flexibility to choose how much reasoning you want to delegate to the LLM and how much you want to handle with customized code. You can define Python functions that get used as tools via Gemini Function Calling.
Reasoning Engine integrates closely with the Python SDK for the Gemini model in Vertex AI, and it can manage prompts, agents, and examples in a modular way. Reasoning Engine is compatible with LangChain, LlamaIndex, or other Python frameworks.
| Description | Sample Name |
|---|---|
| Intro to Building and Deploying an Agent with Reasoning Engine in Vertex AI | intro_reasoning_engine.ipynb |
| Debugging and Optimizing Agents: A Guide to Tracing in Reasoning Engine | tracing_agents_in_reasoning_engine.ipynb |
| Building a Conversational Search Agent with Reasoning Engine and RAG on Vertex AI Search | tutorial_vertex_ai_search_rag_agent.ipynb |
| Building and Deploying a Google Maps API Agent with Reasoning Engine | tutorial_google_maps_agent.ipynb |
| Building and Deploying a LangGraph Application with Reasoning Engine in Vertex AI | tutorial_langgraph.ipynb |
| Deploying a RAG Application with AlloyDB with Reasoning Engine | tutorial_alloydb_rag_agent.ipynb |
| Deploying a RAG Application with Cloud SQL for PostgreSQL with Reasoning Engine | tutorial_cloud_sql_pg_rag_agent.ipynb |