📖 Automate Document Q&A with Multi-Agent RAG Orchestration using Contextual AI & Gemini
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Description
PROBLEM
Managing multiple RAG AI agents can be complex when each has its own purpose and vector database.
- Manually tracking agents and deciding which one to query wastes time.
- LLMs often struggle to determine which agent best fits a user’s request.
This workflow enables automated multi-agent orchestration, dynamically selecting and querying the correct agent using Contextual AI Query Tool and Gemini 2.5 Flash.
How it works
- A form trigger allows users to create new agents by specifying a name, description, datastore, and uploading files.
- A new agent is created with the provided information and files are ingested in the datastore
- We get the status of file ingestion every 30 seconds until the ingestion process is complete
- When users send queries, the Agent Orchestrator identifies the most relevant agent to generate grounded, context-aware responses.
Note: The document ingestion process is asynchronous and may take a few minutes before your agent has the document fully available in the datastore for querying.
How to set up
- Create a free Contextual AI account and obtain your
CONTEXTUALAI_API_KEY. - Add
CONTEXTUALAI_API_KEYas an environment variable in n8n. - For the baseline model, we have used Gemini 2.5 Flash Model, you can find your Gemini API key here
How to customize the workflow
- Replace the Form Trigger with a Webhook Trigger or manual input to integrate with custom systems.
- Swap Gemini 2.5 Flash with another LLM provider
- Update the wait time as per user requirement
- Modify the system prompt to fine-tune how the orchestration logic selects and queries agents.
- You can check out this Contextual AI API reference for more details on agent creation and usage.
- If you have feedback or need support, please email feedback@contextual.ai.
🔗 Nodes Used
AI Agent, Simple Memory, n8n Form Trigger, Chat Trigger, Google Gemini Chat Model
📥 Import
Download workflow.json and import into n8n:
Workflow menu → Import from File