Dynamically switch between LLMs Template

For the Dynamically switch between LLMs Template, automate the handling of customer complaints by dynamically selecting the best AI language model based on user input. This workflow efficiently processes chat messages, generates empathetic responses, and validates the output, ensuring high-quality customer service while minimizing manual intervention.

7/8/2025
22 nodes
Complex
manualcomplexlangchainnoopsticky noteadvancedlogicconditional
Categories:
Complex WorkflowManual Triggered
Integrations:
LangChainNoOpSticky Note

Target Audience

This workflow is designed for:
- Customer Support Teams: To efficiently handle customer complaints and provide timely responses using various language models.
- Developers: Who wish to integrate multiple AI language models dynamically without hardcoding.
- Business Analysts: Looking to analyze sentiment and quality of customer interactions.
- Product Managers: Interested in improving customer satisfaction through automated responses.

Problem Solved

This workflow addresses the challenges of:
- Handling Diverse Customer Complaints: By dynamically selecting the most suitable AI language model to respond to varied customer queries.
- Response Quality Assurance: Ensuring that generated responses meet specific criteria for quality and sentiment.
- Error Management: Providing mechanisms to handle errors gracefully and continue processing without interruption.

Workflow Steps

  • Trigger: The workflow begins when a chat message is received.
    2. Set LLM Index: It initializes the index of the language model to be used.
    3. Generate Response: The workflow generates a response based on the customer’s complaint using the selected AI model.
    4. Validate Response: The generated response is analyzed for quality and sentiment.
    5. Error Checking: The workflow checks for expected errors and handles them appropriately.
    6. Return Result: Finally, the workflow returns the generated response or an error message if applicable.

    • Customization Guide

    Users can customize this workflow by:
    - Adding New Language Models: Integrate additional AI models by modifying the 'Switch Model' node to include new options.
    - Adjusting Sentiment Analysis Criteria: Modify the conditions in the 'Validate response' node to fit specific business requirements.
    - Changing Trigger Conditions: Alter the webhook settings in the 'When chat message received' node to suit different platforms or messaging systems.
    - Editing Response Generation Logic: Customize the prompts and messages in the 'Generate response' node to align with brand voice and customer interaction style.