Key Parameters in Models Configuration
1. Temperature
The Temperature parameter controls the creativity of the chatbot’s responses:- Lower Values (0–0.3): Generate precise, fact-based, and deterministic answers.
 - Higher Values (0.7–1.0): Produce creative, varied, and open-ended responses.
 
- Customer Support: Set the temperature to 
0.2for factual and consistent responses. - Creative Tasks: Set the temperature to 
0.8for generating innovative ideas or content. 
2. Max Tokens
The Max Tokens parameter limits the length of the chatbot’s response.- A higher token limit allows for detailed answers.
 - A lower token limit ensures concise and to-the-point responses.
 
- Summaries: Limit tokens to 
100for short summaries. - Detailed Explanations: Increase the limit to 
500for in-depth explanations. 
3. Rewind Level
The Rewind Level determines how far back the chatbot can reference previous nodes in the flow:- Level 0: No rewind, the chatbot only considers the current node.
 - Level 1–3: The chatbot can reference up to 3 previous nodes for additional context.
 
- Error Handling: Set the rewind level to 
1to retry failed actions. - Complex Conversations: Use rewind levels of 
2–3for maintaining context across multiple nodes. 
Configuring Models in the Node Settings
- Open the LLM Configuration tab in a node’s settings.
 - 
Adjust the following parameters:
- Temperature: Slide the control to the desired level.
 - Max Tokens: Set a specific token limit for responses.
 - Rewind Level: Choose the rewind level for managing conversation context.
 
 

Image showing the LLM Configuration tab with Temperature, Max Tokens, and Rewind Level settings.
Example Configurations
1. Precise and Factual Responses
- Temperature: 
0.1 - Max Tokens: 
200 - Rewind Level: 
0 
2. Creative and Open-Ended Responses
- Temperature: 
0.9 - Max Tokens: 
500 - Rewind Level: 
2 
3. Contextual Conversations
- Temperature: 
0.3 - Max Tokens: 
300 - Rewind Level: 
3 
Testing Model Settings
- Use the Test Tool in the Canvas Workspace to simulate responses.
 - Input queries matching your intended use case.
 - Adjust the parameters as needed for better results.
 
Best Practices for Models Configuration
- Align Parameters with Use Cases: Tailor Temperature and Max Tokens to the specific requirements of your chatbot.
 - Test Iteratively: Run multiple tests to fine-tune the settings.
 - Balance Creativity and Precision: Use mid-range Temperature values (
0.4–0.6) for responses that are both creative and accurate. - Leverage Rewind Levels: Enable context retention for better user interactions.
 
Example Flow with Configured Models
Scenario: A multi-purpose chatbot:- Start Node: Welcomes the user with a creative tone (Temperature 
0.7). - FAQ Node: Provides precise answers with a factual tone (Temperature 
0.2). - Feedback Node: Asks for user feedback with an engaging tone (Temperature 
0.5). 
