Customize LLM Parameters (Temperature, Top P, etc.) for Custom Agents
r
rvkproject
The key parameters users would like to be able to configure are:
1) Temperature: Adjusting the temperature would allow users to control the "creativity" and randomness of the agent's responses, from more deterministic and logical (low temperature) to more varied and exploratory (high temperature).
2) Top P: For OpenAI models, the ability to set the Top P (nucleus sampling) parameter would give users control over the diversity of tokens the model considers, from a broader (high Top P) to a more focused (low Top P) distribution.
3) Frequency Penalty and Presence Penalty: Similarly for OpenAI models, allowing users to adjust the frequency and presence penalties would enable them to encourage or discourage the model from repeating certain words or phrases, or introducing new ones.
4) Response Mode: For Anthropic models, users would like the option to choose between "Full Responses" (more verbose, with explanations) or "Concise" mode (shorter, more direct responses).
Providing these customization options would give greater control over the agent's personality and outputs.
This level of configurability would significantly improve the flexibility and utility of Custom Agents.