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Update magic_beans example to condition situation perception on observations
Make the three questions components to save their state into memory at every update, but only if the state has changed
Improve support for self-talk
Increase DEFAULT_MAX_TOKENS because some models block very short responses.
Add logging to basic agent and agent components for a detailed html generation.
Increase temperature after first failed multiple choice attempt in gpt model
More readable agent chain of thought
Update magic_beans example to condition situation perception on observations
Make summary prompt in observation component composable
Refactoring observation component that uses memory retrieval by time to represent observations.
Improving the the call to action prompting by using answer prefix with the agents' name
Improving player_status by querying the memory for exact matches to the agents name
Minor improvements to plan component: i) rephrased the query to be more aligned with instruction tuned models.ii) added in-context example to improve and unify output iii) no longer printing the goal, since it is a component supplied externally, if the user wants to add it to the agents' context they can do it explicitly.
Use the answer_prefix functionality in the interactive_document for forcing answer to start with a prefix
Allow conditioning of situation perception on observation components.
Fixed
Recover from a common incorrect behavior from models where they repeat the prefix they were supposed to continue
Making sure that schedule executes only ones.
Fixing the conversation component adding empty memories to the GM.
Fixed person_by_situation and situation_perception components, that had a broken default components argument
Fixed colab examples having wrong arguments in agent creation
Added
A test for the GM sequence of calls
Add logging to basic agent and agent components for a detailed html generation.