Ai abstraction refactor

[AumJavalgikar]

Restructured the entire ai module

Removed the following modules :

finetune
models
scripts
tests
tokenizers
tools

Modified the following modules :

agent
utils

Added the following modules :

config
skills
hooks

[coderabbitai]

Walkthrough

The recent update introduces a sophisticated framework for creating and managing AI assistant agents within a role-playing environment. It includes the setup for an assistant agent with customizable features, a multi-agent manager for orchestrating interactions among multiple agents, and a user proxy agent for handling user inputs. Additionally, the update establishes a foundation for configuration and hooks within the system, allowing for enhanced customization and extensibility of agent behaviors and interactions.

Changes

Files	Change Summaries
.../assistant_agent.py, .../userproxy_agent.py	Introduce AssistantAgent and UserProxyAgent for conversational AI interactions.
.../multiagent_manager.py	Adds MultiAgentManager for managing multiple agents in RPGs with diverse game modes.
.../base_agent.py	Updates terminology in BaseAgent class from "tools" to "skills" for improved functionality.
.../config/__init__.py, .../hooks/__init__.py	Adds initialization files for configuration and hooks modules.
.../hooks/hook_base.py, .../hooks/hook_manager.py	Introduces base class and manager for hooks, enhancing agent interactions.

🌟🐇📜✨
In the land of code where the bits do roam,
New agents arise, in a digital home.
With whispers of hooks and a multi-agent dance,
They converse and play, in an AI-enhanced trance.
Here's to the changes, may they bring delight,
As our digital friends, talk into the night.
🌌🤖💬✨

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Review Status

Actionable comments generated: 1

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between abdd43a and ea6a73d.

Files selected for processing (7)

• nextpy/ai/agent/assistant_agent.py (1 hunks)
• nextpy/ai/agent/multiagent_manager.py (1 hunks)
• nextpy/ai/agent/userproxy_agent.py (1 hunks)
• nextpy/ai/config/init.py (1 hunks)
• nextpy/ai/hooks/init.py (1 hunks)
• nextpy/ai/hooks/hook_base.py (1 hunks)
• nextpy/ai/hooks/hook_manager.py (1 hunks)

Files skipped from review due to trivial changes (3)

• nextpy/ai/config/init.py
• nextpy/ai/hooks/init.py
• nextpy/ai/hooks/hook_base.py

Additional comments: 4

nextpy/ai/agent/userproxy_agent.py (2)

• 5-29: The UserProxyAgent class is well-structured, inheriting from AssistantAgent and introducing parameters for async mode and pre/post function calls. This aligns with the PR's objectives of enhancing modularity and flexibility in the AI module. However, ensure that all necessary attributes and methods from AssistantAgent are compatible with UserProxyAgent's functionalities.
• 78-79: Using asyncio.to_thread to wrap the input function is a good approach to prevent blocking the event loop in asynchronous contexts. This allows for non-blocking user input in a_receive_user_input. It's important to ensure that this pattern is consistently used in all places where blocking operations might occur in async functions.

nextpy/ai/agent/assistant_agent.py (1)

• 35-145: The AssistantAgent class introduces a flexible structure for handling both synchronous and asynchronous operations, with support for pre/post function calls. The use of decorators to manage these calls is a good practice, enhancing code modularity and reuse. Ensure that async operations are properly managed to avoid blocking behavior, especially when integrating with other parts of the AI module.

nextpy/ai/agent/multiagent_manager.py (1)

• 6-91: The MultiAgentManager class is well-designed, offering functionalities for managing multiple agents in various modes, including round-robin and auto mode. It supports both synchronous and asynchronous operations, which is crucial for handling multiple conversations or game sequences. Ensure that the async handling is correctly implemented to prevent blocking operations, especially when integrating with other async components in the AI module.

[coderabbitai]

Review Status

Actionable comments generated: 4

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between ea6a73d and 9957c10.

Files selected for processing (1)

• nextpy/ai/agent/base_agent.py (14 hunks)

Additional comments: 4

nextpy/ai/agent/base_agent.py (4)

• 44-44: The skills parameter in the BaseAgent constructor is correctly typed to expect a list of BaseSkill instances. This is a good practice as it ensures type safety and clarity about what kind of objects skills should contain.
• 149-150: Raising a ValueError when the knowledge_variable is not found in input kwargs is appropriate for ensuring the required data is present for the agent's operation. This error handling promotes robustness in the agent's functionality.
• 170-171: Logging a warning when the output key is not found in the output is a good practice for debugging and operational transparency. However, it's also important to ensure that this scenario is handled gracefully in the user interface or calling code to avoid confusion.
• 267-268: The dynamic addition of CLI arguments based on input_variables is a flexible approach that enhances the usability of the CLI interface. This allows for easy extension of the agent's capabilities without modifying the CLI code directly.

[coderabbitai]

Review Status

Actionable comments generated: 0

Configuration used: CodeRabbit UI

Commits

Files that changed from the base of the PR and between 9957c10 and a089d83.

Files selected for processing (1)

• nextpy/ai/agent/base_agent.py (14 hunks)

Files skipped from review as they are similar to previous changes (1)

• nextpy/ai/agent/base_agent.py