altaidevorg/rules-for-ai

Tutorials are for humans, rules are for AI!

This repository also configures its own agents. See what rules-for-ai tells them →

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29Mods indexed here, across every type
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altaidevorg/rules-for-ai

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Flax NNX Filters (filterlib) for selecting Variables in Modules/State using types, tags, paths, predicates, and logical combinations.

not rated 2 1y ago A 29 tokens original MIT

nnx_module

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Explains the core Flax NNX abstraction nnx.Module for defining neural network components as stateful Python classes.

not rated 2 1y ago A 3,606 tokens original MIT

nnx_optimizer

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Explains Flax NNX nnx.Optimizer for managing Module, Optax state, and optimizer updates in training loops.

not rated 2 1y ago A 0 tokens original MIT

nnx_rngs

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Details Flax NNX nnx.Rngs for managing PRNG keys within Modules, explaining streams, key generation, and state management.

not rated 2 1y ago A 28 tokens original MIT

altaidevorg/rules-for-ai

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Tutorial chapter for google-adk's Agent (BaseAgent / LlmAgent), detailing the core agent abstraction, its structure, hierarchy, and the LLM-powered implementation.

not rated 2 1y ago A 4,096 tokens original MIT

basellm

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In the previous chapter, we learned how Event objects capture the history of interactions within a session. Many of these events, particularly agent responses and decisions to use tools, originate from interactions with a Large Language Model (LLM). This chapter introduces BaseLlm, the core abstraction in google-adk…

not rated 2 1y ago A 0 tokens original MIT

basellmflow

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altaidevorg/rules-for-ai

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Details google-adk's BaseLlmFlow, the core engine orchestrating LLM interactions, processors, tool calls, and agent transfers for LlmAgent.

not rated 2 1y ago A 0 tokens original MIT

event

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Details google-adk's Event object, representing interaction units with author, content, actions, and metadata within a Session.

not rated 2 1y ago A 0 tokens original MIT

invocationcontext

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In the previous chapter, we explored BaseLlmFlow, the engine that orchestrates the complex interaction between an Agent (BaseAgent / LlmAgent) and the BaseLlm, especially when handling Tools (BaseTool). We saw that the flow logic often needs access to the current session, services, agent configuration, and more.…

not rated 2 1y ago A 0 tokens original MIT

runner

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Tutorial chapter for google-adk's Runner, detailing its role in orchestrating agent execution, managing sessions, artifacts, memory, and selecting agents.

not rated 2 1y ago A 3,155 tokens original MIT

state

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Details google-adk's State object for managing session state with scopes and delta tracking.

not rated 2 1y ago A 0 tokens original MIT

tool__basetool_

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altaidevorg/rules-for-ai

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In the previous chapter, we explored BaseLlm, the abstraction enabling agents to leverage the generative power of Large Language Models. However, LLMs alone have limitations – their knowledge is often frozen in time, and they cannot directly interact with the outside world or execute specific tasks beyond text…

not rated 2 1y ago A 0 tokens original MIT

toolcontext

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altaidevorg/rules-for-ai

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In the previous chapter, we learned about InvocationContext, the object encapsulating all necessary information for a single agent turn. While components like callbacks receive a CallbackContext that wraps InvocationContext and provides delta-aware state access, Tools (BaseTool) require slightly more specific…

not rated 2 1y ago A 0 tokens original MIT

apierror

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Details google-genai's APIError, the base exception for API service errors, parsing code, message, status from non-200 HTTP responses.

not rated 2 1y ago A 0 tokens original MIT

baseapiclient

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Details the internal google-genai BaseApiClient, the core component for HTTP communication, auth, and endpoint handling.

not rated 2 1y ago A 0 tokens original MIT

chat___asyncchat

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altaidevorg/rules-for-ai

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Explains google-genai Chat/AsyncChat classes, stateful wrappers for managing multi-turn conversation history with generative models.

not rated 2 1y ago A 25 tokens original MIT

client

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altaidevorg/rules-for-ai

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Explains the google-genai Client class, the main entry point for configuring API access (Gemini/Vertex) and interacting with SDK modules.

not rated 2 1y ago A 3,141 tokens original MIT

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