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--- start [2024/12/05 15:13] – brad
+++ start [2024/12/13 18:26] (current) – brad
@@ Line 1: / Line 1: @@
-===== Large Language Model (LLM) Agents =====
+===== AgentWiki =====
-Welcome to the **LLM Agents Wiki**, a comprehensive resource for understanding and leveraging Large Language Model Agents in advanced applications. Delve into the latest developments, explore various architectures and design patterns, and discover the libraries and tools that empower these intelligent systems to perform autonomously across diverse domains.
+Welcome to the **AgentWiki**, a comprehensive resource for understanding and leveraging Large Language Models (LLMs) for agent applications.
+Catch up on the latest developments, explore various architectures and design patterns, and discover the libraries and tools that empower these intelligent systems to perform autonomously across diverse domains.
 ==== Introduction ====
-Large Language Model (LLM) Agents are sophisticated AI systems that utilize large-scale neural language models to perform tasks autonomously. By comprehending natural language, reasoning through complex problems, and interacting with external tools and environments, LLM Agents represent a significant advancement in artificial intelligence. They are capable of planning, executing, and adapting their actions based on given objectives and feedback from their environment.
+🤖 Large Language Model (LLM) Agents are sophisticated AI systems that utilize large-scale neural language models to perform tasks autonomously.
+By comprehending natural language, reasoning through complex problems, and interacting with external tools and environments, LLM Agents represent a significant advancement in artificial intelligence.
+They are capable of planning, executing, and adapting their actions based on given objectives and feedback from their environment.
 ==== Agent System Overview ====
-In an LLM-powered autonomous agent system, the LLM functions as the agent's central processing unit, complemented by several key components:
+🧠 In an LLM-powered autonomous agent system, the LLM functions as the agent's central processing unit, complemented by several key components:
   * **[[planning|Planning]]**
     * Task Decomposition
     * Self-Reflection
   * **[[memory|Memory]]**
     * Hierarchical Memory Systems
     * Efficient Retrieval Mechanisms
   * **[[tool_use|Tool Use]]**
     * External API Integration
     * Dynamic Tool Selection
-These components enable the agent to:
+  * **[[structured_outputs|Structured Outputs]]**
+    * Grammars
+    * Constrained Outputs
-  * **Plan** complex tasks through decomposition and strategic reasoning.
+🚀 These components enable the agent to:
-  * **Remember** past interactions using advanced memory architectures.
+  * **Plan** complex tasks through decomposition and strategic reasoning.
+  * **Remember** past interactions using advanced memory architectures.
   * **Utilize Tools** to extend capabilities beyond text generation.
 ==== Key Features of LLM Agents ====
-  * **[[advanced_reasoning_planning|Advanced Reasoning and Planning]]**: Employ sophisticated reasoning strategies to analyze complex tasks, devise multi-step plans, and sequence actions to achieve specific goals.
+🌀 **[[advanced_reasoning_planning|Advanced Reasoning and Planning]]**:
-  * **[[tool_utilization|Tool Utilization and API Interaction]]**: Interface with external tools, APIs, databases, and services to perform actions such as web searches, code execution, and data manipulation.
+Employ sophisticated reasoning strategies to analyze complex tasks, devise multi-step plans, and sequence actions to achieve specific goals.
-  * **[[hierarchical_memory|Hierarchical Memory and Context Management]]**: Use multi-level memory architectures to maintain extensive context over interactions, enabling long-term coherence and adaptability.
-  * **[[natural_language_understanding|Natural Language Understanding and Generation]]**: Interpret and generate human-like text, facilitating effective communication and instruction following.
+🔧 **[[tool_utilization|Tool Utilization and API Interaction]]**:
-  * **[[autonomy|Autonomy and Adaptive Behavior]]**: Operate independently, making informed decisions and adapting to new information or changes in their environment through iterative learning processes.
+Interface with external tools, APIs, databases, and services to perform actions such as web searches, code execution, and data manipulation.
+📚 **[[hierarchical_memory|Hierarchical Memory and Context Management]]**:
+Use multi-level memory architectures to maintain extensive context over interactions, enabling long-term coherence and adaptability.
+💡 **[[natural_language_understanding|Natural Language Understanding and Generation]]**:
+Interpret and generate human-like text, facilitating effective communication and instruction following.
+🔄 **[[autonomy|Autonomy and Adaptive Behavior]]**:
+Operate independently, making informed decisions and adapting to new information or changes in their environment through iterative learning processes.
+==== Workflows ====
+Workflows in LLM Agent systems streamline the design, implementation, and orchestration of complex tasks by structuring multi-step processes for optimal performance.
+🌊 **Key Workflow Tools**
+  * **[[flowise|Flowise]]**: A visual programming interface for designing agent workflows.
+  * **[[promptflow|PromptFlow]]**: A framework for defining and testing prompt sequences in a systematic manner.
+These tools enhance the modularity and reusability of task definitions, enabling seamless experimentation and deployment.
 ==== Components of LLM Agents ====
@@ Line 39: / Line 67: @@
 === Planning ===
-Planning involves the strategic breakdown of complex tasks into manageable sub-tasks, devising algorithms, and sequencing actions based on logical reasoning and predicted outcomes.
+🧩 Planning involves the strategic breakdown of complex tasks into manageable sub-tasks, devising algorithms, and sequencing actions based on logical reasoning and predicted outcomes.
 == Task Decomposition ==
-  * **[[chain_of_thought|Chain-of-Thought (CoT) Reasoning]]**
+🌳 **[[chain_of_thought|Chain-of-Thought (CoT) Reasoning]]**
-  * **[[tree_of_thoughts|Tree of Thoughts]]**
+🌲 **[[tree_of_thoughts|Tree of Thoughts]]**
-  * **[[llm_with_planning|LLM+P (LLM with Classical Planning)]]**
+⚙️ **[[llm_with_planning|LLM+P (LLM with Classical Planning)]]**
 == Self-Reflection ==
-  * **[[react_framework|ReAct (Reasoning and Acting)]]**
+🔍 **[[react_framework|ReAct (Reasoning and Acting)]]**
-  * **[[reflexion_framework|Reflexion Framework]]**
+🔄 **[[reflexion_framework|Reflexion Framework]]**
-  * **[[chain_of_hindsight|Chain of Hindsight (CoH)]]**
+🪞 **[[chain_of_hindsight|Chain of Hindsight (CoH)]]**
-  * **[[algorithm_distillation|Algorithm Distillation (AD)]]**
+📉 **[[algorithm_distillation|Algorithm Distillation (AD)]]**
 === Memory ===
-Memory mechanisms allow agents to retain, retrieve, and utilize information over extended periods, significantly enhancing their ability to maintain context, learn from past experiences, and build upon accumulated knowledge.
+📦 Memory mechanisms allow agents to retain, retrieve, and utilize information over extended periods, significantly enhancing their ability to maintain context, learn from past experiences, and build upon accumulated knowledge.
 == Hierarchical Memory Systems ==
-  * **[[sensory_memory|Sensory Memory]]**
+🕒 **[[sensory_memory|Sensory Memory]]**
-  * **[[short_term_memory|Short-Term Memory (Working Memory)]]**
+⏳ **[[short_term_memory|Short-Term Memory (Working Memory)]]**
-  * **[[long_term_memory|Long-Term Memory (Persistent Memory)]]**
+📜 **[[long_term_memory|Long-Term Memory (Persistent Memory)]]**
-    * **[[explicit_memory|Explicit/Declarative Memory]]**
+    * 📂 **[[explicit_memory|Explicit/Declarative Memory]]**
-    * **[[implicit_memory|Implicit/Procedural Memory]]**
+    * 🤫 **[[implicit_memory|Implicit/Procedural Memory]]**
 == Efficient Retrieval Mechanisms ==
-  * **[[maximum_inner_product_search|Maximum Inner Product Search (MIPS)]]**
+🔎 **[[maximum_inner_product_search|Maximum Inner Product Search (MIPS)]]**
-    * **[[locality_sensitive_hashing|Locality-Sensitive Hashing (LSH)]]**
+    * 🧮 **[[locality_sensitive_hashing|Locality-Sensitive Hashing (LSH)]]**
-    * **[[approximate_nearest_neighbors|Approximate Nearest Neighbors (ANNOY)]]**
+    * 📊 **[[approximate_nearest_neighbors|Approximate Nearest Neighbors (ANNOY)]]**
-    * **[[hnsw_graphs|Hierarchical Navigable Small World (HNSW) Graphs]]**
+    * 🗺️ **[[hnsw_graphs|Hierarchical Navigable Small World (HNSW) Graphs]]**
-    * **[[faiss|Facebook AI Similarity Search (FAISS)]]**
+    * 🔍 **[[faiss|Facebook AI Similarity Search (FAISS)]]**
-    * **[[scann|Scalable Nearest Neighbors (ScaNN)]]**
+    * 📈 **[[scann|Scalable Nearest Neighbors (ScaNN)]]**
 === Tool Use ===
-Tool use extends the agent's functionality by enabling interaction with external systems, APIs, and tools, allowing the agent to perform actions beyond its inherent capabilities and access up-to-date information.
+🔧 Tool use extends the agent's functionality by enabling interaction with external systems, APIs, and tools, allowing the agent to perform actions beyond its inherent capabilities and access up-to-date information.
-  * **[[mrkl_systems|MRKL Systems (Modular Reasoning, Knowledge, and Language)]]**
+  * 🧰 **[[mrkl_systems|MRKL Systems (Modular Reasoning, Knowledge, and Language)]]**
-  * **[[tool_augmented_language_models|Tool-Augmented Language Models (TALM)]]**
+  * 🛠️ **[[tool_augmented_language_models|Tool-Augmented Language Models (TALM)]]**
-  * **[[toolformer|Toolformer]]**
+  * 🤖 **[[toolformer|Toolformer]]**
 == API Integration ==
-  * **[[openai_function_calling|OpenAI Function Calling and ChatGPT Plugins]]**
+🔗 **[[openai_function_calling|OpenAI Function Calling and ChatGPT Plugins]]**
-  * **[[hugginggpt|HuggingGPT]]**
+🔗 **[[hugginggpt|HuggingGPT]]**
-  * **[[api_bank_benchmark|API-Bank Benchmark]]**
+🗂️ **[[api_bank_benchmark|API-Bank Benchmark]]**
 ==== Types of LLM Agents ====
-  * **[[chain_of_thought_agents|Chain-of-Thought Agents]]**
+🧠 **[[chain_of_thought_agents|Chain-of-Thought Agents]]**
-  * **[[react_agents|ReAct Agents]]**
+🔄 **[[react_agents|ReAct Agents]]**
-  * **[[autonomous_agents|Autonomous Agents]]**
+🤖 **[[autonomous_agents|Autonomous Agents]]**
-    * **[[autogpt|AutoGPT]]**
+    * 🤖 **[[autogpt|AutoGPT]]**
-    * **[[babyagi|BabyAGI]]**
+    * 🤖 **[[babyagi|BabyAGI]]**
-    * **[[agentgpt|AgentGPT]]**
+    * 🤖 **[[agentgpt|AgentGPT]]**
-  * **[[plan_and_execute_agents|Plan-and-Execute Agents]]**
+📋 **[[plan_and_execute_agents|Plan-and-Execute Agents]]**
-  * **[[conversational_agents|Conversational Agents]]**
+💬 **[[conversational_agents|Conversational Agents]]**
-  * **[[tool_using_agents|Tool-Using Agents]]**
+🔧 **[[tool_using_agents|Tool-Using Agents]]**
 ==== Design Patterns for LLM Agents ====
-  * **[[prompt_chaining|Prompt Chaining and Orchestration]]**
+🔗 **[[prompt_chaining|Prompt Chaining and Orchestration]]**
-  * **[[rlhf|Reinforcement Learning from Human Feedback (RLHF)]]**
+📈 **[[rlhf|Reinforcement Learning from Human Feedback (RLHF)]]**
-  * **[[agent_loop|Agent Loop (Perception-Thought-Action Cycle)]]**
+🔄 **[[agent_loop|Agent Loop (Perception-Thought-Action Cycle)]]**
-  * **[[context_window_management|Context Window Management]]**
+🗂️ **[[context_window_management|Context Window Management]]**
-  * **[[tool_integration_patterns|Tool Integration Patterns]]**
+🔧 **[[tool_integration_patterns|Tool Integration Patterns]]**
-  * **[[memory_augmentation_strategies|Memory Augmentation Strategies]]**
+📂 **[[memory_augmentation_strategies|Memory Augmentation Strategies]]**
-  * **[[modular_architectures|Modular and Layered Architectures]]**
+🏗️ **[[modular_architectures|Modular and Layered Architectures]]**
 ==== Libraries and Frameworks ====
@@ Line 117: / Line 145: @@
 **Frameworks & Platforms**
-  * **[[agent_protocol|Agent Protocol]]**
+⚙️ **[[agent_protocol|Agent Protocol]]**
-  * **[[anthropic_context_protocol|Anthropic Model Context Protocol]]**
+🤖 **[[anthropic_context_protocol|Anthropic Model Context Protocol]]**
-  * **[[chatdev|ChatDev]]**
+💻 **[[chatdev|ChatDev]]**
-  * **[[bolt_new|Bolt.new]]**
+⚡ **[[bolt_new|Bolt.new]]**
-  * **[[flowise|Flowise]]**
+🔗 **[[flowise|Flowise]]**
-  * **[[instructor_framework|Instructor]]**
+📋 **[[instructor_framework|Instructor]]**
-  * **[[llamaindex|LlamaIndex]]**
+🔎 **[[llamaindex|LlamaIndex]]**
-  * **[[autogpt|AutoGPT]]**
+🧠 **[[autogpt|AutoGPT]]**
-  * **[[babyagi|BabyAGI]]**
+🤖 **[[babyagi|BabyAGI]]**
-  * **[[langroid|Langroid]]**
+🔗 **[[langroid|Langroid]]**
-  * **[[microsoft_graphrag|Microsoft GraphRAG]]**
+📊 **[[microsoft_graphrag|Microsoft GraphRAG]]**
-  * **[[lite_llm|LiteLLM]]**
+🌟 **[[lite_llm|LiteLLM]]**

🤖 AgentWiki

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