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Notebooks

This page contains a collection of notebooks that demonstrate how to use AutoGen. The notebooks are tagged with the topics they cover. For example, a notebook that demonstrates how to use function calling will be tagged with tool/function.

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Mitigating Prompt hacking with JSON Mode in Autogen
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Use JSON mode and Agent Descriptions to mitigate prompt manipulation and control speaker transition.
JSONdescriptionprompt hackinggroup chatorchestration
Using RetrieveChat for Retrieve Augmented Code Generation and Question Answering
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Explore the use of AutoGen's RetrieveChat for tasks like code generation from docstrings, answering complex questions with human feedback, and exploiting features like Update Context, custom prompts, and few-shot learning.
RAG
Using RetrieveChat Powered by MongoDB Atlas for Retrieve Augmented Code Generation and Question Answering
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Explore the use of AutoGen's RetrieveChat for tasks like code generation from docstrings, answering complex questions with human feedback, and exploiting features like Update Context, custom prompts, and few-shot learning.
MongoDBintegrationRAG
Using RetrieveChat Powered by PGVector for Retrieve Augmented Code Generation and Question Answering
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Explore the use of AutoGen's RetrieveChat for tasks like code generation from docstrings, answering complex questions with human feedback, and exploiting features like Update Context, custom prompts, and few-shot learning.
PGVectorintegrationRAG
Using RetrieveChat with Qdrant for Retrieve Augmented Code Generation and Question Answering
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This notebook demonstrates the usage of QdrantRetrieveUserProxyAgent for RAG.
QdrantintegrationRAG
Agent Tracking with AgentOps
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Use AgentOps to simplify the development process and monitor your agents in production.
integrationmonitoringdebugging
AgentOptimizer: An Agentic Way to Train Your LLM Agent
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AgentOptimizer is able to prompt LLMs to iteratively optimize function/skills of AutoGen agents according to the historical conversation and performance.
optimizationtool/function
Task Solving with Code Generation, Execution and Debugging
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Use conversable language learning model agents to solve tasks and provide automatic feedback through a comprehensive example of writing, executing, and debugging Python code to compare stock price changes.
code generation
Assistants with Azure Cognitive Search and Azure Identity
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This notebook demonstrates the use of Assistant Agents in conjunction with Azure Cognitive Search and Azure Identity
integrationRAGAzure IdentityAzure AI Search
Usage tracking with AutoGen
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cost calculation
cost
Agent Chat with custom model loading
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Define and laod a custom model
integrationcustom model
Agent Chat with Multimodal Models: DALLE and GPT-4V
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Multimodal agent chat with DALL-E and GPT-4v.
multimodalgpt-4v
Use AutoGen in Databricks with DBRX
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Use Databricks DBRX and Foundation Model APIs to build AutoGen applications backed by open-source LLMs.
integrationcode generationdbrxdatabricksopen sourcelakehousecustom modeldata intelligence
Auto Generated Agent Chat: Task Solving with Provided Tools as Functions
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Register function calls using AssistantAgent and UserProxyAgent to execute python or shell code in customized ways. Demonstrating two ways of registering functions.
code generationtool/function
Task Solving with Provided Tools as Functions (Asynchronous Function Calls)
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Learn how to implement both synchronous and asynchronous function calls using AssistantAgent and UserProxyAgent in AutoGen, with examples of their application in individual and group chat settings for task execution with language models.
tool/functionasync
Writing a software application using function calls
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Equip your agent with functions that can efficiently implement features into your software application.
code generationtool/functionfastapisoftware engineering
Currency Calculator: Task Solving with Provided Tools as Functions
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Learn how to register function calls using AssistantAgent and UserProxyAgent.
tool/function
Groupchat with Llamaindex agents
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Integrate llamaindex agents with Autogen.
reactllamaindexintegrationgroup chatsoftware engineering
Group Chat
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Explore the utilization of large language models in automated group chat scenarios, where agents perform tasks collectively, demonstrating how they can be configured, interact with each other, and retrieve specific information from external resources.
orchestrationgroup chatcode generation
Group Chat with Retrieval Augmented Generation
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Implement and manage a multi-agent chat system using AutoGen, where AI assistants retrieve information, generate code, and interact collaboratively to solve complex tasks, especially in areas not covered by their training data.
group chatorchestrationRAG
Group Chat with Customized Speaker Selection Method
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Introduce group chat with customized speaker selection method.
orchestrationgroup chat
FSM - User can input speaker transition constraints
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Explore the demonstration of the Finite State Machine implementation, which allows the user to input speaker transition constraints.
group chatfsmorchestration
Perform Research with Multi-Agent Group Chat
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Perform research using a group chat with a number of specialized agents.
group chatplanningcode generation
StateFlow: Build Workflows through State-Oriented Actions
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StateFlow: Build workflows through state-oriented actions.
orchestrationgroup chatstateflowresearch
Group Chat with Coder and Visualization Critic
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Explore a group chat example using agents such as a coder and visualization agent.
group chatcode generation
Using Guidance with AutoGen
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Constrained responses via guidance.
guidanceintegrationJSON
Auto Generated Agent Chat: Task Solving with Code Generation, Execution, Debugging & Human Feedback
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Code generation, execution, debugging and human feedback.
humancode generation
Generate Dalle Images With Conversable Agents
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Generate images with conversable agents.
capabilitymultimodal
Auto Generated Agent Chat: Function Inception
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Function Inception: Enable AutoGen agents to update/remove functions during conversations.
function inceptiontool/function
Auto Generated Agent Chat: Task Solving with Langchain Provided Tools as Functions
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Use Langchain tools.
langchainintegrationtool/function
Engaging with Multimodal Models: GPT-4V in AutoGen
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Leveraging multimodal models through two different methodologies: MultimodalConversableAgent and VisionCapability.
multimodalgpt-4v
Agent Chat with Multimodal Models: LLaVA
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Leveraging multimodal models like llava.
multimodalllava
Runtime Logging with AutoGen
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Provide capabilities of runtime logging for debugging and performance analysis.
loggingdebugging
Agent with memory using Mem0
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Use Mem0 to create agents with memory.
memory
Solving Multiple Tasks in a Sequence of Async Chats
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Use conversational agents to solve a set of tasks with a sequence of async chats.
orchestrationasyncsequential chats
Solving Multiple Tasks in a Sequence of Chats
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Use conversational agents to solve a set of tasks with a sequence of chats.
orchestrationsequential chats
Nested Chats for Tool Use in Conversational Chess
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LLM-backed agents playing chess with each other using nested chats.
nested chattool/functionorchestration
Conversational Chess using non-OpenAI clients
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LLM-backed agents playing chess with each other using nested chats.
nested chattool/functionorchestration
Solving Complex Tasks with A Sequence of Nested Chats
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Solve complex tasks with one or more sequence chats nested as inner monologue.
nested chatsequential chatsorchestration
Solving Complex Tasks with Nested Chats
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Solve complex tasks with a chat nested as inner monologue.
nested chatreflectionreasoningorchestration
OptiGuide with Nested Chats in AutoGen
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This is a nested chat re-implementation of OptiGuide which is an LLM-based supply chain optimization framework.
nested chathierarchical chatcode generationorchestration
Chat with OpenAI Assistant using function call in AutoGen: OSS Insights for Advanced GitHub Data Analysis
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This Jupyter Notebook demonstrates how to leverage OSS Insight (Open Source Software Insight) for advanced GitHub data analysis by defining `Function calls` in AutoGen for the OpenAI Assistant.
OpenAI Assistanttool/function
Auto Generated Agent Chat: Group Chat with GPTAssistantAgent
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Use GPTAssistantAgent in group chat.
OpenAI Assistantgroup chat
RAG OpenAI Assistants in AutoGen
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OpenAI Assistant with retrieval augmentation.
RAGOpenAI Assistant
OpenAI Assistants in AutoGen
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Two-agent chat with OpenAI assistants.
OpenAI Assistant
Auto Generated Agent Chat: GPTAssistant with Code Interpreter
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This Jupyter Notebook showcases the integration of the Code Interpreter tool which executes Python code dynamically within applications.
OpenAI Assistantcode interpreter
Auto Generated Agent Chat: Collaborative Task Solving with Coding and Planning Agent
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Use planning agent in a function call.
planningorchestrationnested chattool/function
SocietyOfMindAgent
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Explore the demonstration of the SocietyOfMindAgent in the AutoGen library, which runs a group chat as an internal monologue, but appears to the external world as a single agent, offering a structured way to manage complex interactions among multiple agents and handle issues such as extracting responses from complex dialogues and dealing with context window constraints.
orchestrationnested chatgroup chat
SQL Agent for Spider text-to-SQL benchmark
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Natural language text to SQL query using the Spider text-to-SQL benchmark.
SQLtool/function
Interactive LLM Agent Dealing with Data Stream
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Automated continual learning from new data.
streamingasynclearning
WebSurferAgent
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Browse the web with agents.
webnested chattool/function
Implement Swarm with AutoGen GroupChat
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Implement Swarm with AutoGen GroupChat
orchestrationgroup chatstateflowswarm
Chatting with a teachable agent
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Learn how to persist memories across chat sessions using the Teachability capability
teachabilitylearningRAGcapability
Making OpenAI Assistants Teachable
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Teach OpenAI assistants.
teachabilitycapabilitylearningRAGOpenAI Assistant
Auto Generated Agent Chat: Teaching AI New Skills via Natural Language Interaction
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Teach the agent news skills using natural language.
learningteaching
Preprocessing Chat History with `TransformMessages`
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Preprocessing chat history with `TransformMessages`
long context handlingcapability
Auto Generated Agent Chat: Collaborative Task Solving with Multiple Agents and Human Users
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Involve multiple human users via function calls and nested chat.
humantool/function
Translating Video audio using Whisper and GPT-3.5-turbo
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Use tools to extract and translate the transcript of a video file.
whispermultimodaltool/function
Auto Generated Agent Chat: Solving Tasks Requiring Web Info
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Solve tasks requiring web info.
webcode generation
Web Scraping using Apify Tools
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Scrapping web pages and summarizing the content using agents with tools.
webapifyintegrationtool/function
Websockets: Streaming input and output using websockets
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Websockets facilitate real-time, bidirectional communication between web clients and servers, enhancing the responsiveness and interactivity of AutoGen-powered applications.
websocketsstreaming
Agent with memory using Mem0
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Use Mem0 to create agents with memory.
mem0integrationmemory
Solving Multiple Tasks in a Sequence of Chats with Different Conversable Agent Pairs
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Use AutoGen to solve a set of tasks with a sequence of chats.
orchestrationsequential chats
Demonstrating the `AgentEval` framework using the task of solving math problems as an example
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AgentEval: a multi-agent system for assessing utility of LLM-powered applications
eval
Agent Chat with Async Human Inputs
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Async human inputs.
asynchuman
Automatically Build Multi-agent System from Agent Library
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Automatically build multi-agent system from agent library
autobuild
AutoBuild
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Automatically build multi-agent system with AgentBuilder
autobuild
A Uniform interface to call different LLMs
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Uniform interface to call different LLM.
integrationcustom model
From Dad Jokes To Sad Jokes: Function Calling with GPTAssistantAgent
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Use tools in a GPTAssistantAgent Multi-Agent System by utilizing functions such as calling an API and writing to a file.
OpenAI Assistanttool/function
Language Agent Tree Search
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Language Agent Tree Search.
LATSsearchreasoningreflection