agentops
<div align="center"> <a href="https://agentops.ai?ref=gh"> <img src="docs/images/external/logo/github-banner.png" alt="Logo"> </a> </div> <div align="center"> <em>Observability and DevTool platform for AI Agents</em> </div> <br /> <div align="center"> <a href="https://pepy.tech/project/agentops"> <img src="https://static.pepy.tech/badge/agentops/month" alt="Downloads"> </a> <a href="https://github.com/agentops-ai/agentops/issues"> <img src="https://img.shields.io/github/commit-activity/m/agentops-ai/agentops" alt="git commit activity"> </a> <img src="https://img.shields.io/pypi/v/agentops?&color=3670A0" alt="PyPI - Version"> <a href="https://opensource.org/licenses/MIT"> <img src="https://img.shields.io/badge/License-MIT-yellow.svg?&color=3670A0" alt="License: MIT"> </a> <a href="https://smithery.ai/server/@AgentOps-AI/agentops-mcp"> <img src="https://smithery.ai/badge/@AgentOps-AI/agentops-mcp"/> </a> </div> <p align="center"> <a href="https://twitter.com/agentopsai/"> <img src="https://img.shields.io/twitter/follow/agentopsai?style=social" alt="Twitter" style="height: 20px;"> </a> <a href="https://discord.gg/FagdcwwXRR"> <img src="https://img.shields.io/badge/discord-7289da.svg?style=flat-square&logo=discord" alt="Discord" style="height: 20px;"> </a> <a href="https://app.agentops.ai/?ref=gh"> <img src="https://img.shields.io/badge/Dashboard-blue.svg?style=flat-square" alt="Dashboard" style="height: 20px;"> </a> <a href="https://docs.agentops.ai/introduction"> <img src="https://img.shields.io/badge/Documentation-orange.svg?style=flat-square" alt="Documentation" style="height: 20px;"> </a> <a href="https://entelligence.ai/AgentOps-AI&agentops"> <img src="https://img.shields.io/badge/Chat%20with%20Docs-green.svg?style=flat-square" alt="Chat with Docs" style="height: 20px;"> </a> </p> <div align="center"> <video src="https://github.com/user-attachments/assets/dfb4fa8d-d8c4-4965-9ff6-5b8514c1c22f" width="650" autoplay loop muted></video> </div> <br/> AgentOps helps developers build, evaluate, and monitor AI agents. From prototype to production. ## Open Source The AgentOps app is open source under the MIT license. Explore the code in our [app directory](https://github.com/AgentOps-AI/agentops/tree/main/app). ## Key Integrations π <div align="center" style="background-color: white; padding: 20px; border-radius: 10px; margin: 0 auto; max-width: 800px;"> <div style="display: flex; flex-wrap: wrap; justify-content: center; align-items: center; gap: 30px; margin-bottom: 20px;"> <a href="https://docs.agentops.ai/v2/integrations/openai_agents_python"><img src="docs/images/external/openai/agents-sdk.svg" height="45" alt="OpenAI Agents SDK"></a> <a href="https://docs.agentops.ai/v1/integrations/crewai"><img src="docs/v1/img/docs-icons/crew-banner.png" height="45" alt="CrewAI"></a> <a href="https://docs.ag2.ai/docs/ecosystem/agentops"><img src="docs/images/external/ag2/ag2-logo.svg" height="45" alt="AG2 (AutoGen)"></a> <a href="https://docs.agentops.ai/v1/integrations/microsoft"><img src="docs/images/external/microsoft/microsoft_logo.svg" height="45" alt="Microsoft"></a> </div> <div style="display: flex; flex-wrap: wrap; justify-content: center; align-items: center; gap: 30px; margin-bottom: 20px;"> <a href="https://docs.agentops.ai/v1/integrations/langchain"><img src="docs/images/external/langchain/langchain-logo.svg" height="45" alt="LangChain"></a> <a href="https://docs.agentops.ai/v1/integrations/camel"><img src="docs/images/external/camel/camel.png" height="45" alt="Camel AI"></a> <a href="https://docs.llamaindex.ai/en/stable/module_guides/observability/?h=agentops#agentops"><img src="docs/images/external/ollama/ollama-icon.png" height="45" alt="LlamaIndex"></a> <a href="https://docs.agentops.ai/v1/integrations/cohere"><img src="docs/images/external/cohere/cohere-logo.svg" height="45" alt="Cohere"></a> </div> </div> | | | | ------------------------------------- | ------------------------------------------------------------- | | π **Replay Analytics and Debugging** | Step-by-step agent execution graphs | | πΈ **LLM Cost Management** | Track spend with LLM foundation model providers | | π€ **Framework Integrations** | Native Integrations with CrewAI, AG2 (AutoGen), Agno, LangGraph, & more | | βοΈ **Self-Host** | Want to run AgentOps on your own cloud? You're covered | ## Quick Start β¨οΈ ```bash pip install agentops ``` #### Session replays in 2 lines of code Initialize the AgentOps client and automatically get analytics on all your LLM calls. [Get an API key](https://app.agentops.ai/settings/projects) ```python import agentops # Beginning of your program (i.e. main.py, __init__.py) agentops.init( < INSERT YOUR API KEY HERE >) ... # End of program agentops.end_session('Success') ``` All your sessions can be viewed on the [AgentOps dashboard](https://app.agentops.ai?ref=gh) <br/> ## Self-Hosting Looking to run the full AgentOps app (Dashboard + API backend) on your machine? Follow the setup guide in `app/README.md`: - [Run the App and Backend (Dashboard + API)](app/README.md) <details> <summary>Agent Debugging</summary> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/session-drilldown-metadata.png" style="width: 90%;" alt="Agent Metadata"/> </a> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/chat-viewer.png" style="width: 90%;" alt="Chat Viewer"/> </a> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/session-drilldown-graphs.png" style="width: 90%;" alt="Event Graphs"/> </a> </details> <details> <summary>Session Replays</summary> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/session-replay.png" style="width: 90%;" alt="Session Replays"/> </a> </details> <details> <summary>Summary Analytics</summary> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/overview.png" style="width: 90%;" alt="Summary Analytics"/> </a> <a href="https://app.agentops.ai?ref=gh"> <img src="docs/images/external/app_screenshots/overview-charts.png" style="width: 90%;" alt="Summary Analytics Charts"/> </a> </details> ### First class Developer Experience Add powerful observability to your agents, tools, and functions with as little code as possible: one line at a time. <br/> Refer to our [documentation](http://docs.agentops.ai) ```python # Create a session span (root for all other spans) from agentops.sdk.decorators import session @session def my_workflow(): # Your session code here return result ``` ```python # Create an agent span for tracking agent operations from agentops.sdk.decorators import agent @agent class MyAgent: def __init__(self, name): self.name = name # Agent methods here ``` ```python # Create operation/task spans for tracking specific operations from agentops.sdk.decorators import operation, task @operation # or @task def process_data(data): # Process the data return result ``` ```python # Create workflow spans for tracking multi-operation workflows from agentops.sdk.decorators import workflow @workflow def my_workflow(data): # Workflow implementation return result ``` ```python # Nest decorators for proper span hierarchy from agentops.sdk.decorators import session, agent, operation @agent class MyAgent: @operation def nested_operation(self, message): return f"Processed: {message}" @operation def main_operation(self): result = self.nested_operation("test message") return result @session def my_session(): agent = MyAgent() return agent.main_operation() ``` All decorators support: - Input/Output Recording - Exception Handling - Async/await functions - Generator functions - Custom attributes and names ## Integrations π¦Ύ ### OpenAI Agents SDK ποΈ Build multi-agent systems with tools, handoffs, and guardrails. AgentOps natively integrates with the OpenAI Agents SDKs for both Python and TypeScript. #### Python ```bash pip install openai-agents ``` - [Python integration guide](https://docs.agentops.ai/v2/integrations/openai_agents_python) - [OpenAI Agents Python documentation](https://openai.github.io/openai-agents-python/) #### TypeScript ```bash npm install agentops @openai/agents ``` - [TypeScript integration guide](https://docs.agentops.ai/v2/integrations/openai_agents_js) - [OpenAI Agents JS documentation](https://openai.github.io/openai-agents-js) ### CrewAI πΆ Build Crew agents with observability in just 2 lines of code. Simply set an `AGENTOPS_API_KEY` in your environment, and your crews will get automatic monitoring on the AgentOps dashboard. ```bash pip install 'crewai[agentops]' ``` - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/crewai) - [Official CrewAI documentation](https://docs.crewai.com/how-to/AgentOps-Observability) ### AG2 π€ With only two lines of code, add full observability and monitoring to AG2 (formerly AutoGen) agents. Set an `AGENTOPS_API_KEY` in your environment and call `agentops.init()` - [AG2 Observability Example](https://github.com/ag2ai/ag2/blob/main/notebook/agentchat_agentops.ipynb) - [AG2 - AgentOps Documentation](https://docs.ag2.ai/latest/docs/ecosystem/agentops/) ### Camel AI πͺ Track and analyze CAMEL agents with full observability. Set an `AGENTOPS_API_KEY` in your environment and initialize AgentOps to get started. - [Camel AI](https://www.camel-ai.org/) - Advanced agent communication framework - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/camel) - [Official Camel AI documentation](https://docs.camel-ai.org/cookbooks/agents_tracking.html) <details> <summary>Installation</summary> ```bash pip install "camel-ai[all]==0.2.11" pip install agentops ``` ```python import os import agentops from camel.agents import ChatAgent from camel.messages import BaseMessage from camel.models import ModelFactory from camel.types import ModelPlatformType, ModelType # Initialize AgentOps agentops.init(os.getenv("AGENTOPS_API_KEY"), tags=["CAMEL Example"]) # Import toolkits after AgentOps init for tracking from camel.toolkits import SearchToolkit # Set up the agent with search tools sys_msg = BaseMessage.make_assistant_message( role_name='Tools calling operator', content='You are a helpful assistant' ) # Configure tools and model tools = [*SearchToolkit().get_tools()] model = ModelFactory.create( model_platform=ModelPlatformType.OPENAI, model_type=ModelType.GPT_4O_MINI, ) # Create and run the agent camel_agent = ChatAgent( system_message=sys_msg, model=model, tools=tools, ) response = camel_agent.step("What is AgentOps?") print(response) agentops.end_session("Success") ``` Check out our [Camel integration guide](https://docs.agentops.ai/v1/integrations/camel) for more examples including multi-agent scenarios. </details> ### Langchain π¦π AgentOps works seamlessly with applications built using Langchain. To use the handler, install Langchain as an optional dependency: <details> <summary>Installation</summary> ```shell pip install agentops[langchain] ``` To use the handler, import and set ```python import os from langchain.chat_models import ChatOpenAI from langchain.agents import initialize_agent, AgentType from agentops.integration.callbacks.langchain import LangchainCallbackHandler AGENTOPS_API_KEY = os.environ['AGENTOPS_API_KEY'] handler = LangchainCallbackHandler(api_key=AGENTOPS_API_KEY, tags=['Langchain Example']) llm = ChatOpenAI(openai_api_key=OPENAI_API_KEY, callbacks=[handler], model='gpt-3.5-turbo') agent = initialize_agent(tools, llm, agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION, verbose=True, callbacks=[handler], # You must pass in a callback handler to record your agent handle_parsing_errors=True) ``` Check out the [Langchain Examples Notebook](./examples/langchain/langchain_examples.ipynb) for more details including Async handlers. </details> ### Cohere β¨οΈ First class support for Cohere(>=5.4.0). This is a living integration, should you need any added functionality please message us on Discord! - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/cohere) - [Official Cohere documentation](https://docs.cohere.com/reference/about) <details> <summary>Installation</summary> ```bash pip install cohere ``` ```python python import cohere import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) co = cohere.Client() chat = co.chat( message="Is it pronounced ceaux-hear or co-hehray?" ) print(chat) agentops.end_session('Success') ``` ```python python import cohere import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) co = cohere.Client() stream = co.chat_stream( message="Write me a haiku about the synergies between Cohere and AgentOps" ) for event in stream: if event.event_type == "text-generation": print(event.text, end='') agentops.end_session('Success') ``` </details> ### Anthropic οΉ¨ Track agents built with the Anthropic Python SDK (>=0.32.0). - [AgentOps integration guide](https://docs.agentops.ai/v1/integrations/anthropic) - [Official Anthropic documentation](https://docs.anthropic.com/en/docs/welcome) <details> <summary>Installation</summary> ```bash pip install anthropic ``` ```python python import anthropic import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) client = anthropic.Anthropic( # This is the default and can be omitted api_key=os.environ.get("ANTHROPIC_API_KEY"), ) message = client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Tell me a cool fact about AgentOps", } ], model="claude-3-opus-20240229", ) print(message.content) agentops.end_session('Success') ``` Streaming ```python python import anthropic import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) client = anthropic.Anthropic( # This is the default and can be omitted api_key=os.environ.get("ANTHROPIC_API_KEY"), ) stream = client.messages.create( max_tokens=1024, model="claude-3-opus-20240229", messages=[ { "role": "user", "content": "Tell me something cool about streaming agents", } ], stream=True, ) response = "" for event in stream: if event.type == "content_block_delta": response += event.delta.text elif event.type == "message_stop": print("\n") print(response) print("\n") ``` Async ```python python import asyncio from anthropic import AsyncAnthropic client = AsyncAnthropic( # This is the default and can be omitted api_key=os.environ.get("ANTHROPIC_API_KEY"), ) async def main() -> None: message = await client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Tell me something interesting about async agents", } ], model="claude-3-opus-20240229", ) print(message.content) await main() ``` </details> ### Mistral γ½οΈ Track agents built with the Mistral Python SDK (>=0.32.0). - [AgentOps integration example](./examples/mistral//mistral_example.ipynb) - [Official Mistral documentation](https://docs.mistral.ai) <details> <summary>Installation</summary> ```bash pip install mistralai ``` Sync ```python python from mistralai import Mistral import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) client = Mistral( # This is the default and can be omitted api_key=os.environ.get("MISTRAL_API_KEY"), ) message = client.chat.complete( messages=[ { "role": "user", "content": "Tell me a cool fact about AgentOps", } ], model="open-mistral-nemo", ) print(message.choices[0].message.content) agentops.end_session('Success') ``` Streaming ```python python from mistralai import Mistral import agentops # Beginning of program's code (i.e. main.py, __init__.py) agentops.init(<INSERT YOUR API KEY HERE>) client = Mistral( # This is the default and can be omitted api_key=os.environ.get("MISTRAL_API_KEY"), ) message = client.chat.stream( messages=[ { "role": "user", "content": "Tell me something cool about streaming agents", } ], model="open-mistral-nemo", ) response = "" for event in message: if event.data.choices[0].finish_reason == "stop": print("\n") print(response) print("\n") else: response += event.text agentops.end_session('Success') ``` Async ```python python import asyncio from mistralai import Mistral client = Mistral( # This is the default and can be omitted api_key=os.environ.get("MISTRAL_API_KEY"), ) async def main() -> None: message = await client.chat.complete_async( messages=[ { "role": "user", "content": "Tell me something interesting about async agents", } ], model="open-mistral-nemo", ) print(message.choices[0].message.content) await main() ``` Async Streaming ```python python import asyncio from mistralai import Mistral client = Mistral( # This is the default and can be omitted api_key=os.environ.get("MISTRAL_API_KEY"), ) async def main() -> None: message = await client.chat.stream_async( messages=[ { "role": "user", "content": "Tell me something interesting about async streaming agents", } ], model="open-mistral-nemo", ) response = "" async for event in message: if event.data.choices[0].finish_reason == "stop": print("\n") print(response) print("\n") else: response += event.text await main() ``` </details> ### CamelAI οΉ¨ Track agents built with the CamelAI Python SDK (>=0.32.0). - [CamelAI integration guide](https://docs.camel-ai.org/cookbooks/agents_tracking.html#) - [Official CamelAI documentation](https://docs.camel-ai.org/index.html) <details> <summary>Installation</summary> ```bash pip install camel-ai[all] pip install agentops ``` ```python python #Import Dependencies import agentops import os from getpass import getpass from dotenv import load_dotenv #Set Keys load_dotenv() openai_api_key = os.getenv("OPENAI_API_KEY") or "<your openai key here>" agentops_api_key = os.getenv("AGENTOPS_API_KEY") or "<your agentops key here>" ``` </details> [You can find usage examples here!](examples/camelai_examples/README.md). ### LiteLLM π AgentOps provides support for LiteLLM(>=1.3.1), allowing you to call 100+ LLMs using the same Input/Output Format. - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/litellm) - [Official LiteLLM documentation](https://docs.litellm.ai/docs/providers) <details> <summary>Installation</summary> ```bash pip install litellm ``` ```python python # Do not use LiteLLM like this # from litellm import completion # ... # response = completion(model="claude-3", messages=messages) # Use LiteLLM like this import litellm ... response = litellm.completion(model="claude-3", messages=messages) # or response = await litellm.acompletion(model="claude-3", messages=messages) ``` </details> ### LlamaIndex π¦ AgentOps works seamlessly with applications built using LlamaIndex, a framework for building context-augmented generative AI applications with LLMs. <details> <summary>Installation</summary> ```shell pip install llama-index-instrumentation-agentops ``` To use the handler, import and set ```python from llama_index.core import set_global_handler # NOTE: Feel free to set your AgentOps environment variables (e.g., 'AGENTOPS_API_KEY') # as outlined in the AgentOps documentation, or pass the equivalent keyword arguments # anticipated by AgentOps' AOClient as **eval_params in set_global_handler. set_global_handler("agentops") ``` Check out the [LlamaIndex docs](https://docs.llamaindex.ai/en/stable/module_guides/observability/?h=agentops#agentops) for more details. </details> ### Llama Stack π¦π₯ AgentOps provides support for Llama Stack Python Client(>=0.0.53), allowing you to monitor your Agentic applications. - [AgentOps integration example 1](https://github.com/AgentOps-AI/agentops/pull/530/files/65a5ab4fdcf310326f191d4b870d4f553591e3ea#diff-fdddf65549f3714f8f007ce7dfd1cde720329fe54155d54389dd50fbd81813cb) - [AgentOps integration example 2](https://github.com/AgentOps-AI/agentops/pull/530/files/65a5ab4fdcf310326f191d4b870d4f553591e3ea#diff-6688ff4fb7ab1ce7b1cc9b8362ca27264a3060c16737fb1d850305787a6e3699) - [Official Llama Stack Python Client](https://github.com/meta-llama/llama-stack-client-python) ### SwarmZero AI π Track and analyze SwarmZero agents with full observability. Set an `AGENTOPS_API_KEY` in your environment and initialize AgentOps to get started. - [SwarmZero](https://swarmzero.ai) - Advanced multi-agent framework - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/swarmzero) - [SwarmZero AI integration example](https://docs.swarmzero.ai/examples/ai-agents/build-and-monitor-a-web-search-agent) - [SwarmZero AI - AgentOps documentation](https://docs.swarmzero.ai/sdk/observability/agentops) - [Official SwarmZero Python SDK](https://github.com/swarmzero/swarmzero) <details> <summary>Installation</summary> ```bash pip install swarmzero pip install agentops ``` ```python from dotenv import load_dotenv load_dotenv() import agentops agentops.init(<INSERT YOUR API KEY HERE>) from swarmzero import Agent, Swarm # ... ``` </details> ## Evaluations Roadmap π§ | Platform | Dashboard | Evals | | ---------------------------------------------------------------------------- | ------------------------------------------ | -------------------------------------- | | β Python SDK | β Multi-session and Cross-session metrics | β Custom eval metrics | | π§ Evaluation builder API | β Custom event tag tracking | π Agent scorecards | | π§ [Javascript/Typescript SDK (Alpha)](https://github.com/AgentOps-AI/agentops-node) | β Session replays | π Evaluation playground + leaderboard | ## Debugging Roadmap π§ | Performance testing | Environments | LLM Testing | Reasoning and execution testing | | ----------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------- | ------------------------------------------------- | | β Event latency analysis | π Non-stationary environment testing | π LLM non-deterministic function detection | π§ Infinite loops and recursive thought detection | | β Agent workflow execution pricing | π Multi-modal environments | π§ Token limit overflow flags | π Faulty reasoning detection | | π§ Success validators (external) | π Execution containers | π Context limit overflow flags | π Generative code validators | | π Agent controllers/skill tests | β Honeypot and prompt injection detection ([PromptArmor](https://promptarmor.com)) | β API bill tracking | π Error breakpoint analysis | | π Information context constraint testing | π Anti-agent roadblocks (i.e. Captchas) | π CI/CD integration checks | | | π Regression testing | β Multi-agent framework visualization | | | ### Why AgentOps? π€ Without the right tools, AI agents are slow, expensive, and unreliable. Our mission is to bring your agent from prototype to production. Here's why AgentOps stands out: - **Comprehensive Observability**: Track your AI agents' performance, user interactions, and API usage. - **Real-Time Monitoring**: Get instant insights with session replays, metrics, and live monitoring tools. - **Cost Control**: Monitor and manage your spend on LLM and API calls. - **Failure Detection**: Quickly identify and respond to agent failures and multi-agent interaction issues. - **Tool Usage Statistics**: Understand how your agents utilize external tools with detailed analytics. - **Session-Wide Metrics**: Gain a holistic view of your agents' sessions with comprehensive statistics. AgentOps is designed to make agent observability, testing, and monitoring easy. ## Star History Check out our growth in the community: <img src="https://api.star-history.com/svg?repos=AgentOps-AI/agentops&type=Date" style="max-width: 500px" width="50%" alt="Logo"> ## Popular projects using AgentOps | Repository | Stars | | :-------- | -----: | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/2707039?s=40&v=4" width="20" height="20" alt=""> [geekan](https://github.com/geekan) / [MetaGPT](https://github.com/geekan/MetaGPT) | 42787 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/130722866?s=40&v=4" width="20" height="20" alt=""> [run-llama](https://github.com/run-llama) / [llama_index](https://github.com/run-llama/llama_index) | 34446 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/170677839?s=40&v=4" width="20" height="20" alt=""> [crewAIInc](https://github.com/crewAIInc) / [crewAI](https://github.com/crewAIInc/crewAI) | 18287 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/134388954?s=40&v=4" width="20" height="20" alt=""> [camel-ai](https://github.com/camel-ai) / [camel](https://github.com/camel-ai/camel) | 5166 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/152537519?s=40&v=4" width="20" height="20" alt=""> [superagent-ai](https://github.com/superagent-ai) / [superagent](https://github.com/superagent-ai/superagent) | 5050 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/30197649?s=40&v=4" width="20" height="20" alt=""> [iyaja](https://github.com/iyaja) / [llama-fs](https://github.com/iyaja/llama-fs) | 4713 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/188122941?s=40&v=4" width="20" height="20" alt=""> [ag2ai](https://github.com/ag2ai) / [ag2](https://github.com/ag2ai/ag2) | 4240 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/162546372?s=40&v=4" width="20" height="20" alt=""> [BasedHardware](https://github.com/BasedHardware) / [Omi](https://github.com/BasedHardware/Omi) | 2723 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/454862?s=40&v=4" width="20" height="20" alt=""> [MervinPraison](https://github.com/MervinPraison) / [PraisonAI](https://github.com/MervinPraison/PraisonAI) | 2007 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/140554352?s=40&v=4" width="20" height="20" alt=""> [AgentOps-AI](https://github.com/AgentOps-AI) / [Jaiqu](https://github.com/AgentOps-AI/Jaiqu) | 272 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/173542722?s=48&v=4" width="20" height="20" alt=""> [swarmzero](https://github.com/swarmzero) / [swarmzero](https://github.com/swarmzero/swarmzero) | 195 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/3074263?s=40&v=4" width="20" height="20" alt=""> [strnad](https://github.com/strnad) / [CrewAI-Studio](https://github.com/strnad/CrewAI-Studio) | 134 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/18406448?s=40&v=4" width="20" height="20" alt=""> [alejandro-ao](https://github.com/alejandro-ao) / [exa-crewai](https://github.com/alejandro-ao/exa-crewai) | 55 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/64493665?s=40&v=4" width="20" height="20" alt=""> [tonykipkemboi](https://github.com/tonykipkemboi) / [youtube_yapper_trapper](https://github.com/tonykipkemboi/youtube_yapper_trapper) | 47 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/17598928?s=40&v=4" width="20" height="20" alt=""> [sethcoast](https://github.com/sethcoast) / [cover-letter-builder](https://github.com/sethcoast/cover-letter-builder) | 27 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/109994880?s=40&v=4" width="20" height="20" alt=""> [bhancockio](https://github.com/bhancockio) / [chatgpt4o-analysis](https://github.com/bhancockio/chatgpt4o-analysis) | 19 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/14105911?s=40&v=4" width="20" height="20" alt=""> [breakstring](https://github.com/breakstring) / [Agentic_Story_Book_Workflow](https://github.com/breakstring/Agentic_Story_Book_Workflow) | 14 | |<img class="avatar mr-2" src="https://avatars.githubusercontent.com/u/124134656?s=40&v=4" width="20" height="20" alt=""> [MULTI-ON](https://github.com/MULTI-ON) / [multion-python](https://github.com/MULTI-ON/multion-python) | 13 | _Generated using [github-dependents-info](https://github.com/nvuillam/github-dependents-info), by [Nicolas Vuillamy](https://github.com/nvuillam)_