base on Python SDK for AI agent monitoring, LLM cost tracking, benchmarking, and more. Integrates with most LLMs and agent frameworks including OpenAI Agents SDK, CrewAI, Langchain, Autogen, AG2, and CamelAI <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> </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. ## Key Integrations 🔌 <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/v1/integrations/openai-agents"><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/autogen/ag2.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> | | | | ------------------------------------- | ------------------------------------------------------------- | | 📊 **Replay Analytics and Debugging** | Step-by-step agent execution graphs | | 💸 **LLM Cost Management** | Track spend with LLM foundation model providers | | 🧪 **Agent Benchmarking** | Test your agents against 1,000+ evals | | 🔐 **Compliance and Security** | Detect common prompt injection and data exfiltration exploits | | 🤝 **Framework Integrations** | Native Integrations with CrewAI, AG2 (AutoGen), Camel AI, & LangChain | ## Quick Start ⌨️ ```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/> <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 open> <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 🦾 ### OpenAI Agents SDK 🖇️ Build multi-agent systems with tools, handoffs, and guardrails. AgentOps natively integrates with OpenAI Agents. ```bash pip install openai-agents ``` - [AgentOps integration example](https://docs.agentops.ai/v1/integrations/agentssdk) - [Official CrewAI documentation](https://docs.crewai.com/how-to/AgentOps-Observability) ### CrewAI 🛶 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 🤖 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://docs.ag2.ai/notebooks/agentchat_agentops) - [AG2 - AgentOps Documentation](https://docs.ag2.ai/docs/ecosystem/agentops) ### Camel AI 🐪 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 🦜🔗 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.partners.langchain_callback_handler 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_examples.ipynb) for more details including Async handlers. </details> ### Cohere ⌨️ 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 ﹨ 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 〽️ 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 ﹨ 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 🚅 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 🦙 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 🦙🥞 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 🐝 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> ## Time travel debugging 🔮 <div style="justify-content: center"> <img src="docs/images/external/app_screenshots/time_travel_banner.png" alt="Time Travel Banner"> </div> <br /> [Try it out!](https://app.agentops.ai/timetravel) ## Agent Arena 🥊 (coming soon!) ## Evaluations Roadmap 🧭 | Platform | Dashboard | Evals | | ---------------------------------------------------------------------------- | ------------------------------------------ | -------------------------------------- | | ✅ Python SDK | ✅ Multi-session and Cross-session metrics | ✅ Custom eval metrics | | 🚧 Evaluation builder API | ✅ Custom event tag tracking | 🔜 Agent scorecards | | ✅ [Javascript/Typescript SDK](https://github.com/AgentOps-AI/agentops-node) | ✅ Session replays | 🔜 Evaluation playground + leaderboard | ## Debugging Roadmap 🧭 | Performance testing | Environments | LLM Testing | Reasoning and execution testing | | ----------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------- | ------------------------------------------------- | | ✅ Event latency analysis | 🔜 Non-stationary environment testing | 🔜 LLM non-deterministic function detection | 🚧 Infinite loops and recursive thought detection | | ✅ Agent workflow execution pricing | 🔜 Multi-modal environments | 🚧 Token limit overflow flags | 🔜 Faulty reasoning detection | | 🚧 Success validators (external) | 🔜 Execution containers | 🔜 Context limit overflow flags | 🔜 Generative code validators | | 🔜 Agent controllers/skill tests | ✅ Honeypot and prompt injection detection ([PromptArmor](https://promptarmor.com)) | 🔜 API bill tracking | 🔜 Error breakpoint analysis | | 🔜 Information context constraint testing | 🔜 Anti-agent roadblocks (i.e. Captchas) | 🔜 CI/CD integration checks | | | 🔜 Regression testing | 🔜 Multi-agent framework visualization | | | ### Why AgentOps? 🤔 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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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/162546372?s=40&v=4" width="20" height="20" alt=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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=""> &nbsp; [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)_ ", Assign "at most 3 tags" to the expected json: {"id":"10187","tags":[]} "only from the tags list I provide: [{"id":77,"name":"3d"},{"id":89,"name":"agent"},{"id":17,"name":"ai"},{"id":54,"name":"algorithm"},{"id":24,"name":"api"},{"id":44,"name":"authentication"},{"id":3,"name":"aws"},{"id":27,"name":"backend"},{"id":60,"name":"benchmark"},{"id":72,"name":"best-practices"},{"id":39,"name":"bitcoin"},{"id":37,"name":"blockchain"},{"id":1,"name":"blog"},{"id":45,"name":"bundler"},{"id":58,"name":"cache"},{"id":21,"name":"chat"},{"id":49,"name":"cicd"},{"id":4,"name":"cli"},{"id":64,"name":"cloud-native"},{"id":48,"name":"cms"},{"id":61,"name":"compiler"},{"id":68,"name":"containerization"},{"id":92,"name":"crm"},{"id":34,"name":"data"},{"id":47,"name":"database"},{"id":8,"name":"declarative-gui "},{"id":9,"name":"deploy-tool"},{"id":53,"name":"desktop-app"},{"id":6,"name":"dev-exp-lib"},{"id":59,"name":"dev-tool"},{"id":13,"name":"ecommerce"},{"id":26,"name":"editor"},{"id":66,"name":"emulator"},{"id":62,"name":"filesystem"},{"id":80,"name":"finance"},{"id":15,"name":"firmware"},{"id":73,"name":"for-fun"},{"id":2,"name":"framework"},{"id":11,"name":"frontend"},{"id":22,"name":"game"},{"id":81,"name":"game-engine "},{"id":23,"name":"graphql"},{"id":84,"name":"gui"},{"id":91,"name":"http"},{"id":5,"name":"http-client"},{"id":51,"name":"iac"},{"id":30,"name":"ide"},{"id":78,"name":"iot"},{"id":40,"name":"json"},{"id":83,"name":"julian"},{"id":38,"name":"k8s"},{"id":31,"name":"language"},{"id":10,"name":"learning-resource"},{"id":33,"name":"lib"},{"id":41,"name":"linter"},{"id":28,"name":"lms"},{"id":16,"name":"logging"},{"id":76,"name":"low-code"},{"id":90,"name":"message-queue"},{"id":42,"name":"mobile-app"},{"id":18,"name":"monitoring"},{"id":36,"name":"networking"},{"id":7,"name":"node-version"},{"id":55,"name":"nosql"},{"id":57,"name":"observability"},{"id":46,"name":"orm"},{"id":52,"name":"os"},{"id":14,"name":"parser"},{"id":74,"name":"react"},{"id":82,"name":"real-time"},{"id":56,"name":"robot"},{"id":65,"name":"runtime"},{"id":32,"name":"sdk"},{"id":71,"name":"search"},{"id":63,"name":"secrets"},{"id":25,"name":"security"},{"id":85,"name":"server"},{"id":86,"name":"serverless"},{"id":70,"name":"storage"},{"id":75,"name":"system-design"},{"id":79,"name":"terminal"},{"id":29,"name":"testing"},{"id":12,"name":"ui"},{"id":50,"name":"ux"},{"id":88,"name":"video"},{"id":20,"name":"web-app"},{"id":35,"name":"web-server"},{"id":43,"name":"webassembly"},{"id":69,"name":"workflow"},{"id":87,"name":"yaml"}]" returns me the "expected json"