| Name | agentops JSON |
| Version |
0.3.21
JSON |
| download |
| home_page | None |
| Summary | Observability and DevTool Platform for AI Agents |
| upload_time | 2024-12-11 12:24:02 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.7 |
| license | None |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
<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 style="justify-content: center">
<img src="docs/images/external/app_screenshots/dashboard-banner.png" alt="Dashboard Banner">
</div>
<br/>
AgentOps helps developers build, evaluate, and monitor AI agents. From prototype to production.
| | |
| ------------------------------------- | ------------------------------------------------------------- |
| ๐ **Replay Analytics and Debugging** | Step-by-step agent execution graphs |
| ๐ธ **LLM Cost Management** | Track spend with LLM foundation model providers |
| ๐งช **Agent Benchmarking** | Test your agents against 1,000+ evals |
| ๐ **Compliance and Security** | Detect common prompt injection and data exfiltration exploits |
| ๐ค **Framework Integrations** | Native Integrations with CrewAI, AutoGen, & LangChain |
## Quick Start โจ๏ธ
```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
# Automatically associate all Events with the agent that originated them
from agentops import track_agent
@track_agent(name='SomeCustomName')
class MyAgent:
...
```
```python
# Automatically create ToolEvents for tools that agents will use
from agentops import record_tool
@record_tool('SampleToolName')
def sample_tool(...):
...
```
```python
# Automatically create ActionEvents for other functions.
from agentops import record_action
@agentops.record_action('sample function being record')
def sample_function(...):
...
```
```python
# Manually record any other Events
from agentops import record, ActionEvent
record(ActionEvent("received_user_input"))
```
## Integrations ๐ฆพ
### CrewAI ๐ถ
Build Crew agents with observability with only 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)
### AutoGen ๐ค
With only two lines of code, add full observability and monitoring to Autogen agents. Set an `AGENTOPS_API_KEY` in your environment and call `agentops.init()`
- [Autogen Observability Example](https://microsoft.github.io/autogen/docs/notebooks/agentchat_agentops)
- [Autogen - AgentOps Documentation](https://microsoft.github.io/autogen/docs/ecosystem/agentops)
### Langchain ๐ฆ๐
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 โจ๏ธ
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 ๏นจ
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 ใฝ๏ธ
Track agents built with the Anthropic 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>
### LiteLLM ๐
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 ๐ฆ
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 ๐ฆ๐ฅ
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)
## Time travel debugging ๐ฎ
<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 ๐ฅ
(coming soon!)
## Evaluations Roadmap ๐งญ
| Platform | Dashboard | Evals |
| ---------------------------------------------------------------------------- | ------------------------------------------ | -------------------------------------- |
| โ
Python SDK | โ
Multi-session and Cross-session metrics | โ
Custom eval metrics |
| ๐ง Evaluation builder API | โ
Custom event tag trackingย | ๐ Agent scorecards |
| โ
[Javascript/Typescript SDK](https://github.com/AgentOps-AI/agentops-node) | โ
Session replays | ๐ Evaluation playground + leaderboard |
## Debugging Roadmap ๐งญ
| Performance testing | Environments | LLM Testing | Reasoning and execution testing |
| ----------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------- | ------------------------------------------------- |
| โ
Event latency analysis | ๐ Non-stationary environment testing | ๐ LLM non-deterministic function detection | ๐ง Infinite loops and recursive thought detection |
| โ
Agent workflow execution pricing | ๐ Multi-modal environments | ๐ง Token limit overflow flags | ๐ Faulty reasoning detection |
| ๐ง Success validators (external) | ๐ Execution containers | ๐ Context limit overflow flags | ๐ Generative code validators |
| ๐ Agent controllers/skill tests | โ
Honeypot and prompt injection detection ([PromptArmor](https://promptarmor.com)) | ๐ API bill tracking | ๐ Error breakpoint analysis |
| ๐ Information context constraint testing | ๐ Anti-agent roadblocks (i.e. Captchas) | ๐ CI/CD integration checks | |
| ๐ Regression testing | ๐ Multi-agent framework visualization | | |
### Why AgentOps? ๐ค
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 |
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|<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/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)_
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"download_url": "https://files.pythonhosted.org/packages/83/f6/bfd27fa4b948c353eaff579dafdf4eb54833f5c526e00c6f2faee4b467a8/agentops-0.3.21.tar.gz",
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"description": "<div align=\"center\">\n <a href=\"https://agentops.ai?ref=gh\">\n <img src=\"docs/images/external/logo/github-banner.png\" alt=\"Logo\">\n </a>\n</div>\n\n<div align=\"center\">\n <em>Observability and DevTool platform for AI Agents</em>\n</div>\n\n<br />\n\n<div align=\"center\">\n <a href=\"https://pepy.tech/project/agentops\">\n <img src=\"https://static.pepy.tech/badge/agentops/month\" alt=\"Downloads\">\n </a>\n <a href=\"https://github.com/agentops-ai/agentops/issues\">\n <img src=\"https://img.shields.io/github/commit-activity/m/agentops-ai/agentops\" alt=\"git commit activity\">\n </a>\n <img src=\"https://img.shields.io/pypi/v/agentops?&color=3670A0\" alt=\"PyPI - Version\">\n <a href=\"https://opensource.org/licenses/MIT\">\n <img src=\"https://img.shields.io/badge/License-MIT-yellow.svg?&color=3670A0\" alt=\"License: MIT\">\n </a>\n</div>\n\n<p align=\"center\">\n <a href=\"https://twitter.com/agentopsai/\">\n <img src=\"https://img.shields.io/twitter/follow/agentopsai?style=social\" alt=\"Twitter\" style=\"height: 20px;\">\n </a>\n <a href=\"https://discord.gg/FagdcwwXRR\">\n <img src=\"https://img.shields.io/badge/discord-7289da.svg?style=flat-square&logo=discord\" alt=\"Discord\" style=\"height: 20px;\">\n </a>\n <a href=\"https://app.agentops.ai/?ref=gh\">\n <img src=\"https://img.shields.io/badge/Dashboard-blue.svg?style=flat-square\" alt=\"Dashboard\" style=\"height: 20px;\">\n </a>\n <a href=\"https://docs.agentops.ai/introduction\">\n <img src=\"https://img.shields.io/badge/Documentation-orange.svg?style=flat-square\" alt=\"Documentation\" style=\"height: 20px;\">\n </a>\n <a href=\"https://entelligence.ai/AgentOps-AI&agentops\">\n <img src=\"https://img.shields.io/badge/Chat%20with%20Docs-green.svg?style=flat-square\" alt=\"Chat with Docs\" style=\"height: 20px;\">\n </a>\n</p>\n\n\n\n<div style=\"justify-content: center\">\n <img src=\"docs/images/external/app_screenshots/dashboard-banner.png\" alt=\"Dashboard Banner\">\n</div>\n\n<br/>\n\n\nAgentOps helps developers build, evaluate, and monitor AI agents. From prototype to production.\n\n| | |\n| ------------------------------------- | ------------------------------------------------------------- |\n| \ud83d\udcca **Replay Analytics and Debugging** | Step-by-step agent execution graphs |\n| \ud83d\udcb8 **LLM Cost Management** | Track spend with LLM foundation model providers |\n| \ud83e\uddea **Agent Benchmarking** | Test your agents against 1,000+ evals |\n| \ud83d\udd10 **Compliance and Security** | Detect common prompt injection and data exfiltration exploits |\n| \ud83e\udd1d **Framework Integrations** | Native Integrations with CrewAI, AutoGen, & LangChain |\n\n## Quick Start \u2328\ufe0f\n\n```bash\npip install agentops\n```\n\n\n#### Session replays in 2 lines of code\n\nInitialize the AgentOps client and automatically get analytics on all your LLM calls.\n\n[Get an API key](https://app.agentops.ai/settings/projects)\n\n```python\nimport agentops\n\n# Beginning of your program (i.e. main.py, __init__.py)\nagentops.init( < INSERT YOUR API KEY HERE >)\n\n...\n\n# End of program\nagentops.end_session('Success')\n```\n\nAll your sessions can be viewed on the [AgentOps dashboard](https://app.agentops.ai?ref=gh)\n<br/>\n\n<details>\n <summary>Agent Debugging</summary>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/session-drilldown-metadata.png\" style=\"width: 90%;\" alt=\"Agent Metadata\"/>\n </a>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/chat-viewer.png\" style=\"width: 90%;\" alt=\"Chat Viewer\"/>\n </a>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/session-drilldown-graphs.png\" style=\"width: 90%;\" alt=\"Event Graphs\"/>\n </a>\n</details>\n\n<details>\n <summary>Session Replays</summary>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/session-replay.png\" style=\"width: 90%;\" alt=\"Session Replays\"/>\n </a>\n</details>\n\n<details open>\n <summary>Summary Analytics</summary>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/overview.png\" style=\"width: 90%;\" alt=\"Summary Analytics\"/>\n </a>\n <a href=\"https://app.agentops.ai?ref=gh\">\n <img src=\"docs/images/external/app_screenshots/overview-charts.png\" style=\"width: 90%;\" alt=\"Summary Analytics Charts\"/>\n </a>\n</details>\n\n\n### First class Developer Experience\nAdd powerful observability to your agents, tools, and functions with as little code as possible: one line at a time.\n<br/>\nRefer to our [documentation](http://docs.agentops.ai)\n\n```python\n# Automatically associate all Events with the agent that originated them\nfrom agentops import track_agent\n\n@track_agent(name='SomeCustomName')\nclass MyAgent:\n ...\n```\n\n```python\n# Automatically create ToolEvents for tools that agents will use\nfrom agentops import record_tool\n\n@record_tool('SampleToolName')\ndef sample_tool(...):\n ...\n```\n\n```python\n# Automatically create ActionEvents for other functions.\nfrom agentops import record_action\n\n@agentops.record_action('sample function being record')\ndef sample_function(...):\n ...\n```\n\n```python\n# Manually record any other Events\nfrom agentops import record, ActionEvent\n\nrecord(ActionEvent(\"received_user_input\"))\n```\n\n## Integrations \ud83e\uddbe\n\n### CrewAI \ud83d\udef6\n\nBuild Crew agents with observability with only 2 lines of code. Simply set an `AGENTOPS_API_KEY` in your environment, and your crews will get automatic monitoring on the AgentOps dashboard.\n\n```bash\npip install 'crewai[agentops]'\n```\n\n- [AgentOps integration example](https://docs.agentops.ai/v1/integrations/crewai)\n- [Official CrewAI documentation](https://docs.crewai.com/how-to/AgentOps-Observability)\n\n### AutoGen \ud83e\udd16\nWith only two lines of code, add full observability and monitoring to Autogen agents. Set an `AGENTOPS_API_KEY` in your environment and call `agentops.init()`\n\n- [Autogen Observability Example](https://microsoft.github.io/autogen/docs/notebooks/agentchat_agentops)\n- [Autogen - AgentOps Documentation](https://microsoft.github.io/autogen/docs/ecosystem/agentops)\n\n### Langchain \ud83e\udd9c\ud83d\udd17\n\nAgentOps works seamlessly with applications built using Langchain. To use the handler, install Langchain as an optional dependency:\n\n<details>\n <summary>Installation</summary>\n \n```shell\npip install agentops[langchain]\n```\n\nTo use the handler, import and set\n\n```python\nimport os\nfrom langchain.chat_models import ChatOpenAI\nfrom langchain.agents import initialize_agent, AgentType\nfrom agentops.partners.langchain_callback_handler import LangchainCallbackHandler\n\nAGENTOPS_API_KEY = os.environ['AGENTOPS_API_KEY']\nhandler = LangchainCallbackHandler(api_key=AGENTOPS_API_KEY, tags=['Langchain Example'])\n\nllm = ChatOpenAI(openai_api_key=OPENAI_API_KEY,\n callbacks=[handler],\n model='gpt-3.5-turbo')\n\nagent = initialize_agent(tools,\n llm,\n agent=AgentType.CHAT_ZERO_SHOT_REACT_DESCRIPTION,\n verbose=True,\n callbacks=[handler], # You must pass in a callback handler to record your agent\n handle_parsing_errors=True)\n```\n\nCheck out the [Langchain Examples Notebook](./examples/langchain_examples.ipynb) for more details including Async handlers.\n\n</details>\n\n### Cohere \u2328\ufe0f\n\nFirst class support for Cohere(>=5.4.0). This is a living integration, should you need any added functionality please message us on Discord!\n\n- [AgentOps integration example](https://docs.agentops.ai/v1/integrations/cohere)\n- [Official Cohere documentation](https://docs.cohere.com/reference/about)\n\n<details>\n <summary>Installation</summary>\n \n```bash\npip install cohere\n```\n\n```python python\nimport cohere\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\nco = cohere.Client()\n\nchat = co.chat(\n message=\"Is it pronounced ceaux-hear or co-hehray?\"\n)\n\nprint(chat)\n\nagentops.end_session('Success')\n```\n\n```python python\nimport cohere\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\n\nco = cohere.Client()\n\nstream = co.chat_stream(\n message=\"Write me a haiku about the synergies between Cohere and AgentOps\"\n)\n\nfor event in stream:\n if event.event_type == \"text-generation\":\n print(event.text, end='')\n\nagentops.end_session('Success')\n```\n</details>\n\n\n### Anthropic \ufe68\n\nTrack agents built with the Anthropic Python SDK (>=0.32.0).\n\n- [AgentOps integration guide](https://docs.agentops.ai/v1/integrations/anthropic)\n- [Official Anthropic documentation](https://docs.anthropic.com/en/docs/welcome)\n\n<details>\n <summary>Installation</summary>\n \n```bash\npip install anthropic\n```\n\n```python python\nimport anthropic\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\n\nclient = anthropic.Anthropic(\n # This is the default and can be omitted\n api_key=os.environ.get(\"ANTHROPIC_API_KEY\"),\n)\n\nmessage = client.messages.create(\n max_tokens=1024,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me a cool fact about AgentOps\",\n }\n ],\n model=\"claude-3-opus-20240229\",\n )\nprint(message.content)\n\nagentops.end_session('Success')\n```\n\nStreaming\n```python python\nimport anthropic\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\n\nclient = anthropic.Anthropic(\n # This is the default and can be omitted\n api_key=os.environ.get(\"ANTHROPIC_API_KEY\"),\n)\n\nstream = client.messages.create(\n max_tokens=1024,\n model=\"claude-3-opus-20240229\",\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me something cool about streaming agents\",\n }\n ],\n stream=True,\n)\n\nresponse = \"\"\nfor event in stream:\n if event.type == \"content_block_delta\":\n response += event.delta.text\n elif event.type == \"message_stop\":\n print(\"\\n\")\n print(response)\n print(\"\\n\")\n```\n\nAsync\n\n```python python\nimport asyncio\nfrom anthropic import AsyncAnthropic\n\nclient = AsyncAnthropic(\n # This is the default and can be omitted\n api_key=os.environ.get(\"ANTHROPIC_API_KEY\"),\n)\n\n\nasync def main() -> None:\n message = await client.messages.create(\n max_tokens=1024,\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me something interesting about async agents\",\n }\n ],\n model=\"claude-3-opus-20240229\",\n )\n print(message.content)\n\n\nawait main()\n```\n</details>\n\n### Mistral \u303d\ufe0f\n\nTrack agents built with the Anthropic Python SDK (>=0.32.0).\n\n- [AgentOps integration example](./examples/mistral//mistral_example.ipynb)\n- [Official Mistral documentation](https://docs.mistral.ai)\n\n<details>\n <summary>Installation</summary>\n \n```bash\npip install mistralai\n```\n\nSync\n\n```python python\nfrom mistralai import Mistral\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\n\nclient = Mistral(\n # This is the default and can be omitted\n api_key=os.environ.get(\"MISTRAL_API_KEY\"),\n)\n\nmessage = client.chat.complete(\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me a cool fact about AgentOps\",\n }\n ],\n model=\"open-mistral-nemo\",\n )\nprint(message.choices[0].message.content)\n\nagentops.end_session('Success')\n```\n\nStreaming\n\n```python python\nfrom mistralai import Mistral\nimport agentops\n\n# Beginning of program's code (i.e. main.py, __init__.py)\nagentops.init(<INSERT YOUR API KEY HERE>)\n\nclient = Mistral(\n # This is the default and can be omitted\n api_key=os.environ.get(\"MISTRAL_API_KEY\"),\n)\n\nmessage = client.chat.stream(\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me something cool about streaming agents\",\n }\n ],\n model=\"open-mistral-nemo\",\n )\n\nresponse = \"\"\nfor event in message:\n if event.data.choices[0].finish_reason == \"stop\":\n print(\"\\n\")\n print(response)\n print(\"\\n\")\n else:\n response += event.text\n\nagentops.end_session('Success')\n```\n\nAsync\n\n```python python\nimport asyncio\nfrom mistralai import Mistral\n\nclient = Mistral(\n # This is the default and can be omitted\n api_key=os.environ.get(\"MISTRAL_API_KEY\"),\n)\n\n\nasync def main() -> None:\n message = await client.chat.complete_async(\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me something interesting about async agents\",\n }\n ],\n model=\"open-mistral-nemo\",\n )\n print(message.choices[0].message.content)\n\n\nawait main()\n```\n\nAsync Streaming\n\n```python python\nimport asyncio\nfrom mistralai import Mistral\n\nclient = Mistral(\n # This is the default and can be omitted\n api_key=os.environ.get(\"MISTRAL_API_KEY\"),\n)\n\n\nasync def main() -> None:\n message = await client.chat.stream_async(\n messages=[\n {\n \"role\": \"user\",\n \"content\": \"Tell me something interesting about async streaming agents\",\n }\n ],\n model=\"open-mistral-nemo\",\n )\n\n response = \"\"\n async for event in message:\n if event.data.choices[0].finish_reason == \"stop\":\n print(\"\\n\")\n print(response)\n print(\"\\n\")\n else:\n response += event.text\n\n\nawait main()\n```\n</details>\n\n### LiteLLM \ud83d\ude85\n\nAgentOps provides support for LiteLLM(>=1.3.1), allowing you to call 100+ LLMs using the same Input/Output Format. \n\n- [AgentOps integration example](https://docs.agentops.ai/v1/integrations/litellm)\n- [Official LiteLLM documentation](https://docs.litellm.ai/docs/providers)\n\n<details>\n <summary>Installation</summary>\n \n```bash\npip install litellm\n```\n\n```python python\n# Do not use LiteLLM like this\n# from litellm import completion\n# ...\n# response = completion(model=\"claude-3\", messages=messages)\n\n# Use LiteLLM like this\nimport litellm\n...\nresponse = litellm.completion(model=\"claude-3\", messages=messages)\n# or\nresponse = await litellm.acompletion(model=\"claude-3\", messages=messages)\n```\n</details>\n\n### LlamaIndex \ud83e\udd99\n\n\nAgentOps works seamlessly with applications built using LlamaIndex, a framework for building context-augmented generative AI applications with LLMs.\n\n<details>\n <summary>Installation</summary>\n \n```shell\npip install llama-index-instrumentation-agentops\n```\n\nTo use the handler, import and set\n\n```python\nfrom llama_index.core import set_global_handler\n\n# NOTE: Feel free to set your AgentOps environment variables (e.g., 'AGENTOPS_API_KEY')\n# as outlined in the AgentOps documentation, or pass the equivalent keyword arguments\n# anticipated by AgentOps' AOClient as **eval_params in set_global_handler.\n\nset_global_handler(\"agentops\")\n```\n\nCheck out the [LlamaIndex docs](https://docs.llamaindex.ai/en/stable/module_guides/observability/?h=agentops#agentops) for more details.\n\n</details>\n\n### Llama Stack \ud83e\udd99\ud83e\udd5e\n\nAgentOps provides support for Llama Stack Python Client(>=0.0.53), allowing you to monitor your Agentic applications. \n\n- [AgentOps integration example 1](https://github.com/AgentOps-AI/agentops/pull/530/files/65a5ab4fdcf310326f191d4b870d4f553591e3ea#diff-fdddf65549f3714f8f007ce7dfd1cde720329fe54155d54389dd50fbd81813cb)\n- [AgentOps integration example 2](https://github.com/AgentOps-AI/agentops/pull/530/files/65a5ab4fdcf310326f191d4b870d4f553591e3ea#diff-6688ff4fb7ab1ce7b1cc9b8362ca27264a3060c16737fb1d850305787a6e3699)\n- [Official Llama Stack Python Client](https://github.com/meta-llama/llama-stack-client-python)\n\n## Time travel debugging \ud83d\udd2e\n\n<div style=\"justify-content: center\">\n <img src=\"docs/images/external/app_screenshots/time_travel_banner.png\" alt=\"Time Travel Banner\">\n</div>\n\n<br />\n\n[Try it out!](https://app.agentops.ai/timetravel)\n\n## Agent Arena \ud83e\udd4a\n\n(coming soon!)\n\n## Evaluations Roadmap \ud83e\udded\n\n| Platform | Dashboard | Evals |\n| ---------------------------------------------------------------------------- | ------------------------------------------ | -------------------------------------- |\n| \u2705 Python SDK | \u2705 Multi-session and Cross-session metrics | \u2705 Custom eval metrics |\n| \ud83d\udea7 Evaluation builder API | \u2705 Custom event tag tracking\u00a0 | \ud83d\udd1c Agent scorecards |\n| \u2705 [Javascript/Typescript SDK](https://github.com/AgentOps-AI/agentops-node) | \u2705 Session replays | \ud83d\udd1c Evaluation playground + leaderboard |\n\n## Debugging Roadmap \ud83e\udded\n\n| Performance testing | Environments | LLM Testing | Reasoning and execution testing |\n| ----------------------------------------- | ----------------------------------------------------------------------------------- | ------------------------------------------- | ------------------------------------------------- |\n| \u2705 Event latency analysis | \ud83d\udd1c Non-stationary environment testing | \ud83d\udd1c LLM non-deterministic function detection | \ud83d\udea7 Infinite loops and recursive thought detection |\n| \u2705 Agent workflow execution pricing | \ud83d\udd1c Multi-modal environments | \ud83d\udea7 Token limit overflow flags | \ud83d\udd1c Faulty reasoning detection |\n| \ud83d\udea7 Success validators (external) | \ud83d\udd1c Execution containers | \ud83d\udd1c Context limit overflow flags | \ud83d\udd1c Generative code validators |\n| \ud83d\udd1c Agent controllers/skill tests | \u2705 Honeypot and prompt injection detection ([PromptArmor](https://promptarmor.com)) | \ud83d\udd1c API bill tracking | \ud83d\udd1c Error breakpoint analysis |\n| \ud83d\udd1c Information context constraint testing | \ud83d\udd1c Anti-agent roadblocks (i.e. Captchas) | \ud83d\udd1c CI/CD integration checks | |\n| \ud83d\udd1c Regression testing | \ud83d\udd1c Multi-agent framework visualization | | |\n\n### Why AgentOps? \ud83e\udd14\n\nWithout 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:\n\n- **Comprehensive Observability**: Track your AI agents' performance, user interactions, and API usage.\n- **Real-Time Monitoring**: Get instant insights with session replays, metrics, and live monitoring tools.\n- **Cost Control**: Monitor and manage your spend on LLM and API calls.\n- **Failure Detection**: Quickly identify and respond to agent failures and multi-agent interaction issues.\n- **Tool Usage Statistics**: Understand how your agents utilize external tools with detailed analytics.\n- **Session-Wide Metrics**: Gain a holistic view of your agents' sessions with comprehensive statistics.\n\nAgentOps is designed to make agent observability, testing, and monitoring easy.\n\n\n## Star History\n\nCheck out our growth in the community:\n\n<img src=\"https://api.star-history.com/svg?repos=AgentOps-AI/agentops&type=Date\" style=\"max-width: 500px\" width=\"50%\" alt=\"Logo\">\n\n## Popular projects using AgentOps\n\n\n| Repository | Stars |\n| :-------- | -----: |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n|<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 |\n\n\n_Generated using [github-dependents-info](https://github.com/nvuillam/github-dependents-info), by [Nicolas Vuillamy](https://github.com/nvuillam)_\n",
"bugtrack_url": null,
"license": null,
"summary": "Observability and DevTool Platform for AI Agents",
"version": "0.3.21",
"project_urls": {
"Homepage": "https://github.com/AgentOps-AI/agentops",
"Issues": "https://github.com/AgentOps-AI/agentops/issues"
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