openenv/pr_784/en/_app/immutable/nodes/7.4e30acfe.js

import{s as Ye,n as Ae,o as Pe}from"../chunks/scheduler.2b22cead.js";import{S as Be,i as Ne,e as s,s as i,c as r,h as Ie,a as o,d as n,b as a,f as We,g as p,j as f,k as Se,l as Ue,m as l,n as m,t as u,o as c,p as d}from"../chunks/index.1a0e8013.js";import{C as qe,H as v,E as Ee}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.e2bf9d10.js";import{C as _e}from"../chunks/CodeBlock.fb3fd2b3.js";function Xe(be){let $,X,q,z,h,V,g,F,T,Me="This environment exposes a Calendar Gym tools through the OpenEnv reset/step/state interface. The server runs a FastAPI app that serves the OpenEnv endpoints.",Q,_,D,b,O,M,R,w,we=`On Server health success response will be:
<code>{&quot;status&quot;:&quot;healthy&quot;,&quot;service&quot;:&quot;calendar-env&quot;}</code>`,K,y,ee,x,te,C,ne,L,le,k,ye="For a quick demo, simply update <code>llm_api_key</code> in <code>scenario_config.json</code> and run:",ie,J,ae,H,xe="The existing config includes a sample scenario for testing.",se,j,oe,G,Ce="To customize for your use case, edit <code>scenario_config.json</code> and update these fields:",re,Z,Le="<strong>llm variables:</strong>",pe,W,ke="<li><code>llm_api_key</code> - Your OpenAI/Anthropic/Google API key (or set via env var)</li> <li><code>llm_model</code> - Model name (e.g., <code>gpt-4o-mini</code>, <code>claude-3-5-sonnet-20241022</code>)</li> <li><code>llm_provider</code> - Provider: <code>openai</code>, <code>anthropic</code>, or <code>google</code></li>",me,S,Je="<strong>Scenario Variables</strong>",ue,Y,He="<li><code>user_prompt</code> - Task for the agent to complete</li> <li><code>system_prompt</code> - Instructions for agent behavior</li> <li><code>context</code> - The auth headers for gym like (x-access-token)</li> <li><code>seed_database_file</code> - Path to SQL file for custom data</li> <li><code>verifiers</code> - SQL queries to validate task completion</li> <li><code>expected_tools</code> - Tools agent should use (for tracking)</li>",ce,A,de,P,je="<strong>Run scenario-based benchmark:</strong>",fe,B,$e,N,Ge="Output will be saved to <code>response_output/</code> folder with execution details, tool calls, and verification results.",ve,I,Ze=`<strong>Notebook Evaluation:</strong>
For interactive evaluation and testing, use the: <a href="client_notebooks/OpenEnv_and_mcp_Single_Gym_Client_Meta_Turing.ipynb"><code>Jupyter notebook</code></a>`,he,U,ge,E,Te;return h=new qe({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),g=new v({props:{title:"Calendar Environment",local:"calendar-environment",headingTag:"h1"}}),_=new v({props:{title:"Server Setup",local:"server-setup",headingTag:"h2"}}),b=new v({props:{title:"Docker (Recommended)",local:"docker-recommended",headingTag:"h3"}}),M=new _e({props:{code:"Y2QlMjBlbnZzJTJGY2FsZW5kYXJfZW52JTBBZG9ja2VyJTIwYnVpbGQlMjAtdCUyMGNhbGVuZGFyLWVudiUzQWxhdGVzdCUyMC4lMEFkb2NrZXIlMjBydW4lMjAtLXJtJTIwLXAlMjA4MDA0JTNBODAwNCUyMGNhbGVuZGFyLWVudiUzQWxhdGVzdCUwQWN1cmwlMjBodHRwJTNBJTJGJTJGbG9jYWxob3N0JTNBODAwNCUyRmhlYWx0aA==",highlighted:`<span class="hljs-built_in">cd</span> envs/calendar_env
docker build -t calendar-env:latest .
docker run --<span class="hljs-built_in">rm</span> -p 8004:8004 calendar-env:latest
curl http://localhost:8004/health`,lang:"bash",wrap:!1}}),y=new v({props:{title:"Without Docker",local:"without-docker",headingTag:"h3"}}),x=new _e({props:{code:"Y2QlMjBlbnZzJTJGY2FsZW5kYXJfZW52JTBBcHl0aG9uMyUyMC1tJTIwdmVudiUyMHZlbnYlMEFzb3VyY2UlMjB2ZW52JTJGYmluJTJGYWN0aXZhdGUlMEFwaXAlMjBpbnN0YWxsJTIwLXIlMjByZXF1aXJlbWVudHMudHh0JTBBdXZpY29ybiUyMHNlcnZlci5hcHAlM0FhcHAlMjAtLWhvc3QlMjAwLjAuMC4wJTIwLS1wb3J0JTIwODAwNA==",highlighted:`<span class="hljs-built_in">cd</span> envs/calendar_env
python3 -m venv venv
<span class="hljs-built_in">source</span> venv/bin/activate
pip install -r requirements.txt
uvicorn server.app:app --host 0.0.0.0 --port 8004`,lang:"bash",wrap:!1}}),C=new v({props:{title:"Client Setup",local:"client-setup",headingTag:"h2"}}),L=new v({props:{title:"Quick Start (Demo)",local:"quick-start-demo",headingTag:"h3"}}),J=new _e({props:{code:"cHl0aG9uJTIwY2xpZW50LnB5JTIwLS1zY2VuYXJpbyUyMHNjZW5hcmlvX2NvbmZpZy5qc29u",highlighted:"python client.py --scenario scenario_config.json",lang:"bash",wrap:!1}}),j=new v({props:{title:"Configure Scenario",local:"configure-scenario",headingTag:"h3"}}),A=new v({props:{title:"Run Client",local:"run-client",headingTag:"h3"}}),B=new _e({props:{code:"cHl0aG9uJTIwY2xpZW50LnB5JTIwLS1zY2VuYXJpbyUyMHNjZW5hcmlvX2NvbmZpZy5qc29uJTIw",highlighted:"python client.py --scenario scenario_config.json ",lang:"bash",wrap:!1}}),U=new 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