openenv/pr_813/en/_app/immutable/nodes/28.e1b09efd.js

import{s as ys,n as cs,o as ws}from"../chunks/scheduler.2b22cead.js";import{S as us,i as Us,e as i,s as n,c as p,h as js,a as M,d as l,b as a,f as ms,g as o,j as y,k as Ts,l as ds,m as s,n as J,t as r,o as m,p as T}from"../chunks/index.1a0e8013.js";import{C as Is,H as c,E as gs}from"../chunks/MermaidChart.svelte_svelte_type_style_lang.f5f19e58.js";import{C as w}from"../chunks/CodeBlock.640a2a71.js";function hs(bl){let u,Le,Fe,qe,U,De,j,Pe,d,fl='An OpenEnv environment that integrates the <a href="https://github.com/open-thought/reasoning-gym" rel="nofollow">Reasoning Gym</a> library to provide single-step reasoning tasks. Each episode presents one question from a configurable dataset, the agent submits an answer, and receives a score.',Oe,I,Ke,g,vl="The simplest way to use the Reasoning Gym environment is through the <code>ReasoningGymEnv</code> class:",et,h,tt,C,$l="That’s it! The <code>ReasoningGymEnv.from_docker_image()</code> method handles:",lt,b,Bl="<li>Starting the Docker container</li> <li>Waiting for the server to be ready</li> <li>Connecting to the environment</li> <li>Container cleanup when you call <code>close()</code></li>",st,f,nt,v,Wl="Before using the environment, you need to build the Docker image:",at,$,it,B,Mt,W,Zl="You can easily deploy your OpenEnv environment to Hugging Face Spaces using the <code>openenv push</code> command:",pt,Z,ot,A,Al="The <code>openenv push</code> command will:",Jt,G,Gl="<li>Validate that the directory is an OpenEnv environment (checks for <code>openenv.yaml</code>)</li> <li>Prepare a custom build for Hugging Face Docker space (enables web interface)</li> <li>Upload to Hugging Face (ensuring you’re logged in)</li>",rt,R,mt,E,Rl="<li>Authenticate with Hugging Face: The command will prompt for login if not already authenticated</li>",Tt,N,yt,V,El="<li><code>--directory</code>, <code>-d</code>: Directory containing the OpenEnv environment (defaults to current directory)</li> <li><code>--repo-id</code>, <code>-r</code>: Repository ID in format ‘username/repo-name’ (defaults to ‘username/env-name’ from openenv.yaml)</li> <li><code>--base-image</code>, <code>-b</code>: Base Docker image to use (overrides Dockerfile FROM)</li> <li><code>--private</code>: Deploy the space as private (default: public)</li>",ct,x,wt,X,ut,Q,Nl=`After deployment, your space will be available at:
<code>https://huggingface.co/spaces/&lt;repo-id&gt;</code>`,Ut,k,Vl="The deployed space includes:",jt,S,xl="<li><strong>Web Interface</strong> at <code>/web</code> - Interactive UI for exploring the environment</li> <li><strong>API Documentation</strong> at <code>/docs</code> - Full OpenAPI/Swagger interface</li> <li><strong>Health Check</strong> at <code>/health</code> - Container health monitoring</li> <li><strong>WebSocket</strong> at <code>/ws</code> - Persistent session endpoint for low-latency interactions</li>",dt,H,It,z,gt,_,Xl="Each episode is <strong>single-step</strong>:",ht,F,Ql="<li><code>reset()</code> returns a question</li> <li><code>step(answer)</code> returns score and marks episode as done</li> <li><code>reset()</code> without params gets next question from same dataset</li>",Ct,Y,bt,L,kl="<strong>ReasoningGymAction</strong>: Contains the agent’s answer",ft,q,Sl="<li><code>answer</code> (str) - The agent’s answer to the current question</li>",vt,D,$t,P,Hl="<strong>ReasoningGymObservation</strong>: Contains the question or result",Bt,O,zl="<li><code>question</code> (Optional[str]) - The current question (only in reset)</li> <li><code>score</code> (Optional[float]) - Score for the answer, 0.0 to 1.0 (only after step)</li> <li><code>correct_answer</code> (Optional[str]) - The correct answer (only after step)</li> <li><code>dataset_metadata</code> (Optional[Dict]) - Metadata from the reasoning gym dataset entry</li> <li><code>done</code> (bool) - Always True after step (single-step episodes)</li> <li><code>reward</code> (float) - Equal to score (0.0 to 1.0)</li>",Wt,K,Zt,ee,_l="The reward equals the score returned by the dataset’s scoring function:",At,te,Fl="<li>Correct answer → score: 1.0</li> <li>Incorrect answer → score: 0.0 to 1.0 (dataset-dependent, may use partial credit)</li>",Gt,le,Rt,se,Et,ne,Yl="Use a single dataset with configuration:",Nt,ae,Vt,ie,Ll="Available datasets from reasoning_gym library:",xt,Me,ql='<li><code>leg_counting</code> - Count legs of various objects</li> <li><code>reverse_sort</code> - Sort lists in reverse order</li> <li><code>chess_state_eval</code> - Chess position evaluation</li> <li>And more (see <a href="https://github.com/open-thought/reasoning-gym" rel="nofollow">Reasoning Gym documentation</a>)</li>',Xt,pe,Qt,oe,Dl="Mix multiple datasets with custom weights:",kt,Je,St,re,Ht,me,Pl="The dataset persists across resets until configuration changes:",zt,Te,_t,ye,Ft,ce,Yt,we,Ol="If you already have a Reasoning Gym environment server running, you can connect directly:",Lt,ue,qt,Ue,Kl="Note: When connecting to an existing server, <code>env.close()</code> will NOT stop the server.",Dt,je,Pt,de,es="The client supports context manager usage for automatic connection management:",Ot,Ie,Kt,ge,ts="The client uses WebSocket connections for:",el,he,ls="<li><strong>Lower latency</strong>: No HTTP connection overhead per request</li> <li><strong>Persistent session</strong>: Server maintains your environment state</li> <li><strong>Efficient for episodes</strong>: Better for many sequential steps</li>",tl,Ce,ll,be,ss="The server is configured to support multiple concurrent WebSocket connections:",sl,fe,nl,ve,al,$e,il,Be,ns="Test the environment logic directly without starting the HTTP server:",Ml,We,pl,Ze,as="This verifies that:",ol,Ae,is="<li>Environment resets correctly</li> <li>Step executes actions properly</li> <li>Dataset creation and iteration works</li> <li>Scoring is calculated correctly</li>",Jl,Ge,rl,Re,Ms="Run the server locally for development:",ml,Ee,Tl,Ne,ps="Then test with:",yl,Ve,cl,xe,wl,Xe,ul,Qe,Ul,ke,os="The Reasoning Gym environment is ideal for:",jl,Se,Js="<li><strong>LLM Evaluation</strong>: Benchmark reasoning capabilities across diverse tasks</li> <li><strong>Agent Training</strong>: Train RL agents on reasoning tasks with clear score signals</li> <li><strong>Curriculum Learning</strong>: Mix datasets with composite configurations for progressive difficulty</li> <li><strong>Research</strong>: Reproducible environments with seed control for scientific experiments</li> <li><strong>Educational</strong>: Learn about environment design and agent-environment interaction</li>",dl,He,Il,ze,rs='<li><a href="https://github.com/open-thought/reasoning-gym" rel="nofollow">Reasoning Gym Library</a></li> <li><a href="https://github.com/huggingface/OpenEnv" rel="nofollow">OpenEnv Documentation</a></li> <li><a href="https://github.com/huggingface/OpenEnv/blob/main/README.md" rel="nofollow">OpenEnv Environment Design</a></li>',gl,_e,hl,Ye,Cl;return U=new Is({props:{containerStyle:"float: right; margin-left: 10px; display: inline-flex; position: relative; z-index: 10;"}}),j=new c({props:{title:"Reasoning Gym Environment",local:"reasoning-gym-environment",headingTag:"h1"}}),I=new c({props:{title:"Quick Start",local:"quick-start",headingTag:"h2"}}),h=new w({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> reasoning_gym_env <span class="hljs-keyword">import</span> ReasoningGymAction, ReasoningGymEnv

<span class="hljs-keyword">try</span>:
    <span class="hljs-comment"># Create environment from Docker image</span>
    env = ReasoningGymEnv.from_docker_image(<span class="hljs-string">&quot;reasoning_gym-env:latest&quot;</span>)

    <span class="hljs-comment"># Create a dataset with 10 leg_counting questions</span>
    result = env.reset(
        dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>,
        seed=<span class="hljs-number">42</span>,
        size=<span class="hljs-number">10</span>
    )
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Question: <span class="hljs-subst">{result.observation.question}</span>&quot;</span>)
    <span class="hljs-comment"># Question: &quot;How many legs does a cat have?&quot;</span>

    <span class="hljs-comment"># Submit answer</span>
    result = env.step(ReasoningGymAction(answer=<span class="hljs-string">&quot;4&quot;</span>))
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Score: <span class="hljs-subst">{result.observation.score}</span>&quot;</span>)  <span class="hljs-comment"># 1.0 (correct)</span>
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Correct answer: <span class="hljs-subst">{result.observation.correct_answer}</span>&quot;</span>)  <span class="hljs-comment"># &quot;4&quot;</span>
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Reward: <span class="hljs-subst">{result.reward}</span>&quot;</span>)  <span class="hljs-comment"># 1.0</span>
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Done: <span class="hljs-subst">{result.done}</span>&quot;</span>)  <span class="hljs-comment"># True (single-step episodes)</span>

    <span class="hljs-comment"># Access dataset metadata if available</span>
    <span class="hljs-keyword">if</span> result.observation.dataset_metadata:
        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Metadata: <span class="hljs-subst">{result.observation.dataset_metadata}</span>&quot;</span>)  <span class="hljs-comment"># Dataset-specific info</span>

    <span class="hljs-comment"># Get next question from same dataset</span>
    result = env.reset()  <span class="hljs-comment"># No params = reuse dataset</span>
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Next question: <span class="hljs-subst">{result.observation.question}</span>&quot;</span>)

    <span class="hljs-comment"># Note: First reset() without params creates a default leg_counting dataset</span>
    <span class="hljs-comment"># with seed=42 and size=1000 for reproducible, out-of-the-box functionality</span>

<span class="hljs-keyword">finally</span>:
    <span class="hljs-comment"># Always clean up</span>
    env.close()`,lang:"python",wrap:!1}}),f=new c({props:{title:"Building the Docker Image",local:"building-the-docker-image",headingTag:"h2"}}),$=new w({props:{code:"JTIzJTIwRnJvbSUyMHRoZSUyMHJlYXNvbmluZ19neW1fZW52JTIwZGlyZWN0b3J5JTBBZG9ja2VyJTIwYnVpbGQlMjAtdCUyMHJlYXNvbmluZ19neW0tZW52JTNBbGF0ZXN0JTIwLWYlMjBzZXJ2ZXIlMkZEb2NrZXJmaWxlJTIwLg==",highlighted:`<span class="hljs-comment"># From the reasoning_gym_env directory</span>
docker build -t reasoning_gym-env:latest -f server/Dockerfile .`,lang:"bash",wrap:!1}}),B=new c({props:{title:"Deploying to Hugging Face Spaces",local:"deploying-to-hugging-face-spaces",headingTag:"h2"}}),Z=new w({props:{code:"JTIzJTIwRnJvbSUyMHRoZSUyMGVudmlyb25tZW50JTIwZGlyZWN0b3J5JTIwKHdoZXJlJTIwb3BlbmVudi55YW1sJTIwaXMlMjBsb2NhdGVkKSUwQW9wZW5lbnYlMjBwdXNoJTBBJTBBJTIzJTIwT3IlMjBzcGVjaWZ5JTIwb3B0aW9ucyUwQW9wZW5lbnYlMjBwdXNoJTIwLS1uYW1lc3BhY2UlMjBteS1vcmclMjAtLXByaXZhdGU=",highlighted:`<span class="hljs-comment"># From the environment directory (where openenv.yaml is located)</span>
openenv push

<span class="hljs-comment"># Or specify options</span>
openenv push --namespace my-org --private`,lang:"bash",wrap:!1}}),R=new c({props:{title:"Prerequisites",local:"prerequisites",headingTag:"h3"}}),N=new c({props:{title:"Options",local:"options",headingTag:"h3"}}),x=new c({props:{title:"Examples",local:"examples",headingTag:"h3"}}),X=new w({props:{code:"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",highlighted:`<span class="hljs-comment"># Push to your personal namespace (defaults to username/env-name from openenv.yaml)</span>
openenv push

<span class="hljs-comment"># Push to a specific repository</span>
openenv push --repo-id my-org/reasoning-gym-env

<span class="hljs-comment"># Push with a custom base image</span>
openenv push --base-image ghcr.io/huggingface/openenv-base:latest

<span class="hljs-comment"># Push as a private space</span>
openenv push --private

<span class="hljs-comment"># Combine options</span>
openenv push --repo-id my-org/reasoning-gym --base-image custom-base:latest --private`,lang:"bash",wrap:!1}}),H=new c({props:{title:"Environment Details",local:"environment-details",headingTag:"h2"}}),z=new c({props:{title:"Episode Structure",local:"episode-structure",headingTag:"h3"}}),Y=new c({props:{title:"Action",local:"action",headingTag:"h3"}}),D=new c({props:{title:"Observation",local:"observation",headingTag:"h3"}}),K=new c({props:{title:"Reward",local:"reward",headingTag:"h3"}}),le=new c({props:{title:"Dataset Configuration",local:"dataset-configuration",headingTag:"h2"}}),se=new c({props:{title:"Simple Datasets",local:"simple-datasets",headingTag:"h3"}}),ae=new w({props:{code:"cmVzdWx0JTIwJTNEJTIwZW52LnJlc2V0KCUwQSUyMCUyMCUyMCUyMGRhdGFzZXRfbmFtZSUzRCdsZWdfY291bnRpbmcnJTJDJTBBJTIwJTIwJTIwJTIwc2VlZCUzRDQyJTJDJTBBJTIwJTIwJTIwJTIwc2l6ZSUzRDEwJTBBKQ==",highlighted:`result = env.reset(
    dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>,
    seed=<span class="hljs-number">42</span>,
    size=<span class="hljs-number">10</span>
)`,lang:"python",wrap:!1}}),pe=new c({props:{title:"Composite Datasets",local:"composite-datasets",headingTag:"h3"}}),Je=new w({props:{code:"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",highlighted:`result = env.reset(
    dataset_name=<span class="hljs-string">&#x27;composite&#x27;</span>,
    dataset_specs=[
        {
            <span class="hljs-string">&quot;name&quot;</span>: <span class="hljs-string">&quot;leg_counting&quot;</span>,
            <span class="hljs-string">&quot;weight&quot;</span>: <span class="hljs-number">3</span>,  <span class="hljs-comment"># 3x more likely</span>
            <span class="hljs-string">&quot;config&quot;</span>: {}
        },
        {
            <span class="hljs-string">&quot;name&quot;</span>: <span class="hljs-string">&quot;reverse_sort&quot;</span>,
            <span class="hljs-string">&quot;weight&quot;</span>: <span class="hljs-number">1</span>,
            <span class="hljs-string">&quot;config&quot;</span>: {<span class="hljs-string">&quot;min_length&quot;</span>: <span class="hljs-number">3</span>, <span class="hljs-string">&quot;max_length&quot;</span>: <span class="hljs-number">5</span>}
        }
    ],
    seed=<span class="hljs-number">42</span>,
    size=<span class="hljs-number">20</span>
)`,lang:"python",wrap:!1}}),re=new c({props:{title:"Dataset Persistence",local:"dataset-persistence",headingTag:"h3"}}),Te=new w({props:{code:"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",highlighted:`<span class="hljs-comment"># Create dataset</span>
result = env.reset(dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>, seed=<span class="hljs-number">42</span>, size=<span class="hljs-number">10</span>)
question1 = result.observation.question

<span class="hljs-comment"># Get next question from SAME dataset</span>
result = env.reset()  <span class="hljs-comment"># No params = reuse dataset</span>
question2 = result.observation.question

<span class="hljs-comment"># Create NEW dataset (different seed)</span>
result = env.reset(dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>, seed=<span class="hljs-number">99</span>, size=<span class="hljs-number">10</span>)
question3 = result.observation.question  <span class="hljs-comment"># From new dataset</span>`,lang:"python",wrap:!1}}),ye=new c({props:{title:"Advanced Usage",local:"advanced-usage",headingTag:"h2"}}),ce=new c({props:{title:"Connecting to an Existing Server",local:"connecting-to-an-existing-server",headingTag:"h3"}}),ue=new w({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> reasoning_gym_env <span class="hljs-keyword">import</span> ReasoningGymEnv, ReasoningGymAction

<span class="hljs-comment"># Connect to existing server</span>
env = ReasoningGymEnv(base_url=<span class="hljs-string">&quot;http://localhost:8000&quot;</span>)

<span class="hljs-comment"># Use as normal</span>
result = env.reset(
    dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>,
    dataset_config={<span class="hljs-string">&quot;min_animals&quot;</span>: <span class="hljs-number">5</span>, <span class="hljs-string">&quot;max_animals&quot;</span>: <span class="hljs-number">15</span>}
    seed=<span class="hljs-number">42</span>,
    size=<span class="hljs-number">10</span>
)
result = env.step(ReasoningGymAction(answer=<span class="hljs-string">&quot;4&quot;</span>))`,lang:"python",wrap:!1}}),je=new c({props:{title:"Using the Context Manager",local:"using-the-context-manager",headingTag:"h3"}}),Ie=new w({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> reasoning_gym_env <span class="hljs-keyword">import</span> ReasoningGymAction, ReasoningGymEnv

<span class="hljs-comment"># Connect with context manager (auto-connects and closes)</span>
<span class="hljs-keyword">with</span> ReasoningGymEnv(base_url=<span class="hljs-string">&quot;http://localhost:8000&quot;</span>) <span class="hljs-keyword">as</span> env:
    result = env.reset(
        dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>,
        seed=<span class="hljs-number">42</span>,
        size=<span class="hljs-number">5</span>
    )
    <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Question: <span class="hljs-subst">{result.observation.question}</span>&quot;</span>)

    <span class="hljs-comment"># Multiple steps with low latency</span>
    <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">5</span>):
        result = env.step(ReasoningGymAction(answer=<span class="hljs-string">&quot;4&quot;</span>))
        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Score: <span class="hljs-subst">{result.observation.score}</span>&quot;</span>)
        <span class="hljs-keyword">if</span> result.done:
            result = env.reset()  <span class="hljs-comment"># Get next question</span>`,lang:"python",wrap:!1}}),Ce=new c({props:{title:"Concurrent WebSocket Sessions",local:"concurrent-websocket-sessions",headingTag:"h3"}}),fe=new w({props:{code:"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",highlighted:`<span class="hljs-keyword">from</span> reasoning_gym_env <span class="hljs-keyword">import</span> ReasoningGymAction, ReasoningGymEnv
<span class="hljs-keyword">from</span> concurrent.futures <span class="hljs-keyword">import</span> ThreadPoolExecutor

<span class="hljs-keyword">def</span> <span class="hljs-title function_">run_episode</span>(<span class="hljs-params">client_id: <span class="hljs-built_in">int</span></span>):
    <span class="hljs-keyword">with</span> ReasoningGymEnv(base_url=<span class="hljs-string">&quot;http://localhost:8000&quot;</span>) <span class="hljs-keyword">as</span> env:
        result = env.reset(
            dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>,
            seed=<span class="hljs-number">42</span> + client_id,  <span class="hljs-comment"># Different seed per client</span>
            size=<span class="hljs-number">10</span>
        )
        total_score = <span class="hljs-number">0.0</span>
        <span class="hljs-keyword">for</span> i <span class="hljs-keyword">in</span> <span class="hljs-built_in">range</span>(<span class="hljs-number">10</span>):
            result = env.step(ReasoningGymAction(answer=<span class="hljs-string">&quot;4&quot;</span>))
            total_score += result.observation.score
            <span class="hljs-keyword">if</span> result.done:
                result = env.reset()  <span class="hljs-comment"># Next question</span>
        <span class="hljs-keyword">return</span> client_id, total_score

<span class="hljs-comment"># Run 4 episodes concurrently</span>
<span class="hljs-keyword">with</span> ThreadPoolExecutor(max_workers=<span class="hljs-number">4</span>) <span class="hljs-keyword">as</span> executor:
    results = <span class="hljs-built_in">list</span>(executor.<span class="hljs-built_in">map</span>(run_episode, <span class="hljs-built_in">range</span>(<span class="hljs-number">4</span>)))
    <span class="hljs-keyword">for</span> client_id, score <span class="hljs-keyword">in</span> results:
        <span class="hljs-built_in">print</span>(<span class="hljs-string">f&quot;Client <span class="hljs-subst">{client_id}</span>: Total score = <span class="hljs-subst">{score}</span>&quot;</span>)`,lang:"python",wrap:!1}}),ve=new c({props:{title:"Development & Testing",local:"development--testing",headingTag:"h2"}}),$e=new c({props:{title:"Direct Environment Testing",local:"direct-environment-testing",headingTag:"h3"}}),We=new w({props:{code:"JTIzJTIwRnJvbSUyMHRoZSUyMHJlYXNvbmluZ19neW1fZW52JTIwZGlyZWN0b3J5JTBBcHl0aG9uMyUyMHNlcnZlciUyRnJlYXNvbmluZ19neW1fZW52aXJvbm1lbnQucHk=",highlighted:`<span class="hljs-comment"># From the reasoning_gym_env directory</span>
python3 server/reasoning_gym_environment.py`,lang:"bash",wrap:!1}}),Ge=new c({props:{title:"Running Locally",local:"running-locally",headingTag:"h3"}}),Ee=new w({props:{code:"JTIzJTIwRnJvbSUyMHRoZSUyMHJlYXNvbmluZ19neW1fZW52JTIwZGlyZWN0b3J5JTBBdXZpY29ybiUyMHNlcnZlci5hcHAlM0FhcHAlMjAtLXJlbG9hZA==",highlighted:`<span class="hljs-comment"># From the reasoning_gym_env directory</span>
uvicorn server.app:app --reload`,lang:"bash",wrap:!1}}),Ve=new w({props:{code:"ZnJvbSUyMHJlYXNvbmluZ19neW1fZW52JTIwaW1wb3J0JTIwUmVhc29uaW5nR3ltRW52JTJDJTIwUmVhc29uaW5nR3ltQWN0aW9uJTBBJTBBZW52JTIwJTNEJTIwUmVhc29uaW5nR3ltRW52KGJhc2VfdXJsJTNEJTIyaHR0cCUzQSUyRiUyRmxvY2FsaG9zdCUzQTgwMDAlMjIpJTBBcmVzdWx0JTIwJTNEJTIwZW52LnJlc2V0KGRhdGFzZXRfbmFtZSUzRCdsZWdfY291bnRpbmcnJTJDJTIwc2VlZCUzRDQyJTJDJTIwc2l6ZSUzRDUpJTBBcHJpbnQocmVzdWx0Lm9ic2VydmF0aW9uLnF1ZXN0aW9uKQ==",highlighted:`<span class="hljs-keyword">from</span> reasoning_gym_env <span class="hljs-keyword">import</span> ReasoningGymEnv, ReasoningGymAction

env = ReasoningGymEnv(base_url=<span class="hljs-string">&quot;http://localhost:8000&quot;</span>)
result = env.reset(dataset_name=<span class="hljs-string">&#x27;leg_counting&#x27;</span>, seed=<span class="hljs-number">42</span>, size=<span class="hljs-number">5</span>)
<span class="hljs-built_in">print</span>(result.observation.question)`,lang:"python",wrap:!1}}),xe=new c({props:{title:"Project Structure",local:"project-structure",headingTag:"h2"}}),Xe=new w({props:{code:"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",highlighted:`reasoning_gym_env/
├── <span class="hljs-string">.dockerignore</span>         <span class="hljs-comment"># Docker build exclusions</span>
├── __init__.py           <span class="hljs-comment"># Module exports</span>
├── README.md             <span class="hljs-comment"># This file</span>
├── openenv.yaml          <span class="hljs-comment"># OpenEnv manifest</span>
├── pyproject.toml        <span class="hljs-comment"># Project metadata and dependencies</span>
├── client.py             <span class="hljs-comment"># ReasoningGymEnv client</span>
├── models.py             <span class="hljs-comment"># Action and Observation models</span>
└── server/
    ├── __init__.py       <span class="hljs-comment"># Server module exports</span>
    ├── reasoning_gym_environment.py  <span class="hljs-comment"># Core environment logic</span>
    ├── app.py            <span class="hljs-comment"># FastAPI application (HTTP + WebSocket endpoints)</span>
    ├── requirements.txt  <span class="hljs-comment"># Server dependencies</span>
    └── Dockerfile        <span class="hljs-comment"># Container image definition</span>`,lang:"",wrap:!1}}),Qe=new c({props:{title:"Use Cases",local:"use-cases",headingTag:"h2"}}),He=new c({props:{title:"Learn More",local:"learn-more",headingTag:"h2"}}),_e=new 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