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‎docs/index.md‎

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**Next**: [Getting Started](getting-started.md)
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<sup><sup>Practicus AI docs for v25.5.3 (Built on 2025-10-23 12:47)</sup></sup>
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<sup><sup>Practicus AI docs for v25.5.4 (Built on 2025-10-25 11:11)</sup></sup>

‎docs/sdk/practicuscore.html‎

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<h2>Contents</h2>
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<ul>
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<li><a href="#practicus-ai-sdk-v2553">Practicus AI SDK v25.5.3</a>
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<li><a href="#practicus-ai-sdk-v2554">Practicus AI SDK v25.5.4</a>
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<ul>
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<li><a href="#overview">Overview</a></li>
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<li><a href="#key-functionality">Key Functionality</a></li>
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<h1 class="modulename">
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practicuscore </h1>
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<div class="docstring"><h1 id="practicus-ai-sdk-v2553">Practicus AI SDK v25.5.3</h1>
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<div class="docstring"><h1 id="practicus-ai-sdk-v2554">Practicus AI SDK v25.5.4</h1>
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<h2 id="overview">Overview</h2>
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<div class="attr variable">
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<span class="name">IGNORED_REQ_HEADERS</span> =
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<input id="ModelServer.IGNORED_REQ_HEADERS-view-value" class="view-value-toggle-state" type="checkbox" aria-hidden="true" tabindex="-1">
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<label class="view-value-button pdoc-button" for="ModelServer.IGNORED_REQ_HEADERS-view-value"></label><span class="default_value">{&#39;te&#39;, &#39;connection&#39;, &#39;transfer-encoding&#39;, &#39;host&#39;, &#39;authorization&#39;, &#39;keep-alive&#39;, &#39;trailers&#39;, &#39;proxy-authorization&#39;, &#39;upgrade&#39;, &#39;proxy-authenticate&#39;, &#39;content-length&#39;}</span>
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<label class="view-value-button pdoc-button" for="ModelServer.IGNORED_REQ_HEADERS-view-value"></label><span class="default_value">{&#39;connection&#39;, &#39;content-length&#39;, &#39;transfer-encoding&#39;, &#39;host&#39;, &#39;keep-alive&#39;, &#39;trailers&#39;, &#39;proxy-authorization&#39;, &#39;authorization&#39;, &#39;te&#39;, &#39;proxy-authenticate&#39;, &#39;upgrade&#39;}</span>
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</div>
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<div id="ModelServer.IGNORED_RESP_HEADERS" class="classattr">
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<div class="attr variable">
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<span class="name">IGNORED_RESP_HEADERS</span> =
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<span class="default_value">{&#39;connection&#39;, &#39;transfer-encoding&#39;, &#39;content-encoding&#39;}</span>
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<span class="default_value">{&#39;content-encoding&#39;, &#39;connection&#39;, &#39;transfer-encoding&#39;}</span>
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</div>

‎docs/sdk/search.js‎

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‎docs/technical-tutorial/distributed-computing/spark/auto-scaled/interactive/start-cluster.md‎

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# Let's define worker features of the cluster
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worker_config = prt.WorkerConfig(
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.3",
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.4",
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# Please make sure to use a worker size with
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# privileged access.
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worker_size=auto_dist_worker_size,

‎docs/technical-tutorial/distributed-computing/spark/batch-job/batch-job.md‎

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)
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worker_config = prt.WorkerConfig(
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.3",
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.4",
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worker_size=worker_size,
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distributed_config=distributed_config,
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log_level=log_level,

‎docs/technical-tutorial/distributed-computing/spark/interactive/start-cluster.md‎

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# Let's define worker features of the cluster
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worker_config = prt.WorkerConfig(
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.3",
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worker_image="ghcr.io/practicusai/practicus-spark-worker:25.5.4",
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worker_size=worker_size,
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distributed_config=distributed_config,
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)

‎docs/technical-tutorial/generative-ai/model-serving/llm/model-serving.md‎

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1. **Define Container Image in Practicus AI:**
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* Navigate to `Infrastructure > Container Images` in the Practicus AI console.
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* Add a new image. Use a vLLM-enabled image provided by Practicus AI, for example: `ghcr.io/practicusai/practicus-modelhost-gpu-vllm:25.5.3` (replace with the latest/appropriate version).
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* Add a new image. Use a vLLM-enabled image provided by Practicus AI, for example: `ghcr.io/practicusai/practicus-modelhost-gpu-vllm:25.5.4` (replace with the latest/appropriate version).
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2. **Create Model Deployment:**
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* Go to `ML Model Hosting > Model Deployments`.
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```dockerfile
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# Use a Practicus AI image that includes GPU support and vLLM
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FROM ghcr.io/practicusai/practicus-modelhost-gpu-vllm:25.5.3
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FROM ghcr.io/practicusai/practicus-modelhost-gpu-vllm:25.5.4
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# --- Configuration baked into the image ---
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ENV PRT_SERVE_MODEL="TinyLlama/TinyLlama-1.1B-Chat-v1.0"

‎docs/technical-tutorial/unified-devops/build-custom-images.md‎

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# Create a Dockerfile in ~/build
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dockerfile_content = """
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# Use a base image from your private registry or a public source
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FROM my-registry.practicus.my-company.com/practicusai/practicus-minimal:25.5.3
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FROM my-registry.practicus.my-company.com/practicusai/practicus-minimal:25.5.4
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success = prt.containers.build_image(
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tag="25.5.3",
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tag="25.5.4",
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registry_credentials=[
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Once your image is successfully pushed, you can reference it in any future Practicus AI Worker by its full name, for example:
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```
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my-registry.practicus.my-company.com/demo/practicus-minimal-my:25.5.3
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my-registry.practicus.my-company.com/demo/practicus-minimal-my:25.5.4
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# worker_image="my-registry.practicus.my-company.com/demo/practicus-minimal-my:25.5.3",
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# worker_image="my-registry.practicus.my-company.com/demo/practicus-minimal-my:25.5.4",
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# or else, the current Practicus AI platform version is used if the tag is omitted.
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worker_image="my-registry.practicus.my-company.com/demo/practicus-minimal-my",
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tag="25.5.4" \
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build_args="{\"ENV_VAR\": \"value\"}" \
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registry_credentials="[(\"my-registry.practicus.my-company.com\", \"my-robot-user\", \"token\")]"
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‎docs/technical-tutorial/unified-devops/git-integrated-cicd.md‎

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jobs:
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Sample-Job:
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runs-on: practicus-25.5.4
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jobs:
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Explore-PracticusAI-Actions:
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runs-on: practicus-25.5.4
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jobs:
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runs-on: practicus-25.5.4
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runs-on: practicus-25.5.4
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‎mkdocs.yml‎

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- Enterprise SSO: ops-tutorial/enterprise-sso.md
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- AI Assistants: ops-tutorial/ai_assistants.md
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- MFA (Multi-Factor Authentication): ops-tutorial/mfa.md
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- SDK v25.5.3: sdk/practicuscore.html
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- SDK v25.5.4: sdk/practicuscore.html
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- Legacy:
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- Setup Guide: setup-guide.md
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- Open MLOps:

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