'deep' 검색 결과

Add DeepEval tracing to Python AI applications so execution steps appear in Confident AI. Choose a supported integration or manual @observe instrumentation, then capture inputs, outputs, step types, tags, and metadata.

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• Trace execution steps in a Python AI application
• Select tracing integrations for an existing framework
• Add manual tracing with @observe

Build repeatable DeepEval tests for AI agents, chatbots, and applications that retrieve documents to answer questions. Reuse or generate evaluation datasets, inspect failures, and improve prompts, tools, or retrieval through repeated evaluation runs.

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• Add repeatable quality tests for an AI agent
• Evaluate chatbot behavior across multiple conversation turns
• Generate evaluation datasets from documentation

Helps configure and troubleshoot DeepSpeed for training large models across multiple devices. Covers memory optimization, parallel training, and DeepNVMe storage transfers, with examples for tuning data movement and configuring models that divide work among specialized components.

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• Configuring distributed training for large models
• Tuning tensor transfers to NVMe storage
• Setting up models with specialized expert components

Implement and troubleshoot large-model training with DeepSpeed across multiple GPUs. The skill covers memory optimization, parallel training, and numerical precision choices, alongside examples for storage transfers and models that divide work among specialized components.

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• Review settings for distributed model training
• Tune transfers between NVMe storage and tensors
• Configure training with specialized model components

Automate Deepgram operations through Rube MCP, a connection for agent tools. The skill finds available actions, checks the service connection, and runs tasks using the latest required input fields.

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• Finding available Deepgram actions
• Checking the Deepgram connection before a task
• Running multiple operations in a workflow

Set up and manage DeepTutor from the command line, a text interface for running commands. Run learning tasks, build searchable document collections, manage sessions and notebooks, diagnose installation issues, and launch the server or Web app.

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• Set up DeepTutor and diagnose installation issues
• Build and search a knowledge base from PDFs
• Generate practice questions from learning materials

Automate Deepgram operations through Rube MCP, a connection for agent tools. The skill finds available actions, checks the service connection, and runs tasks using the latest required input fields.

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• Finding available Deepgram actions
• Checking the Deepgram connection before a task
• Running multiple operations in a workflow

Get documentation-based help with deepsec, an AI vulnerability scanner. Initialize or resume setup, configure scans and model credentials, and create detection rules or plugins using the documentation bundled with the installed version.

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• Initializing deepsec and resuming interrupted setup
• Configuring scans, models, and credentials
• Creating or customizing vulnerability detection rules

Everything Claude Code의 스킬과 훅을 DeepSeek Harness에 연결합니다. 설정 생성, 동작 확인, 업데이트와 인식 문제 조사를 안내합니다.

• DSH에 ECC 스킬을 설치합니다
• 프로필에 훅을 연결합니다
• 스킬과 훅의 인식 문제를 조사합니다

Send proofs, planning questions, or difficult debugging tasks to DeepSeek's reasoning model. Receive the final answer and model-provided reasoning text in separate fields, with token usage reported for reviewing responses and costs.

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• Requesting a mathematical proof
• Planning work that requires several reasoning steps
• Investigating root causes of difficult bugs

Send a single request to DeepSeek for summarization, information extraction, or simple classification. Receive the response and token usage as JSON for further processing, with structured status information when the API is unavailable.

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• Summarizing text in a single request
• Extracting information from text
• Classifying text into simple categories

Design and improve DeepTutor skills by turning concrete usage examples into reusable instructions. Learn how to write descriptions that signal when to use a skill, structure SKILL.md, and separate supporting reference material.

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• Turn a recurring workflow into a DeepTutor skill
• Clarify when an existing skill should be used
• Split lengthy instructions into reference files

Delegate scoped repository analysis or implementation to DeepSeek Harness without opening its interactive interface. Collect its final text, check the exit status, and inspect repository changes when the task requires read-only work.

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• Diagnose a failing test without editing files
• Delegate a scoped repository investigation
• Request implementation in a specified project

Configure OpenTelemetry to send AI application traces, records of execution steps, to Confident AI. Reuse existing exporters, choose the regional endpoint, and add AI-specific attributes without requiring the deepeval Python package.

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• Send existing AI application traces to Confident AI
• Configure tracing for a non-Python AI application
• Choose the US or EU endpoint for an API key

Study a reference adaptation connecting the shared skillopt_sleep cycle to a custom DeepSeek backend for OpenClaw. It provides prototype wrappers, sample tasks, and a porting checklist for developers building an integration.

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• Study a prototype DeepSeek backend for OpenClaw
• Identify changes needed for current engine interfaces
• Review sample tasks and environment-specific settings

Train Mixture of Experts models, which activate selected specialist networks for each input. The skill guides architecture, input routing, workload balancing, and GPU distribution using DeepSpeed or HuggingFace, with examples for training configuration and inference optimization.

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• Designing a model that activates only selected expert networks
• Balancing workloads across expert networks
• Distributing experts across multiple GPUs

Retrieve content from URLs and PDFs, then summarize, quote, convert, or save it as readable Markdown. When built-in search falls short, use DeepSeek as an optional search fallback, with explicit handling of extraction failures.

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• Summarizing a linked article or PDF
• Extracting passages with source citations
• Converting and saving web content as Markdown

Adapt existing PyTorch training scripts to use multiple GPUs or machines with limited code changes. The skill guides configuration, launch commands, mixed precision, which uses lower-precision numbers, and DeepSpeed or FSDP settings for distributing training work and memory.

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• Move a single-GPU training script to multiple GPUs
• Configure mixed precision training
• Set up DeepSpeed or FSDP to reduce memory use

Adapt PyTorch training scripts for multiple GPUs or machines with Accelerate. This skill guides code changes, configuration, and launch commands, including mixed precision, which combines numerical formats, and DeepSpeed or FSDP integration for distributed training.

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• Moving single-GPU training to multiple GPUs
• Configuring mixed precision training
• Setting up DeepSpeed or FSDP

Build and train Mixture of Experts models, which activate selected specialist networks for each input. Use DeepSpeed or HuggingFace workflows to configure routing, balance workloads, distribute experts across GPUs, and optimize inference.

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• Designing MoE models for a limited compute budget
• Implementing Mixtral-style expert routing
• Adjusting expert workloads and training stability

Send prompts to Novita AI models such as DeepSeek and GLM from the command line. Retrieve answers as readable text or structured JSON, stream responses as they arrive, and check available models and API connectivity.

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• Send questions to DeepSeek or GLM
• Display responses as they arrive
• Retrieve AI responses as JSON

Guide multi-step coding tasks with deepseek-v4-pro or deepseek-v4-flash in thinking mode. Verify files and symbols, write plans with confirmed file paths and line numbers, and use a verifier agent before changes spanning three or more files.

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• Verify that files and functions exist before editing
• Write plans with confirmed file paths and line numbers
• Check assumptions before changes spanning three or more files

Search open-access academic papers through DeepXiv, then move from brief summaries to section outlines and individual sections. Find trending papers and focus reading on the parts needed to answer a research question.

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• Find papers on a research topic
• Read only a paper's Introduction section
• Explore papers trending over the past two weeks

Run an AI vulnerability scan on uncommitted changes, changes against main, or an entire codebase. Filter candidate files, investigate potential security issues, and review findings with severity ratings, with options to revalidate and export results.

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• Checking uncommitted changes for vulnerabilities
• Reviewing security issues in changes against main
• Scanning an existing codebase