'ollama' 검색 결과

Switch a NanoClaw agent group to a local Ollama model by configuring environment variables and model settings. The skill covers setup checks, optional blocking of Anthropic API access, verification, troubleshooting, and switching back to Claude.

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• Running a NanoClaw agent with a local model
• Reducing use of the Anthropic API
• Trying open-weight models through Ollama

Connect a container agent to local Ollama models through MCP, a protocol for agent tools. The agent can list models and generate responses, with optional tools to download, delete, inspect, and check loaded models.

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• Delegate response generation to a local model
• Check which Ollama models are installed
• Download or delete models through the agent

Manage Ollama models and run text generation, chat, and embeddings, which represent text as numerical vectors, through command-line requests. Check server status, inspect model details, and receive structured JSON output for agent workflows.

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• Download models and inspect their details
• Generate text or chat with a chosen model
• Convert text into numerical vectors

Diagnose failed model requests from OpenShell sandboxes to hosted APIs or local servers such as Ollama and vLLM. Check provider attachment, access rules, credentials, network layout, and client settings to identify the narrowest configuration change needed.

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• Diagnose failed requests to hosted model APIs
• Troubleshoot connections to Ollama or LM Studio
• Investigate credential and endpoint mismatch errors

Connect cognee to model providers, databases, storage services, and development tools. Guides configuration of language models and embeddings, the numerical representations used for search, including the separate settings each requires.

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• Switching model providers or using Ollama locally
• Connecting cognee to Postgres or Neo4j
• Storing cognee data in S3

Convert chat messages into template strings for local model runtimes such as Ollama or llama.cpp. Optionally route queries among a few registered intents using embeddings, numerical representations of meaning, without calling a model.

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• Preparing prompt strings for Ollama
• Formatting conversations for a local model
• Routing queries among a few intents

Convert LLMs to GGUF and reduce model size through quantization, which stores weights at lower numerical precision. Prepare models for CPU or Apple Silicon inference, compare compression levels, and integrate them with local AI tools.

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• Preparing an LLM for CPU-only use
• Running a local model on Apple Silicon
• Comparing model size and quality across quantization levels

Convert language models to GGUF and reduce their size through quantization, which stores model weights at lower precision. Guides cover compression choices, local inference on CPUs and Apple Silicon, and integration with tools such as Ollama.

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• Running a language model on a CPU-only computer
• Choosing model compression for available memory
• Configuring Metal acceleration on Apple Silicon

Extract webpage content from a URL through 9Router and receive Markdown, plain text, or HTML. Choose among supported extraction services, limit output length, or use a fallback chain that tries another provider when needed.

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• Convert a webpage to Markdown
• Extract article content as plain text
• Limit extracted content to a chosen character count

Configure permission checks for unattended Antigravity CLI runs. The setup combines blocking rules, automatic approval for scoped operations, AI classification for ambiguous calls, and single-use approval tokens to control tool access within a verified workspace.

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• Setting up permission checks for unattended Antigravity CLI runs
• Defining rules for shell commands, file changes, and network access
• Configuring a local model to classify ambiguous tool calls

Design and build visual stories where scrolling changes charts, maps, or video. Plan meaningful scene transitions, choose suitable implementation tools, and provide mobile layouts and static alternatives for readers who prefer reduced motion.

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• Build a story with charts that change as readers scroll
• Create a timeline combining maps and video
• Compare scrolling narratives with step-by-step displays

Query images with a local Ollama vision model without loading the image into the main agent context. Use when you need to describe a screenshot, check whether rendered content is present, detect overlapping elements, or ask any visual question about a PNG/JPEG/WebP file. Requires Ollama running locally with the Gemma 4 multimodal model (`gemma4` on Ollama). Script: .agents/skills/vision/scripts/ask.py. Trigger phrases: "describe image", "what does this screenshot show", "does the canvas contain content", "check screenshot visually", "look at this image", "any overlapping elements", "vision query".

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Optimize Ollama configuration for the current machine's hardware. Use when asked to speed up Ollama, tune local LLM performance, or pick models that fit available GPU/RAM. Don't use for LM Studio, llama.cpp, vLLM, or hosted-API LLM providers.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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Use when integrating an app with local AI models through Ollama — connection checks, model listing/selection, local-only mode, cloud-fallback consent, visible run states, and recovering from Ollama errors.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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Operational guide for the NV oOS WordPress Playground demo blueprints — the Content Graph "Project Asteria" demo, the Complete bundle × local Ollama demo, and the Docs Hub wp.org Live Preview demo. Covers blueprint authoring patterns (embedded runPHP seed snippets, generator scripts, preview-safe vs standalone split), CORS hosting gotchas, the CI Plugin Check gate (built-ZIP scan, rsync/distignore sync, ABSPATH guards), Playground worker crash modes (PHP-side localhost fetches, inline-script UTF-8, SPA SSE-hold mount bursts, crash-truncation SyntaxErrors), local Ollama integration (OLLAMA_ORIGINS, browser policy matrix, plugin settings + assistant meta keys), and the CLI validation harness (probe builder, mount quirks, server-mode 502 boot). Use when extending or debugging the demo blueprints, adding a new Playground demo, or triaging a crashing Playground instance.

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Add Ollama MCP server so the container agent can call local models and optionally manage the Ollama model library.

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Add an AI assistant to an existing web app so users can operate its interface with everyday instructions. Covers embedding the panel, connecting a language model, testing interactions, and protecting API keys in production.

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• Add natural-language controls to a business dashboard
• Introduce an AI assistant into a legacy web app
• Build guided product demos using the actual interface

Delegate code changes and multi-step development tasks to OpenHands CLI using a model supported by LiteLLM, a connection layer for model providers. Run tasks without an interactive interface, inspect progress events, and resume previous conversations.

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• Delegate code changes to OpenHands
• Run coding tasks with a LiteLLM-supported model
• Check progress on long-running development tasks

Guides implementation and maintenance of Claude applications using language-specific references and official SDKs, the libraries used to call the API. Covers tool integration, streaming responses, model migration, cost reviews, prompt audits, and evaluation workflows.

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• Adding Claude API calls to an application
• Building an agent that uses custom tools
• Migrating existing Claude integrations to another model

Estimate the cost per million tokens, units of model text, on hardware you own using power consumption, electricity rates, hardware costs, and measured generation speed. Compare utilization levels to find when local operation costs less than a hosted model.

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• Compare local model costs with a hosted API
• Estimate costs at different utilization levels
• Include electricity and hardware depreciation in costs

Build Claude applications using guidance for the official Anthropic SDK. Choose an integration approach, implement streaming and tool use, and follow workflows for model migration, prompt audits, evaluation, and cost optimization.

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• Build a summarization app with Claude API
• Choose how to run an agent with custom tools
• Migrate existing code to a newer Claude model