Results for “search”

Diagnoses and improves Qdrant search relevance by isolating embedding model, configuration, or query strategy issues.

Diagnoses and resolves slow Qdrant search performance issues including high latency, low throughput, and slow filtered searches.

Searches the aem.live documentation for information on AEM Edge Delivery Services features, then fetches and reads full page content for detailed guidance.

Search models, datasets, Spaces, and papers on the Hugging Face Hub, retrieve repository details and documentation, run compute jobs, and use Gradio Spaces as AI tools via the Hugging Face MCP server.

Index folders of PDFs and other documents into LanceDB for vector search, then query them with semantic search, page filters, verbatim quotes, and cross-document aggregation.

Search archived video using natural language, ingest video files or RTSP streams, and manage ingested sources.

Integrate with Azure AI services including Search, Speech, OpenAI, and Document Intelligence for search, transcription, OCR, and text-to-speech tasks.

Helps software engineers with discrete job search tasks: job description analysis, CV tailoring, cover letter writing, offer evaluation, and follow-up emails.

Selects, configures, deploys, verifies, debugs, or tears down a VSS profile (base, search, lvs, warehouse, edge) for NVIDIA's video search and summarization stack.

Adds autotuning to CuTile kernels using the exhaustive_search API with a tune-once/cache/direct-launch pattern, covering occupancy-only and complex tile-size search spaces.

Guides optimization of Qdrant query latency by tuning segments, memory, quantization, and search parameters.

Optimize Qdrant vector search performance through indexing strategies, query tuning, memory management, and hardware considerations.

Build production RAG pipelines and persistent agent memory using Pinecone as the vector database backend.

Integrate Qdrant vector search into applications using officially supported client SDKs for Python, JavaScript, Rust, Go, .NET, and Java.

Fetch dataset metadata, paginate rows, search text, apply filters, and download parquet URLs from the Hugging Face Dataset Viewer API.

Searches and extracts data from Burp Suite project files (.burp) using the burpsuite-project-file-parser extension, enabling regex searches on response headers and bodies, extraction of security audit findings, and analysis of proxy history and site map data.

Guides monitoring and observability setup for Qdrant vector search deployments, including Prometheus scraping, health checks, and metric-based debugging of production issues.

Guides embedding model migration in Qdrant without downtime, covering alias swap, side-by-side, and hybrid search strategies.

Optimize PostgreSQL databases with advanced features, performance tuning, and best practices for JSONB, full-text search, window functions, and indexing.

Rewrites AEM Edge Delivery Services page content for AI search discoverability (Generative Engine Optimization) by analyzing structure, clarity, and factual density.

Guides scaling Qdrant vector search with time-based data rotation using shard rotation, collection rotation, or filter-and-delete strategies.

Forces web searches and reading of official docs before implementing, integrating, or debugging third-party APIs, libraries, and services to ensure accuracy and avoid guesswork.

Create and manage persistent AI agents with threads, messages, runs, and tools using the Azure AI Agents SDK for .NET.

Searches a local cache of Windows WinMD metadata to find the right Windows API for any capability and retrieve full type details including methods, properties, events, and enumeration values.

Guides users through an interactive tour of the context-matic MCP server, explaining its purpose and demonstrating all available APIs with live tool calls.

Discovers and researches companies matching an ideal customer profile, using Browserbase Search API and a Plan→Research→Synthesize pattern to produce scored reports and CSV exports.

Runs a three-layer verification pipeline on AI-generated output: extracts verifiable claims, finds supporting or contradicting sources via web search, and produces a structured verification report with source links for human review.

Search, manage, and scaffold skills in the Gemini Enterprise Agent Platform Skill Registry.

Manage Browserbase platform resources, Functions, and API workflows through the `browse` CLI.

Navigate the PhysicsNeMo repository by discovering model families, datapipes, and examples through live file search, without writing training code.