Set up Python projects with uv, manage required packages, and create isolated environments for each project. Covers Python versions, dependency updates, migration from existing tools, and lockfiles that record package versions for repeatable installations.
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Decide whether an LLM needs additional training or whether retrieval and better prompts will suffice. Match available examples, preferences, or verifiable results to a training method, then assess model size and memory requirements before starting.
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Design backtests that evaluate trading strategies against historical data. Account for trading costs, avoid using future information or excluding delisted securities, and compare strategies using separate development and evaluation periods.
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Prepare datasets for language model training by formatting examples, checking conversation templates, and packing examples into training sequences. Document data sources, synthetic data ratios, and validation results in a dataset card before starting a run.
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Build Python applications that handle other work while waiting for network or database operations. Use asyncio and async/await to run tasks concurrently, manage errors and timeouts, and handle cancellation with appropriate cleanup.
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Help implement automated subscription billing, invoice generation and delivery, and recovery of failed payments. Cover subscription states, renewals, usage-based charges, prorated plan changes, and tax calculations as parts of the billing workflow.
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Design recommendation and ranking systems that select the best items for a user or situation. Organize retrieval, enrichment, filtering, scoring, selection, and background actions into six stages, then generate a runnable scaffold for your chosen stack.
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Integrate PayPal into online checkout flows with one-time payments, subscriptions, refunds, and payment notifications. Includes client-side buttons, server-side payment handling, and sandbox testing to check the purchase flow before using live credentials.
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Explains how PluginEval combines structural checks and experimental model assessments into quality scores. Helps interpret low scores, identify improvement areas, set marketplace thresholds, and explain what evaluation badges actually represent.
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Set up distributed tracing with Jaeger and Tempo to follow requests across services. Examine delays, service dependencies, and error propagation, with guidance on sampling, linking logs to traces, and troubleshooting missing trace data.
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Build Grafana dashboards that show application and infrastructure health through request rates, errors, response times, and resource usage. Organize metrics into useful panels, add filters and alerts, and manage dashboard definitions as code.
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Turn graded execution traces and production logs into model training examples and preferred-versus-rejected response pairs. Select useful records, remove sensitive information, exclude evaluation examples, and preserve links to the original runs.
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Validate generated PowerPoint decks for layout problems, accessibility, editable content, source references, and file integrity. Follow a repair and recheck workflow, keeping audit reports and build records together for delivery.
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Add structured logs, performance metrics, and traces that follow requests across Python services. Establish consistent log fields and request IDs so production failures can be investigated using recorded activity and service health signals.
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Set consistent Python conventions for naming, formatting, type checking, and documentation. Configure ruff and mypy or pyright, write clear function descriptions, and organize README and changelog content so a team can maintain shared standards.
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Add retries and timeouts to Python service calls, with increasing and randomized waits between attempts. Use examples to distinguish temporary failures from permanent errors, limit retry duration, and record retries in logs.
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Organize Python projects with clear file responsibilities, directory layouts, and public interfaces—the functions and classes intended for other code to use. Covers new projects, existing code reorganization, test placement, package exports, and dependency direction.
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Calculate portfolio risk and performance measures, including potential losses, declines from past peaks, and returns relative to risk. Use multiple indicators to support risk limits, position sizing, and ongoing monitoring.
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Create or repair a JSON specification for an editable PowerPoint deck. Define exact object positions, sizes, styles, and layering, alongside reading order and image descriptions, so the build process follows an explicitly authored layout.
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Prepare GRPO reinforcement learning configurations for tasks with programmatically checkable answers, such as math, code, and structured output. Design and inspect reward functions, then select training variants when runs show instability or exploit flaws in scoring.
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Choose a model training method and configuration from paired response preferences or individual positive and negative ratings. Covers DPO, ORPO, KTO, and SimPO, including pair construction, repeated training rounds, and troubleshooting learning settings.
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Identify software protections that hinder inspection, such as debugger detection and obfuscation that makes code harder to understand. Support authorized binary analysis and CTF security challenges with protection findings, bypass strategies, reports, and analysis scripts.
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Analyze a reference PowerPoint deck without changing it. Extract its structure, colors, typography, and layout patterns to inform a new presentation, and inspect the underlying package for broken links or malformed document data.
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Configure supervised fine-tuning for models that process images and text. Define which components remain unchanged, set LoRA adapters for updating selected model weights, choose image resolution limits, and investigate training runs whose evaluation results fail to improve.
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