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Align Python version and repo-declared dependencies (requirements.txt / environment.yml) before installing packages for NLP research code reproduction.
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Run score Not tested
See how to installReview the instructions the agent will receive before you install.
When reproducing an NLP research repo, always align the environment to the repo’s declared dependencies first. Most failures come from Python version mismatch or installing packages without following requirements.txt / environment.yml.
environment.yml / environment.yaml (often pins Python + channels + non-pip deps)requirements.txt (pip deps)environment.yml as the base, requirements.txt as supplemental unless README says otherwise/root/python_int.txt containing:python -VV (required; Python version is often the root cause)python -m pip --versionpython -m pip freezeIf the repo expects a specific Python major/minor and the current Python does not match, it’s usually best to set up a matching environment before installing dependencies. Example: set up a fresh Python 3.11 environment (Docker / Ubuntu) with uv # Install uv apt-get update apt-get install -y --no-install-recommends curl ca-certificates rm -rf /var/lib/apt/lists/* curl -LsSf https://astral.sh/uv/0.9.7/install.sh | sh export PATH="/root/.local/bin:$PATH"
# Install Python + create a venv
uv python install 3.11.8
uv venv --python 3.11.8 /opt/py311
# Use the new Python for installs/runs
/opt/py311/bin/python -VV
/opt/py311/bin/python -m pip install -U pip setuptools wheel
Prefer installing from the repo’s dependency files (avoid random upgrades), then run a quick import/smoke test.
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Use this skill when reading sensor data from CSV files, writing simulation results to CSV, processing time-series data with pandas, or handling missing values in datasets.
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DC power flow analysis for power systems. Use when computing power flows using DC approximation, building susceptance matrices, calculating line flows and loading percentages, or performing sensitivity analysis on transmission networks.
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A library for building, validating, visualizing, and serializing dialogue graphs. Use this when parsing scripts or creating branching narrative structures.
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Use this skill whenever the user wants to create, read, edit, or manipulate Word documents (.docx files). Triggers include: any mention of "Word doc", "word document", ".docx", or requests to produce professional documents with formatting like tables of contents, headings, page numbers, or letterheads. Also use when extracting or reorganizing content from .docx files, inserting or replacing images in documents, performing find-and-replace in Word files, working with tracked changes or comments, or converting content into a polished Word document. If the user asks for a "report", "memo", "letter", "template", or similar deliverable as a Word or .docx file, use this skill. Do NOT use for PDFs, spreadsheets, Google Docs, or general coding tasks unrelated to document generation.
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Generator economic dispatch and cost optimization for power systems. Use when minimizing generation costs, computing optimal generator setpoints, calculating operating margins, or working with generator cost functions.
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