Results for “dxpy”

Build and deploy apps/applets on the DNAnexus cloud genomics platform, manage data objects, run workflows, and use the dxpy Python SDK for genomics pipeline development and execution.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming. Use when you need to build complex AI systems, program LMs declaratively, optimize prompts automatically, create modular AI pipelines, or build RAG systems and agents.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Use for writing, reviewing, debugging, testing, or optimizing Python CVXPY optimization models. Trigger on Variable, Parameter, Expression, Constraint, Objective, Problem, DCP, DPP, DGP, DQCP, solver selection/status, dual values, mixed-integer, cone, or repeated parametric solves. Do not use for scipy.optimize-only, PyMC inference, symbolic algebra without optimization, or hand-written solver implementations.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

DSPy: declarative LM programs, auto-optimize prompts, RAG.

Specialized AI assistant for DSPy development with deep knowledge of predictors, optimizers, adapters, and GEPA integration. Provides session management, codebase indexing, and command-based workflows.

Build complex AI systems with declarative programming, optimize prompts automatically, and create modular RAG systems and agents using Stanford NLP's DSPy framework.

Integrates Dify with external systems via REST APIs, webhooks, and the MCP protocol, including client and server implementations.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Write, review, debug, or test Python Xarray workflows for labeled N-dimensional DataArray and Dataset operations, including coordinates, alignment, indexing, groupby, resample, rolling, weighted reduction, Dask-backed execution, and NetCDF/Zarr I/O.

Generates RFQ-ready 2D DXF files and optional SVG previews from a validated JSON spec, ideal for sheet and plate parts like brackets and hole patterns.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Program LM pipelines with DSPy — define Signatures (input/output fields), build Modules (ChainOfThought, ReAct, Predict), compose them into Programs, then optimize with Teleprompters (BootstrapFewShot, MIPRO, COPRO) to auto-improve prompts from examples.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Develop quantitative trading strategies with the vn.py framework, covering CTA, spread, and options strategies with support for 20+ broker gateways.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identific...

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Debug Python with pdb, breakpoint(), post-mortem inspection, and debugpy remote attach.

Python video composition with moviepy 2.x — overlaying deterministic text on AI-generated video (LTX-2, SadTalker), compositing clips, single-file build.py video projects. Use when adding labels/captions/lower-thirds to LTX-2 or SadTalker outputs, building short ad-style spots in pure Python without Remotion, or doing programmatic video composition. Triggers include text overlay on video, label LTX-2 clip, caption SadTalker output, lower third, build.py video, moviepy, Python video composition, sub-30s ad spot.

You are an expert in DSPy, the Stanford framework that replaces prompt engineering with programming. You help developers define LLM tasks as typed signatures, compose them into modules, and automatically optimize prompts/few-shot examples using teleprompters — so instead of manually crafting prompts, you write Python code and DSPy finds the best prompts for your task.

Build complex AI systems with declarative programming, optimize prompts automatically, create modular RAG systems and agents with DSPy - Stanford NLP's framework for systematic LM programming

Use for writing, reviewing, debugging, testing, or optimizing Python NumPy ndarray code. Trigger on array construction, shape/axis reasoning, dtypes and casting, broadcasting, indexing, copies/views, ufuncs, reductions, vectorization, random Generator, linear algebra, FFT, masked/structured arrays, memory layout, or NumPy interoperability. Do not use for pandas/Polars table semantics, JAX/CuPy-only arrays, symbolic SymPy, or pure Python sequences without a NumPy boundary.

DSPy declarative framework for automatic prompt optimization treating prompts as code with systematic evaluation and compilers

RAG with Dspy. building RAG systems.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Analyze single-cell RNA-seq data with Scanpy, covering quality control, normalization, clustering, marker gene identification, visualization, and trajectory analysis.

Debug Python: pdb REPL + debugpy remote (DAP).

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.