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Constrain LLM output with grammars; guarantee valid JSON.
Passed 23 of 24 test cases with the skill, and 19 of 24 without it.
and 1 more in the full report
4 fixed19 passed either way1 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 4 test cases the skill fixed. Same model, same prompt, with and without the skill.
What pip command installs Guidance along with optional dependencies required for local Hugging Face Transformers models and llama.cpp models?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies pip install guidance[transformers] or guidance[llama_cpp] | Missed | Passed |
The instructions your model reads when the skill loads.
Use Guidance when you need to:
GitHub Stars: 18,000+ | From: Microsoft Research
# Base installation
pip install guidance
# With specific backends
pip install guidance[transformers] # Hugging Face models
pip install guidance[llama_cpp] # llama.cpp models
from guidance import models, gen
# Load model (supports OpenAI, Transformers, llama.cpp)
lm = models.OpenAI("gpt-4")
# Generate with constraints
result = lm + "The capital of France is " + gen("capital", max_tokens=5)
print(result["capital"]) # "Paris"
test cases passed, vs 19 / 24 without
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