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| Metadata-Version: 2.4 | |
| Name: promptguru | |
| Version: 0.1.0 | |
| Summary: Modular prompt engineering library | |
| Author-email: Naga Adithya Kaushik <[email protected]> | |
| License: Apache-2.0 | |
| Project-URL: Homepage, https://huggingface.co/spaces/GenAIDevTOProd/PromptGuru | |
| Keywords: prompts,nlp,llm,huggingface,templates | |
| Requires-Python: >=3.8 | |
| Description-Content-Type: text/markdown | |
| Requires-Dist: PyYAML>=6.0 | |
| # PromptGuru | |
| **Modular prompt engineering library** for BERT, Mistral, LLaMA, and FLAN-T5 using YAML templates. | |
| Includes modes like **ELI5**, **DevMode**, **Refine**, **Classification**, and **QA**. | |
| ## Why | |
| - Lightweight and framework-agnostic | |
| - YAML-first: edit prompts without changing code | |
| - Consistent modes across multiple model families | |
| ## Install (Local Dev) | |
| ```bash | |
| pip install PyYAML | |
| ``` | |
| > For now, clone or copy this repo. PyPI packaging steps are included below. | |
| ## Usage | |
| ```python | |
| from promptguru.engine import PromptEngine | |
| engine = PromptEngine(model_type="mistral", mode="eli5") | |
| prompt = engine.generate_prompt("What is quantum entanglement?") | |
| print(prompt) | |
| ``` | |
| ## Templates | |
| Templates live in `promptguru/templates/`: | |
| - `bert.yaml` → `classification`, `fill_mask`, `qa` | |
| - `mistral.yaml` → `eli5`, `devmode`, `refine` | |
| - `llama.yaml` → `eli5`, `devmode`, `refine` | |
| - `flan_t5.yaml` → `eli5`, `devmode`, `explain_and_tag` | |
| ## Roadmap | |
| - Add inference adapters (HF Inference API, OpenRouter) behind a common interface | |
| - Add more modes (contrastive QA, chain-of-thought, safety/risk tags) | |
| ## License | |
| Apache 2.0 | |