# NL2FOL

## Docs

- [CVCGenerator](https://mintlify.wiki/lovishchopra/NL2FOL/api/cvc-generator.md): Parser and generator for CVC5 SMT solver input files
- [Helper Functions](https://mintlify.wiki/lovishchopra/NL2FOL/api/helpers.md): Utility functions for string processing and formula manipulation
- [NL2FOL](https://mintlify.wiki/lovishchopra/NL2FOL/api/nl2fol.md): Core class for converting natural language to first-order logic
- [SMTResults](https://mintlify.wiki/lovishchopra/NL2FOL/api/smt-results.md): Interpreter for SMT solver results and counterexample generation
- [First-Order Logic](https://mintlify.wiki/lovishchopra/NL2FOL/concepts/first-order-logic.md): Understanding first-order logic fundamentals for fallacy detection
- [Logical Fallacies](https://mintlify.wiki/lovishchopra/NL2FOL/concepts/logical-fallacies.md): Understanding the logical fallacies detected by NL2FOL
- [SMT Solving](https://mintlify.wiki/lovishchopra/NL2FOL/concepts/smt-solving.md): Using SMT solvers to verify logical validity of first-order formulas
- [Translation Pipeline](https://mintlify.wiki/lovishchopra/NL2FOL/concepts/translation-pipeline.md): Multi-stage pipeline for converting natural language to first-order logic
- [Basic Usage](https://mintlify.wiki/lovishchopra/NL2FOL/examples/basic-usage.md): Learn how to translate natural language to first-order logic with a simple example
- [Custom Datasets](https://mintlify.wiki/lovishchopra/NL2FOL/examples/custom-datasets.md): Learn how to process your own datasets for logical fallacy detection
- [Model Backends](https://mintlify.wiki/lovishchopra/NL2FOL/examples/model-backends.md): Switch between GPT-4 and Llama models for natural language to first-order logic translation
- [Installation](https://mintlify.wiki/lovishchopra/NL2FOL/installation.md): Set up NL2FOL and install all required dependencies
- [Introduction](https://mintlify.wiki/lovishchopra/NL2FOL/introduction.md): NL2FOL translates natural language to first-order logic for detecting logical fallacies using LLMs and SMT solvers
- [Quick Start](https://mintlify.wiki/lovishchopra/NL2FOL/quickstart.md): Run your first logical fallacy detection using NL2FOL
- [Evaluation Metrics](https://mintlify.wiki/lovishchopra/NL2FOL/usage/evaluation.md): Calculate performance metrics for logical fallacy detection
- [FOL to SMT Conversion](https://mintlify.wiki/lovishchopra/NL2FOL/usage/fol-to-smt.md): Convert first-order logic formulas to SMT-LIB format and run CVC4/CVC5 solver
- [Interpreting SMT Results](https://mintlify.wiki/lovishchopra/NL2FOL/usage/interpretation.md): Understand and explain SMT solver outputs with LLM-generated interpretations
- [Natural Language to First-Order Logic](https://mintlify.wiki/lovishchopra/NL2FOL/usage/nl-to-fol.md): Learn how to translate natural language arguments to first-order logic formulas

## OpenAPI Specs

- [openapi](https://mintlify.wiki/lovishchopra/NL2FOL/api-reference/openapi.json)