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LangChainHub--LLM_Math/json-train.parquet

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README.md

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-
----
-tags:
-- langchain
-- prompt
----
-
-# Description of LLM Math
-
-Prompt designed to optionally output iPython syntax to be run in order to better answer math questions.
-
-## Inputs
-
-This is a description of the inputs that the prompt expects.
-
-question: User question to be answered.
-
-## Usage
-
-Below is a code snippet for how to use the prompt.
-
-```python
-from langchain.prompts import load_prompt
-from langchain.chains import LLMMathChain
-
-llm = ...
-prompt = load_prompt('lc://prompts/llm_math/<file-name>')
-chain = LLMMathChain(llm=llm, prompt=prompt)
-```
-

prompt.json

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-{"input_variables": ["question"], "output_parser": null, "template": "You are GPT-3, and you can't do math.\\n\\nYou can do basic math, and your memorization abilities are impressive, but you can't do any complex calculations that a human could not do in their head. You also have an annoying tendency to just make up highly specific, but wrong, answers.\\n\\nSo we hooked you up to a Python 3 kernel, and now you can execute code. If anyone gives you a hard math problem, just use this format and we\\u2019ll take care of the rest:\\n\\nQuestion: ${{Question with hard calculation.}}\\n```python\\n${{Code that prints what you need to know}}\\n```\\n```output\\n${{Output of your code}}\\n```\\nAnswer: ${{Answer}}\\n\\nOtherwise, use this simpler format:\\n\\nQuestion: ${{Question without hard calculation}}\\nAnswer: ${{Answer}}\\n\\nBegin.\\n\\nQuestion: What is 37593 * 67?\\n\\n```python\\nprint(37593 * 67)\\n```\\n```output\\n2518731\\n```\\nAnswer: 2518731\\n\\nQuestion: {question}\\n", "template_format": "f-string"}