# Prompt Template
## Desription Prompt Template.
## Code Example ### Example ```python from towhee import ops, pipe import requests towhee_docs = requests.get('https://raw.githubusercontent.com/towhee-io/towhee/main/README.md').content temp = """{question} input: {context} """ sys_message = """Your name is TowheeChat.""" p = ( pipe.input('question', 'doc', 'history') .map('doc', 'doc', lambda x: x[:2000]) .map(('question', 'doc', 'history'), 'prompt', ops.prompt.template(temp, ['question', 'context'], sys_message)) .map('prompt', 'answer', ops.LLM.OpenAI()) .output('answer') ) an1 = p('What is your name?', [], []).get()[0] print(an1) an2 = p('Tell me something about Towhee', towhee_docs, []).get()[0] print(an2) an3 = p('How to use it', towhee_docs, [('Tell me something about Towhee', an2)]).get()[0] print(an3) ``` ## Factory Constructor Create the operator via the following factory method: ***ops.prompt.template(temp, keys, sys_msg)*** **Parameters:** ***temp***: *str* ​ A template to create a prompt as the last user message. ***keys***: *list* ​ A list of keys used in template. ***sys_msg***: *str=None* ​ A system message, defaults to None. If None, it will not pass any system message.
**Returns:** *List[Dict]* # More Resources - [ChatGPT+ Vector database + prompt-as-code - The CVP Stack - Zilliz blog](https://zilliz.com/blog/ChatGPT-VectorDB-Prompt-as-code): Extend the capability of ChatGPT with a Vector database and prompts-as-code - [What is Prompt as Code (Prompt Engineering)](https://zilliz.com/glossary/prompt-as-code-(prompt-engineering)): Explores what prompt engineering is, how it works in NLP, and best practices for effective prompt engineering. - [An LLM Powered Text to Image Prompt Generation with Milvus - Zilliz blog](https://zilliz.com/blog/llm-powered-text-to-image-prompt-generation-with-milvus): An interesting LLM project powered by the Milvus vector database for generating more efficient text-to-image prompts. - [Prompting in LangChain - Zilliz blog](https://zilliz.com/blog/prompting-langchain): Prompting is one of today's most popular and important tasks in AI app building. Learn how to use LangChain for more complex prompts. - [What is Prompt Chaining](https://zilliz.com/glossary/prompt-chaining): Prompt chaining in NLP uses structured prompts to break a complex task into smaller subtasks. This sequential approach improves coherence and accuracy in LLM outputs.