history=[('Who won the world series in 2020?', 'The Los Angeles Dodgers won the World Series in 2020.')]
question = 'Where was it played?'
answer = p(question, [], history).get()[0]
message = [{"question": "Building a website can be done in 10 simple steps:"}]
answer = chat(message)
```
*Write a [retrieval-augmented generation pipeline](https://towhee.io/tasks/detail/pipeline/retrieval-augmented-generation) with explicit inputs/outputs name specifications:*
*Write a pipeline with explicit inputs/outputs name specifications:*
```python
from towhee import pipe, ops
temp = '''Use the following pieces of context to answer the question at the end.
docs.append('Towhee is a cutting-edge framework designed to streamline the processing of unstructured data through the use of Large Language Model (LLM) based pipeline orchestration.')
ans2 = p(q2, docs, history).get()[0]
print(q2, ans2)
history=[('Who won the world series in 2020?', 'The Los Angeles Dodgers won the World Series in 2020.')]
question = 'Where was it played?'
answer = p(question, [], history).get()[0]
```
<br/>
@ -132,8 +103,8 @@ A dictionary of supported models with model name as key and huggingface hub id &