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This notebook covers how to get started with JinaChat chat models.

from langchain_community.chat_models import JinaChat
from langchain_core.messages import HumanMessage, SystemMessage
from import (
chat = JinaChat(temperature=0)
messages = [
content="You are a helpful assistant that translates English to French."
content="Translate this sentence from English to French. I love programming."
AIMessage(content="J'aime programmer.", additional_kwargs={}, example=False)

You can make use of templating by using a MessagePromptTemplate. You can build a ChatPromptTemplate from one or more MessagePromptTemplates. You can use ChatPromptTemplate's format_prompt -- this returns a PromptValue, which you can convert to a string or Message object, depending on whether you want to use the formatted value as input to an llm or chat model.

For convenience, there is a from_template method exposed on the template. If you were to use this template, this is what it would look like:

template = (
"You are a helpful assistant that translates {input_language} to {output_language}."
system_message_prompt = SystemMessagePromptTemplate.from_template(template)
human_template = "{text}"
human_message_prompt = HumanMessagePromptTemplate.from_template(human_template)
chat_prompt = ChatPromptTemplate.from_messages(
[system_message_prompt, human_message_prompt]

# get a chat completion from the formatted messages
input_language="English", output_language="French", text="I love programming."
AIMessage(content="J'aime programmer.", additional_kwargs={}, example=False)

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