Nebula (Symbl.ai)
Overview
This notebook covers how to get started with Nebula - Symbl.ai's chat model.
Integration details
Head to the API reference for detailed documentation.
Model features: TODO
Setup
Credentials
To get started, request a Nebula API key and set the NEBULA_API_KEY
environment variable:
import getpass
import os
os.environ["NEBULA_API_KEY"] = getpass.getpass()
Installation
The integration is set up in the langchain-community
package.
Instantiation
from langchain_community.chat_models.symblai_nebula import ChatNebula
from langchain_core.messages import AIMessage, HumanMessage, SystemMessage
chat = ChatNebula(max_tokens=1024, temperature=0.5)
Invocation
messages = [
SystemMessage(
content="You are a helpful assistant that answers general knowledge questions."
),
HumanMessage(content="What is the capital of France?"),
]
chat.invoke(messages)
AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])
Async
await chat.ainvoke(messages)
AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])
Streaming
for chunk in chat.stream(messages):
print(chunk.content, end="", flush=True)
The capital of France is Paris.
Batch
chat.batch([messages])
[AIMessage(content=[{'role': 'human', 'text': 'What is the capital of France?'}, {'role': 'assistant', 'text': 'The capital of France is Paris.'}])]
Chaining
from langchain_core.prompts import ChatPromptTemplate
prompt = ChatPromptTemplate.from_template("Tell me a joke about {topic}")
chain = prompt | chat
API Reference:ChatPromptTemplate
chain.invoke({"topic": "cows"})
AIMessage(content=[{'role': 'human', 'text': 'Tell me a joke about cows'}, {'role': 'assistant', 'text': "Sure, here's a joke about cows:\n\nWhy did the cow cross the road?\n\nTo get to the udder side!"}])
API reference
Check out the API reference for more detail.
Related
- Chat model conceptual guide
- Chat model how-to guides