Prerequisites
Before chatting, you need an agent with knowledge configured. Follow the Create your Hypergraph guide first to get your agent_id.
Chat via the SDK API
Send a message and get a response:
import os
import uuid
import requests
API_KEY = os.environ["RIPPLETIDE_API_KEY"]
BASE_URL = "https://agent.rippletide.com/api/sdk"
headers = {"x-api-key": API_KEY, "Content-Type": "application/json"}
agent_id = "your-agent-id" # from the agent creation step
conversation_id = str(uuid.uuid4()) # one ID per conversation session
response = requests.post(f"{BASE_URL}/chat/{agent_id}", headers=headers, json={
"user_message": "What products can I order?",
"conversation_uuid": conversation_id
})
print(response.json()["answer"])
conversation_uuid for follow-up messages in the same conversation. Generate a new UUID to start a fresh session.
API Reference: Chat API
LangChain Integration
This feature is experimental.
Installation
pip install langchain langchain-openai
Usage
Rippletide exposes an Azure OpenAI-compatible endpoint, so you can use AzureChatOpenAI from LangChain:
import os
import uuid
from langchain_core.messages import SystemMessage, HumanMessage
from langchain_openai import AzureChatOpenAI
API_KEY = os.environ["RIPPLETIDE_API_KEY"]
agent_id = "your-agent-id" # from the agent creation step
conversation_id = str(uuid.uuid4())
rippletide_llm = AzureChatOpenAI(
model="v1",
api_key=API_KEY,
azure_endpoint="https://agent.rippletide.com",
azure_deployment="v1",
api_version="2024-12-01-preview",
openai_api_type="azure",
default_headers={
"x-rippletide-agent-id": agent_id,
"x-rippletide-conversation-id": str(conversation_id),
},
)
messages = [
SystemMessage(content="You are a helpful assistant."),
HumanMessage(content="What products can I order?")
]
response = rippletide_llm.invoke(messages)
print(response.content)
Use in a LangChain chain
Once initialized, rippletide_llm works like any other LangChain LLM:
from langchain.prompts import ChatPromptTemplate
prompt = ChatPromptTemplate.from_messages([
("system", "You are a helpful assistant for an electronics store."),
("human", "{question}")
])
chain = prompt | rippletide_llm
result = chain.invoke({"question": "How long does delivery take?"})
print(result.content)
Next Steps
