JavaScript
const ReiCoreSdk = require("reicore-sdk");
const apiKey = "your_unit_secret_token";
const reiAgent = new ReiCoreSdk({ agentSecretKey: apiKey });
// Example function to query Rei Agent
async function queryReiAgent(message) {
try {
const response = await reiAgent.chatCompletions(message);
return response;
} catch (error) {
console.error("Error querying Rei Agent:", error);
return null;
}
}
// Example usage in your agent
async function yourAgentFunction() {
// Your agent's logic here
const query = "What are the latest developments in quantum computing?";
const reiResponse = await queryReiAgent(query);
// Process the response
}
Python
from client import Client
client = Client(
api_key="your_unit_secret_token",
base_url="https://api.reilabs.org"
)
# Example function to query Rei Agent
def query_rei_agent(message):
try:
response = client.chat.completions.create(
model="Unit01",
messages=[
{"role": "user", "content": message}
],
functions=[{
"name": "query_rei_agent",
"description": "Query the Rei Agent for information or assistance",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The query to send to the Rei Agent"
}
},
"required": ["query"]
}
}]
)
return response.choices[0].message.content
except Exception as e:
print(f"Error querying Rei Agent: {e}")
return None
# Example usage in your agent
def your_agent_function():
# Your agent's logic here
query = "What are the latest developments in quantum computing?"
rei_response = query_rei_agent(query)
# Process the response
Example integration with OpenAI
from openai import OpenAI
from client import Client as ReiClient
# Initialize both clients
openai_client = OpenAI(api_key="your_openai_key")
rei_client = ReiClient(api_key="your_unit_secret_token")
def hybrid_agent_query(query):
# First, get context from OpenAI
openai_response = openai_client.chat.completions.create(
model="gpt-4o",
messages=[{"role": "user", "content": query}]
)
# Then, enhance with Rei Agent's specialized knowledge
rei_response = rei_client.chat.completions.create(
model="Unit01",
messages=[
{"role": "user", "content": query},
{"role": "assistant", "content": openai_response.choices[0].message.content}
]
)
return rei_response.choices[0].message.content