Image Generation
from openai import OpenAI
client = OpenAI(
api_key="YOUR_API_KEY",
base_url="https://eachsense-agent.core.eachlabs.run/v1"
)
# Simple generation
response = client.chat.completions.create(
model="eachsense/beta",
messages=[{
"role": "user",
"content": "Generate a professional headshot portrait, natural lighting"
}],
stream=False
)
print(response.choices[0].message.content)
print(f"Generated: {response.generations}")
import OpenAI from "openai";
const client = new OpenAI({
apiKey: "YOUR_API_KEY",
baseURL: "https://eachsense-agent.core.eachlabs.run/v1",
});
const response = await client.chat.completions.create({
model: "eachsense/beta",
messages: [
{ role: "user", content: "Generate a professional headshot portrait" },
],
stream: false,
});
console.log(response.choices[0].message.content);
console.log("Generated:", response.generations);
Image Editing with Upload
import requests
response = requests.post(
"https://eachsense-agent.core.eachlabs.run/v1/chat/completions",
headers={
"Content-Type": "application/json",
"X-API-Key": "YOUR_API_KEY"
},
json={
"messages": [{"role": "user", "content": "Remove the background from this image"}],
"image_urls": ["https://example.com/photo.jpg"],
"stream": False
}
)
data = response.json()
print(f"Edited: {data['generations']}")
Multi-Turn Conversation
import requests
SESSION_ID = "design-session"
URL = "https://eachsense-agent.core.eachlabs.run/v1/chat/completions"
HEADERS = {"Content-Type": "application/json", "X-API-Key": "YOUR_API_KEY"}
def chat(message):
response = requests.post(URL, headers=HEADERS, json={
"messages": [{"role": "user", "content": message}],
"session_id": SESSION_ID,
"stream": False
})
data = response.json()
print(f"Assistant: {data['choices'][0]['message']['content']}")
if data.get("generations"):
print(f"Generated: {data['generations']}")
return data
# Conversation flow
chat("Generate a cyberpunk cityscape at night")
chat("Add more neon lights and flying cars")
chat("Now make it a 5-second video")
Workflow via Natural Language
import requests
import json
URL = "https://eachsense-agent.core.eachlabs.run/v1/chat/completions"
HEADERS = {"Content-Type": "application/json", "X-API-Key": "YOUR_API_KEY"}
# Create workflow
response = requests.post(URL, headers=HEADERS, json={
"messages": [{
"role": "user",
"content": "Create a workflow: 1) Generate portrait from description, 2) Animate into 5s video"
}],
"stream": True
}, stream=True)
for line in response.iter_lines():
if not line:
continue
line = line.decode("utf-8")
if line.startswith("data: ") and line[6:] != "[DONE]":
event = json.loads(line[6:])
if event["type"] == "workflow_created":
print(f"Workflow created: {event['workflow_id']}")
elif event["type"] == "text_response":
print(event["content"])
Streaming with Event Handling
import requests
import json
def stream_generation(prompt):
response = requests.post(
"https://eachsense-agent.core.eachlabs.run/v1/chat/completions",
headers={"Content-Type": "application/json", "X-API-Key": "YOUR_API_KEY"},
json={
"messages": [{"role": "user", "content": prompt}],
"stream": True
},
stream=True
)
generations = []
for line in response.iter_lines():
if not line:
continue
line = line.decode("utf-8")
if not line.startswith("data: "):
continue
data = line[6:]
if data == "[DONE]":
break
event = json.loads(data)
if event["type"] == "thinking_delta":
print(f"Thinking: {event['content']}", end="")
elif event["type"] == "text_response":
print(f"\n{event['content']}")
elif event["type"] == "generation_response":
generations.append(event["url"])
print(f"Generated: {event['url']}")
elif event["type"] == "error":
print(f"Error: {event['message']}")
elif event["type"] == "complete":
print("Done!")
return generations
# Usage
urls = stream_generation("Generate a sunset landscape in oil painting style")
Eco Mode for Fast Prototyping
# Use eco mode for faster, cheaper generations during development
response = client.chat.completions.create(
model="eachsense/beta",
messages=[{"role": "user", "content": "Generate a quick test portrait"}],
stream=False,
extra_body={"mode": "eco"}
)