BREAD for your agents.

curl https://api.breadai.io/v1/chat/completions \
  -H "Authorization: Bearer $BREAD_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "bread-auto",
    "messages": [{"role": "user", "content": "Summarise why bread rises in one sentence."}]
  }'

from openai import OpenAI

client = OpenAI(base_url="https://api.breadai.io/v1", api_key="bread_sk_...")

reply = client.chat.completions.create(
    model="bread-auto",   # the best model with a free host; or name one, e.g. bread-chat-27b
    messages=[{"role": "user", "content": "Summarise why bread rises in one sentence."}],
)
print(reply.choices[0].message.content)

import OpenAI from "openai";

const client = new OpenAI({ baseURL: "https://api.breadai.io/v1", apiKey: process.env.BREAD_API_KEY });

const stream = await client.chat.completions.create({
  model: "bread-chat-8b",
  messages: [{ role: "user", content: "Write a haiku about sourdough." }],
  stream: true,
});
for await (const chunk of stream) process.stdout.write(chunk.choices[0]?.delta?.content ?? "");

from openai import OpenAI
import json

client = OpenAI(base_url="https://api.breadai.io/v1", api_key="bread_sk_...")
tools = [{"type": "function", "function": {
    "name": "get_weather",
    "description": "Current weather for a city",
    "parameters": {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]},
}}]
messages = [{"role": "user", "content": "What's the weather in Sydney?"}]

reply = client.chat.completions.create(model="bread-chat-8b", messages=messages, tools=tools)
call = reply.choices[0].message.tool_calls[0]
args = json.loads(call.function.arguments)          # {"city": "Sydney"}

result = {"temp": 22, "sky": "sunny"}                # your code runs the tool, not BREAD
messages += [reply.choices[0].message, {"role": "tool", "tool_call_id": call.id, "content": json.dumps(result)}]
final = client.chat.completions.create(model="bread-chat-8b", messages=messages, tools=tools)
print(final.choices[0].message.content)

reply = client.chat.completions.create(
    model="bread-chat-8b",
    response_format={"type": "json_object"},
    messages=[{"role": "user", "content": "Classify: 'the crust was perfect'. Reply as JSON with sentiment and score."}],
)
data = json.loads(reply.choices[0].message.content)   # {"sentiment": "positive", "score": 0.95}