Use with frameworks

# pip install langchain-openai
import os
 
from langchain_openai import ChatOpenAI
 
llm = ChatOpenAI(
    model="Amara S1.2",
    base_url="https://app.syntic.ai/v1",
    api_key=os.environ["SYNTIC_API_KEY"],
    max_tokens=500,
)
print(llm.invoke("Give me two names for a bicycle repair café.").content)
 
for chunk in llm.stream("Describe a quiet harbour at dawn in two sentences."):
    print(chunk.content, end="", flush=True)

// npm install @langchain/openai
import { ChatOpenAI } from '@langchain/openai'
 
const llm = new ChatOpenAI({
  model: 'Amara S1.2',
  apiKey: process.env.SYNTIC_API_KEY,
  configuration: { baseURL: 'https://app.syntic.ai/v1' },
  maxTokens: 500,
})
 
const reply = await llm.invoke('Give me two names for a bicycle repair café.')
console.log(reply.content)

# pip install llama-index-llms-openai-like
import os
 
from llama_index.llms.openai_like import OpenAILike
 
llm = OpenAILike(
    model="Amara S1.2",
    api_base="https://app.syntic.ai/v1",
    api_key=os.environ["SYNTIC_API_KEY"],
    is_chat_model=True,
    is_function_calling_model=True,
    context_window=262144,
    max_tokens=500,
)
print(llm.complete("Give me two names for a bicycle repair café."))

// npm install ai @ai-sdk/openai-compatible
import { createOpenAICompatible } from '@ai-sdk/openai-compatible'
import { streamText } from 'ai'
 
const syntic = createOpenAICompatible({
  name: 'syntic',
  baseURL: 'https://app.syntic.ai/v1',
  apiKey: process.env.SYNTIC_API_KEY,
})
 
const result = streamText({
  model: syntic('Amara S1.2'),
  prompt: 'Describe a quiet harbour at dawn in two sentences.',
})
for await (const text of result.textStream) process.stdout.write(text)