openrouter-skill

from langchain_openai import ChatOpenAI
import os

# Any OpenRouter model works with ChatOpenAI
llm = ChatOpenAI(
    model="deepseek/deepseek-chat",
    openai_api_key=os.getenv("OPENROUTER_API_KEY"),
    openai_api_base="https://openrouter.ai/api/v1",
    default_headers={
        "HTTP-Referer": "https://your-app.com",  # Optional but recommended
        "X-Title": "Your App Name"
    }
)

response = llm.invoke("Explain quantum computing in simple terms")

from langchain_core.messages import HumanMessage
import base64

llm = ChatOpenAI(
    model="qwen/qwen-2-vl-72b-instruct",
    openai_api_key=os.getenv("OPENROUTER_API_KEY"),
    openai_api_base="https://openrouter.ai/api/v1"
)

# From URL
response = llm.invoke([
    HumanMessage(content=[
        {"type": "text", "text": "Analyze this chart and identify key trends"},
        {"type": "image_url", "image_url": {"url": "https://example.com/chart.png"}}
    ])
])

# From base64
with open("chart.png", "rb") as f:
    image_data = base64.b64encode(f.read()).decode()

response = llm.invoke([
    HumanMessage(content=[
        {"type": "text", "text": "What does this chart show?"},
        {"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_data}"}}
    ])
])

# OpenRouter's Auto model selects the best model for your prompt
llm = ChatOpenAI(
    model="openrouter/auto",  # Powered by NotDiamond
    openai_api_key=os.getenv("OPENROUTER_API_KEY"),
    openai_api_base="https://openrouter.ai/api/v1"
)

Task Type
│
├─ Vision/Charts ──────────> qwen/qwen-2-vl-72b-instruct ($0.40/M)
├─ Code Generation ────────> deepseek/deepseek-coder ($0.14/$0.28)
├─ Deep Reasoning ─────────> qwen/qwq-32b ($0.15/$0.40)
├─ Long Documents ─────────> moonshot/moonshot-v1-128k ($0.55/M)
├─ Fast/Cheap Tasks ───────> qwen/qwen-2.5-7b-instruct ($0.09/M)
├─ General Analysis ───────> deepseek/deepseek-chat ($0.27/$1.10)
└─ Unknown/Auto ───────────> openrouter/auto

from enum import Enum
from langchain_openai import ChatOpenAI
import os

class ChineseModel(str, Enum):
    DEEPSEEK_CHAT = "deepseek/deepseek-chat"
    DEEPSEEK_CODER = "deepseek/deepseek-coder"
    QWEN_VL = "qwen/qwen-2-vl-72b-instruct"
    QWEN_FAST = "qwen/qwen-2.5-7b-instruct"
    QWQ_REASONING = "qwen/qwq-32b"
    MOONSHOT_LONG = "moonshot/moonshot-v1-128k"
    AUTO = "openrouter/auto"

def create_llm(model: ChineseModel, **kwargs) -> ChatOpenAI:
    """Factory for OpenRouter LLMs with sensible defaults."""
    return ChatOpenAI(
        model=model.value,
        openai_api_key=os.getenv("OPENROUTER_API_KEY"),
        openai_api_base="https://openrouter.ai/api/v1",
        default_headers={
            "HTTP-Referer": os.getenv("APP_URL", "http://localhost"),
            "X-Title": os.getenv("APP_NAME", "LangChain App")
        },
        **kwargs
    )

# Usage
chat_llm = create_llm(ChineseModel.DEEPSEEK_CHAT)
vision_llm = create_llm(ChineseModel.QWEN_VL)
fast_llm = create_llm(ChineseModel.QWEN_FAST, temperature=0)

# .env
OPENROUTER_API_KEY=sk-or-v1-...
APP_URL=https://your-app.com      # For attribution (optional)
APP_NAME=Your App Name            # For attribution (optional)