Using ASI:One with LangChain

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import os
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage, SystemMessage
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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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    temperature=0.7,
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)
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messages = [
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    SystemMessage(content="You are a helpful AI assistant."),
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    HumanMessage(content="What is agentic AI?"),
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]
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response = llm.invoke(messages)
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print(response.content)

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import os
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from langchain_openai import ChatOpenAI
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from langchain_core.messages import HumanMessage
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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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    streaming=True,
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)
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for chunk in llm.stream([HumanMessage(content="Explain blockchain in simple terms")]):
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    print(chunk.content, end="", flush=True)

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import os
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from typing import List
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from langchain_openai import ChatOpenAI
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from pydantic import BaseModel, Field
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class Product(BaseModel):
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    """A product extracted from text."""
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    name: str = Field(description="Product name")
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    price: float = Field(description="Price in USD")
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    category: str = Field(description="Product category")
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class ProductList(BaseModel):
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    """A list of products."""
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    products: List[Product] = Field(description="List of extracted products")
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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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)
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structured_llm = llm.with_structured_output(ProductList)
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text = """
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Our store has the following items:
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- Wireless Mouse ($29.99) - Electronics
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- Organic Coffee Beans ($14.50) - Groceries
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- Running Shoes ($89.00) - Sports
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"""
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result = structured_llm.invoke(f"Extract all products from this text:\n{text}")
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for product in result.products:
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    print(f"- {product.name}: ${product.price} ({product.category})")

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import os
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from langchain_core.tools import tool
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from langchain_openai import ChatOpenAI
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@tool
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def get_weather(city: str) -> str:
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    """Get the current weather for a city."""
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    # In production, call a real weather API
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    return f"The weather in {city} is sunny, 22°C"
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@tool
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def search_restaurants(city: str, cuisine: str) -> str:
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    """Search for restaurants in a city by cuisine type."""
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    return f"Found 5 {cuisine} restaurants in {city}"
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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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)
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llm_with_tools = llm.bind_tools([get_weather, search_restaurants])
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response = llm_with_tools.invoke(
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    "What's the weather in Tokyo and find me some sushi restaurants there?"
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)
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print(response.tool_calls)

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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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    extra_body={"enable_thinking": True, "thinking_budget": 2048},
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)

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llm = ChatOpenAI(
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    model="asi1",
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    base_url="https://api.asi1.ai/v1",
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    api_key=os.getenv("ASI_ONE_API_KEY"),
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    extra_body={"planner_mode": True},
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    default_headers={"x-session-id": "4f9c2b18-6d1e-4a77-9f30-2c5b8e7a1d64"},
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)