LlamaIndex Agents integration

from llama_index.llms.openai_like import OpenAILike
import os

# Configure OpenAI-compatible LLM with Orq.ai AI Gateway
llm = OpenAILike(
    model="gpt-4o",
    api_key=os.getenv("ORQ_API_KEY"),
    api_base="https://api.orq.ai/v3/router",
    is_chat_model=True,
)

import asyncio
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.tools import FunctionTool
from llama_index.llms.openai_like import OpenAILike
import os

# Configure LLM with Orq.ai AI Gateway
llm = OpenAILike(
    model="gpt-4o",
    api_key=os.getenv("ORQ_API_KEY"),
    api_base="https://api.orq.ai/v3/router",
    is_chat_model=True,
)

# Define a tool
def get_weather(location: str) -> str:
    """Get the current weather for a location."""
    return f"The weather in {location} is sunny and 72°F"

# Create agent
agent = ReActAgent(
    tools=[FunctionTool.from_defaults(get_weather)],
    llm=llm,
)

async def main():
    response = await agent.run("What's the weather in San Francisco?")
    print(response)

asyncio.run(main())

import asyncio
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.tools import FunctionTool
from llama_index.llms.openai_like import OpenAILike
import os

llm = OpenAILike(
    model="gpt-4o",
    api_key=os.getenv("ORQ_API_KEY"),
    api_base="https://api.orq.ai/v3/router",
    is_chat_model=True,
)

def add(a: int, b: int) -> int:
    """Add two integers."""
    return a + b

def multiply(a: int, b: int) -> int:
    """Multiply two integers."""
    return a * b

def get_company_info(company: str) -> str:
    """Get basic information about a company."""
    companies = {
        "openai": "OpenAI is an AI research company founded in 2015.",
        "anthropic": "Anthropic is an AI safety company founded in 2021.",
    }
    return companies.get(company.lower(), f"No information found for {company}")

agent = ReActAgent(
    tools=[
        FunctionTool.from_defaults(add),
        FunctionTool.from_defaults(multiply),
        FunctionTool.from_defaults(get_company_info),
    ],
    llm=llm,
    system_prompt="You are a helpful assistant with access to math and company information tools.",
)

async def main():
    response = await agent.run("What is 15 * 4, and tell me about Anthropic?")
    print(response)

asyncio.run(main())

import asyncio
from llama_index.core.agent.workflow import ReActAgent
from llama_index.core.tools import FunctionTool
from llama_index.llms.openai_like import OpenAILike
import os

def get_time(timezone: str) -> str:
    """Get the current time in a timezone."""
    return f"The current time in {timezone} is 14:30"

# Use Claude
claude_llm = OpenAILike(
    model="anthropic/claude-sonnet-4-6",
    api_key=os.getenv("ORQ_API_KEY"),
    api_base="https://api.orq.ai/v3/router",
    is_chat_model=True,
)

# Use Gemini
gemini_llm = OpenAILike(
    model="google-ai/gemini-2.5-pro",
    api_key=os.getenv("ORQ_API_KEY"),
    api_base="https://api.orq.ai/v3/router",
    is_chat_model=True,
)

agent = ReActAgent(
    tools=[FunctionTool.from_defaults(get_time)],
    llm=claude_llm,
)

async def main():
    response = await agent.run("What time is it in Tokyo?")
    print(response)

asyncio.run(main())