Use large language models from Model Studio

pip install llama-index-core
pip install llama-index-llms-openai-like

import os
from llama_index.core import Settings
from llama_index.llms.openai_like import OpenAILike

# Replace the default LLM used by LlamaIndex with a Model Studio model.
Settings.llm = OpenAILike(
    model="qwen-plus",
    api_base="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    is_chat_model=True
)

import os
from llama_index.llms.openai_like import OpenAILike

# The model to call.
llm = OpenAILike(
    model="qwen-plus",
    api_base="https://dashscope.aliyuncs.com/compatible-mode/v1",
    api_key=os.getenv("DASHSCOPE_API_KEY"),
    is_chat_model=True
)

response = llm.complete("Can you recommend a 5-day travel itinerary for the Jiangsu-Zhejiang-Shanghai region?")
print(response)

pip install llama-index-core
pip install llama-index-llms-dashscope

import os
from llama_index.core import Settings
from llama_index.llms.dashscope import DashScope

# Replace the default LLM used by LlamaIndex with a Model Studio model.
Settings.llm = DashScope(model_name="qwen-plus", api_key=os.getenv("DASHSCOPE_API_KEY"))

import os
from llama_index.llms.dashscope import DashScope

llm = DashScope(model_name="qwen-plus", api_key=os.getenv("DASHSCOPE_API_KEY"))
response = llm.complete("Can you recommend a 5-day travel itinerary for the Jiangsu-Zhejiang-Shanghai region?")
print(response)