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chore: update Next.js build artifacts (2026-10-23 22:19 UTC, node v24.19.0)

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Yuneng Jiang 2026-10-23 15:19:46 -07:00
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client = openai.OpenAI(
api_key="your_api_key",
base_url="${s}" # LiteLLM Proxy is OpenAI compatible, Read More: https://docs.litellm.ai/docs/proxy/user_keys
)
response = client.chat.completions.create(
model="gpt-3.5-turbo", # model to send to the proxy
messages = [
{
"role": "user",
"content": "this is a test request, write a short poem"
}
]
)
print(response)`})}),(0,t.jsx)(r.TabsContent,{value:"llamaindex",keepMounted:!0,children:(0,t.jsx)(n.default,{language:"python",code:`import os, dotenv
from llama_index.llms import AzureOpenAI
from llama_index.embeddings import AzureOpenAIEmbedding
from llama_index import VectorStoreIndex, SimpleDirectoryReader, ServiceContext
llm = AzureOpenAI(
engine="azure-gpt-3.5", # model_name on litellm proxy
temperature=0.0,
azure_endpoint="${s}", # litellm proxy endpoint
api_key="<your-master-key>", # litellm proxy API Key
api_version="2023-07-01-preview",
)
embed_model = AzureOpenAIEmbedding(
deployment_name="azure-embedding-model",
azure_endpoint="${s}",
api_key="<your-master-key>",
api_version="2023-07-01-preview",
)
documents = SimpleDirectoryReader("llama_index_data").load_data()
service_context = ServiceContext.from_defaults(llm=llm, embed_model=embed_model)
index = VectorStoreIndex.from_documents(documents, service_context=service_context)
query_engine = index.as_query_engine()
response = query_engine.query("What did the author do growing up?")
print(response)`})}),(0,t.jsx)(r.TabsContent,{value:"langchain",keepMounted:!0,children:(0,t.jsx)(n.default,{language:"python",code:`from langchain.chat_models import ChatOpenAI
from langchain.prompts.chat import (
ChatPromptTemplate,
HumanMessagePromptTemplate,
SystemMessagePromptTemplate,
)
from langchain.schema import HumanMessage, SystemMessage
chat = ChatOpenAI(
openai_api_base="${s}",
model = "gpt-3.5-turbo",
temperature=0.1
)
messages = [
SystemMessage(
content="You are a helpful assistant that im using to make a test request to."
),
HumanMessage(
content="test from litellm. tell me why it's amazing in 1 sentence"
),
]
response = chat(messages)
print(response)`})})]})]})})};var l=e.i(541202),d=e.i(135214),m=e.i(592392);e.s(["default",0,()=>{let{accessToken:e}=(0,d.default)(),n=(0,m.default)(e);return(0,t.jsxs)(t.Fragment,{children:[(0,t.jsx)(l.DeprecationBanner,{featureName:"The API Reference tab"}),(0,t.jsx)(i,{proxySettings:n})]})}],191905)},541202,e=>{"use strict";var t=e.i(843476),n=e.i(271645),r=e.i(522016),s=e.i(952571),a=e.i(37727);e.s(["DeprecationBanner",0,({featureName:e})=>{let[o,i]=(0,n.useState)(!1);return o?null:(0,t.jsxs)("div",{role:"alert",className:"mb-4 flex items-start gap-3 rounded-lg border border-border bg-muted/50 px-4 py-3 text-sm",children:[(0,t.jsx)(s.Info,{className:"mt-0.5 size-4 shrink-0 text-muted-foreground"}),(0,t.jsxs)("div",{className:"min-w-0 flex-1",children:[(0,t.jsx)("p",{className:"font-medium",children:`${e} is on a draft deprecation list`}),(0,t.jsxs)("p",{className:"mt-1 break-words text-muted-foreground",children:[`${e} is one of several experimental features we're considering removing, potentially as early as September 1, 2026. This list is a draft and is not final. If you rely on this feature, please share feedback on the `,(0,t.jsx)(r.default,{href:"https://github.com/BerriAI/litellm/discussions/32090",target:"_blank",rel:"noopener noreferrer",className:"underline underline-offset-4",children:"deprecation discussion"}),"."]})]}),(0,t.jsx)("button",{type:"button","aria-label":"Close",onClick:()=>i(!0),className:"shrink-0 rounded-md p-0.5 text-muted-foreground transition-colors hover:text-foreground",children:(0,t.jsx)(a.X,{className:"size-4"})})]})}])}]);

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