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Use LlamaIndex with Bridge

In short: Install llama-index-llms-openai-like and create an OpenAILike with Bridge's API base, your key and is_chat_model=True. Set is_function_calling_model=True for tools and context_window to the model's real context. Every Bridge model then works in LlamaIndex, billed in naira.

Updated 8 November 2026

pip install llama-index-llms-openai-like

import os
from llama_index.llms.openai_like import OpenAILike

llm = OpenAILike(
    model="gemini-3.5-flash-lite",
    api_base="https://wekoya-api.wekoya.tech/v1",
    api_key=os.environ["WEKOYA_API_KEY"],
    is_chat_model=True,
    is_function_calling_model=True,
    context_window=1048576,  # this model's context, from its page
)
print(llm.complete("Hello"))

• is_chat_model=True is required: without it LlamaIndex calls the old completions endpoint, which Bridge does not have.
• context_window defaults to 3,900 tokens. Set it to the model's context from its page on the models page.
• For embeddings, Bridge serves gemini-embedding-2 on OpenAI's embeddings route. See embeddings.

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