Integrations · Python
LlamaIndex Integration
Build RAG applications with LlamaIndex and XALEN. Index classical texts and query them with domain-specialist models.
1. Install
pip install llama-index-llms-openai-like
2. Code
#89B4FA;">from llama_index.llms.openai_like import OpenAILike
#89B4FA;">from llama_index.core import VectorStoreIndex, SimpleDirectoryReader
llm = OpenAILike(
model=#A6E3A1;">"vedika-standard",
api_key=#A6E3A1;">"xln_test_YOUR_KEY",
api_base=#A6E3A1;">"https://api.xalen.io/v1"
)
documents = SimpleDirectoryReader(#A6E3A1;">"./texts").load_data()
index = VectorStoreIndex.from_documents(documents)
query_engine = index.as_query_engine(llm=llm)
response = query_engine.query(#A6E3A1;">"What does BPHS say about Gajakesari Yoga?")
#89B4FA;">print(response)
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