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Modernized LlamaIndex integration (#1613)

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Updated LlamaIndex example
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James Braza 2024-01-20 01:06:32 -08:00 • committed by GitHub
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examples/llamaindex/main.py
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@ -1,38 +1,29 @@
import os
import weaviate
from llama_index import ServiceContext, VectorStoreIndex, StorageContext
from llama_index.llms import LocalAI
from llama_index import ServiceContext, VectorStoreIndex
from llama_index.llms import LOCALAI_DEFAULTS, OpenAILike
from llama_index.vector_stores import WeaviateVectorStore
from llama_index.storage.storage_context import StorageContext
# Weaviate client setup
client = weaviate.Client("http://weviate.default")
# Weaviate vector store setup
vector_store = WeaviateVectorStore(weaviate_client=client, index_name="AIChroma")
vector_store = WeaviateVectorStore(
weaviate_client=weaviate.Client("http://weviate.default"), index_name="AIChroma"
)
# Storage context setup
storage_context = StorageContext.from_defaults(vector_store=vector_store)
# LocalAI setup
llm = LocalAI(temperature=0, model_name="gpt-3.5-turbo", api_base="http://local-ai.default", api_key="stub")
llm.globally_use_chat_completions = True;
# LLM setup, served via LocalAI
llm = OpenAILike(temperature=0, model="gpt-3.5-turbo", **LOCALAI_DEFAULTS)
# Service context setup
service_context = ServiceContext.from_defaults(llm=llm, embed_model="local")
# Load index from stored vectors
index = VectorStoreIndex.from_vector_store(
vector_store,
storage_context=storage_context,
service_context=service_context
vector_store, service_context=service_context
)
# Query engine setup
query_engine = index.as_query_engine(similarity_top_k=1, vector_store_query_mode="hybrid")
query_engine = index.as_query_engine(
similarity_top_k=1, vector_store_query_mode="hybrid"
)
# Query example
response = query_engine.query("What is LocalAI?")
print(response)
print(response)