Llamaindex chat with docs

llamaindex.py

from llama_index.llms import Ollama
from llama_index import VectorStoreIndex, SimpleDirectoryReader
from llama_index import ServiceContext

from llama_index import (
    ServiceContext,
    SimpleDirectoryReader,
    StorageContext,
    VectorStoreIndex,
    set_global_service_context,
)

llama2 = Ollama(model="llama2")

service_context = (
    ServiceContext
    .from_defaults(
        llm=llama2,
        embed_model="local:BAAI/bge-small-en-v1.5",
        chunk_size=300
    )
)

documents = SimpleDirectoryReader("data").load_data()
set_global_service_context(service_context)
nodes = (
    service_context
    .node_parser
    .get_nodes_from_documents(documents)
)

storage_context = StorageContext.from_defaults()
storage_context.docstore.add_documents(nodes)
index = (
    VectorStoreIndex
    .from_documents(
        documents,
        storage_context=storage_context,
        llm=llama2
        )
)
query_engine = index.as_query_engine()

response = query_engine.query("what is Jim's profession? Answer concisely.")
print(response)