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You can configure the
ServiceContext by creating an instance of the
ServiceContext class and providing the required components as arguments. Here's a list of the components you need to provide:
llm_predictor: LLMPredictorprompt_helper: PromptHelperembed_model: BaseEmbeddingnode_parser: NodeParserllama_logger: LlamaLoggerchunk_size_limit: chunk size limit (optional)
Alternatively, you can use the
from_defaults class method to create a
ServiceContext with default values for the components. If you want to use a specific value for a component, you can provide it as an argument to the
from_defaults method.
Here's an example of how to create a
ServiceContext using the
from_defaults method:
from gpt_index.indices.service_context import ServiceContext
service_context = ServiceContext.from_defaults(
llm_predictor=my_llm_predictor,
prompt_helper=my_prompt_helper,
embed_model=my_embed_model,
node_parser=my_node_parser,
llama_logger=my_llama_logger,
chunk_size_limit=my_chunk_size_limit
)Replace
my_* variables with your own instances of the corresponding components.
For more information, refer to the
ServiceContext documentation (
https://gpt-index.readthedocs.io/en/latest/reference/service_context.html).
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