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examples: better defaults

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mudler 2023-05-07 00:58:30 +02:00
parent cbdcc839f3
commit 02979566ee
2 changed files with 5 additions and 5 deletions
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2
examples/query_data/query.py
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@ -10,7 +10,7 @@ from llama_index import StorageContext, load_index_from_storage
base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
# This example uses text-davinci-003 by default; feel free to change if desired
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo",openai_api_base=base_path))
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
# Configure prompt parameters and initialise helper
max_input_size = 1024

8
examples/query_data/store.py
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@ -13,15 +13,15 @@ base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo", openai_api_base=base_path))
# Configure prompt parameters and initialise helper
max_input_size = 256
num_output = 256
max_chunk_overlap = 10
max_input_size = 512
num_output = 512
max_chunk_overlap = 30
prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
# Load documents from the 'data' directory
documents = SimpleDirectoryReader('data').load_data()
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper, chunk_size_limit = 257)
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper, chunk_size_limit = 512)
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist(persist_dir="./storage")