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import os
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# Uncomment to specify your OpenAI API key here (local testing only, not in production!), or add corresponding environment variable (recommended)
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# os.environ['OPENAI_API_KEY']= ""
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from llama_index import LLMPredictor, PromptHelper, ServiceContext
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from langchain.llms.openai import OpenAI
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from llama_index import StorageContext, load_index_from_storage
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base_path = os.environ.get('OPENAI_API_BASE', 'http://localhost:8080/v1')
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# This example uses text-davinci-003 by default; feel free to change if desired
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llm_predictor = LLMPredictor(llm=OpenAI(temperature=0, model_name="gpt-3.5-turbo",openai_api_base=base_path))
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# Configure prompt parameters and initialise helper
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max_input_size = 1024
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num_output = 256
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max_chunk_overlap = 20
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prompt_helper = PromptHelper(max_input_size, num_output, max_chunk_overlap)
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# Load documents from the 'data' directory
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service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
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# rebuild storage context
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storage_context = StorageContext.from_defaults(persist_dir='./storage')
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# load index
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index = load_index_from_storage(storage_context, service_context=service_context, )
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query_engine = index.as_query_engine()
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response = query_engine.query("XXXXXX your question here XXXXX")
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print(response)
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