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import gradio as gr
import git
git.Git().clone("https://github.com/Jesse-zj/bobo-test.git")
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTVectorStoreIndex, LLMPredictor, PromptHelper,ServiceContext
from llama_index import StorageContext, load_index_from_storage
from langchain import OpenAI
import sys
import os
from IPython.display import Markdown, display
openai_api_key = os.environ['OPENAI_API_KEY']
def construct_index(directory_path):
# set maximum input size
max_input_size = 4096
# set number of output tokens
num_outputs = 1000
# set maximum chunk overlap
max_chunk_overlap = 30
# set chunk size limit
chunk_size_limit = 600
# define LLM
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003", max_tokens=num_outputs))
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
documents = SimpleDirectoryReader(directory_path).load_data()
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
index = GPTVectorStoreIndex.from_documents(
documents, service_context=service_context
)
index.storage_context.persist('index.json')
return index
def ask_ai(query):
# set maximum input size
max_input_size = 4096
# set number of output tokens
num_outputs = 1000
# set maximum chunk overlap
max_chunk_overlap = 30
# set chunk size limit
chunk_size_limit = 600
# define LLM
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003", max_tokens=num_outputs))
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
# rebuild storage context
storage_context = StorageContext.from_defaults(persist_dir="index.json")
# load index
index = load_index_from_storage(storage_context, service_context=service_context)
query_engine = index.as_query_engine()
response = query_engine.query(query)
return str(response)
construct_index('bobo-test')
iface = gr.Interface(fn=ask_ai, inputs="textbox", outputs="text")
iface.launch()
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