How to Train an AI Chatbot With Custom Knowledge Base Using ChatGPT API
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#openai #chatgpt #chatgpttutorial #chatgptforbeginners #chatgptprompts #chatgptapi
from llama_index import SimpleDirectoryReader, GPTListIndex, readers, GPTSimpleVectorIndex,LLMPredictor, PromptHelper, ServiceContext
from langchain import OpenAI
import sys
from IPython.display import Markdown, display
import sys
import os
os.environ["OPENAI_API_KEY"] = ""
def CreateDataIndex(documentPath):
max_input_size = 4096
num_outputs = 2000
max_chunk_overlap = 20
chunk_size_limit = 600
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap,chunk_size_limit=chunk_size_limit)
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.5, model_name="text-davinci-003",max_tokens=num_outputs))
documents = SimpleDirectoryReader(documentPath).load_data()
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor, prompt_helper=prompt_helper)
index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context)
index.save_to_disk('indexData.json')
return index
def May_I_Help_You():
index = GPTSimpleVectorIndex.load_from_disk('indexData.json')
while True:
query = input("What do you want to ask? ")
response = index.query(query)
display(Markdown(f"Response: {response.response}"))
