Enter Query: do you offer Unity3D? INFO:llama_index.token_counter.token_counter:> [retrieve] Total LLM token usage: 0 tokens INFO:llama_index.token_counter.token_counter:> [retrieve] Total embedding token usage: 7 tokens INFO:llama_index.token_counter.token_counter:> [get_response] Total LLM token usage: 1803 tokens INFO:llama_index.token_counter.token_counter:> [get_response] Total embedding token usage: 0 tokens INFO:llama_index.token_counter.token_counter:> [get_response] Total LLM token usage: 1803 tokens INFO:llama_index.token_counter.token_counter:> [get_response] Total embedding token usage: 0 tokens Output: Yes, they offer resources skilled in Unity3D for game development.
import logging logging.getLogger().handlers.clear()
from langchain import OpenAI
from llama_index import SimpleDirectoryReader, LangchainEmbedding, GPTListIndex, GPTVectorStoreIndex, PromptHelper, StorageContext, load_index_from_storage
from llama_index import LLMPredictor, ServiceContext
import os
from dotenv import dotenv_values
os.environ['OPENAI_API_KEY'] = dotenv_values()['OPENAI_API_KEY']
def construct_index(directory_path):
# set maximum input size
max_input_size = 4096
# set number of output tokens
num_outputs = 256
# set maximum chunk overlap
max_chunk_overlap = 0.2
# set chunk size limit
chunk_size_limit = 600
prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
# define LLM
llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.2, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
documents = SimpleDirectoryReader(directory_path).load_data()
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist('index.json')
return index
def ask_bot(query, input_index='index.json'):
storage_context = StorageContext.from_defaults(persist_dir=input_index)
index = load_index_from_storage(storage_context)
query_engine = index.as_query_engine(response_mode='compact')
response = query_engine.query(query)
response = str(response)
print("Output: " + response)
return response
# construct_index('knowledge/')from llama_index import SimpleDirectoryReader, ListIndex, VectorStoreIndex, StorageContext, load_index_from_storage
from llama_index import ServiceContext
from llama_index.llms import OpenAI
import os
from dotenv import dotenv_values
os.environ['OPENAI_API_KEY'] = dotenv_values()['OPENAI_API_KEY']
def get_service_context():
chunk_size = 600
num_outputs = 256
context_window = 4096
# define LLM
llm = OpenAI(temperature=0.2, model="gpt-3.5-turbo", max_tokens=num_outputs)
service_context = ServiceContext.from_defaults(
llm=llm,
chunks_size=chunk_size,
context_window=context_window,
)
return service_context
def construct_index(directory_path):
service_context = get_service_context()
documents = SimpleDirectoryReader(directory_path).load_data()
index = GPTVectorStoreIndex.from_documents(documents, service_context=service_context)
index.storage_context.persist(persist_dir='./storage')
return index
def ask_bot(query, input_index_dir='./storage'):
service_context = get_service_context()
storage_context = StorageContext.from_defaults(persist_dir=input_index_dir)
index = load_index_from_storage(storage_context, service_context=service_context)
query_engine = index.as_query_engine(
response_mode='compact',
similarity_top_k=3, # bump up the top k from 2 due to smaller chunk size?
)
response = query_engine.query(query)
response = str(response)
print("Output: " + response)
return response
# construct_index('knowledge/')File "/Library/Frameworks/Python.framework/Versions/3.11/lib/python3.11/site-packages/openai/util.py", line 186, in default_api_key
raise openai.error.AuthenticationError(
openai.error.AuthenticationError: No API key provided. You can set your API key in code using 'openai.api_key = <API-KEY>', or you can set the environment variable OPENAI_API_KEY=<API-KEY>). If your API key is stored in a file, you can point the openai module at it with 'openai.api_key_path = <PATH>'. You can generate API keys in the OpenAI web interface. See https://platform.openai.com/account/api-keys for details.openai.api_key = "sk-..."