Spaces:
Runtime error
Runtime error
File size: 3,513 Bytes
827c483 728663b 827c483 728663b f2f0f51 827c483 f2f0f51 827c483 728663b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
import os
import gradio as gr
from llama_index import GPTSimpleVectorIndex, SimpleDirectoryReader, ServiceContext,LLMPredictor
from langchain.chat_models import ChatOpenAI
from llama_index.llm_predictor.chatgpt import ChatGPTLLMPredictor
import huggingface_hub
from huggingface_hub import Repository
from datetime import datetime
import csv
DATASET_REPO_URL = "https://huggingface.co/datasets/diazcalvi/kionlinde"#"https://huggingface.co/datasets/julien-c/persistent-space-dataset"
DATA_FILENAME = "kion.json"
DATA_FILE = os.path.join("data", DATA_FILENAME)
HF_TOKEN = os.environ.get("HF_TOKEN")
print("is none?", HF_TOKEN is None)
print("hfh", huggingface_hub.__version__)
#os.system("git config --global user.name \"Carlos Diaz\"")
#os.system("git config --global user.email \"[email protected]\"")
##repo = Repository(
# local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
#)
index_name = "./data/kion.json"
documents_folder = "./documents"
#@st.experimental_memo
#@st.cache_resource
def initialize_index(index_name, documents_folder):
#llm_predictor = ChatGPTLLMPredictor()
llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")) # text-davinci-003"))"gpt-3.5-turbo"
service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor)
if os.path.exists(index_name):
index = GPTSimpleVectorIndex.load_from_disk(index_name)
else:
documents = SimpleDirectoryReader(documents_folder).load_data()
index = GPTSimpleVectorIndex.from_documents(documents)
index.save_to_disk(index_name)
print(DATA_FILE)
index.save_to_disk(DATA_FILE)
return index
#@st.experimental_memo
#@st.cache_data(max_entries=200, persist=True)
def query_index(_index, query_text):
response = _index.query(query_text)
return str(response)
def generate_html() -> str:
with open(DATA_FILE) as csvfile:
reader = csv.DictReader(csvfile)
rows = []
for row in reader:
rows.append(row)
rows.reverse()
if len(rows) == 0:
return "no messages yet"
else:
html = "<div class='chatbot'>"
for row in rows:
html += "<div>"
html += f"<span>{row['name']}</span>"
html += f"<span class='message'>{row['message']}</span>"
html += "</div>"
html += "</div>"
return html
def store_message(name: str, message: str):
if name and message:
print(DATA_FILE)
print(DATA_FILENAME)
print(DATASET_REPO_URL)
with open(DATA_FILE, "a") as csvfile:
writer = csv.DictWriter(csvfile, fieldnames=["name", "message", "time"])
writer.writerow(
{"name": name, "message": message, "time": str(datetime.now())}
)
commit_url = repo.push_to_hub()
print(commit_url)
return commit_url #generate_html()
def greet(text):
response = query_index(index, "Act as a KION equipment expert:" + text)
return response
index = None
api_key = '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'#st.text_input("Enter your OpenAI API key here:", type="password")
if api_key:
os.environ['OPENAI_API_KEY'] = api_key
index = initialize_index(index_name, documents_folder)
if index is None:
st.warning("Please enter your api key first.")
iface = gr.Interface(fn=greet, inputs="text", outputs="text")
iface.launch() |