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Runtime error
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22a9440 eb9bbc9 22a9440 29ff848 eb9bbc9 22a9440 f43048b 29ff848 96e634c 29ff848 eb9bbc9 29ff848 96e634c 29ff848 c7cdf77 29ff848 308df49 8810fc0 29ff848 96e634c 7a0a525 29ff848 3dc878a 29ff848 22a9440 eb9bbc9 29ff848 22a9440 d19a684 22a9440 96e634c 22a9440 75c051b 22a9440 | 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 | from gpt_index import GPTSimpleVectorIndex
from langchain import OpenAI
import gradio as gr
import sys
import os
import datetime
import huggingface_hub
from huggingface_hub import Repository
from datetime import datetime
import csv
os.environ["OPENAI_API_KEY"] = os.environ['SECRET_CODE']
# Need to write to persistent dataset because cannot store temp data on spaces
DATASET_REPO_URL = "https://huggingface.co/datasets/peterpull/MediatorBot"
DATA_FILENAME = "data.csv"
DATA_FILE = os.path.join("data", DATA_FILENAME)
# I am guessing we need a write access token.
HF_TOKEN = os.environ.get("HF_TOKEN")
print("HF TOKEN is none?", HF_TOKEN is None)
print("HF hub ver", huggingface_hub.__version__)
repo = Repository(
local_dir="data",
clone_from=DATASET_REPO_URL,
use_auth_token=HF_TOKEN)
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['chatinput']}</span>"
html += f"<span class='message'>{row['chatresponse']}</span>"
html += f"<span class='time'>{row['time']}</span>"
html += "</div>"
html += "</div>"
return html
def store_message(chatinput: str, chatresponse: str):
if chatinput and chatresponse:
with open(DATA_FILE, "a") as csvfile:
writer = csv.writer(csvfile, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
if csvfile.tell() == 0:
writer.writerow(['User input', 'Chatbot response', 'Date and Time'])
writer.writerow([chatinput, chatresponse, datetime.now().strftime('%Y-%m-%d %H:%M:%S')])
commit_url = repo.push_to_hub()
print(commit_url)
return generate_html()
#gets the index file which is the context data
def get_index(index_file_path):
if os.path.exists(index_file_path):
return GPTSimpleVectorIndex.load_from_disk(index_file_path)
else:
print(f"Error: '{index_file_path}' does not exist.")
sys.exit()
# passes the prompt to the chatbot
def chatbot(input_text, mentioned_person='Mediator John Haynes'):
index = get_index('./index/indexsmall.json')
prompt = f"You are {mentioned_person}: {input_text}\n\n At the end of your answer ask a provocative question."
response = index.query(prompt, response_mode="compact")
store_message(input_text,response)
# return the response
return response.response
iface = gr.Interface(fn=chatbot,
inputs=gr.inputs.Textbox("Enter your question"),
outputs="text",
title="AI Chatbot trained on J. Haynes mediation material, v0.1",
description="test")
iface.launch()
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