File size: 1,490 Bytes
26df9fd |
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 |
import os
import streamlit as st
from embedchain import App
# Load environment variables
try:
from dotenv import load_dotenv
load_dotenv()
except ImportError:
pass # dotenv not installed, likely running on Hugging Face Spaces
# Function to get the API key
def get_api_key(name):
api_key = os.environ.get(name)
if not api_key:
api_key = st.secrets.get(name)
if not api_key:
raise ValueError(
f"{name} is not set. Please set it in your environment or Streamlit secrets.")
return api_key
config_dict = {
'app': {
'config': {
'name': 'ttv-ec'
}
},
'llm': {
'provider': 'huggingface',
'config': {
'model': 'mistralai/Mistral-7B-Instruct-v0.2',
'top_p': 0.5,
'stream': False,
'prompt': """You are an AI assistant that answers questions based solely on the information provided in your knowledge base.
Question: $query
Context: $context
If the information to answer a question is not available in your knowledge base,
respond with 'I don't have enough information to answer that question.
""",
'api_key': get_api_key('HF_TOKEN')
}
},
'embedder': {
'provider': 'huggingface',
'config': {
'model': 'sentence-transformers/all-mpnet-base-v2',
'api_key': get_api_key('HF_TOKEN')
}
}
}
def create_app():
return App.from_config(config=config_dict)
|