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import streamlit as st
from transformers import pipeline
import os
import PyPDF2
# Sidebar components
st.sidebar.title("TherapyGPT Settings")
# Model selection dropdown
model_option = st.sidebar.selectbox(
"Choose AI Model:",
("GPT-4o", "distilgpt2", "gpt-neo")
)
# Document upload
uploaded_file = st.sidebar.file_uploader(
"Upload Document", type=["txt", "pdf"])
# Workspace/session management
workspace_name = st.sidebar.text_input("Workspace Name", value="Default")
if st.sidebar.button("Create Workspace"):
st.session_state.workspace = workspace_name
st.session_state.chat_history = [] # Reset chat history
# Main chat area
st.title("TherapyGPT Chat")
# Display chat history if it exists
if 'chat_history' not in st.session_state:
st.session_state.chat_history = []
for message in st.session_state.chat_history:
st.write(f"{message['role']}: {message['content']}")
# User input
user_input = st.text_input("You:", "")
if st.button("Send"):
if user_input:
# Placeholder for model interaction (we'll integrate this next)
st.session_state.chat_history.append(
{"role": "User", "content": user_input})
response = "I'm here to help." # Temporary placeholder
st.session_state.chat_history.append(
{"role": "TherapyGPT", "content": response})
# Load the model based on selection
@st.cache_resource
def load_model(model_name):
return pipeline("text-generation", model=model_name)
# Model selection logic
if model_option == "GPT-4o":
# Replace with appropriate model
model = load_model("ruslandev/llama-3-8b-gpt-4o-ru1.0-gguf")
elif model_option == "distilgpt2":
pipe = pipeline("text-generation", model="distilbert/distilgpt2")
else:
# Example HuggingFace model
pipe = pipeline("text-generation", model="EleutherAI/gpt-neo-1.3B")
def read_file(file):
if file.name.endswith('.txt'):
return file.read().decode('utf-8')
elif file.name.endswith('.pdf'):
pdf_reader = PyPDF2.PdfReader(file)
return '\n'.join([page.extract_text() for page in pdf_reader.pages])
if uploaded_file:
file_content = read_file(uploaded_file)
st.sidebar.text_area("File Content", file_content, height=200)
if 'workspaces' not in st.session_state:
st.session_state.workspaces = {}
# Load or create the workspace
if workspace_name not in st.session_state.workspaces:
st.session_state.workspaces[workspace_name] = []
# Use the chat history for this workspace
chat_history = st.session_state.workspaces[workspace_name]
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