Create app.py

app.py

@@ -0,0 +1,87 @@
+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]