Divymakesml commited on
Commit
5fb33c2
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1 Parent(s): 9369110

Update app.py

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Files changed (1) hide show
  1. app.py +8 -8
app.py CHANGED
@@ -18,12 +18,17 @@ You can create a requirements.txt with:
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  Deploy this file (app.py) along with requirements.txt to Hugging Face Spaces.
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  """
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- # Dependency checks
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  try:
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  import streamlit as st
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  except ImportError:
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  raise ImportError("Missing dependency: streamlit. Install it with 'pip install streamlit'.")
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  try:
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  from transformers import pipeline
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  except ImportError:
@@ -34,15 +39,10 @@ try:
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  except ImportError:
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  raise ImportError("Missing dependency: torch. Install it with 'pip install torch'.")
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- import os
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-
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- # Optional: display a note if running on Hugging Face Spaces (the SPACE_ID env var is set in Spaces)
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  if os.environ.get("SPACE_ID"):
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  st.info("Running on Hugging Face Spaces.")
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- # Configure the Streamlit page
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- st.set_page_config(page_title="AI Friend Therapist Assistant", layout="centered")
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-
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  # Load the Hugging Face summarization model (cached to avoid reloading)
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  @st.cache(allow_output_mutation=True)
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  def load_summarizer():
@@ -64,7 +64,7 @@ st.write(
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  # Text area for user input
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  user_input = st.text_area("Your message", height=150)
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- # When the user clicks "Send", process the input
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  if st.button("Send"):
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  if user_input.strip():
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  # Append the message to conversation history
 
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  Deploy this file (app.py) along with requirements.txt to Hugging Face Spaces.
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  """
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+ # Dependency checks and initial imports
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  try:
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  import streamlit as st
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  except ImportError:
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  raise ImportError("Missing dependency: streamlit. Install it with 'pip install streamlit'.")
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+ # Immediately set the page configuration
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+ st.set_page_config(page_title="AI Friend Therapist Assistant", layout="centered")
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+
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+ import os
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+
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  try:
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  from transformers import pipeline
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  except ImportError:
 
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  except ImportError:
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  raise ImportError("Missing dependency: torch. Install it with 'pip install torch'.")
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+ # Optional: display a note if running on Hugging Face Spaces
 
 
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  if os.environ.get("SPACE_ID"):
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  st.info("Running on Hugging Face Spaces.")
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  # Load the Hugging Face summarization model (cached to avoid reloading)
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  @st.cache(allow_output_mutation=True)
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  def load_summarizer():
 
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  # Text area for user input
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  user_input = st.text_area("Your message", height=150)
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+ # Process user input when "Send" is clicked
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  if st.button("Send"):
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  if user_input.strip():
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  # Append the message to conversation history