call username variable in workflow, display model name

.github/workflows/hugging_face.yml

@@ -12,11 +12,10 @@ jobs:
       - uses: actions/checkout@v3
         with:
           fetch-depth: 0
-          lfs: true
-      - name: Navigate to frontend directory
-        run: cd ./frontend
+          lfs: true      
       - name: Push to hub
         env:
           HF_TOKEN: ${{ secrets.HF_TOKEN }}
-        run: git push https://salgadev:$HF_TOKEN@huggingface.co/spaces/salgadev/docverifyrag main
+          HF_USER: ${{ variables.HF_USER }}
+        run: git push https://$HF_USER:$HF_TOKEN@huggingface.co/spaces/$HF_USER/docverifyrag main
 

app.py

@@ -1,9 +1,9 @@
-import streamlit as st
 import io
 import os
+import streamlit as st
 import tempfile
 
-from scripts import generate_metadata, ingest
+from scripts import generate_metadata, ingest, model_name
 
 
 st.title('DocVerifyRAG')
@@ -19,8 +19,9 @@ if uploaded_file is not None:
             st.write(f'Created temporary file {file_path}')
 
         docs = ingest(file_path)
+        st.write('## Querying Together.ai API')
         metadata = generate_metadata(docs)
-        st.write('## Converted Text')
+        st.write(f'## Metadata Generated by {model_name}')
         st.write(metadata)
 
         # Clean up the temporary file

scripts.py

@@ -72,8 +72,9 @@ def generate_metadata(docs):
     )
 
     # Call the LLM with the JSON schema
+    model_name = "mistralai/Mixtral-8x7B-Instruct-v0.1"
     chat_completion = client.chat.completions.create(
-        model="mistralai/Mixtral-8x7B-Instruct-v0.1",        
+        model=model_name,        
         messages=[
             {
                 "role": "system",