Rename Movie_app.py to app.py

Movie_app.py

@@ -1,68 +0,0 @@
-import streamlit as st
-
-st.set_page_config(page_title="Turkish Review Analysis - via AG", page_icon='📖')
-st.header("📖Movie Review Analysis - TR")
-
-with st.sidebar:
-    hf_key = st.text_input("HuggingFace Access Key", key="hf_key", type="password")
-
-MODEL_MOVIE = {
-    "albert": "anilguven/albert_tr_turkish_movie_reviews",  # Add the emoji for the Meta-Llama model
-    "distilbert": "anilguven/distilbert_tr_turkish_movie_reviews",
-    "bert": "anilguven/bert_tr_turkish_movie_reviews",
-    "electra": "anilguven/electra_tr_turkish_movie_reviews",
-}
-
-MODEL_MOVIES = ["albert","distilbert","bert","electra"]
-
-# Use a pipeline as a high-level helper
-from transformers import pipeline
-# Create a mapping from formatted model names to their original identifiers
-def format_model_name(model_key):
-    name_parts = model_key
-    formatted_name = ''.join(name_parts)  # Join them into a single string with title case
-    return formatted_name
-
-formatted_names_to_identifiers = {
-    format_model_name(key): key for key in MODEL_MOVIE.keys()
-}
-
-with st.expander("About this app"):
-    st.write(f"""
-    1-Choose your model for movie review analysis (negative or positive).\n
-    2-Enter your sample text.\n
-    3-And model predict your text's result. 
-    """)
-    
-# Debug to ensure names are formatted correctly
-#st.write("Formatted Model Names to Identifiers:", formatted_names_to_identifiers)
-
-model_name: str = st.selectbox("Model", options=MODEL_MOVIES)
-selected_model = MODEL_MOVIE[model_name]
-
-if not hf_key:
-    st.info("Please add your HuggingFace Access Key to continue.")
-    st.stop()
-
-access_token = hf_key
-pipe = pipeline("text-classification", model=selected_model, token=access_token)
-
-#from transformers import AutoTokenizer, AutoModelForSequenceClassification
-#tokenizer = AutoTokenizer.from_pretrained(selected_model)
-#pipe = AutoModelForSequenceClassification.from_pretrained(pretrained_model_name_or_path=selected_model)
-
-comment = st.text_input("Enter your text for analysis")#User input
-
-st.text('')
-if st.button("Submit for Analysis"):#User Review Button
-    if not hf_key:
-        st.info("Please add your HuggingFace Access Key to continue.")
-        st.stop()
-    else:
-        result = pipe(comment)[0]
-        label=''
-        if result["label"] == "LABEL_0": label = "Negative"
-        else: label = "Positive"
-        st.text(label + " comment with " + str(result["score"]) + " accuracy")
-
-

app.py

@@ -0,0 +1,15 @@
+import streamlit as st
+
+st.set_page_config(page_title="Turkish Review Analysis - via AG", page_icon='📖')
+st.header("📖Positive-Negative Review Analysis")
+
+
+st.write(f"""
+Do you want to review analysis for Turkish language? \n
+This space analyzes your movie or hotel reviews as positive-negative. \n
+You also upload your own file and obtain file analysis results, then download it. \n
+I wait to try your data.
+""")
+    
+
+