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README.md

@@ -3,6 +3,6 @@ title: Kaleidoscope Data - LLM Data Cleaner
 emoji: 🧹
 sdk: streamlit
 sdk_version: 1.24.0
-app_file: /app/app.py
+app_file: app.py
 pinned: false
 ---

app/app.py

@@ -0,0 +1,30 @@
+# this app is streamlit app for the current project hosted on huggingface spaces
+
+import streamlit as st
+from openai_chat_completion import OpenAIChatCompletions
+
+st.title("Kaleidoscope Data - Data Cleaning LLM App")
+
+st.write("This app is a demo of the LLM model for data cleaning. It is a work in progress and is not yet ready for production use.")
+
+# text box or csv upload
+text_input = st.text_input("Enter text", "")
+# csv_file = st.file_uploader("Upload CSV", type=['csv'])
+
+# button to run data cleaning API on text via c class in openai_chat_completion.py
+if st.button("Run Data Cleaning API"):
+    
+    # if text_input is not empty, run data cleaning API on text_input
+    
+    model = "gpt-4" # "gpt-3.5-turbo"
+    sys_mes = "prompts/gpt4-system-message.txt"
+    
+    # instantiate OpenAIChatCompletions class
+    # get response from openai_chat_completion method
+    chat = OpenAIChatCompletions(model=model, system_message=sys_mes)
+    response = chat.openai_chat_completion(text_input, n_shot=5)
+    
+    
+    # display response
+    st.write(response['choices'][0]['message']['content'])
+    

requirements.txt

@@ -5,3 +5,4 @@ pandas==2.0.2
 python-dotenv==1.0.0
 scikit_learn==1.2.2
 tenacity==8.2.2
+streamlit==1.24.0