Update app.py

app.py

@@ -0,0 +1,82 @@
+#structure data extraction 
+from openai import OpenAI
+import json
+from dotenv import load_dotenv
+
+load_dotenv()
+api_key = os.getenv("OPENAI_API_KEY")
+client = OpenAI(api_key=api_key)
+
+def extract_student_info(description):
+    """
+    Extracts structured student information from a given description.
+    """
+    # Initialize the dictionary to store extracted information
+    student_info = {
+        "name": None,
+        "major": None,
+        "school": None,
+        "grades": None,
+        "club": []
+    }
+
+    # Use OpenAI's function calling to extract information
+    # (Assuming you have set up the function calling as per OpenAI's documentation)
+
+    return student_info
+
+functions = [
+    {
+        "name": "extract_student_info",
+        "description": "Extracts structured student information from a given description.",
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "description": {
+                    "type": "string",
+                    "description": "A detailed description of the student."
+                }
+            },
+            "required": ["description"]
+        }
+    }
+]
+
+def query_openai(prompt):
+    response = client.chat.completions.create(
+        model='gpt-4o-mini',
+        messages=[{'role': 'user', 'content': prompt}],
+        functions=functions,
+        function_call='auto',
+    )
+
+    message = response['choices'][0]['message']
+
+    if message.get('function_call'):
+        function_name = message['function_call']['name']
+        function_args = json.loads(message['function_call']['arguments'])
+
+        if function_name == 'extract_student_info':
+            description = function_args.get('description')
+            function_response = extract_student_info(description)
+
+            return function_response
+
+    return message['content']
+
+import gradio as gr
+
+def gradio_interface(description):
+    prompt = f"Please extract the following information from the given text and return it as a JSON object:\n\nname\nmajor\nschool\ngrades\nclub\nThis is the body of text to extract the information from:\n{description}"
+    result = query_openai(prompt)
+    return result
+
+iface = gr.Interface(
+    fn=gradio_interface,
+    inputs=gr.inputs.Textbox(lines=10, label="Student Description"),
+    outputs=gr.outputs.JSON(label="Extracted Student Information"),
+    title="Student Information Extractor",
+    description="Enter a student's description to extract structured information."
+)
+
+iface.launch()