Delete gradio_iface.py

gradio_iface.py

@@ -1,91 +0,0 @@
-import requests
-import os
-import json
-import gradio as gr
-from dotenv import load_dotenv
-
-load_dotenv()
-
-api_key = os.getenv('API_KEY')
-
-
-# Mapping function to class
-function_mapping = {
-    "Creation_dossier_kbis": 'POST',
-    "Redaction_non_juridique": 'DRAFT',
-    "Redaction_juridique": '0',
-    "Resume": '0',
-    "Salutations": 'DRAFT',
-    "Traduction": 'DRAFT',
-    "Information_utilisateur": 'GET',
-    "Information_dossier": 'GET',
-    "Information_personne_societe": 'GET',
-    "Autre_demande": '0'
-}
-
-# Load tools
-with open("tools-intent-detection.json", "r", encoding="utf-8") as file:
-    tools = json.load(file)
-
-# API configuration
-url = 'https://openai-dev-fra-001.openai.azure.com/openai/deployments/gpt-4o/chat/completions?api-version=2024-10-21'
-headers = {
-    'api-key': api_key,
-    'Content-Type': 'application/json'
-}
-
-def get_model_response(user_prompt):
-    # messages list
-    messages = [
-        {
-            "role": "system",
-            "content": ""
-        },
-        {
-            "role": "user",
-            "content": user_prompt
-        }
-    ]
-    
-    # payload
-    data = {
-        "model": "gpt-4o",
-        "messages": messages,
-        "tools": tools,
-        "tool_choice": "required"
-    }
-    
-    # API call
-    response = requests.post(url, headers=headers, data=json.dumps(data))
-    
-    # Process the response
-    if response.status_code != 200:
-        return f"Error: {response.status_code} - {response.text}", "0"
-    else:
-        response_data = response.json()
-        if 'choices' in response_data:
-            reply = response_data["choices"][0]["message"]
-            
-            # Extract function name from tool_calls
-            if 'tool_calls' in reply and len(reply['tool_calls']) > 0:
-                function_name = reply['tool_calls'][0]['function']['name']
-                # Get the corresponding class from the mapping
-                category = function_mapping.get(function_name, "0")  # 0 is default if function name not found
-                return function_name, category
-            else:
-                return "No function called", "0"
-        else:
-            return "Unexpected response format.", "0"
-
-# Gradio app
-iface = gr.Interface(
-    title="Intent Detection Playground",
-    fn=get_model_response,
-    inputs=gr.Textbox(label="User Prompt"),
-    outputs=[
-        gr.Textbox(label="Intention"),
-        gr.Textbox(label="Category")
-    ]
-)
-
-iface.launch()