Update app.py

app.py

@@ -1,6 +1,7 @@
 import requests
 import json
-import os 
+import os
+import gradio as gr
 
 api_token = os.environ.get("TOKEN")
 API_URL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-8B-Instruct"
@@ -37,7 +38,7 @@ assistant
         response = output[0].get('generated_text', '').strip().lower()
 
         questions = response.count('questions')
-        ChatmodelLLM = response.count('Chatmodel/LLM')
+        chat_model_llm = response.count('chatmodel/llm')
         other = response.count('other')
         image_generation = response.count("image_generation")
         fine_tuning = response.count("fine_tuning")
@@ -49,9 +50,9 @@ assistant
 
         if questions == 2:
             return 'questions'
-        elif ChatmodelLLM == 2:
+        elif chat_model_llm == 2:
             return 'Chat Model/LLM'
-        elif other == 2: 
+        elif other == 2:
             return "Other"
         elif image_generation == 2:
             return "Image Generation"
@@ -71,11 +72,11 @@ assistant
             return f"Erreur: Réponse ambiguë - '{response}'"
 
 # URL de base de l'API
-base_url = "https://huggingface.co/api/posts?skip=20&sort=recent"
+base_url = "https://huggingface.co/api/posts"
 
 # Paramètres pour la pagination
 skip = 0  # Nombre d'éléments à sauter
-limit = 1000  # Nombre maximal d'éléments à récupérer par requête
+limit = 100  # Nombre maximal d'éléments à récupérer par requête
 
 # Liste pour stocker tous les posts avec leur texte
 all_posts_with_text = []
@@ -113,8 +114,16 @@ while True:
 
 # Maintenant, all_posts_with_text contient tous les posts récupérés avec leur texte
 
-# Initialisation des compteurs
-questions_count, Chat_ModelLLM_count, Other_count, ImageGeneration_count, Fine_tuning_count, EthicsandBias_count, Datasets_count, ToolsandLibraries_count, Tutorials_and_Guides_count,Debugging_count = 0,0,0,0,0,0,0,0,0,0
+questions_count = 0
+chat_model_llm_count = 0
+other_count = 0
+image_generation_count = 0
+fine_tuning_count = 0
+ethics_and_bias_count = 0
+datasets_count = 0
+tools_and_libraries_count = 0
+tutorials_and_guides_count = 0
+debugging_count = 0
 
 # Appliquer votre algorithme d'analyse à tous les posts
 for i, post in enumerate(all_posts_with_text, 1):
@@ -124,40 +133,36 @@ for i, post in enumerate(all_posts_with_text, 1):
     # Appeler votre algorithme d'analyse
     resultat = analyze_sentiment(text)
 
-    # Incrémenter les compteurs en fonction du résultat
     if resultat == 'questions':
         questions_count += 1
     elif resultat == "Chat Model/LLM":
-        Chat_ModelLLM_count += 1
+        chat_model_llm_count += 1
     elif resultat == 'Other':
-        Other_count += 1
+        other_count += 1
     elif resultat == "Image Generation":
-        ImageGeneration_count += 1
+        image_generation_count += 1
     elif resultat == "Fine-tuning":
-        Fine_tuning_count += 1
+        fine_tuning_count += 1
     elif resultat == "Ethics and Bias":
-        EthicsandBias_count += 1
+        ethics_and_bias_count += 1
     elif resultat == 'Datasets':
-        Datasets_count += 1
+        datasets_count += 1
     elif resultat == 'Tools and Libraries':
-        ToolsandLibraries_count += 1
+        tools_and_libraries_count += 1
     elif resultat == "Tutorials and Guides":
-        Tutorials_and_Guides_count += 1
+        tutorials_and_guides_count += 1
     elif resultat == "Debugging":
-        Debugging_count += 1
-
-# Affichage des résultats
-print(
-
-    f"Questions: {questions_count}",
-    f"Chat Model/LLM: {Chat_ModelLLM_count}",
-    f"Other: {Other_count}",
-    f"Image Generation: {ImageGeneration_count}",
-    f"Fine-tuning: {Fine_tuning_count}",
-    f"Ethics and Bias: {EthicsandBias_count}",
-    f"Datasets: {Datasets_count}",
-    f"Tools and Libraries: {ToolsandLibraries_count}",
-    f"Tutorials and Guides: {Tutorials_and_Guides_count}",
-    f"Debugging: {Debugging_count}"
-
-)
+        debugging_count += 1
+
+# Vous pouvez adapter votre algorithme d'analyse selon vos besoins spécifiques
+
+print(f"Questions: {questions_count}")
+print(f"Chat Model/LLM: {chat_model_llm_count}")
+print(f"Other: {other_count}")
+print(f"Image Generation: {image_generation_count}")
+print(f"Fine-tuning: {fine_tuning_count}")
+print(f"Ethics and Bias: {ethics_and_bias_count}")
+print(f"Datasets: {datasets_count}")
+print(f"Tools and Libraries: {tools_and_libraries_count}")
+print(f"Tutorials and Guides: {tutorials_and_guides_count}")
+print(f"Debugging: {debugging_count}")