Update app.py

app.py

@@ -9,6 +9,7 @@ from flask import Flask, request, jsonify, send_file
 from gtts import gTTS
 from groq import Groq
 import google.generativeai as genai
+from google.generativeai.types import GenerationConfig
 
 # --- CONFIGURAÇÃO INICIAL ---
 app = Flask(__name__)
@@ -45,7 +46,6 @@ except Exception as e:
 @app.route('/list-models')
 def list_models():
     available_models = []
-    # Lista de modelos Groq para geração de texto foi atualizada.
     groq_text_models = [
         "llama-3.1-8b-instant", 
         "llama-3.3-70b-versatile", 
@@ -63,7 +63,6 @@ def list_models():
                             "value": f"gemini:{model_name}",
                             "name": m.display_name
                         })
-
         if groq_client:
             for model_id in groq_text_models:
                  display_name = model_id.split('/')[-1].replace('-instant', '').replace('-versatile', '')
@@ -71,14 +70,12 @@ def list_models():
                     "value": f"groq:{model_id}",
                     "name": f"Groq: {display_name}"
                 })
-                
     except Exception as e:
         print(f"Erro ao listar modelos: {e}")
         return jsonify([
             {"value": "gemini:gemini-2.5-flash-latest", "name": "Gemini 2.5 Flash (Fallback)"},
             {"value": "groq:llama-3.1-8b-instant", "name": "Llama 3.1 8B (Fallback)"}
         ])
-
     return jsonify(available_models)
 
 
@@ -123,13 +120,12 @@ def explain_proxy():
             schema = {"type": "object", "properties": {"term": {"type": "string"}, "translation": {"type": "string"}, "context_sentence": {"type": "string"}, "gapped_sentence": {"type": "string"}, "definition": {"type": "string"}}, "required": ["term", "translation", "context_sentence", "gapped_sentence", "definition"]}
             prompt = f"Analyze '{word}' in context: '{context}'. Generate a JSON for a flashcard. The 'gapped_sentence' must replace '{word}' with '______________'."
             return jsonify(get_ai_text_response(model_provider, model_name, system_instruction_base, prompt, json_schema=schema))
-        
         else:
             prompt = f"Analyze '{word}' in context: '{context}'. Provide a one-sentence English explanation, then '---', then the Portuguese translation."
             parts = get_ai_text_response(model_provider, model_name, system_instruction_base, prompt).split('---', 1)
             return jsonify({"explanation": parts[0].strip(), "translation": parts[1].strip() if len(parts) > 1 else 'N/A'})
-
     except Exception as e:
+        print(f"AI ANALYSIS ERROR in /explain-proxy: {e}")
         return jsonify({"error": f"AI analysis failed: {e}"}), 500
 
 @app.route('/activity-feedback', methods=['POST'])
@@ -141,7 +137,6 @@ def activity_feedback():
     user_response = data.get('user_response', '')
 
     if not original_prompt or not user_response: return jsonify({"error": "Original prompt and user response are required."}), 400
-
     if (model_provider == 'gemini' and not genai_client) or (model_provider == 'groq' and not groq_client):
         return jsonify({"error": f"{model_provider.upper()}_API_KEY not configured."}), 503
 
@@ -155,7 +150,6 @@ def activity_feedback():
         "Structure your feedback with markdown for clarity (e.g., using ### Corrected Version)."
     )
     user_prompt = f"The original task was: \"{original_prompt}\"\n\nHere is the user's response:\n---\n{user_response}\n---\nPlease provide your feedback."
-
     try:
         feedback_text = get_ai_text_response(model_provider, model_name, system_instruction, user_prompt)
         return jsonify({"feedback": feedback_text})
@@ -179,13 +173,18 @@ def analyze_image():
         model = genai_client.GenerativeModel(model_name)
         schema = { "type": "object", "properties": { "vocabulary": { "type": "array", "items": { "type": "object", "properties": { "term": {"type": "string"}, "definition": {"type": "string"} }, "required": ["term", "definition"] } } }, "required": ["vocabulary"] }
         prompt = [ "Act as an English teacher. Identify 5-7 key objects/concepts in this image. For each, provide its English name and a simple definition. Return a single JSON object conforming to the schema.", image ]
-        response = model.generate_content(prompt, generation_config={"response_mime_type": "application/json", "response_schema": schema})
+        
+        # CORREÇÃO: Usa o objeto GenerationConfig
+        config = GenerationConfig(response_mime_type="application/json", response_schema=schema)
+        response = model.generate_content(prompt, generation_config=config)
+        
         return jsonify(json.loads(response.text)['vocabulary'])
     except Exception as e:
         return jsonify({"error": f"Image analysis failed: {e}"}), 500
 
 @app.route('/chat-with-ai', methods=['POST'])
 def chat_with_ai():
+    # ... (código existente sem alterações) ...
     if not groq_client: return jsonify({"error": "GROQ_API_KEY not configured."}), 503
     data = request.get_json()
     history, user_message = data.get('history', []), data.get('message', '')
@@ -200,6 +199,7 @@ def chat_with_ai():
 
 @app.route('/pronunciation-feedback', methods=['POST'])
 def pronunciation_feedback():
+    # ... (código existente sem alterações) ...
     if not groq_client: return jsonify({"error": "GROQ_API_KEY not configured."}), 503
     data = request.get_json()
     target_text, user_text = data.get('target_text'), data.get('user_text')
@@ -215,6 +215,7 @@ def pronunciation_feedback():
 
 @app.route('/generate-image', methods=['POST'])
 def generate_image():
+    # ... (código existente sem alterações) ...
     if not genai_client: return jsonify({"error": "GEMINI_API_KEY not configured."}), 503
     data = request.get_json()
     prompt = data.get('prompt')
@@ -231,9 +232,12 @@ def generate_image():
 def get_ai_text_response(provider, model_name, system_instruction, user_prompt, json_schema=None):
     if provider == 'gemini':
         model = genai_client.GenerativeModel(model_name, system_instruction=system_instruction)
-        config = {}
+        
+        # CORREÇÃO: Cria o objeto GenerationConfig a partir do dicionário.
+        config = None
         if json_schema:
-            config = {"response_mime_type": "application/json", "response_schema": json_schema}
+            config = GenerationConfig(response_mime_type="application/json", response_schema=json_schema)
+        
         response = model.generate_content(user_prompt, generation_config=config)
         
         parsed_json = json.loads(response.text)
@@ -241,9 +245,10 @@ def get_ai_text_response(provider, model_name, system_instruction, user_prompt,
             required_keys = json_schema.get("required", [])
             if not all(key in parsed_json and parsed_json[key] for key in required_keys):
                 raise ValueError(f"AI response missing required keys. Required: {required_keys}, Got: {list(parsed_json.keys())}")
-        return parsed_json
+        return parsed_json if json_schema else response.text.strip()
 
     elif provider == 'groq':
+        # ... (código existente sem alterações) ...
         final_user_prompt = user_prompt
         if json_schema:
              final_user_prompt += f"\n\nYou MUST respond with a single JSON object that strictly follows this schema. Do not add any other text before or after the JSON object:\n{json.dumps(json_schema)}"