Delete app.py

app.py

@@ -1,272 +0,0 @@
-#app.py
-import os
-import io
-import json
-import base64
-from PIL import Image
-
-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__)
-
-# --- CONFIGURAÇÃO DAS APIS LLM ---
-genai_client = None
-groq_client = None
-
-# 1. Configuração Gemini
-try:
-    GEMINI_API_KEY = os.environ.get("GEMINI_API_KEY")
-    if GEMINI_API_KEY:
-        genai.configure(api_key=GEMINI_API_KEY)
-        genai_client = genai
-    else:
-        print("AVISO: GEMINI_API_KEY não configurada.")
-except Exception as e:
-    genai_client = None
-    print(f"ERRO ao inicializar o cliente Gemini: {e}.")
-
-# 2. Configuração Groq
-try:
-    GROQ_API_KEY = os.environ.get("GROQ_API_KEY")
-    if GROQ_API_KEY:
-        groq_client = Groq(api_key=GROQ_API_KEY)
-    else:
-        print("AVISO: GROQ_API_KEY não configurada.")
-except Exception as e:
-    groq_client = None
-    print(f"ERRO ao inicializar o cliente Groq: {e}.")
-
-
-# --- ROTA PARA LISTAR MODELOS DINAMICAMENTE ---
-@app.route('/list-models')
-def list_models():
-    available_models = []
-    groq_text_models = [
-        "llama-3.1-8b-instant", 
-        "llama-3.3-70b-versatile", 
-        "openai/gpt-oss-120b",
-        "openai/gpt-oss-20b"
-    ]
-    try:
-        if genai_client:
-            for m in genai_client.list_models():
-                if 'generateContent' in m.supported_generation_methods:
-                    model_name = m.name.replace("models/", "")
-                    if "flash" in model_name or "pro" in model_name:
-                         available_models.append({
-                            "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', '')
-                 available_models.append({
-                    "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)
-
-
-# --- ROTAS PRINCIPAIS ---
-
-@app.route('/tts-proxy', methods=['POST'])
-def tts_proxy():
-    data = request.get_json()
-    text = data.get('text', '')
-    tld = data.get('tld', 'co.uk') 
-    if not text: return jsonify({"error": "No text provided"}), 400
-    try:
-        tts = gTTS(text=text, lang='en', tld=tld)
-        mp3_fp = io.BytesIO()
-        tts.write_to_fp(mp3_fp)
-        mp3_fp.seek(0)
-        return send_file(mp3_fp, mimetype='audio/mpeg')
-    except Exception as e:
-        return jsonify({"error": f"Failed to generate audio via gTTS: {e}"}), 500
-
-@app.route('/explain-proxy', methods=['POST'])
-def explain_proxy():
-    data = request.get_json()
-    model_provider, model_name = data.get('model', 'gemini:gemini-2.5-flash-latest').split(':', 1)
-    context_focus = data.get('context_focus', 'General/Social')
-    custom_prompt = data.get('custom_prompt', None)
-    word = data.get('word', '').strip()
-    context = data.get('context', '')
-    for_flashcard = data.get('for_flashcard', False)
-
-    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
-    
-    system_instruction_base = f"You are a professional English tutor. The user's study focus is '{context_focus}'. All your responses must be in ENGLISH."
-    try:
-        if custom_prompt:
-            activity_text = get_ai_text_response(model_provider, model_name, system_instruction_base, custom_prompt)
-            return jsonify({"explanation": activity_text})
-        
-        if not word: return jsonify({"error": "No word selected."}), 400
-        
-        if for_flashcard:
-            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'])
-def activity_feedback():
-    data = request.get_json()
-    model_provider, model_name = data.get('model', 'gemini:gemini-2.5-flash-latest').split(':', 1)
-    context_focus = data.get('context_focus', 'General/Social')
-    original_prompt = data.get('original_prompt', '')
-    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
-
-    system_instruction = (
-        "You are an expert English teacher providing feedback. "
-        f"The user's study focus is '{context_focus}'. "
-        "Your entire response MUST be in English. "
-        "Provide clear, constructive feedback on the user's writing. "
-        "Point out grammar, spelling, or style errors. "
-        "Offer a corrected or improved version of their text. "
-        "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})
-    except Exception as e:
-        return jsonify({"error": f"AI feedback failed: {e}"}), 500
-
-@app.route('/analyze-image', methods=['POST'])
-def analyze_image():
-    if not genai_client: return jsonify({"error": "GEMINI_API_KEY not configured."}), 503
-    data = request.get_json()
-    base64_image = data.get('image')
-    model_value = data.get('model', 'gemini:gemini-2.5-flash-latest')
-    
-    model_name = 'gemini-2.5-flash-latest' # Default
-    if model_value.startswith('gemini:'):
-        model_name = model_value.split(':', 1)[1]
-
-    if not base64_image: return jsonify({"error": "No image data."}), 400
-    try:
-        image = Image.open(io.BytesIO(base64.b64decode(base64_image.split(',')[1])))
-        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 ]
-        
-        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():
-    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', '')
-    if not user_message: return jsonify({"error": "No message."}), 400
-    try:
-        system = "You are 'Groq Chat', a friendly English tutor. Keep responses concise (1-2 sentences). If the user makes a grammar mistake, gently correct it. Ask questions to keep the conversation flowing. Always respond in English."
-        messages = [{"role": "system", "content": system}] + history + [{"role": "user", "content": user_message}]
-        response = groq_client.chat.completions.create(model="llama-3.1-8b-instant", messages=messages, temperature=0.7)
-        return jsonify({"response": response.choices[0].message.content.strip()})
-    except Exception as e:
-        return jsonify({"error": f"AI chat failed: {e}"}), 500
-
-@app.route('/pronunciation-feedback', methods=['POST'])
-def pronunciation_feedback():
-    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')
-    if not target_text or not user_text: return jsonify({"error": "Required data missing."}), 400
-    try:
-        system_instruction = "You are an expert American English pronunciation coach. The user tried to say a target sentence, and their speech was transcribed. Based on the likely pronunciation differences, provide brief, friendly, and actionable feedback in Portuguese. Focus on 1-2 key points. If it's very close, praise the user."
-        user_prompt = f"Target: \"{target_text}\"\nTranscription: \"{user_text}\"\n\nProvide pronunciation feedback."
-        messages = [{"role": "system", "content": system_instruction}, {"role": "user", "content": user_prompt}]
-        response = groq_client.chat.completions.create(model="llama-3.1-8b-instant", messages=messages, temperature=0.5)
-        return jsonify({"feedback": response.choices[0].message.content.strip()})
-    except Exception as e:
-        return jsonify({"error": f"Pronunciation analysis failed: {e}"}), 500
-
-@app.route('/generate-image', methods=['POST'])
-def generate_image():
-    if not genai_client: return jsonify({"error": "GEMINI_API_KEY not configured."}), 503
-    data = request.get_json()
-    prompt = data.get('prompt')
-    if not prompt: return jsonify({"error": "Image prompt is required."}), 400
-    try:
-        model = genai_client.GenerativeModel(model_name='gemini-2.5-flash-image-preview')
-        response = model.generate_content(prompt)
-        base64_image_data = response.parts[0].inline_data.data
-        return jsonify({"image_base64": base64_image_data})
-    except Exception as e:
-        return jsonify({"error": f"Image generation failed: {e}"}), 500
-
-# --- FUNÇÃO AUXILIAR E ROTA RAIZ ---
-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 = None
-        if json_schema:
-            config = GenerationConfig(response_mime_type="application/json", response_schema=json_schema)
-        
-        response = model.generate_content(user_prompt, generation_config=config)
-        
-        if json_schema:
-            parsed_json = json.loads(response.text)
-            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 or has empty values.")
-            return parsed_json
-        else:
-            return response.text.strip()
-
-    elif provider == 'groq':
-        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)}"
-        
-        messages = [{"role": "system", "content": system_instruction}, {"role": "user", "content": final_user_prompt}]
-        config = {'response_format': {"type": "json_object"}} if json_schema else {}
-        response = groq_client.chat.completions.create(model=model_name, messages=messages, **config)
-        
-        if json_schema:
-            parsed_json = json.loads(response.choices[0].message.content)
-            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 or has empty values.")
-            return parsed_json
-        else:
-            return response.choices[0].message.content.strip()
-
-    raise Exception(f"Unsupported provider: {provider}")
-
-@app.route('/')
-def root():
-    return send_file('index.html')
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860)