Update app.py

GenAI/proxy/app.py

@@ -46,6 +46,16 @@ if not TEST_MODE:
         print("Executando em modo de teste...")
         TEST_MODE = True
 
+# --------------------------
+# Modelos suportados
+# --------------------------
+
+SUPPORTED_MODELS = {
+    "gpt5": "ocid1.generativeaimodel.oc1.us-chicago-1.amaaaaaask7dceyasebknceb4ekbiaiisjtu3fj5i7s4io3ignvg4ip2uyma",
+    "grok3mini": "ocid1.generativeaimodel.oc1.us-chicago-1.amaaaaaask7dceyavwbgai5nlntsd5hngaileroifuoec5qxttmydhq7mykq",
+    "llama4maverick": "ocid1.generativeaimodel.oc1.us-chicago-1.amaaaaaask7dceyayjawvuonfkw2ua4bob4rlnnlhs522pafbglivtwlfzta"
+}
+
 # --------------------------
 # Session Store
 # --------------------------
@@ -114,10 +124,13 @@ def session_controller(region, agent_endpoint_id, channel, cuid):
 # Inferência GenAI
 # --------------------------
 
-def call_inference_model(region, compartment_id, model_id, prompt):
+def call_inference_model(region, compartment_id, model_id, prompt, **kwargs):
     if TEST_MODE:
         return {"response": {"text": f"Resposta simulada: {prompt}", "finish_reason": "stop"}}
 
+    if model_id not in SUPPORTED_MODELS.values():
+        return {"error": "Modelo não implementado"}
+
     try:
         endpoint = f"https://inference.generativeai.{region}.oci.oraclecloud.com"
 
@@ -134,12 +147,18 @@ def call_inference_model(region, compartment_id, model_id, prompt):
         chat_request = oci.generative_ai_inference.models.GenericChatRequest(
             api_format=oci.generative_ai_inference.models.BaseChatRequest.API_FORMAT_GENERIC,
             messages=[message],
-            max_tokens=50000,
+            max_tokens=kwargs.get("max_tokens", 600),
-            temperature=1,
+            temperature=kwargs.get("temperature", 1),
-            top_p=1,
+            top_p=kwargs.get("top_p", 1),
-            top_k=0
+            top_k=kwargs.get("top_k", 0),
+            frequency_penalty=kwargs.get("frequency_penalty", 0),
+            presence_penalty=kwargs.get("presence_penalty", 0)
         )
 
+        if model_id == SUPPORTED_MODELS["gpt5"]:
+            chat_request.reasoning_effort = kwargs.get("reasoning_effort", "MEDIUM")
+            chat_request.verbosity = kwargs.get("verbosity", "MEDIUM")
+
         chat_detail = oci.generative_ai_inference.models.ChatDetails(
             serving_mode=oci.generative_ai_inference.models.OnDemandServingMode(model_id=model_id),
             chat_request=chat_request,
@@ -149,171 +168,12 @@ def call_inference_model(region, compartment_id, model_id, prompt):
         chat_response = generative_ai_inference_client.chat(chat_detail)
         choice = chat_response.data.chat_response.choices[0]
 
-        return {"response": {
+        return {
+            "response": {
                 "text": choice.message.content[0].text,
                 "finish_reason": choice.finish_reason
-        }}
+            }
+        }
 
     except Exception as e:
         return {"error": str(e)}
-
-# --------------------------
-# Autenticação
-# --------------------------
-
-def check_api_key():
-    expected_key = os.environ.get("API_KEY")
-    if not expected_key:
-        print("AVISO: API_KEY não configurada.")
-        return
-
-    auth_header = request.headers.get("Authorization", "")
-    token = ""
-    if auth_header.startswith("Bearer "):
-        token = auth_header.split("Bearer ")[1].strip()
-    else:
-        token = request.headers.get("X-API-Key")
-
-    if token != expected_key:
-        abort(401, description="API key inválida.")
-
-@app.before_request
-def before_all_requests():
-    check_api_key()
-
-# --------------------------
-# Endpoints REST
-# --------------------------
-
-@app.route("/", methods=["GET"])
-def test():
-    return jsonify({"status": "ok"})
-
-@app.route("/genai-agent/<region>/<agent_endpoint_id>/session", methods=["POST"])
-def manage_session(region, agent_endpoint_id):
-    data = request.get_json()
-    channel = data.get("channel")
-    cuid = data.get("cuid")
-    if not all([channel, cuid]):
-        return jsonify({"error": "Parâmetros 'channel' e 'cuid' são obrigatórios"}), 400
-    response_data = session_controller(region, agent_endpoint_id, channel, cuid)
-    return jsonify(response_data)
-
-@app.route("/genai-agent/<region>/<agent_endpoint_id>/<session_id>/chat", methods=["POST"])
-def agent_chat(region, agent_endpoint_id, session_id):
-    data = request.get_json()
-    user_message = data.get("userMessage")
-    if not user_message:
-        return jsonify({"error": "userMessage é obrigatório"}), 400
-
-    try:
-        base_url = f"https://agent-runtime.generativeai.{region}.oci.oraclecloud.com/20240531"
-        chat_url = f"{base_url}/agentEndpoints/{agent_endpoint_id}/actions/chat"
-        session_obj = requests.Session()
-        session_obj.auth = signer
-        payload = {
-            "userMessage": user_message,
-            "shouldStream": False,
-            "sessionId": session_id
-        }
-        response = session_obj.post(chat_url, json=payload)
-        response.raise_for_status()
-        return jsonify({"agentResponse": response.json()})
-
-    except Exception as e:
-        return jsonify({"error": str(e)}), 500
-
-@app.route("/genai/<region>/<compartment_id>/<model_id>/inference", methods=["POST"])
-def inference(region, compartment_id, model_id):
-    data = request.get_json()
-    prompt = data.get("prompt")
-    if not prompt:
-        return jsonify({"error": "Campo 'prompt' é obrigatório."}), 400
-
-    response_data = call_inference_model(region, compartment_id, model_id, prompt)
-    return jsonify(response_data)
-
-@app.route("/genai/<region>/<compartment_id>/<model_id>/v1/chat/completions", methods=["POST"])
-def openai_compatible_chat(region, compartment_id, model_id):
-    data = request.get_json()
-    messages = data.get("messages", [])
-    temperature = data.get("temperature", 1)
-    top_p = data.get("top_p", 1)
-    top_k = data.get("top_k", 0)
-    max_tokens = data.get("max_tokens", 1000)
-
-    user_prompt = next((m["content"] for m in reversed(messages) if m["role"] == "user"), None)
-    if not user_prompt:
-        return jsonify({"error": "mensagem do usuário é obrigatória"}), 400
-
-    response = call_inference_model(region, compartment_id, model_id, user_prompt)
-    if "error" in response:
-        return jsonify({"error": response["error"]}), 500
-
-    result_text = response["response"]["text"]
-    finish_reason = response["response"].get("finish_reason", "stop")
-
-    return jsonify({
-        "id": f"chatcmpl-{uuid.uuid4().hex[:12]}",
-        "object": "chat.completion",
-        "created": int(time.time()),
-        "model": model_id,
-        "choices": [
-            {
-                "index": 0,
-                "message": {"role": "assistant", "content": result_text},
-                "finish_reason": finish_reason
-            }
-        ]
-    })
-
-@app.route("/genai/<region>/<compartment_id>/<model_id>/v1/completions", methods=["POST"])
-def openai_compatible_completion(region, compartment_id, model_id):
-    data = request.get_json()
-    prompt = data.get("prompt")
-    temperature = data.get("temperature", 1)
-    top_p = data.get("top_p", 1)
-    top_k = data.get("top_k", 0)
-    max_tokens = data.get("max_tokens", 1000)
-    stop = data.get("stop")
-
-    if not prompt:
-        return jsonify({"error": "Campo 'prompt' é obrigatório."}), 400
-
-    response = call_inference_model(region, compartment_id, model_id, prompt)
-    if "error" in response:
-        return jsonify({"error": response["error"]}), 500
-
-    result_text = response["response"]["text"]
-    finish_reason = response["response"].get("finish_reason", "stop")
-
-    if stop:
-        if isinstance(stop, list):
-            for s in stop:
-                if s in result_text:
-                    result_text = result_text.split(s)[0]
-                    break
-        elif isinstance(stop, str) and stop in result_text:
-            result_text = result_text.split(stop)[0]
-
-    return jsonify({
-        "id": f"cmpl-{uuid.uuid4().hex[:12]}",
-        "object": "text_completion",
-        "created": int(time.time()),
-        "model": model_id,
-        "choices": [
-            {
-                "index": 0,
-                "text": result_text,
-                "logprobs": None,
-                "finish_reason": finish_reason
-            }
-        ]
-    })
-
-# --------------------------
-# Inicialização
-# --------------------------
-
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=8000)