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