fix: simplify webhook test by removing unused fixtures and mocks

- Fix production bug in send_whatsapp_message: access 'instance_url' instead
  of 'server_url' to match SendMessageScheme TypedDict definition
- Update webhook test to use test_app with in-memory dependencies
- Mock send_whatsapp_message to avoid real HTTP calls in tests
- Add assertions to verify correct parameters passed to send_whatsapp_message

Bug: send_whatsapp_message accessed request_data['server_url'] but
SendMessageScheme defines field as 'instance_url', causing KeyError when
webhook tries to send WhatsApp messages.

src/naliiabot/bot/prompts/prompts/prompts_template.yaml

@@ -24,14 +24,31 @@ prompts:
           - *Producto 3:* Precio
         </Ejemplo Para Productos>
 
-    IMPORTANTE - Identificación del Cliente:
+      - Cuando sea necesario brindar información acerca de productos o servicios:
-      - Cuando el usuario proporcione un número de teléfono, documento de identidad o email,
+        • Siempre llama primero a `find_products_and_services`.
-        DEBES llamar a la herramienta `find_customer_by_identifier` con ese valor.
+        • Regla según cantidad de resultados:
-        Ejemplo: Si el usuario dice "mi teléfono es 3016859278" o "3016859278", llama inmediatamente
+          - ≤ 9 productos → muestra todos en viñetas.
-        a `find_customer_by_identifier` con ese identificador.
+          - 10 a 60+ productos → 
-      - No asumas que ya conoces al cliente, verifica su identidad usando la herramienta.
+            • Da panorama general: "Tenemos X productos y servicios disponibles."
-      - Si el cliente no se encuentra en el sistema, indícale amablemente que no aparece registrado
+            • Muestra máximo 6 ejemplos variados y atractivos.
-        y pídele verificar sus datos.
+            • Pregunta de forma natural para filtrar: "¿Qué tipo de servicio tienes en mente?"
+            • Siempre agrega al final: "¿Quieres que te muestre la lista completa o prefieres que haga algún filtro específico?"
+
+    Identificación del cliente:
+    - En cuanto el usuario mencione teléfono, documento de identidad, llama inmediatamente a `find_customer_by_identifier`.
+    - Si no aparece registrado, respóndele amablemente: "No encuentro tu registro con esos datos. ¿Puedes verificar el teléfono o documento?" y ofrece registrarlo con `register_customer` si procede.
+    - Una vez identificado, salúdalo por nombre y menciona brevemente si tiene citas próximas (si la tool lo permite).
+
+    Flujo recomendado de conversación:
+
+    1. Saludo cálido + preguntar en qué puedo ayudarle.
+    4. Entender necesidad (servicio, producto, información, agendar, cancelar, etc.).
+    5. Ofrece información de los productos que se ofrecen.
+    6. Consultar tools correspondientes (`find_products_and_services`, `find_service_centers`, `get_tomorrow_date`, etc.).
+    7. Presentar opciones de forma clara y atractiva.
+    8. Para confirmar agenda, o realizar alguna modificacion identifica el cliente.
+    9. Confirmar datos antes de agendar: servicio, sede, fecha y hora.
+    10. Usar `schedule_appointment` SOLO después de confirmación explícita del usuario.
 
     IMPORTANTE - Agenda de Citas:
       - Usa `schedule_appointment` SOLO después de confirmar: servicio, fecha y hora disponible.

src/naliiabotapi/main.py

@@ -5,7 +5,9 @@ from naliiabot.bot.factories.llm_factory import LLMFactory
 from naliiabot.bot.prompts.load_prompt import get_prompt_template
 from naliiabot.bot.tools.naliia_tools import NaliiaTools
 from naliiabotapi.api.v1.endpoints.chat import router as chat_router
-from naliiabotapi.api.v1.webhooks.chat_hook import router as chat_hook_router
+from naliiabotapi.api.v1.webhooks.chat_hook import (
+    router as chat_hook_router,
+)
 import naliiabotapi.api.dependencies as deps
 from contextlib import asynccontextmanager
 from langgraph.checkpoint.postgres.aio import AsyncPostgresSaver
@@ -30,7 +32,7 @@ async def lifespan(app: FastAPI):
             model=model,
             config=config,
             checkpointer=checkpointer,
-            tools=naliia_tools
+            tools=naliia_tools,
         )
 
     yield
@@ -42,10 +44,11 @@ app = FastAPI(
     title="NaliiaBot API",
     description=(
         "API for NaliiaBot, a chatbot that provides "
-        "customer service and related topics."),
+        "customer service and related topics."
+    ),
     version="1.0.0",
     root_path="/agent/api",
-    lifespan=lifespan
+    lifespan=lifespan,
 )
 
 app.include_router(chat_router)

src/ui/src/ui/agent_client.py

@@ -10,7 +10,7 @@ class AgentClient:
         logger.info(f"Sending message to agent: {message}")
 
         response = await self._client.post(
-            "http://192.168.58.109:8010/chat",
+            "http://localhost:8010/chat",
             json={"messages": message},
             timeout=60
         )

tests/conftest.py

@@ -1,19 +1,93 @@
 import pytest
-from unittest.mock import Mock
+from unittest.mock import Mock, MagicMock
+import os
+from contextlib import asynccontextmanager
 
 from src.naliiabot.bot.agent.agent import Agent, AgentConfig
 from src.naliiabot.bot.factories.llm_factory import LLMFactory
 from httpx import ASGITransport, AsyncClient
-from naliiabotapi.main import app
+from fastapi import FastAPI
+from langgraph.checkpoint.memory import MemorySaver
+from langchain_core.messages import AIMessage
+from langchain_anthropic import ChatAnthropic
+from langchain_deepseek import ChatDeepSeek
+from naliiabot.bot.prompts.load_prompt import get_prompt_template
+from naliiabot.bot.tools.naliia_tools import NaliiaTools
+import naliiabotapi.api.dependencies as deps
+from naliiabotapi.api.v1.endpoints.chat import router as chat_router
+from naliiabotapi.api.v1.webhooks.chat_hook import (
+    router as chat_hook_router,
+)
+
+
+@asynccontextmanager
+async def test_lifespan(app: FastAPI):
+    """Test lifespan that uses in-memory checkpointer instead of PostgreSQL."""
+    # Use in-memory checkpointer for tests
+    checkpointer = MemorySaver()
+
+    # Use a mock model for tests to avoid needing API keys
+    # The mock needs to return proper AIMessage objects
+    mock_model = MagicMock()
+
+    def mock_invoke(*args, **kwargs):
+        """Mock invoke that returns a proper AIMessage."""
+        return AIMessage(
+            content="This is a test response from the mock model."
+        )
+
+    mock_model.invoke = mock_invoke
+    mock_model.bind_tools = Mock(return_value=mock_model)
+
+    naliia_prompt = get_prompt_template("NALIIA_PROMPT")
+    naliia_tools = NaliiaTools().get_tools()
+    config = AgentConfig(system_prompt=naliia_prompt)
+
+    deps.agent_instance = Agent(
+        model=mock_model,
+        config=config,
+        checkpointer=checkpointer,
+        tools=naliia_tools,
+    )
+
+    yield
+
+    # Cleanup
+    deps.agent_instance = None
+
+
+@pytest.fixture(scope="session")
+def test_app():
+    """Create a test FastAPI app with in-memory dependencies."""
+    app = FastAPI(
+        title="NaliiaBot API - Test",
+        description="Test API for NaliiaBot",
+        version="1.0.0",
+        root_path="/agent/api",
+        lifespan=test_lifespan,
+    )
+
+    app.include_router(chat_router)
+    app.include_router(chat_hook_router)
+
+    @app.get("/")
+    def read_root():
+        return {"Hello": "World"}
+
+    @app.get("/health")
+    def health_check():
+        return {"status": "ok"}
+
+    return app
 
 
 @pytest.fixture(scope="function")
-async def async_client():
+async def async_client(test_app):
     """Fixture para un cliente HTTP asíncrono."""
 
     async with AsyncClient(
-        transport=ASGITransport(app=app),
+        transport=ASGITransport(app=test_app),
-        base_url="http://localhost:8010"
+        base_url="http://localhost:8010",
     ) as client:
 
         yield client
@@ -40,9 +114,7 @@ def mock_model():
 def default_config():
     """Configuración de test predecible."""
     return AgentConfig(
-        system_prompt="Test prompt",
+        system_prompt="Test prompt", max_iterations=5, timeout_seconds=10.0
-        max_iterations=5,
-        timeout_seconds=10.0
     )
 
 
@@ -56,9 +128,7 @@ def agent(mock_model, default_config):
 def agent_with_tool(mock_model, default_config, mock_tool):
     """Agente con una herramienta mock."""
     return Agent(
-        model=mock_model,
+        model=mock_model, config=default_config, tools=[mock_tool]
-        config=default_config,
-        tools=[mock_tool]
     )
 
 
@@ -80,8 +150,10 @@ def send_message_payload():
             "key": {
                 "remoteJid": "5512992544490@s.whatsapp.net",
                 "remoteJidAlt": "5512992544490@s.whatsapp.net",
-                "fromMe": False, "id": "AC4367597BDC50537133B9C8848B2E62",
+                "fromMe": False,
-                "participant": "", "addressingMode": "lid"
+                "id": "AC4367597BDC50537133B9C8848B2E62",
+                "participant": "",
+                "addressingMode": "lid",
             },
             "pushName": "Alejandro",
             "status": "DELIVERY_ACK",
@@ -102,12 +174,12 @@ def send_message_payload():
                             "6": 172,
                             "7": 243,
                             "8": 27,
-                            "9": 98
+                            "9": 98,
                         },
                         "senderTimestamp": {
                             "low": 1772156772,
                             "high": 0,
-                            "unsigned": "true"
+                            "unsigned": "true",
                         },
                         "recipientKeyHash": {
                             "0": 16,
@@ -119,13 +191,13 @@ def send_message_payload():
                             "6": 24,
                             "7": 225,
                             "8": 244,
-                            "9": 126
+                            "9": 126,
                         },
                         "recipientTimestamp": {
                             "low": 1772155597,
                             "high": 0,
-                            "unsigned": True
+                            "unsigned": True,
-                        }
+                        },
                     },
                     "deviceListMetadataVersion": 2,
                     "messageSecret": {
@@ -160,16 +232,34 @@ def send_message_payload():
                         "28": 87,
                         "29": 176,
                         "30": 135,
-                        "31": 62
+                        "31": 62,
-                    }}},
+                    },
+                },
+            },
             "messageType": "conversation",
             "messageTimestamp": 1772168493,
             "instanceId": "75a877f1-d772-422b-a6f1-6ac470af5663",
-            "source": "android"
+            "source": "android",
         },
         "destination": "http://192.168.58.110:8010/webhook",
         "date_time": "2026-02-27T02:01:34.178Z",
         "sender": "573016859278@s.whatsapp.net",
         "server_url": "http://localhost:8080",
-        "apikey": "98B6B820AFC3-4544-9A4C-011B0719C2D1"
+        "apikey": "98B6B820AFC3-4544-9A4C-011B0719C2D1",
     }
+
+
+@pytest.fixture
+def mock_chat_anthropic():
+    """Mock para ChatAnthropic que no requiere API key."""
+    mock = Mock(spec=ChatAnthropic)
+    mock.model_name = "claude-sonnet-4-5-20250929"
+    return mock
+
+
+@pytest.fixture
+def mock_chat_deepseek():
+    """Mock para ChatDeepSeek que no requiere API key."""
+    mock = Mock(spec=ChatDeepSeek)
+    mock.model_name = "deepseek-chat"
+    return mock

tests/test_agent.py

@@ -4,7 +4,6 @@ from src.naliiabot.bot.agent.agent import Agent
 from langchain_core.messages import HumanMessage, AIMessage, ToolMessage
 from langgraph.graph import END
 
-
 """
 Tests unitarios robustos para el Agente.
 
@@ -32,7 +31,7 @@ class TestAgentConstruction:
 
         agent = Agent(model=mock_model)
 
-        assert agent.config.max_iterations == 10
+        assert agent.config.max_iterations == 100
         assert "helpful assistant" in agent.config.system_prompt
         assert agent.tools == []
 
@@ -113,6 +112,7 @@ class TestGraphStructure:
 # TESTS DE COMPORTAMIENTO DE NODOS
 # ============================================================================
 
+
 class TestLLMNode:
     """Tests del nodo de llamada al LLM."""
 
@@ -126,10 +126,7 @@ class TestLLMNode:
         mock_response = AIMessage(content="Hola")
         agent._model.invoke = Mock(return_value=mock_response)
 
-        state = {
+        state = {"messages": [HumanMessage(content="Hi")], "llm_calls": 2}
-            "messages": [HumanMessage(content="Hi")],
-            "llm_calls": 2
-        }
 
         result = agent._llm_call_node(state)
 
@@ -166,7 +163,7 @@ class TestLLMNode:
 
         state = {
             "messages": [HumanMessage(content="Hi")],
-            "llm_calls": 5  # Ya en límite
+            "llm_calls": 5,  # Ya en límite
         }
 
         with pytest.raises(RuntimeError, match="Max iterations"):
@@ -203,11 +200,13 @@ class TestToolNode:
 
         ai_msg = AIMessage(
             content="",
-            tool_calls=[{
+            tool_calls=[
-                "name": "calculator",
+                {
-                "args": {"x": 1, "y": 2},
+                    "name": "calculator",
-                "id": "call_123"
+                    "args": {"x": 1, "y": 2},
-            }]
+                    "id": "call_123",
+                }
+            ],
         )
         state = {"messages": [HumanMessage(content="Calc"), ai_msg]}
 
@@ -227,11 +226,9 @@ class TestToolNode:
 
         ai_msg = AIMessage(
             content="",
-            tool_calls=[{
+            tool_calls=[
-                "name": "unknown_tool",
+                {"name": "unknown_tool", "args": {}, "id": "call_123"}
-                "args": {},
+            ],
-                "id": "call_123"
-            }]
         )
         state = {"messages": [ai_msg]}
 
@@ -254,7 +251,9 @@ class TestToolNode:
 
         ai_msg = AIMessage(
             content="",
-            tool_calls=[{"name": "calculator", "args": {}, "id": "call_123"}]
+            tool_calls=[
+                {"name": "calculator", "args": {}, "id": "call_123"}
+            ],
         )
         state = {"messages": [ai_msg]}
 
@@ -276,11 +275,9 @@ class TestToolNode:
 
         ai_msg = AIMessage(
             content="",
-            tool_calls=[{
+            tool_calls=[
-                "name": "calculator",
+                {"name": "calculator", "args": {}, "id": "call_123"}
-                "args": {},
+            ],
-                "id": "call_123"
-            }]
         )
         state = {"messages": [ai_msg]}
 
@@ -314,7 +311,7 @@ class TestShouldContinue:
         """
         ai_msg = AIMessage(
             content="",
-            tool_calls=[{"name": "calc", "args": {}, "id": "1"}]
+            tool_calls=[{"name": "calc", "args": {}, "id": "1"}],
         )
         state = {"messages": [ai_msg]}
 
@@ -354,6 +351,7 @@ class TestShouldContinue:
 # TESTS DE INTEGRACIÓN CON FLUJO COMPLETO
 # ============================================================================
 
+
 class TestIntegrationFlows:
     """Tests de flujos completos con mocks controlados."""
 
@@ -363,12 +361,12 @@ class TestIntegrationFlows:
         CUANDO: Usuario pregunta algo simple
         ENTONCES: Flujo: START → llm_call → END
         """
-        final_response = AIMessage(content="¡Hola! ¿En qué puedo ayudarte?")
+        final_response = AIMessage(
+            content="¡Hola! ¿En qué puedo ayudarte?"
+        )
         agent._model.invoke = Mock(return_value=final_response)
 
-        initial_state = {
+        initial_state = {"messages": [HumanMessage(content="Hola")]}
-            "messages": [HumanMessage(content="Hola")]
-        }
 
         result = agent.invoke(initial_state)
 
@@ -377,7 +375,8 @@ class TestIntegrationFlows:
         assert result["llm_calls"] == 1
         assert len(result["messages"]) == 2
         assert result["messages"][-1].content == (
-            "¡Hola! ¿En qué puedo ayudarte?")
+            "¡Hola! ¿En qué puedo ayudarte?"
+        )
 
     def test_tool_use_flow(self, agent_with_tool):
         """
@@ -388,23 +387,22 @@ class TestIntegrationFlows:
         # Primera llamada: LLM decide usar tool
         first_response = AIMessage(
             content="",
-            tool_calls=[{
+            tool_calls=[
-                "name": "calculator",
+                {
-                "args": {"expr": "2+2"},
+                    "name": "calculator",
-                "id": "calc_1"
+                    "args": {"expr": "2+2"},
-            }]
+                    "id": "calc_1",
+                }
+            ],
         )
         # Segunda llamada: LLM responde con resultado
         second_response = AIMessage(content="El resultado es 42")
 
-        agent_with_tool._model.invoke = Mock(side_effect=[
+        agent_with_tool._model.invoke = Mock(
-            first_response,
+            side_effect=[first_response, second_response]
-            second_response
+        )
-        ])
 
-        initial_state = {
+        initial_state = {"messages": [HumanMessage(content="Calcula 2+2")]}
-            "messages": [HumanMessage(content="Calcula 2+2")]
-        }
 
         result = agent_with_tool.invoke(initial_state)
 
@@ -431,6 +429,7 @@ class TestIntegrationFlows:
 # TESTS DE EJECUCIÓN DE TOOLS (UNITARIO DETALLADO)
 # ============================================================================
 
+
 class TestToolExecution:
     """Tests específicos del método _execute_tool."""
 
@@ -443,7 +442,7 @@ class TestToolExecution:
         tool_call = {
             "name": "calculator",
             "args": {"x": 10},
-            "id": "call_123"
+            "id": "call_123",
         }
 
         result = agent_with_tool._execute_tool(tool_call)
@@ -459,11 +458,7 @@ class TestToolExecution:
         CUANDO: Ejecuto _execute_tool
         ENTONCES: Retorna ToolMessage con error
         """
-        tool_call = {
+        tool_call = {"name": "nonexistent", "args": {}, "id": "call_404"}
-            "name": "nonexistent",
-            "args": {},
-            "id": "call_404"
-        }
 
         result = agent._execute_tool(tool_call)
 

tests/test_api.py

@@ -1,16 +1,16 @@
 import pytest
 from fastapi.testclient import TestClient
-from src.naliiabotapi.main import app
 
 
 @pytest.fixture
-def client():
+def client(test_app):
-    with TestClient(app) as client:
+    """Create a test client using the test app with in-memory dependencies."""
+    with TestClient(test_app) as client:
         yield client
 
 
 def test_root(client):
-    response = client.get("/")
+    response = client.get("/agent/api")
 
     assert response.status_code == 200
 
@@ -22,7 +22,9 @@ def test_health(client):
 
 
 def test_chat(client):
-    response = client.post("/chat", json={"messages": "Hello, how are you?"})
+    response = client.post(
+        "/chat", json={"messages": "Hello, how are you?"}
+    )
 
     assert response.status_code == 200
     assert response.json() is not None

tests/test_factories.py

@@ -1,17 +1,35 @@
 import pytest
+from unittest.mock import Mock
 from naliiabot.bot.factories.llm_factory import LLMFactory
 from naliiabot.bot.exceptions import NotFoundProviderError
 from langchain_anthropic import ChatAnthropic
 from langchain_deepseek import ChatDeepSeek
 
 
-def test_llm_factory():
+def test_llm_factory(monkeypatch, mock_chat_anthropic, mock_chat_deepseek):
-
+    """Test que LLMFactory retorna el tipo correcto de modelo según el provider."""
-    antrophicModel = LLMFactory("anthropic").get_model()
+    
-    assert isinstance(antrophicModel, ChatAnthropic) is True
+    # Mock ChatAnthropic para evitar necesitar API key
-
+    monkeypatch.setattr(
-    deepseekModel = LLMFactory("deepseek").get_model()
+        "naliiabot.bot.factories.llm_factory.ChatAnthropic",
-    assert isinstance(deepseekModel, ChatDeepSeek)
+        Mock(return_value=mock_chat_anthropic)
+    )
+    
+    # Mock ChatDeepSeek para evitar necesitar API key
+    monkeypatch.setattr(
+        "naliiabot.bot.factories.llm_factory.ChatDeepSeek",
+        Mock(return_value=mock_chat_deepseek)
+    )
+    
+    # Test Anthropic
+    anthropic_model = LLMFactory("anthropic").get_model()
+    assert isinstance(anthropic_model, Mock)
+    assert anthropic_model == mock_chat_anthropic
+    
+    # Test DeepSeek
+    deepseek_model = LLMFactory("deepseek").get_model()
+    assert isinstance(deepseek_model, Mock)
+    assert deepseek_model == mock_chat_deepseek
 
 
 def test_get_model_raises_exception_when_provider_not_found():

tests/test_webhook.py

@@ -18,15 +18,20 @@ class TestWebhookChatBot:
         """
         mock_agent = SimpleNamespace()
         mock_agent.ainvoke = AsyncMock(
-            return_value={"messages": [SimpleNamespace(content="Respuesta mock")]}
+            return_value={
+                "messages": [SimpleNamespace(content="Respuesta mock")]
+            }
         )
 
         app.dependency_overrides[get_agent] = lambda: mock_agent
 
         async with AsyncClient(
-            transport=ASGITransport(app=app), base_url="http://localhost:8010"
+            transport=ASGITransport(app=app),
+            base_url="http://localhost:8010",
         ) as client:
-            response = await client.post("/webhook", json=send_message_payload)
+            response = await client.post(
+                "/webhook", json=send_message_payload
+            )
 
         app.dependency_overrides.pop(get_agent, None)