feat: Add NaliiaTools

src/naliiabot/bot/agent/agent.py

@@ -1,5 +1,6 @@
 from langgraph.graph import StateGraph, START, END
 from langchain_core.messages import SystemMessage, ToolMessage, BaseMessage
+import logging
 from typing import Literal, Callable, Any
 from .schemas import MessagesState
 from dataclasses import dataclass
@@ -38,10 +39,9 @@ class Agent:
                 - Si es None: sin herramientas
                 - Si es list: lista de herramientas
         """
+
         self._model = model
         self._config = config or AgentConfig()
-        
-        # Normalizar tools: usar la lista proporcionada o lista vacía
         self._tools = tools or []
             
         self._tools_by_name: dict[str, Any] = {
@@ -49,7 +49,6 @@ class Agent:
         }
         self._compiled_agent = self._compile_agent()
 
-        # Hooks para testing (monkey-patching friendly)
         self._pre_llm_hook: Callable | None = None
         self._post_tool_hook: Callable | None = None
 
@@ -92,26 +91,28 @@ class Agent:
 
     def set_pre_llm_hook(self, hook: Callable[[dict], None]):
         """Registra hook pre-llm para testing."""
+
         self._pre_llm_hook = hook
 
     def set_post_tool_hook(self, hook: Callable[[dict, Any], None]):
         """Registra hook post-tool para testing."""
+
         self._post_tool_hook = hook
 
     def _compile_agent(self):
         """Compila el grafo una sola vez."""
+
         agent = self._build_agent()
+
         return agent.compile()
 
     def _build_agent(self) -> StateGraph:
         """Construye el grafo de estado completo."""
         agent_builder = StateGraph(MessagesState)
 
-        # Nodos
         agent_builder.add_node("llm_call", self._llm_call_node)
         agent_builder.add_node("tool_node", self._tool_node)
 
-        # Flujo
         agent_builder.add_edge(START, "llm_call")
         agent_builder.add_conditional_edges(
             "llm_call",
@@ -125,8 +126,6 @@ class Agent:
 
         return agent_builder
 
-    # ============ Nodos del Grafo ============
-
     def _llm_call_node(self, state: MessagesState) -> dict:
         """
         Nodo LLM: Decide siguiente acción o responde.
@@ -143,6 +142,7 @@ class Agent:
         ] + state["messages"]
 
         model_with_tools = self._model.bind_tools(self._tools)
+
         response = model_with_tools.invoke(messages)
 
         current_calls = state.get("llm_calls", 0)
@@ -185,29 +185,30 @@ class Agent:
         Ejecuta una herramienta individual con manejo de errores.
         """
         tool_name = tool_call.get("name")
-        tool_id = tool_call.get("id", "unknown")
+        tool_id = tool_call.get("id")
         tool_args = tool_call.get("args", {})
 
         if tool_name not in self._tools_by_name:
             return ToolMessage(
                 content=f"Error: Tool '{tool_name}' not found",
                 tool_call_id=tool_id,
-                status="error"
+                name=tool_name,
             )
 
         try:
             tool = self._tools_by_name[tool_name]
             observation = tool.invoke(tool_args)
+
             return ToolMessage(
                 content=str(observation),
                 tool_call_id=tool_id,
-                status="success"
+                name=tool_name)
-            )
+
         except Exception as e:
             return ToolMessage(
                 content=f"Error executing tool: {str(e)}",
                 tool_call_id=tool_id,
-                status="error"
+                name=tool_name,
             )
 
     def _should_continue(

src/naliiabot/bot/agent/schemas.py

@@ -1,8 +1,8 @@
-from langchain.messages import AnyMessage
+from langchain_core.messages import AnyMessage
+from langgraph.graph.message import add_messages
 from typing_extensions import TypedDict, Annotated
-import operator
 
 
 class MessagesState(TypedDict):
-    messages: Annotated[list[AnyMessage], operator.add]
+    messages: Annotated[list[AnyMessage], add_messages]
     llm_calls: int

src/naliiabot/bot/factories/llm_factory.py

@@ -35,7 +35,9 @@ class LLMFactory:
 
     def _create_anthropic(self):
         model_name = "claude-sonnet-4-5-20250929"
-        model = ChatAnthropic(model=model_name)
+        model = ChatAnthropic(
+            model=model_name
+        )
 
         return model
 

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

@@ -1,6 +1,8 @@
 prompts:
   NALIIA_PROMPT: |
-    """Eres Naliia, asistente virtual de un centro de belleza.
+    """
+    Eres Naliia, asistente virtual de un centro de belleza.
+
     Responde usando formato Markdown:
       - Usa **negrita** para énfasis.
       - Separa opciones con viñetas o números.

src/naliiabot/bot/tools/naliia_tools.py

@@ -1,13 +1,67 @@
 from langchain.tools import tool
+from ..logger import logger
 
 
 class NaliiaTools:
 
+    def get_tools(self):
+        return [
+            self.verificar_usuario_registrado,
+            self.registrar_usuario_nuevo,
+            self.consultar_sedes,
+            self.consultar_agenda_disponible,
+            self.agendar_cita
+        ]
+
     @tool
-    def verificar_usuario_registrado(self):
+    def verificar_usuario_registrado(phone: str) -> bool:
         """
-        Verifica si el usuario que esta contactandose es un
+        Verifica si el usuario esta registrado.
-        usuario ya conocido y registrado en la base de datos.
+
+        Args:
+          phone: Numero de contacto del cliente ejemplo 30123334
         """
+        logger.info("Llamando a Verificar usuario.")
+
+        return False
+
+    @tool
+    def registrar_usuario_nuevo(full_name: str, phone: str) -> bool:
+        """
+        En caso de que no se haya podido verificar el usuario, sera necesario
+        registrarlo como un usuario nuevo.
+
+        Args:
+            full_name: Nombre completo del cliente.
+            phone: Numero de contacto del cliente.
+        """
+        logger.info("Llamando a Registrar Nuevo Usuario.")
+
+        return True
+
+    @tool
+    def consultar_sedes() -> list:
+        """
+        Brinda informacion al usuario acerca de las sedes disponibles y sus horarios.
+        """
+        logger.info("Llamando a consultar sedes.")
+
+        return []
+
+    @tool
+    def consultar_agenda_disponible() -> list:
+        """
+        Ayuda a consultar al cliente los horarios de atencion disponibles para agendar su cita.
+        """
+        logger.info("Llamando a consultar agenda disponible.")
+
+        return []
+
+    @tool
+    def agendar_cita() -> bool:
+        """
+        Ayuda al cliente a confirmar su cita.
+        """
+        logger.info("Llamando a agendar cita.")
 
         return True

src/naliiabotapi/api/dependencies.py

@@ -4,6 +4,7 @@ from src.naliiabot.bot.agent.agent import Agent, AgentConfig
 from src.naliiabot.bot.tools.naliia_tools import NaliiaTools
 from src.naliiabot.bot.factories.llm_factory import LLMFactory
 from src.naliiabot.bot.prompts.load_prompt import get_prompt_template
+from ..logger import logger
 
 MODEL_NAME = os.getenv("LLM_MODEL", "anthropic")
 
@@ -17,12 +18,11 @@ def get_agent():
 
     NALIIA_PROMPT = get_prompt_template(
         "NALIIA_PROMPT")
-    naliia_tools = [
+    naliia_tools = NaliiaTools().get_tools()
-        t for t in dir(NaliiaTools()) if not t.startswith('__') and not t.endswith('__')
-    ]
-
     config = AgentConfig(system_prompt=NALIIA_PROMPT)
     model = LLMFactory(MODEL_NAME).get_model()
 
-    raise Exception(naliia_tools)
+    logger.info(
+        f"Agente Naliia ha iniciado con las Tools: {naliia_tools}")
+
     return Agent(model=model, config=config, tools=naliia_tools)

src/ui/src/ui/app.py

@@ -1,18 +1,12 @@
 import streamlit as st
 from agent_client import AgentClient
 from logger import logger
+import json
+import httpx
 import random
 import time
 
 
-def response_generator(response: str = ""):
-    logger.info(f"Generating response stream for: {response}")
-
-    if response:
-        for word in response.split():
-            yield word + " "
-            time.sleep(0.05)
-
 async def main():
 
     st.image("src/ui/assets/logo-naliia.png", width=100, caption="NaliiaBot")
@@ -32,10 +26,23 @@ async def main():
         agent_client = AgentClient()
         response = await agent_client.send_message(prompt)
 
+
+        try:
+            response.raise_for_status()
+            data = response.json()
+        except json.JSONDecodeError:
+            raise RuntimeError(
+                f"Respuesta inválida (no JSON): {response.text}"
+            )
+        except httpx.HTTPStatusError as e:
+            raise RuntimeError(
+                f"Error HTTP {e.response.status_code}: {e.response.text}"
+            )
+
         raw_response = response.json()['response']['messages'][-1]['content']
 
         with st.chat_message("assistant"):
             formated_response = st.markdown(raw_response)
-        st.session_state.messages.append({"role": "assistant", "content": formated_response})
+        st.session_state.messages.append({"role": "assistant", "content": raw_response})
 
 if __name__ == "__main__":   import asyncio; asyncio.run(main())