Refactor

- moved action_registry fnction to action_registry file
- removed unnecesasry functions in pupeline and fixed events

src/app/agents/action_registry.py

@@ -7,3 +7,11 @@ def register_friendly_actions(actions: dict[str, str]):
     """
     global ACTION_DESCRIPTIONS
     ACTION_DESCRIPTIONS.update(actions)
+
+def get_user_friendly_action(tool_name: str) -> str:
+    """
+    Restituisce un messaggio leggibile e descrittivo per l'utente
+    leggendo dal registro globale.
+    """
+    # Usa il dizionario ACTION_DESCRIPTIONS importato
+    return ACTION_DESCRIPTIONS.get(tool_name, f"⚙️ Eseguo l'operazione: {tool_name}...")

src/app/agents/core.py

@@ -155,12 +155,20 @@ class RunMessage:
         self.base_message = f"Running configurations: \n{prefix}{inputs}{suffix}\n\n"
         self.emojis = ['🔳', '➡️', '✅']
         self.placeholder = '<<<>>>'
+        self.set_steps(["Query Check", "Info Recovery", "Report Generation"])
+
+    def set_steps(self, steps: list[str]) -> 'RunMessage':
+        """
+        Inizializza gli step di esecuzione con lo stato iniziale.
+        Args:
+            steps (list[str]): Lista degli step da includere nel messaggio.
+        Returns:
+            RunMessage: L'istanza aggiornata di RunMessage.
+        """
+        self.steps_total = [(f"{self.placeholder} {step}", 0) for step in steps]
+        self.steps_total[0] = (self.steps_total[0][0], 1)  # Primo step in esecuzione
         self.current = 0
-        self.steps_total = [
+        return self
-            (f"{self.placeholder} Query Check", 1),
-            (f"{self.placeholder} Info Recovery", 0),
-            (f"{self.placeholder} Report Generation", 0),
-        ]
 
     def update(self) -> 'RunMessage':
         """
@@ -177,15 +185,15 @@ class RunMessage:
             self.steps_total[self.current] = (text_curr, state_curr + 1)
         return self
 
-    def update_step(self, text_extra: str = "") -> 'RunMessage':
+    def update_step_with_tool(self, tool_used: str = "") -> 'RunMessage':
         """
         Aggiorna il messaggio per lo step corrente.
         Args:
-            text_extra (str, optional): Testo aggiuntivo da includere nello step. Defaults to "".
+            tool_used (str, optional): Testo aggiuntivo da includere nello step. Defaults to "".
         """
         text_curr, state_curr = self.steps_total[self.current]
-        if text_extra:
+        if tool_used:
-            text_curr = f"{text_curr.replace('╚', '╠')}\n╚═ {text_extra}"
+            text_curr = f"{text_curr.replace('╚', '╠')}\n╚═ {tool_used}"
         self.steps_total[self.current] = (text_curr, state_curr)
         return self
 
@@ -197,3 +205,4 @@ class RunMessage:
         """
         steps = [msg.replace(self.placeholder, self.emojis[state]) for msg, state in self.steps_total]
         return self.base_message + "\n".join(steps)
+

src/app/agents/pipeline.py

@@ -1,50 +1,45 @@
-import asyncio
 from enum import Enum
 import logging
 import random
-from typing import Any, Callable
+from typing import Any, AsyncGenerator, Callable
 from agno.agent import RunEvent
 from agno.run.workflow import WorkflowRunEvent
 from agno.workflow.types import StepInput, StepOutput
 from agno.workflow.step import Step
 from agno.workflow.workflow import Workflow
-
-from app.agents.action_registry import ACTION_DESCRIPTIONS
 from app.agents.core import *
 
 logging = logging.getLogger("pipeline")
 
 
-def _get_user_friendly_action(tool_name: str) -> str:
-    """
-    Restituisce un messaggio leggibile e descrittivo per l'utente
-    leggendo dal registro globale.
-    """
-    # Usa il dizionario ACTION_DESCRIPTIONS importato
-    return ACTION_DESCRIPTIONS.get(tool_name, f"⚙️ Eseguo l'operazione: {tool_name}...")
-
-
 class PipelineEvent(str, Enum):
     QUERY_CHECK = "Query Check"
-    QUERY_ANALYZER = "Query Analyzer"
+    QUERY_CHECK_END = "Query Check End"
     INFO_RECOVERY = "Info Recovery"
+    INFO_RECOVERY_END = "Info Recovery End"
     REPORT_GENERATION = "Report Generation"
-    REPORT_TRANSLATION = "Report Translation"
+    REPORT_GENERATION_END = "Report Generation End"
-    RUN_FINISHED = WorkflowRunEvent.workflow_completed.value
+    TOOL_USED = RunEvent.tool_call_started.value
-    TOOL_USED = RunEvent.tool_call_completed.value
+    TOOL_USED_END = RunEvent.tool_call_completed.value
+    RUN_END = WorkflowRunEvent.workflow_completed.value
 
     def check_event(self, event: str, step_name: str) -> bool:
-        return event == self.value or (WorkflowRunEvent.step_completed == event and step_name == self.value)
+        if event == self.value:
+            return True
+
+        index = self.value.rfind(" End")
+        value = self.value[:index] if index > -1 else self.value
+        step_state = WorkflowRunEvent.step_completed if index > -1 else WorkflowRunEvent.step_started
+        return step_name == value and step_state == event
 
     @classmethod
-    def get_log_events(cls, run_id: int) -> list[tuple['PipelineEvent', Callable[[Any], None]]]:
+    def get_log_events(cls, run_id: int) -> list[tuple['PipelineEvent', Callable[[Any], str | None]]]:
         return [
-            (PipelineEvent.QUERY_CHECK, lambda _: logging.info(f"[{run_id}] Query Check completed.")),
+            (PipelineEvent.QUERY_CHECK_END, lambda _: logging.info(f"[{run_id}] Query Check completed.")),
-            (PipelineEvent.QUERY_ANALYZER, lambda _: logging.info(f"[{run_id}] Query Analyzer completed.")),
+            (PipelineEvent.INFO_RECOVERY_END, lambda _: logging.info(f"[{run_id}] Info Recovery completed.")),
-            (PipelineEvent.INFO_RECOVERY, lambda _: logging.info(f"[{run_id}] Info Recovery completed.")),
+            (PipelineEvent.REPORT_GENERATION_END, lambda _: logging.info(f"[{run_id}] Report Generation completed.")),
-            (PipelineEvent.REPORT_GENERATION, lambda _: logging.info(f"[{run_id}] Report Generation completed.")),
+            (PipelineEvent.TOOL_USED_END, lambda e: logging.info(f"[{run_id}] Tool used [{e.tool.tool_name} {e.tool.tool_args}] by {e.agent_name}.")),
-            (PipelineEvent.TOOL_USED, lambda e: logging.info(f"[{run_id}] Tool used [{e.tool.tool_name} {e.tool.tool_args}] by {e.agent_name}.")),
+            (PipelineEvent.RUN_END, lambda _: logging.info(f"[{run_id}] Run completed.")),
-            (PipelineEvent.RUN_FINISHED, lambda _: logging.info(f"[{run_id}] Run completed.")),
         ]
 
 
@@ -63,7 +58,7 @@ class Pipeline:
         """
         self.inputs = inputs
 
-    def interact(self, listeners: list[tuple[PipelineEvent, Callable[[Any], None]]] = []) -> str:
+    async def interact(self, listeners: list[tuple[PipelineEvent, Callable[[Any], str | None]]] = []) -> str:
         """
         Esegue la pipeline di agenti per rispondere alla query dell'utente.
         Args:
@@ -71,9 +66,12 @@ class Pipeline:
         Returns:
             La risposta generata dalla pipeline.
         """
-        return asyncio.run(self.interact_async(listeners))
+        response = ""
+        async for chunk in self.interact_stream(listeners):
+            response = chunk
+        return response
 
-    async def interact_async(self, listeners: list[tuple[PipelineEvent, Callable[[Any], None]]] = []) -> str:
+    async def interact_stream(self, listeners: list[tuple[PipelineEvent, Callable[[Any], str | None]]] = []) -> AsyncGenerator[str, None]:
         """
         Versione asincrona che esegue la pipeline di agenti per rispondere alla query dell'utente.
         Args:
@@ -91,26 +89,6 @@ class Pipeline:
         )
 
         workflow = self.build_workflow()
-        result = await self.run(workflow, query, events=events)
-        return result
-
-    async def interact_stream(self, listeners: list[tuple[PipelineEvent, Callable[[Any], None]]] = []):
-        """
-        Versione asincrona in streaming che ESEGUE (yield) la pipeline,
-        restituendo gli aggiornamenti di stato e il risultato finale.
-        """
-        run_id = random.randint(1000, 9999)  # Per tracciare i log
-        logging.info(f"[{run_id}] Pipeline query: {self.inputs.user_query}")
-
-        events = [*PipelineEvent.get_log_events(run_id), *listeners]
-        query = QueryInputs(
-            user_query=self.inputs.user_query,
-            strategy=self.inputs.strategy.description
-        )
-
-        workflow = self.build_workflow()
-
-        # Delega al classmethod 'run_stream' per lo streaming
         async for item in self.run_stream(workflow, query, events=events):
             yield item
 
@@ -143,69 +121,37 @@ class Pipeline:
         ])
 
     @classmethod
-    async def run(cls, workflow: Workflow, query: QueryInputs,
+    async def run_stream(cls, workflow: Workflow, query: QueryInputs, events: list[tuple[PipelineEvent, Callable[[Any], str | None]]]) -> AsyncGenerator[str, None]:
-                  events: list[tuple[PipelineEvent, Callable[[Any], None]]]) -> str:
-        """
-        Esegue il workflow e gestisce gli eventi, restituendo solo il risultato finale.
-        Consuma il generatore 'run_stream'.
-        """
-        final_result = "Errore durante l'esecuzione del workflow."
-        # Consuma il generatore e salva solo l'ultimo item
-        async for item in cls.run_stream(workflow, query, events):
-            final_result = item
-
-        return final_result
-
-    @classmethod
-    async def run_stream(cls, workflow: Workflow, query: QueryInputs,
-                         events: list[tuple[PipelineEvent, Callable[[Any], None]]]):
         """
         Esegue il workflow e restituisce gli eventi di stato e il risultato finale.
+        Args:
+            workflow: L'istanza di Workflow da eseguire.
+            query: Gli input della query.
+            events: La lista di eventi e callback da gestire durante l'esecuzione.
+        Yields:
+            Aggiornamenti di stato e la risposta finale generata dal workflow.
         """
         iterator = await workflow.arun(query, stream=True, stream_intermediate_steps=True)
         content = None
-        current_active_step = None
 
         async for event in iterator:
             step_name = getattr(event, 'step_name', '')
 
-            # 1. Chiama i listeners (per i log)
+            # Chiama i listeners (se presenti) per ogni evento
             for app_event, listener in events:
                 if app_event.check_event(event.event, step_name):
-                    listener(event)
+                    update = listener(event)
+                    if update: yield update
 
-            # 2. Restituisce gli aggiornamenti di stato per Gradio
+            # Salva il contenuto finale quando uno step è completato
-            if event.event == WorkflowRunEvent.step_started.value:
+            if event.event == WorkflowRunEvent.step_completed.value:
-                current_active_step = step_name
-                if step_name == PipelineEvent.QUERY_CHECK.value:
-                    yield "🔍 Sto controllando la tua richiesta..."
-                elif step_name == PipelineEvent.INFO_RECOVERY.value:
-                    yield "📊 Sto recuperando i dati (mercato, news, social)..."
-                elif step_name == PipelineEvent.REPORT_GENERATION.value:
-                    yield "✍️ Sto scrivendo il report finale..."
-
-            # Gestisce gli eventi di tool promossi dal Team
-            elif event.event == PipelineEvent.TOOL_USED.value:
-                if current_active_step == PipelineEvent.INFO_RECOVERY.value:
-                    tool_object = getattr(event, 'tool', None)
-                    if tool_object:
-                        tool_name = getattr(tool_object, 'tool_name', 'uno strumento sconosciuto')
-                        user_message = _get_user_friendly_action(tool_name)
-                        yield f"{user_message}"
-                    else:
-                        yield f"Sto usando uno strumento sconosciuto..."
-
-            # 3. Salva il contenuto finale quando uno step è completato
-            elif event.event == WorkflowRunEvent.step_completed.value:
-                current_active_step = None
                 content = getattr(event, 'content', '')
 
-        # 4. Restituisce la risposta finale
+        # Restituisce la risposta finale
         if content and isinstance(content, str):
             think_str = "</think>"
             think = content.rfind(think_str)
-            final_answer = content[(think + len(think_str)):] if think != -1 else content
+            yield content[(think + len(think_str)):] if think != -1 else content
-            yield final_answer
         elif content and isinstance(content, QueryOutputs):
             yield content.response
         else:

src/app/interface/chat.py

@@ -1,7 +1,9 @@
 import os
 import json
+from typing import Any, Callable
 import gradio as gr
-from app.agents.pipeline import Pipeline, PipelineInputs
+from app.agents.action_registry import get_user_friendly_action
+from app.agents.pipeline import Pipeline, PipelineEvent, PipelineInputs
 
 
 class ChatManager:
@@ -56,10 +58,15 @@ class ChatManager:
         """
         self.inputs.user_query = message
         pipeline = Pipeline(self.inputs)
+        listeners: list[tuple[PipelineEvent, Callable[[Any], str | None]]] = [
+            (PipelineEvent.QUERY_CHECK, lambda _: "🔍 Sto controllando la tua richiesta..."),
+            (PipelineEvent.INFO_RECOVERY, lambda _: "📊 Sto recuperando i dati (mercato, news, social)..."),
+            (PipelineEvent.REPORT_GENERATION, lambda _: "✍️ Sto scrivendo il report finale..."),
+            (PipelineEvent.TOOL_USED, lambda e:  get_user_friendly_action(e.tool.tool_name))
+        ]
 
         response = None
-        # Itera sul nuovo generatore asincrono
+        async for chunk in pipeline.interact_stream(listeners=listeners):
-        async for chunk in pipeline.interact_stream():
             response = chunk  # Salva l'ultimo chunk (che sarà la risposta finale)
             yield response  # Restituisce l'aggiornamento (o la risposta finale) a Gradio
 

src/app/interface/telegram.py

@@ -271,7 +271,7 @@ class TelegramApp:
         await bot.delete_message(chat_id=chat_id, message_id=update.message.id)
 
         def update_user(update_step: str = "") -> None:
-            if update_step: run_message.update_step(update_step)
+            if update_step: run_message.update_step_with_tool(update_step)
             else: run_message.update()
 
             message = run_message.get_latest()
@@ -280,11 +280,11 @@ class TelegramApp:
 
         await bot.send_chat_action(chat_id=chat_id, action=ChatAction.TYPING)
         pipeline = Pipeline(inputs)
-        report_content = await pipeline.interact_async(listeners=[
+        report_content = await pipeline.interact(listeners=[
-            (PipelineEvent.QUERY_CHECK, lambda _: update_user()),
+            (PipelineEvent.QUERY_CHECK_END, lambda _: update_user()),
-            (PipelineEvent.TOOL_USED, lambda e: update_user(e.tool.tool_name.replace('get_', '').replace("_", "\\_"))),
+            (PipelineEvent.TOOL_USED_END, lambda e: update_user(e.tool.tool_name.replace('get_', '').replace("_", "\\_"))),
-            (PipelineEvent.INFO_RECOVERY, lambda _: update_user()),
+            (PipelineEvent.INFO_RECOVERY_END, lambda _: update_user()),
-            (PipelineEvent.REPORT_GENERATION, lambda _: update_user()),
+            (PipelineEvent.REPORT_GENERATION_END, lambda _: update_user()),
         ])
 
         # attach report file to the message