Refactoring architetturale e spostamento classi base

- Eliminazione del file __init__.py obsoleto che importava ChatManager e Pipeline
- Spostamento della classe Pipeline in agents/pipeline.py
- Spostamento della classe ChatManager in utils/chat_manager.py
- Aggiornamento di __main__.py per importare da app.utils e app.agents, e modifica della logica per utilizzare Pipeline invece di chat per la selezione di provider e stile
- Creazione della cartella base con classi base comuni: markets.py (ProductInfo, Price, MarketWrapper), news.py (Article, NewsWrapper), social.py (SocialPost, SocialComment, SocialWrapper)
- Aggiornamento di tutti gli import nel progetto (markets/, news/, social/, utils/, tests/) per utilizzare la nuova struttura base/

src/app/__init__.py

@@ -1,4 +0,0 @@
-from app.chat_manager import ChatManager
-from app.pipeline import Pipeline
-
-__all__ = ["ChatManager", "Pipeline"]

src/app/__main__.py

@@ -1,19 +1,23 @@
 import gradio as gr
-from agno.utils.log import log_info #type: ignore
 from dotenv import load_dotenv
-from app import ChatManager
+from agno.utils.log import log_info #type: ignore
+from app.utils import ChatManager
+from app.agents import Pipeline
 
 
 if __name__ == "__main__":
     # Inizializzazioni
     load_dotenv()
+    pipeline = Pipeline()
     chat = ChatManager()
 
     ########################################
     # Funzioni Gradio
     ########################################
     def respond(message: str, history: list[dict[str, str]]) -> tuple[list[dict[str, str]], list[dict[str, str]], str]:
-        response = chat.send_message(message)
+        chat.send_message(message)
+        response = pipeline.interact(message)
+        chat.receive_message(response)
         history.append({"role": "user", "content": message})
         history.append({"role": "assistant", "content": response})
         return history, history, ""
@@ -42,18 +46,18 @@ if __name__ == "__main__":
         # Dropdown provider e stile
         with gr.Row():
             provider = gr.Dropdown(
-                choices=chat.list_providers(),
+                choices=pipeline.list_providers(),
                 type="index",
                 label="Modello da usare"
             )
-            provider.change(fn=chat.choose_provider, inputs=provider, outputs=None)
+            provider.change(fn=pipeline.choose_predictor, inputs=provider, outputs=None)
 
             style = gr.Dropdown(
-                choices=chat.list_styles(),
+                choices=pipeline.list_styles(),
                 type="index",
                 label="Stile di investimento"
             )
-            style.change(fn=chat.choose_style, inputs=style, outputs=None)
+            style.change(fn=pipeline.choose_style, inputs=style, outputs=None)
 
         chatbot = gr.Chatbot(label="Conversazione", height=500, type="messages")
         msg = gr.Textbox(label="Scrivi la tua richiesta", placeholder="Es: Quali sono le crypto interessanti oggi?")

src/app/agents/__init__.py

@@ -1,5 +1,6 @@
 from app.agents.models import AppModels
 from app.agents.predictor import PredictorInput, PredictorOutput, PredictorStyle, PREDICTOR_INSTRUCTIONS
 from app.agents.team import create_team_with
+from app.agents.pipeline import Pipeline
 
-__all__ = ["AppModels", "PredictorInput", "PredictorOutput", "PredictorStyle", "PREDICTOR_INSTRUCTIONS", "create_team_with"]
+__all__ = ["AppModels", "PredictorInput", "PredictorOutput", "PredictorStyle", "PREDICTOR_INSTRUCTIONS", "create_team_with", "Pipeline"]

src/app/agents/pipeline.py

@@ -1,8 +1,8 @@
 from agno.run.agent import RunOutput
-from app.agents import AppModels
+from app.agents.models import AppModels
 from app.agents.team import create_team_with
 from app.agents.predictor import PREDICTOR_INSTRUCTIONS, PredictorInput, PredictorOutput, PredictorStyle
-from app.markets.base import ProductInfo
+from app.base.markets import ProductInfo
 
 
 class Pipeline:

src/app/agents/predictor.py

@@ -1,6 +1,6 @@
 from enum import Enum
 from pydantic import BaseModel, Field
-from app.markets.base import ProductInfo
+from app.base.markets import ProductInfo
 
 
 class PredictorStyle(Enum):

src/app/markets/__init__.py

@@ -1,5 +1,5 @@
 from agno.tools import Toolkit
-from app.markets.base import MarketWrapper, Price, ProductInfo
+from app.base.markets import MarketWrapper, Price, ProductInfo
 from app.markets.binance import BinanceWrapper
 from app.markets.coinbase import CoinBaseWrapper
 from app.markets.cryptocompare import CryptoCompareWrapper

src/app/markets/binance.py

@@ -1,7 +1,7 @@
 import os
 from typing import Any
 from binance.client import Client # type: ignore
-from app.markets.base import ProductInfo, MarketWrapper, Price
+from app.base.markets import ProductInfo, MarketWrapper, Price
 
 
 def extract_product(currency: str, ticker_data: dict[str, Any]) -> ProductInfo:

src/app/markets/coinbase.py

@@ -3,7 +3,7 @@ from enum import Enum
 from datetime import datetime, timedelta
 from coinbase.rest import RESTClient # type: ignore
 from coinbase.rest.types.product_types import Candle, GetProductResponse, Product # type: ignore
-from app.markets.base import ProductInfo, MarketWrapper, Price
+from app.base.markets import ProductInfo, MarketWrapper, Price
 
 
 def extract_product(product_data: GetProductResponse | Product) -> ProductInfo:

src/app/markets/cryptocompare.py

@@ -1,7 +1,7 @@
 import os
 from typing import Any
 import requests
-from app.markets.base import ProductInfo, MarketWrapper, Price
+from app.base.markets import ProductInfo, MarketWrapper, Price
 
 
 def extract_product(asset_data: dict[str, Any]) -> ProductInfo:

src/app/markets/yfinance.py

@@ -1,6 +1,6 @@
 import json
 from agno.tools.yfinance import YFinanceTools
-from app.markets.base import MarketWrapper, ProductInfo, Price
+from app.base.markets import MarketWrapper, ProductInfo, Price
 
 
 def extract_product(stock_data: dict[str, str]) -> ProductInfo:

src/app/news/__init__.py

@@ -1,6 +1,6 @@
 from agno.tools import Toolkit
 from app.utils import WrapperHandler
-from app.news.base import NewsWrapper, Article
+from app.base.news import NewsWrapper, Article
 from app.news.news_api import NewsApiWrapper
 from app.news.googlenews import GoogleNewsWrapper
 from app.news.cryptopanic_api import CryptoPanicWrapper

src/app/news/cryptopanic_api.py

@@ -2,7 +2,7 @@ import os
 from typing import Any
 import requests
 from enum import Enum
-from app.news.base import NewsWrapper, Article
+from app.base.news import NewsWrapper, Article
 
 
 class CryptoPanicFilter(Enum):

src/app/news/duckduckgo.py

@@ -1,7 +1,7 @@
 import json
 from typing import Any
 from agno.tools.duckduckgo import DuckDuckGoTools
-from app.news.base import Article, NewsWrapper
+from app.base.news import Article, NewsWrapper
 
 
 def extract_article(result: dict[str, Any]) -> Article:

src/app/news/googlenews.py

@@ -1,6 +1,6 @@
 from typing import Any
 from gnews import GNews # type: ignore
-from app.news.base import Article, NewsWrapper
+from app.base.news import Article, NewsWrapper
 
 
 def extract_article(result: dict[str, Any]) -> Article:

src/app/news/news_api.py

@@ -1,7 +1,7 @@
 import os
 from typing import Any
 import newsapi # type: ignore
-from app.news.base import Article, NewsWrapper
+from app.base.news import Article, NewsWrapper
 
 
 def extract_article(result: dict[str, Any]) -> Article:

src/app/social/__init__.py

@@ -1,6 +1,6 @@
 from agno.tools import Toolkit
 from app.utils import WrapperHandler
-from app.social.base import SocialPost, SocialWrapper
+from app.base.social import SocialPost, SocialWrapper
 from app.social.reddit import RedditWrapper
 
 __all__ = ["SocialAPIsTool", "RedditWrapper", "SocialPost"]

src/app/social/reddit.py

@@ -1,7 +1,7 @@
 import os
 from praw import Reddit # type: ignore
 from praw.models import Submission, MoreComments # type: ignore
-from app.social.base import SocialWrapper, SocialPost, SocialComment
+from app.base.social import SocialWrapper, SocialPost, SocialComment
 
 
 MAX_COMMENTS = 5

src/app/utils/__init__.py

@@ -1,4 +1,5 @@
 from app.utils.market_aggregation import aggregate_history_prices, aggregate_product_info
 from app.utils.wrapper_handler import WrapperHandler
+from app.utils.chat_manager import ChatManager
 
-__all__ = ["aggregate_history_prices", "aggregate_product_info", "WrapperHandler"]
+__all__ = ["aggregate_history_prices", "aggregate_product_info", "WrapperHandler", "ChatManager"]

src/app/utils/chat_manager.py

@@ -1,10 +1,5 @@
 import json
 import os
-from app import Pipeline
-
-SAVE_DIR = os.path.join(os.path.dirname(__file__), "..", "saves")
-os.makedirs(SAVE_DIR, exist_ok=True)
-
 
 class ChatManager:
     """
@@ -15,19 +10,19 @@ class ChatManager:
     """
 
     def __init__(self):
-        self.pipeline = Pipeline()
         self.history: list[dict[str, str]] = []  # [{"role": "user"/"assistant", "content": "..."}]
 
-    def send_message(self, message: str) -> str:
+    def send_message(self, message: str) -> None:
         """
         Aggiunge un messaggio utente, chiama la Pipeline e salva la risposta nello storico.
         """
         # Aggiungi messaggio utente allo storico
         self.history.append({"role": "user", "content": message})
 
-        # Pipeline elabora la query
-        response = self.pipeline.interact(message)
-
+    def receive_message(self, response: str) -> str:
+        """
+        Riceve un messaggio dalla pipeline e lo aggiunge allo storico.
+        """
         # Aggiungi risposta assistente allo storico
         self.history.append({"role": "assistant", "content": response})
 
@@ -37,19 +32,17 @@ class ChatManager:
         """
         Salva la chat corrente in src/saves/<filename>.
         """
-        path = os.path.join(SAVE_DIR, filename)
-        with open(path, "w", encoding="utf-8") as f:
+        with open(filename, "w", encoding="utf-8") as f:
             json.dump(self.history, f, ensure_ascii=False, indent=2)
 
     def load_chat(self, filename: str = "chat.json") -> None:
         """
         Carica una chat salvata da src/saves/<filename>.
         """
-        path = os.path.join(SAVE_DIR, filename)
-        if not os.path.exists(path):
+        if not os.path.exists(filename):
             self.history = []
             return
-        with open(path, "r", encoding="utf-8") as f:
+        with open(filename, "r", encoding="utf-8") as f:
             self.history = json.load(f)
 
     def reset_chat(self) -> None:
@@ -63,16 +56,3 @@ class ChatManager:
         Restituisce lo storico completo della chat.
         """
         return self.history
-
-    # Facciamo pass-through di provider e style, così Gradio può usarli
-    def choose_provider(self, index: int):
-        self.pipeline.choose_predictor(index)
-
-    def choose_style(self, index: int):
-        self.pipeline.choose_style(index)
-
-    def list_providers(self) -> list[str]:
-        return self.pipeline.list_providers()
-
-    def list_styles(self) -> list[str]:
-        return self.pipeline.list_styles()

src/app/utils/market_aggregation.py

@@ -1,5 +1,5 @@
 import statistics
-from app.markets.base import ProductInfo, Price
+from app.base.markets import ProductInfo, Price
 
 
 def aggregate_history_prices(prices: dict[str, list[Price]]) -> list[Price]:

tests/agents/test_predictor.py

@@ -1,7 +1,7 @@
 import pytest
 from app.agents import AppModels
 from app.agents.predictor import PREDICTOR_INSTRUCTIONS, PredictorInput, PredictorOutput, PredictorStyle
-from app.markets.base import ProductInfo
+from app.base.markets import ProductInfo
 
 def unified_checks(model: AppModels, input):
     llm = model.get_agent(PREDICTOR_INSTRUCTIONS, output=PredictorOutput) # type: ignore[arg-type]

tests/utils/test_market_aggregator.py

@@ -1,5 +1,5 @@
 import pytest
-from app.markets.base import ProductInfo, Price
+from app.base.markets import ProductInfo, Price
 from app.utils.market_aggregation import aggregate_history_prices, aggregate_product_info