6 Commits

7 changed files with 75 additions and 29 deletions

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@@ -4,6 +4,18 @@ from typing import TypedDict, Literal
class Task(TypedDict):
"""
Represents a single task in the execution plan.
Attributes:
name (str): The unique name of the task.
status (Literal["pending", "completed", "failed"]): The current status of the task.
- "pending": The task is yet to be executed.
- "completed": The task has been successfully executed.
- "failed": The task execution was unsuccessful.
result (str | None): An optional field to store the result or outcome of the task.
This could be a summary, an error message, or any relevant information.
"""
name: str
status: Literal["pending", "completed", "failed"]
result: str | None
@@ -13,6 +25,7 @@ class PlanMemoryTool(Toolkit):
def __init__(self):
self.tasks: list[Task] = []
Toolkit.__init__(self, # type: ignore[call-arg]
name="Plan Memory Tool",
instructions="Provides stateful, persistent memory for the Team Leader. " \
"This is your primary to-do list and state tracker. " \
"Use it to create, execute step-by-step, and record the results of your execution plan.",

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@@ -9,6 +9,7 @@ class Article(BaseModel):
time: str = ""
title: str = ""
description: str = ""
url: str = ""
class NewsWrapper:
"""

View File

@@ -29,6 +29,7 @@ def extract_articles(response: dict[str, Any]) -> list[Article]:
article.time = item.get('published_at', '')
article.title = item.get('title', '')
article.description = item.get('description', '')
article.url = item.get('url', '')
articles.append(article)
return articles

View File

@@ -1,6 +1,5 @@
import json
from typing import Any
from agno.tools.duckduckgo import DuckDuckGoTools
from ddgs import DDGS
from app.api.core.news import Article, NewsWrapper
@@ -10,6 +9,7 @@ def extract_article(result: dict[str, Any]) -> Article:
article.time = result.get("date", "")
article.title = result.get("title", "")
article.description = result.get("body", "")
article.url = result.get("url", "")
return article
class DuckDuckGoWrapper(NewsWrapper):
@@ -19,16 +19,14 @@ class DuckDuckGoWrapper(NewsWrapper):
"""
def __init__(self):
self.tool = DuckDuckGoTools()
self.tool = DDGS()
self.query = "crypto"
def get_top_headlines(self, limit: int = 100) -> list[Article]:
results = self.tool.duckduckgo_news(self.query, max_results=limit)
json_results = json.loads(results)
return [extract_article(result) for result in json_results]
results = self.tool.news(self.query, max_results=limit)
return [extract_article(result) for result in results]
def get_latest_news(self, query: str, limit: int = 100) -> list[Article]:
results = self.tool.duckduckgo_news(query or self.query, max_results=limit)
json_results = json.loads(results)
return [extract_article(result) for result in json_results]
results = self.tool.news(query or self.query, max_results=limit)
return [extract_article(result) for result in results]

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@@ -9,6 +9,7 @@ def extract_article(result: dict[str, Any]) -> Article:
article.time = result.get("publishedAt", "")
article.title = result.get("title", "")
article.description = result.get("description", "")
article.url = result.get("url", "")
return article
class GoogleNewsWrapper(NewsWrapper):

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@@ -10,6 +10,7 @@ def extract_article(result: dict[str, Any]) -> Article:
article.time = result.get("publishedAt", "")
article.title = result.get("title", "")
article.description = result.get("description", "")
article.url = result.get("url", "")
return article
class NewsApiWrapper(NewsWrapper):

View File

@@ -13,48 +13,79 @@ logging = logging.getLogger("crypto_symbols")
BASE_URL = "https://finance.yahoo.com/markets/crypto/all/"
class CryptoSymbolsTools(Toolkit):
"""
Classe per ottenere i simboli delle criptovalute tramite Yahoo Finance.
Class for obtaining cryptocurrency symbols via Yahoo Finance.
(This class-level docstring is for developers).
"""
def __init__(self, cache_file: str = 'resources/cryptos.csv'):
self.cache_file = cache_file
self.final_table = pd.read_csv(self.cache_file) if os.path.exists(self.cache_file) else pd.DataFrame() # type: ignore
Toolkit.__init__(self, # type: ignore
name="Crypto Symbols Tool",
instructions="Tool to get cryptocurrency symbols and search them by name.",
tools=[
self.get_all_symbols,
self.get_symbols_by_name,
],
)
try:
self.final_table = pd.read_csv(self.cache_file) if os.path.exists(self.cache_file) else pd.DataFrame(
columns=['Symbol', 'Name'])
except Exception:
self.final_table = pd.DataFrame(columns=['Symbol', 'Name'])
Toolkit.__init__(self, # type: ignore
name="Crypto Symbols Tool",
instructions="A utility tool to find and verify the correct cryptocurrency symbols (tickers). " \
"Use this to translate a cryptocurrency name (e.g., 'Bitcoin') into its official symbol " \
"(e.g., 'BTC-USD') *before* delegating tasks to the MarketAgent.",
tools=[
self.get_all_symbols,
self.get_symbols_by_name,
],
)
def get_all_symbols(self) -> list[str]:
"""
Restituisce tutti i simboli delle criptovalute.
Returns a complete list of all available cryptocurrency symbols (tickers).
Warning: This list can be very long. Prefer 'get_symbols_by_name'
if you are searching for a specific asset.
Returns:
list[str]: Lista di tutti i simboli delle criptovalute.
list[str]: A comprehensive list of all supported crypto symbols (e.g., "BTC-USD", "ETH-USD").
"""
return self.final_table['Symbol'].tolist() if not self.final_table.empty else []
def get_symbols_by_name(self, query: str) -> list[tuple[str, str]]:
"""
Cerca i simboli che contengono la query.
Searches the cryptocurrency database for assets matching a name or symbol.
Use this to find the exact, correct symbol for a cryptocurrency name.
(e.g., query="Bitcoin" might return [("BTC-USD", "Bitcoin USD")]).
Args:
query (str): Query di ricerca.
query (str): The name, partial name, or symbol to search for (e.g., "Bitcoin", "ETH").
Returns:
list[tuple[str, str]]: Lista di tuple (simbolo, nome) che contengono la query.
list[tuple[str, str]]: A list of tuples, where each tuple contains
the (symbol, full_name) of a matching asset.
Returns an empty list if no matches are found.
"""
query_lower = query.lower()
positions = self.final_table['Name'].str.lower().str.contains(query_lower)
return self.final_table[positions][['Symbol', 'Name']].apply(tuple, axis=1).tolist()
if self.final_table.empty or 'Name' not in self.final_table.columns or 'Symbol' not in self.final_table.columns:
return []
try:
# Cerca sia nel nome che nel simbolo, ignorando maiuscole/minuscole
mask = self.final_table['Name'].str.contains(query, case=False, na=False) | \
self.final_table['Symbol'].str.contains(query, case=False, na=False)
filtered_df = self.final_table[mask]
# Converte il risultato in una lista di tuple
return list(zip(filtered_df['Symbol'], filtered_df['Name']))
except Exception:
return []
async def fetch_crypto_symbols(self, force_refresh: bool = False) -> None:
"""
Recupera tutti i simboli delle criptovalute da Yahoo Finance e li memorizza in cache.
It retrieves all cryptocurrency symbols from Yahoo Finance and caches them.
Args:
force_refresh (bool): Se True, forza il recupero anche se i dati sono già in cache.
force_refresh (bool): If True, it forces the retrieval even if the data are already in the cache.
"""
if not force_refresh and not self.final_table.empty:
return