dc9dc98298
* Creazione branch tool, refactor degli import e soppressione dei warning * Update pytest configuration and dependencies in pyproject.toml * Add news API integration and related configurations - Update .env.example to include NEWS_API_KEY configuration - Add newsapi-python dependency in pyproject.toml - Implement NewsAPI class for fetching news articles - Create Article model for structured news data - Add tests for NewsAPI functionality in test_news_api.py - Update pytest configuration to include news marker * Add news API functionality and update tests for article retrieval * ToDo: 1. Aggiungere un aggregator per i dati recuperati dai provider. 2. Lavorare effettivamente all'issue Done: 1. creati test per i provider 2. creato market_providers_api_demo.py per mostrare i dati recuperati dalle api dei providers 3. aggiornato i provider 4. creato il provider binance sia pubblico che con chiave 5. creato error_handler.py per gestire decoratori e utilità: retry automatico, gestione timeout... * Refactor news API integration to use NewsApiWrapper and GnewsWrapper; add tests for Gnews API functionality * Add CryptoPanic API integration and related tests; update .env.example and test configurations * Implement WrapperHandler for managing multiple news API wrappers; add tests for wrapper functionality * Enhance WrapperHandler - docstrings - add try_call_all method - update tests * pre merge con phil * Add DuckDuckGo and Google News wrappers; refactor CryptoPanic and NewsAPI - Implemented DuckDuckGoWrapper for news retrieval using DuckDuckGo tools. - Added GoogleNewsWrapper for accessing Google News RSS feed. - Refactored CryptoPanicWrapper to unify get_top_headlines and get_latest_news methods. - Updated NewsApiWrapper to simplify top headlines retrieval. - Added tests for DuckDuckGo and Google News wrappers. - Enhanced documentation for CryptoPanicWrapper and NewsApiWrapper. - Created base module for social media integrations. * - Refactor struttura progetto: divisione tra agent e toolkit * Refactor try_call_all method to return a dictionary of results; update tests for success and partial failures * Fix class and test method names for DuckDuckGoWrapper * Add Reddit API wrapper and related tests; update environment configuration * pre merge con giacomo * Fix import statements * Fixes - separated tests - fix tests - fix bugs reintroduced my previous merge * Refactor market API wrappers to streamline product and price retrieval methods * Add BinanceWrapper to market API exports * Finito ISSUE 3 * Final review - rm PublicBinanceAgent & updated demo - moved in the correct folder some tests - fix binance bug --------- Co-authored-by: trojanhorse47 <cosmomemory@hotmail.it> Co-authored-by: Berack96 <giacomobertolazzi7@gmail.com> Co-authored-by: Giacomo Bertolazzi <31776951+Berack96@users.noreply.github.com>
52 lines
3.0 KiB
Python
52 lines
3.0 KiB
Python
from enum import Enum
|
|
from pydantic import BaseModel, Field
|
|
from app.markets.base import ProductInfo
|
|
|
|
|
|
class PredictorStyle(Enum):
|
|
CONSERVATIVE = "Conservativo"
|
|
AGGRESSIVE = "Aggressivo"
|
|
|
|
class PredictorInput(BaseModel):
|
|
data: list[ProductInfo] = Field(..., description="Market data as a list of ProductInfo")
|
|
style: PredictorStyle = Field(..., description="Prediction style")
|
|
sentiment: str = Field(..., description="Aggregated sentiment from news and social analysis")
|
|
|
|
class ItemPortfolio(BaseModel):
|
|
asset: str = Field(..., description="Name of the asset")
|
|
percentage: float = Field(..., description="Percentage allocation to the asset")
|
|
motivation: str = Field(..., description="Motivation for the allocation")
|
|
|
|
class PredictorOutput(BaseModel):
|
|
strategy: str = Field(..., description="Concise operational strategy in Italian")
|
|
portfolio: list[ItemPortfolio] = Field(..., description="List of portfolio items with allocations")
|
|
|
|
PREDICTOR_INSTRUCTIONS = """
|
|
You are an **Allocation Algorithm (Crypto-Algo)** specialized in analyzing market data and sentiment to generate an investment strategy and a target portfolio.
|
|
|
|
Your sole objective is to process the user_input data and generate the strictly structured output as required by the response format. **You MUST NOT provide introductions, preambles, explanations, conclusions, or any additional comments that are not strictly required.**
|
|
|
|
## Processing Instructions (Absolute Rule)
|
|
|
|
The allocation strategy must be **derived exclusively from the "Allocation Logic" corresponding to the requested *style*** and the provided market/sentiment data. **DO NOT** use external or historical knowledge.
|
|
|
|
## Allocation Logic
|
|
|
|
### "Aggressivo" Style (Aggressive)
|
|
* **Priority:** Maximizing return (high volatility accepted).
|
|
* **Focus:** Higher allocation to **non-BTC/ETH assets** with high momentum potential (Altcoins, mid/low-cap assets).
|
|
* **BTC/ETH:** Must serve as a base (anchor), but their allocation **must not exceed 50%** of the total portfolio.
|
|
* **Sentiment:** Use positive sentiment to increase exposure to high-risk assets.
|
|
|
|
### "Conservativo" Style (Conservative)
|
|
* **Priority:** Capital preservation (volatility minimized).
|
|
* **Focus:** Major allocation to **BTC and/or ETH (Large-Cap Assets)**.
|
|
* **BTC/ETH:** Their allocation **must be at least 70%** of the total portfolio.
|
|
* **Altcoins:** Any allocations to non-BTC/ETH assets must be minimal (max 30% combined) and for assets that minimize speculative risk.
|
|
* **Sentiment:** Use positive sentiment only as confirmation for exposure, avoiding reactions to excessive "FOMO" signals.
|
|
|
|
## Output Requirements (Content MUST be in Italian)
|
|
|
|
1. **Strategy (strategy):** Must be a concise operational description **in Italian ("in Italiano")**, with a maximum of 5 sentences.
|
|
2. **Portfolio (portfolio):** The sum of all percentages must be **exactly 100%**. The justification (motivation) for each asset must be a single clear sentence **in Italian ("in Italiano")**.
|
|
""" |