Refactor and update structure (#20)
* Aggiorna gli agenti e il modello del team per utilizzare OLLAMA_QWEN_1B * Riorganizza e rinomina funzioni di estrazione in moduli di mercato e notizie; migliora la gestione delle importazioni * Spostato main nel corretto file __main__ e aggiornato il README.md * Aggiunta cartella per i modelli, agenti e team * Aggiornata la posizione delle istruzioni * Rimossi TODO e Aggiunto documentazione per metodi aggregated * Aggiornate le istruzioni del coordinatore del team * utils type checks * Rinominato BaseWrapper in MarketWrapper e fix type check markets * fix type checks di notizie e social. * Aggiunti type hints finali * Riorganizzati gli import * 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/ * Aggiornato Readme * Corretto il valore predefinito della valuta in BinanceWrapper da "USDT" a "USD" * fix type in tests * fix type per models * Rinominato 'quote_currency' in 'currency' e aggiornato il trattamento del timestamp in Price * fix errors found by Copilot * WrapperHandler: semplificata la logica di chiamata delle funzioni sui wrapper * fix docs * fix demos, semplificata logica lista ollama
This commit was merged in pull request #20.
This commit is contained in:
Giacomo Bertolazzi
committed by
GitHub
GitHub
parent
85153c405b
commit
517842c834
109
src/app/agents/team.py
Normal file
109
src/app/agents/team.py
Normal file
@@ -0,0 +1,109 @@
|
||||
from agno.team import Team
|
||||
from app.agents import AppModels
|
||||
from app.markets import MarketAPIsTool
|
||||
from app.news import NewsAPIsTool
|
||||
from app.social import SocialAPIsTool
|
||||
|
||||
|
||||
def create_team_with(models: AppModels, coordinator: AppModels | None = None) -> Team:
|
||||
market_agent = models.get_agent(
|
||||
instructions=MARKET_INSTRUCTIONS,
|
||||
name="MarketAgent",
|
||||
tools=[MarketAPIsTool()]
|
||||
)
|
||||
news_agent = models.get_agent(
|
||||
instructions=NEWS_INSTRUCTIONS,
|
||||
name="NewsAgent",
|
||||
tools=[NewsAPIsTool()]
|
||||
)
|
||||
social_agent = models.get_agent(
|
||||
instructions=SOCIAL_INSTRUCTIONS,
|
||||
name="SocialAgent",
|
||||
tools=[SocialAPIsTool()]
|
||||
)
|
||||
|
||||
coordinator = coordinator or models
|
||||
return Team(
|
||||
model=coordinator.get_model(COORDINATOR_INSTRUCTIONS),
|
||||
name="CryptoAnalysisTeam",
|
||||
members=[market_agent, news_agent, social_agent],
|
||||
)
|
||||
|
||||
COORDINATOR_INSTRUCTIONS = """
|
||||
You are the expert coordinator of a financial analysis team specializing in cryptocurrencies.
|
||||
|
||||
Your team consists of three agents:
|
||||
- **MarketAgent**: Provides quantitative market data, price analysis, and technical indicators.
|
||||
- **NewsAgent**: Scans and analyzes the latest news, articles, and official announcements.
|
||||
- **SocialAgent**: Gauges public sentiment, trends, and discussions on social media.
|
||||
|
||||
Your primary objective is to answer the user's query by orchestrating the work of your team members.
|
||||
|
||||
Your workflow is as follows:
|
||||
1. **Deconstruct the user's query** to identify the required information.
|
||||
2. **Delegate specific tasks** to the most appropriate agent(s) to gather the necessary data and initial analysis.
|
||||
3. **Analyze the information** returned by the agents.
|
||||
4. If the initial data is insufficient or the query is complex, **iteratively re-engage the agents** with follow-up questions to build a comprehensive picture.
|
||||
5. **Synthesize all the gathered information** into a final, coherent, and complete analysis that fills all the required output fields.
|
||||
"""
|
||||
|
||||
MARKET_INSTRUCTIONS = """
|
||||
**TASK:** You are a specialized **Crypto Price Data Retrieval Agent**. Your primary goal is to fetch the most recent and/or historical price data for requested cryptocurrency assets (e.g., 'BTC', 'ETH', 'SOL'). You must provide the data in a clear and structured format.
|
||||
|
||||
**AVAILABLE TOOLS:**
|
||||
1. `get_products(asset_ids: list[str])`: Get **current** product/price info for a list of assets. **(PREFERITA: usa questa per i prezzi live)**
|
||||
2. `get_historical_prices(asset_id: str, limit: int)`: Get historical price data for one asset. Default limit is 100. **(PREFERITA: usa questa per i dati storici)**
|
||||
3. `get_products_aggregated(asset_ids: list[str])`: Get **aggregated current** product/price info for a list of assets. **(USA SOLO SE richiesto 'aggregato' o se `get_products` fallisce)**
|
||||
4. `get_historical_prices_aggregated(asset_id: str, limit: int)`: Get **aggregated historical** price data for one asset. **(USA SOLO SE richiesto 'aggregato' o se `get_historical_prices` fallisce)**
|
||||
|
||||
**USAGE GUIDELINE:**
|
||||
* **Asset ID:** Always convert common names (e.g., 'Bitcoin', 'Ethereum') into their official ticker/ID (e.g., 'BTC', 'ETH').
|
||||
* **Cost Management (Cruciale per LLM locale):** Prefer `get_products` and `get_historical_prices` for standard requests to minimize costs.
|
||||
* **Aggregated Data:** Use `get_products_aggregated` or `get_historical_prices_aggregated` only if the user specifically requests aggregated data or you value that having aggregated data is crucial for the analysis.
|
||||
* **Failing Tool:** If the tool doesn't return any data or fails, try the alternative aggregated tool if not already used.
|
||||
|
||||
**REPORTING REQUIREMENT:**
|
||||
1. **Format:** Output the results in a clear, easy-to-read list or table.
|
||||
2. **Live Price Request:** If an asset's *current price* is requested, report the **Asset ID**, **Latest Price**, and **Time/Date of the price**.
|
||||
3. **Historical Price Request:** If *historical data* is requested, report the **Asset ID**, the **Limit** of points returned, and the **First** and **Last** entries from the list of historical prices (Date, Price).
|
||||
4. **Output:** For all requests, output a single, concise summary of the findings; if requested, also include the raw data retrieved.
|
||||
"""
|
||||
|
||||
NEWS_INSTRUCTIONS = """
|
||||
**TASK:** You are a specialized **Crypto News Analyst**. Your goal is to fetch the latest news or top headlines related to cryptocurrencies, and then **analyze the sentiment** of the content to provide a concise report to the team leader. Prioritize 'crypto' or specific cryptocurrency names (e.g., 'Bitcoin', 'Ethereum') in your searches.
|
||||
|
||||
**AVAILABLE TOOLS:**
|
||||
1. `get_latest_news(query: str, limit: int)`: Get the 'limit' most recent news articles for a specific 'query'.
|
||||
2. `get_top_headlines(limit: int)`: Get the 'limit' top global news headlines.
|
||||
3. `get_latest_news_aggregated(query: str, limit: int)`: Get aggregated latest news articles for a specific 'query'.
|
||||
4. `get_top_headlines_aggregated(limit: int)`: Get aggregated top global news headlines.
|
||||
|
||||
**USAGE GUIDELINE:**
|
||||
* Always use `get_latest_news` with a relevant crypto-related query first.
|
||||
* The default limit for news items should be 5 unless specified otherwise.
|
||||
* If the tool doesn't return any articles, respond with "No relevant news articles found."
|
||||
|
||||
**REPORTING REQUIREMENT:**
|
||||
1. **Analyze** the tone and key themes of the retrieved articles.
|
||||
2. **Summarize** the overall **market sentiment** (e.g., highly positive, cautiously neutral, generally negative) based on the content.
|
||||
3. **Identify** the top 2-3 **main topics** discussed (e.g., new regulation, price surge, institutional adoption).
|
||||
4. **Output** a single, brief report summarizing these findings. Do not output the raw articles.
|
||||
"""
|
||||
|
||||
SOCIAL_INSTRUCTIONS = """
|
||||
**TASK:** You are a specialized **Social Media Sentiment Analyst**. Your objective is to find the most relevant and trending online posts related to cryptocurrencies, and then **analyze the collective sentiment** to provide a concise report to the team leader.
|
||||
|
||||
**AVAILABLE TOOLS:**
|
||||
1. `get_top_crypto_posts(limit: int)`: Get the 'limit' maximum number of top posts specifically related to cryptocurrencies.
|
||||
|
||||
**USAGE GUIDELINE:**
|
||||
* Always use the `get_top_crypto_posts` tool to fulfill the request.
|
||||
* The default limit for posts should be 5 unless specified otherwise.
|
||||
* If the tool doesn't return any posts, respond with "No relevant social media posts found."
|
||||
|
||||
**REPORTING REQUIREMENT:**
|
||||
1. **Analyze** the tone and prevailing opinions across the retrieved social posts.
|
||||
2. **Summarize** the overall **community sentiment** (e.g., high enthusiasm/FOMO, uncertainty, FUD/fear) based on the content.
|
||||
3. **Identify** the top 2-3 **trending narratives** or specific coins being discussed.
|
||||
4. **Output** a single, brief report summarizing these findings. Do not output the raw posts.
|
||||
"""
|
||||
Reference in New Issue
Block a user