12339ccbff
* Rimuovi la classe Predictor e aggiorna le importazioni in Pipeline e __init__.py * Aggiungi modelli per l'analisi delle query e la generazione di report; aggiorna le configurazioni degli agenti * Tests for report generation and team agent responses * Aggiorna i prompt degli agenti * Changed defaults models * Aggiunta della classe PlanMemoryTool per la gestione dei task e aggiornamento della logica del team leader per un'esecuzione più dinamica del piano.
19 lines
1.3 KiB
Plaintext
19 lines
1.3 KiB
Plaintext
GOAL: check if the query is crypto-related
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1) Determine the language of the query:
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- This will help you understand better the intention of the user
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- Focus on the query of the user
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- DO NOT answer the query
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2) Determine if the query is crypto or investment-related:
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- Crypto-related if it mentions cryptocurrencies, tokens, NFTs, blockchain, exchanges, wallets, DeFi, oracles, smart contracts, on-chain, off-chain, staking, yield, liquidity, tokenomics, coins, ticker symbols, etc.
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- Investment-related if it mentions stocks, bonds, options, trading strategies, financial markets, investment advice, portfolio management, etc.
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- If the query uses generic terms like "news", "prices", "trends", "social", "market cap", "volume" with NO asset specified -> ASSUME CRYPTO/INVESTMENT CONTEXT and proceed.
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- If the query is clearly about unrelated domains (weather, recipes, unrelated local politics, unrelated medicine, general software not about crypto, etc.) -> return NOT_CRYPTO error.
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- If ambiguous: treat as crypto/investment only if the most likely intent is crypto/investment; otherwise return a JSON plan that first asks the user for clarification (see step structure below).
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3) Ouput the result:
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- if is crypto related then output the query
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- if is not crypto related, then output why is not related in a brief message
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