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| """ | |
| A sophisticated analyzer using the Google Gemini Pro API. | |
| This module provides structured analysis of financial text, including: | |
| - Nuanced sentiment with reasoning. | |
| - Key entity extraction (e.g., cryptocurrencies). | |
| - Topic classification. | |
| - Potential market impact assessment. | |
| - Synthesis of multiple news items into a daily briefing. | |
| """ | |
| import os | |
| import logging | |
| import httpx | |
| import json | |
| from typing import Optional, TypedDict, List, Union | |
| # Configure logging | |
| logger = logging.getLogger(__name__) | |
| # --- Type Definitions for Structured Data --- | |
| class AnalysisResult(TypedDict): | |
| sentiment: str | |
| sentiment_score: float | |
| reason: str | |
| entities: List[str] | |
| topic: str | |
| impact: str | |
| summary: str | |
| error: Optional[str] | |
| url: Optional[str] # To store the article URL | |
| class GeminiAnalyzer: | |
| """Manages interaction with the Google Gemini API for deep text analysis.""" | |
| API_URL = "https://generativelanguage.googleapis.com/v1beta/models/gemini-1.5-pro-latest:generateContent" | |
| def __init__(self, client: httpx.AsyncClient, api_key: Optional[str] = None): | |
| self.client = client | |
| self.api_key = api_key or os.getenv("GEMINI_API_KEY") | |
| if not self.api_key: | |
| raise ValueError("GEMINI_API_KEY is not set. Please add it as a repository secret.") | |
| self.params = {"key": self.api_key} | |
| self.headers = {"Content-Type": "application/json"} | |
| def _build_analysis_prompt(self, text: str) -> dict: | |
| """Creates the structured JSON prompt for analyzing a single piece of text.""" | |
| return { | |
| "contents": [{ | |
| "parts": [{ | |
| "text": f""" | |
| Analyze the following financial text from the cryptocurrency world. | |
| Provide your analysis as a single, minified JSON object with NO markdown formatting. | |
| The JSON object must have these exact keys: "sentiment", "sentiment_score", "reason", "entities", "topic", "impact", "summary". | |
| - "sentiment": MUST be one of "POSITIVE", "NEGATIVE", or "NEUTRAL". | |
| - "sentiment_score": A float between -1.0 (very negative) and 1.0 (very positive). | |
| - "reason": A brief, one-sentence explanation for the sentiment score. | |
| - "entities": A JSON array of strings listing the primary cryptocurrencies or tokens mentioned (e.g., ["Bitcoin", "ETH"]). | |
| - "topic": MUST be one of "Regulation", "Partnership", "Technical Update", "Market Hype", "Security", or "General News". | |
| - "impact": Assess the potential short-term market impact. MUST be one of "LOW", "MEDIUM", or "HIGH". | |
| - "summary": A concise, one-sentence summary of the provided text. | |
| Text to analyze: "{text}" | |
| """ | |
| }] | |
| }] | |
| } | |
| async def analyze_text(self, text: str) -> AnalysisResult: | |
| """Sends text to Gemini and returns a structured analysis.""" | |
| prompt = self._build_analysis_prompt(text) | |
| try: | |
| response = await self.client.post(self.API_URL, headers=self.headers, params=self.params, json=prompt, timeout=60.0) | |
| response.raise_for_status() | |
| full_response = response.json() | |
| json_text = full_response["candidates"][0]["content"]["parts"][0]["text"] | |
| analysis: AnalysisResult = json.loads(json_text) | |
| analysis["error"] = None | |
| return analysis | |
| except Exception as e: | |
| logger.error(f"❌ Gemini Analysis Error: {e}") | |
| return { | |
| "sentiment": "ERROR", "sentiment_score": 0, "reason": str(e), | |
| "entities": [], "topic": "Unknown", "impact": "Unknown", | |
| "summary": "Failed to analyze text due to an API or parsing error.", "error": str(e) | |
| } | |
| async def generate_daily_briefing(self, analysis_items: List[dict]) -> str: | |
| """Generates a high-level market briefing from a list of analyzed news items.""" | |
| if not analysis_items: | |
| return "### Briefing Unavailable\nNo news items were analyzed in the last period." | |
| context = "\n".join([f"- {item.get('summary')} (Impact: {item.get('impact')}, Topic: {item.get('topic')})" for item in analysis_items]) | |
| briefing_prompt = { | |
| "contents": [{ | |
| "parts": [{ | |
| "text": f""" | |
| You are a senior crypto market analyst named 'Sentinel'. Your tone is professional, concise, and insightful. | |
| Based on the following list of analyzed news items from the last 24 hours, write a "Daily Market Briefing". | |
| The briefing must have three sections using markdown: | |
| 1. "### Executive Summary": A single, impactful paragraph summarizing the overall market mood and key events. | |
| 2. "### Top Bullish Signals": 2-3 bullet points on the most positive developments. | |
| 3. "### Top Bearish Signals": 2-3 bullet points on the most significant risks or negative news. | |
| Here is the data to analyze: | |
| {context} | |
| """ | |
| }] | |
| }], | |
| "safetySettings": [ | |
| {"category": "HARM_CATEGORY_HARASSMENT", "threshold": "BLOCK_NONE"}, | |
| {"category": "HARM_CATEGORY_HATE_SPEECH", "threshold": "BLOCK_NONE"}, | |
| {"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT", "threshold": "BLOCK_NONE"}, | |
| {"category": "HARM_CATEGORY_DANGEROUS_CONTENT", "threshold": "BLOCK_NONE"}, | |
| ] | |
| } | |
| try: | |
| response = await self.client.post(self.API_URL, headers=self.headers, params=self.params, json=briefing_prompt, timeout=120.0) | |
| response.raise_for_status() | |
| full_response = response.json() | |
| briefing_text = full_response["candidates"][0]["content"]["parts"][0]["text"] | |
| return briefing_text | |
| except Exception as e: | |
| logger.error(f"❌ Gemini Briefing Error: {e}") | |
| return "### Briefing Unavailable\nCould not generate the daily market briefing due to a Gemini API error." |