Update app/gemini_analyzer.py

app/gemini_analyzer.py

@@ -6,7 +6,6 @@ This module provides structured analysis of financial text, including:
 - 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
@@ -17,7 +16,7 @@ from typing import Optional, TypedDict, List, Union
 # Configure logging
 logger = logging.getLogger(__name__)
 
-# --- Type Definitions for Structured Data ---
+# --- Pydantic-like models for structured output ---
 class AnalysisResult(TypedDict):
     sentiment: str
     sentiment_score: float
@@ -27,7 +26,7 @@ class AnalysisResult(TypedDict):
     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."""
@@ -42,8 +41,8 @@ class GeminiAnalyzer:
         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."""
+    def _build_prompt(self, text: str) -> dict:
+        """Creates the structured JSON prompt for the Gemini API."""
         return {
             "contents": [{
                 "parts": [{
@@ -67,66 +66,45 @@ class GeminiAnalyzer:
             }]
         }
 
+    def _extract_json(self, text: str) -> Optional[dict]:
+        """Finds and parses the first valid JSON object in a string."""
+        try:
+            # Find the first '{' and the last '}' to isolate the JSON blob
+            start_index = text.find('{')
+            end_index = text.rfind('}')
+            if start_index != -1 and end_index != -1 and end_index > start_index:
+                json_str = text[start_index:end_index+1]
+                return json.loads(json_str)
+        except json.JSONDecodeError as e:
+            logger.error(f"Failed to decode JSON from extracted text: {text} | Error: {e}")
+        return None
+
     async def analyze_text(self, text: str) -> AnalysisResult:
         """Sends text to Gemini and returns a structured analysis."""
-        prompt = self._build_analysis_prompt(text)
+        prompt = self._build_prompt(text)
         try:
-            response = await self.client.post(self.API_URL, headers=self.headers, params=self.params, json=prompt, timeout=60.0)
+            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"]
+            response_text = full_response["candidates"][0]["content"]["parts"][0]["text"]
             
-            analysis: AnalysisResult = json.loads(json_text)
-            analysis["error"] = None
-            return analysis
+            # Use the new robust JSON extractor
+            analysis = self._extract_json(response_text)
+
+            if analysis:
+                analysis["error"] = None
+                return analysis
+            else:
+                # This will be logged if the helper function fails
+                raise ValueError(f"Could not extract valid JSON from Gemini response: {response_text}")
 
         except Exception as e:
             logger.error(f"❌ Gemini Analysis Error: {e}")
             return {
-                "sentiment": "ERROR", "sentiment_score": 0, "reason": str(e),
+                "sentiment": "ERROR", "sentiment_score": 0.0, "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."
+                "summary": "Failed to perform analysis.", "error": str(e)
+            }