Update core/stock_analysis.py

core/stock_analysis.py

@@ -69,26 +69,105 @@ def analyze_stock(ticker, llm):
     news_docs = get_google_news_documents(f"Trending News for {ticker}", max_articles=10)
     docs = web_docs + news_docs
 
-    prompt_template = """You are an expert Stock Market Trader...
-
+    prompt_template = """You are an expert Stock Market Trader specializing in stock market insights derived from fundamental analysis, analytical trends, profit-based evaluations, news indicators from different sites and detailed company financials. 
+    Using your expertise, please analyze the stock based on the provided context below.
+    
     Context:
     {input_documents}
-
+    
     Task:
-    Summarize the stock...
-    RETURN JSON with this schema:
+    Summarize the stock based on its historical and current data. Keep it CONCISE & BRIEF.
+    Evaluate the stock on the following parameters:
+    1. Company Fundamentals: Assess the stock's intrinsic value, growth potential, and financial health.
+    2. Current & Future Price Trends: Analyze historical price movements and current price trends.
+    3. News and Sentiment: Review recent news articles, press releases, and social media sentiment.
+    4. Red Flags: Identify any potential risks or warning signs.
+    5. Provide a rating for the stock on a scale of 1 to 10.
+    6. Advise if the stock is a good buy for the next 1,5, 10 weeks.
+    7. Suggest at what price we need to buy and hold or sell the stock
 
-    ```json
+    PROVIDE THE DETAILS based on just the FACTS present in the document
+    PROVIDE THE DETAILS IN an JSON Object. Stick to the below JSON object
     {{
       "stock_summary": {{
         "company_name": "",
         "ticker": "",
         "exchange": "",
-        ...
+        "description": "",
+        "current_price": "",
+        "market_cap": "",
+        "historical_performance": {{
+          "5_day": "",
+          "1_month": "",
+          "6_months": "",
+          "1_year": "",
+          "5_years": ""
+        }}
+      }},
+      "evaluation_parameters": {{
+        "company_fundamentals": {{
+          "assessment": "",
+          "key_metrics": {{
+            "pe_ratio": "",
+            "volume":"",
+            "revenue_growth_yoy": "",
+            "net_income_growth_yoy": "",
+            "eps_growth_yoy": "",
+            "dividend_yield": "",
+            "balance_sheet": "",
+            "return_on_capital": ""
+          }}
+        }},
+        "current_and_future_price_trends": {{
+          "assessment": "",
+          "historical_trends": "",
+          "current_trends": "",
+          "technical_analysis_notes": "",
+          "technical_indicators":""
+        }},
+        "news_and_sentiment": {{
+          "assessment": "",
+          "positive_sentiment": [
+            "",
+            "",
+            ""
+          ],
+          "negative_sentiment": [
+            "",
+            "",
+            ""
+          ]
+        }},
+        "red_flags": [
+          {{
+            "flag": "",
+            "details": ""
+          }},
+          {{
+            "flag": "",
+            "details": ""
+          }},
+          {{
+            "flag": "",
+            "details": ""
+          }}
+        ]
+      }},
+      "overall_rating": {{
+        "rating": "ranging from 1 to 10, 1 being low rated, 10 being highly rated",
+        "justification": ""
       }},
-      ...
+      "investment_advice": {{
+        "next_1_weeks_outlook": "",
+        "next_5_weeks_outlook": "",
+        "next_10_weeks_outlook": "",
+        "price_action_suggestions": {{
+          "buy": "",
+          "hold": "",
+          "sell": ""
+        }}
+      }}
     }}
-    ```
     """
 
     prompt = PromptTemplate.from_template(prompt_template)