Update app.py

app.py

@@ -62,11 +62,14 @@ class FinancialAnalyzer:
             logger.error(f"Error loading models: {str(e)}")
             raise
 
-    def analyze_financials(self, csv_data: str) -> str:
+    def analyze_financials(self, income_data: pd.DataFrame, balance_data: pd.DataFrame) -> str:
         """Generate financial analysis using Tiny Llama and analyze sentiment using FinBERT"""
         try:
+            # Combine the data for AI to process (can adjust prompt as needed)
+            combined_data = f"Income Statement Data:\n{income_data.to_string()}\n\nBalance Sheet Data:\n{balance_data.to_string()}"
+
             # Generate status and insights using Tiny Llama
-            status_prompt = f"Please analyze the following financial data and provide status, insights, and metrics:\n\n{csv_data}"
+            status_prompt = f"Please analyze the following financial data and provide status, insights, and metrics:\n\n{combined_data}"
             response = self.analysis_model(
                 status_prompt,
                 max_length=1500,
@@ -94,12 +97,9 @@ class FinancialAnalyzer:
 
             # Return a comprehensive report
             result = f"""# Financial Analysis Report
-
 ### Sentiment Analysis: {sentiment_label} ({sentiment_score:.1%})
-
 ### Financial Status and Insights:
 {insights_result}
-
 ### Recommendations and Roadmap:
 {roadmap_result}
 """
@@ -109,11 +109,10 @@ class FinancialAnalyzer:
             logger.error(f"Analysis error: {str(e)}")
             return f"Analysis Error: {str(e)}"
 
-# Function to read CSV and convert to text format
-def csv_to_text(file_path: str) -> str:
-    """Convert CSV to raw text format for model input"""
-    df = pd.read_csv(file_path)
-    return df.to_string(index=False)  # Convert DataFrame to string without index
+# Function to read CSV and convert to DataFrame
+def read_csv(file_path: str) -> pd.DataFrame:
+    """Read CSV and return a DataFrame"""
+    return pd.read_csv(file_path)
 
 def analyze_statements(income_statement, balance_sheet):
     """Main function to analyze financial statements"""
@@ -121,16 +120,13 @@ def analyze_statements(income_statement, balance_sheet):
         if not income_statement or not balance_sheet:
             return "Please upload both Income Statement and Balance Sheet CSV files."
             
-        # Read files as raw text (no need to clean manually)
-        income_data = csv_to_text(income_statement.name)
-        balance_data = csv_to_text(balance_sheet.name)
+        # Read files as DataFrames (no need to clean manually)
+        income_data = read_csv(income_statement.name)
+        balance_data = read_csv(balance_sheet.name)
         
-        # Combine the data for AI to process (can adjust prompt as needed)
-        combined_data = f"Income Statement Data:\n{income_data}\n\nBalance Sheet Data:\n{balance_data}"
-
         # Create analyzer and process data
         analyzer = FinancialAnalyzer()
-        result = analyzer.analyze_financials(combined_data)
+        result = analyzer.analyze_financials(income_data, balance_data)
         
         # Clear memory
         clear_gpu_memory()
@@ -167,4 +163,4 @@ if __name__ == "__main__":
         iface.launch(server_name="0.0.0.0", server_port=7860)
     except Exception as e:
         logger.error(f"Launch error: {str(e)}")
-        sys.exit(1)
+        sys.exit(1)