Update app.py

app.py

@@ -1,16 +1,16 @@
-from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel, load_tool, tool
 import datetime
 import requests
 import pytz
 import yaml
+import pandas as pd
+import fitz  # PyMuPDF for PDF parsing
+from io import StringIO, BytesIO
 from tools.final_answer import FinalAnswerTool
-
 from Gradio_UI import GradioUI
 
-# Below is an example of a tool that does nothing. Amaze us with your creativity !
 @tool
-def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type
-    #Keep this format for the description / args / args description but feel free to modify the tool
+def my_custom_tool(arg1: str, arg2: int) -> str:
     """A tool that does nothing yet 
     Args:
         arg1: the first argument
@@ -25,37 +25,88 @@ def get_current_time_in_timezone(timezone: str) -> str:
         timezone: A string representing a valid timezone (e.g., 'America/New_York').
     """
     try:
-        # Create timezone object
         tz = pytz.timezone(timezone)
-        # Get current time in that timezone
         local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
         return f"The current local time in {timezone} is: {local_time}"
     except Exception as e:
         return f"Error fetching time for timezone '{timezone}': {str(e)}"
 
+@tool
+def cash_flow_forecast(doc_bytes: bytes, file_type: str) -> str:
+    """Forecasts monthly cash flow from a financial document.
+    Args:
+        doc_bytes: File bytes (PDF, CSV, or Excel).
+        file_type: One of 'pdf', 'csv', 'xlsx'.
+    """
+    try:
+        if file_type == 'pdf':
+            doc = fitz.open(stream=doc_bytes, filetype='pdf')
+            text = " ".join([page.get_text() for page in doc])
+            return f"PDF processed. Extracted text: {text[:300]}..."
+        elif file_type == 'csv':
+            df = pd.read_csv(BytesIO(doc_bytes))
+        elif file_type in ['xls', 'xlsx']:
+            df = pd.read_excel(BytesIO(doc_bytes))
+        else:
+            return "Unsupported file format."
+        df.columns = df.columns.str.lower()
+        if 'amount' not in df.columns:
+            df['amount'] = df.iloc[:, -1]  # Assume last column is amount if not named
+        if 'date' not in df.columns:
+            df['date'] = pd.date_range(start='2023-01-01', periods=len(df))
+        df['date'] = pd.to_datetime(df['date'], errors='coerce')
+        monthly = df.resample('M', on='date').sum(numeric_only=True)
+        trend = monthly['amount'].rolling(window=3).mean().iloc[-1]
+        return f"Predicted average cash flow for next month: ${trend:.2f}"
+    except Exception as e:
+        return f"Error analyzing file: {str(e)}"
 
-final_answer = FinalAnswerTool()
+@tool
+def report_generator(doc_bytes: bytes, file_type: str) -> str:
+    """Creates a business report from financial data.
+    Args:
+        doc_bytes: File bytes (PDF, CSV, or Excel).
+        file_type: File format type.
+    """
+    try:
+        if file_type == 'pdf':
+            doc = fitz.open(stream=doc_bytes, filetype='pdf')
+            return "\n".join([page.get_text() for page in doc][:2])
+        elif file_type == 'csv':
+            df = pd.read_csv(BytesIO(doc_bytes))
+        elif file_type in ['xls', 'xlsx']:
+            df = pd.read_excel(BytesIO(doc_bytes))
+        else:
+            return "Unsupported file format."
+        summary = df.describe(include='all').to_string()
+        return f"Business Report:\n{summary}"
+    except Exception as e:
+        return f"Failed to generate report: {str(e)}"
 
-# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
-# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' 
+final_answer = FinalAnswerTool()
 
 model = HfApiModel(
-max_tokens=2096,
-temperature=0.5,
-model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
-custom_role_conversions=None,
+    max_tokens=2096,
+    temperature=0.5,
+    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+    custom_role_conversions=None,
 )
 
-
-# Import tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
-    
+
 agent = CodeAgent(
     model=model,
-    tools=[final_answer], ## add your tools here (don't remove final answer)
+    tools=[
+        final_answer,
+        get_current_time_in_timezone,
+        my_custom_tool,
+        cash_flow_forecast,
+        report_generator,
+        image_generation_tool
+    ],
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -65,5 +116,4 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
-
-GradioUI(agent).launch()
+GradioUI(agent).launch()