Fix Excel reading and Python runner

agent.py

@@ -48,9 +48,10 @@ async def main(query: str, file_url: str | None) -> str:
 
     ctx = Context(agent)
 
+    prompt = query if file_url is None else f"{query}. Use the URL {file_url} as the Url path of attached files mentioned in the question. Attached file are required to answer the question. To run Python code use Code Intrepreter tool."
     message = ChatMessage(
         role="user",
-        content=f"{query}. Use the URL {file_url} as the Url path of the image, audio or Excel files which are mentioned in the question and are required to answer the question."
+        content=prompt
     )
 
     response = await agent.run(message, ctx=ctx)

app.py

@@ -20,7 +20,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
 
     load_dotenv()
-    
+
     # --- Determine HF Space Runtime URL and Repo URL ---
     space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
 
@@ -79,6 +79,9 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             continue
         try:
             file_url = f"{files_url}/{task_id}"
+            if "application/json" in requests.get(file_url).headers.get("Content-Type"):
+                file_url = None
+        
             agent_output = asyncio.run(agent.main(question_text, file_url))
             submitted_answer = str(agent_output)
             answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})

excel_file_reader.py

@@ -1,10 +1,11 @@
 from typing import Optional
-from llama_index.readers.remote import RemoteReader
 from google import genai
 from google.genai import types
-import pathlib
 import pandas as pd
+import requests
 import os
+import io
+from io import BytesIO
 
 def excel_file_reader(file_url: str, analysis_prompt: Optional[str] = None) -> str:
     """
@@ -23,26 +24,27 @@ def excel_file_reader(file_url: str, analysis_prompt: Optional[str] = None) -> s
 
         gemini_llm =  genai.Client(api_key=os.getenv("GOOGLE_API_KEY"))
 
-        loader = RemoteReader()
-        documents = loader.load_data(url=file_url)
-        
-        if len(documents) > 0:
-            file_path = documents[0].metadata.get("file_path", None)
-            print(f"Converting file {file_path} ")
-            if file_path:
-                    sheets = pd.read_excel(file_path, sheet_name=None)
-                    for sheet_name, sheet_data in sheets.items():
-                        sheet_data.to_csv(f"{sheet_name}.csv", index=False)
-                        filepath = pathlib.Path(f"{sheet_name}.csv")
+        resp = requests.get(file_url)
+       
+        sheets = pd.read_excel(BytesIO(resp.content), sheet_name=None)
+        for _, sheet_data in sheets.items():
+            csv_buffer = io.StringIO()
+            sheet_data.to_csv(csv_buffer, index=False)
+            csv_bytes = csv_buffer.getvalue().encode('utf-8')
+            
+            text = analysis_prompt or "Provide a detailed description of this CSV file."
+            csv_part = types.Part.from_bytes(
+                data=csv_bytes,
+                mime_type='text/csv'
+            )
+            
+            response = gemini_llm.models.generate_content(
+                model="gemini-2.0-flash",
+                contents=[text, csv_part]
+            )
 
-                        text=analysis_prompt or "Provide a detailed description of this CSV file."
-                        csv_bytes = types.Part.from_bytes(data=filepath.read_bytes(),mime_type='text/csv',)
-                        response = gemini_llm.models.generate_content(
-                            model="gemini-2.0-flash",
-                            contents=[text,csv_bytes])
+            return response.text
 
-                        return response.text
-                    
         return ""
             
     except Exception as e: