Update app.py

app.py

@@ -16,15 +16,18 @@ login(token=os.environ["HUGGINGFACEHUB_API_TOKEN"])
 search_tool = DuckDuckGoSearchTool()
 
 # --- Tool 1: Wikipedia Search Tool ---
+import wikipedia
+
 class WikipediaTool(Tool):
     name = "wikipedia_search"
     description = "Search Wikipedia for a given topic and return a concise summary."
+    
     parameters = {
-    "type": "object",
-    "properties": {
-        "query": {
-            "type": "string",
-            "description": "The topic to search on Wikipedia"
+        "type": "object",
+        "properties": {
+            "query": {
+                "type": "string",
+                "description": "The topic to search on Wikipedia"
             }
         },
         "required": ["query"]
@@ -35,7 +38,7 @@ class WikipediaTool(Tool):
     def forward(self, query: str) -> str:
         try:
             page = wikipedia.page(query)
-            return page.summary[:1000]  # truncate to first 1000 characters
+            return page.summary[:1000]
         except wikipedia.exceptions.DisambiguationError as e:
             return f"Disambiguation: {', '.join(e.options[:5])}"
         except wikipedia.exceptions.PageError:
@@ -44,16 +47,23 @@ class WikipediaTool(Tool):
             return f"Error: {str(e)}"
 
 
+
 # --- Tool 2: Audio Transcription Tool (uses whisper base) ---
+import base64
+import whisper
+import tempfile
+import os
+
 class AudioTranscriptionTool(Tool):
     name = "audio_transcriber"
     description = "Transcribes an uploaded audio file to text using Whisper."
+    
     parameters = {
-    "type": "object",
-    "properties": {
-        "audio": {
-            "type": "string",  # Must be base64-encoded string if passed to LLM
-            "description": "The audio file (base64-encoded) to transcribe"
+        "type": "object",
+        "properties": {
+            "audio": {
+                "type": "string",
+                "description": "The audio file in base64-encoded format"
             }
         },
         "required": ["audio"]
@@ -61,30 +71,39 @@ class AudioTranscriptionTool(Tool):
 
     output_type = "string"
 
-    def forward(self, audio: bytes) -> str:
+    def forward(self, audio: str) -> str:
         try:
+            decoded_audio = base64.b64decode(audio)
             model = whisper.load_model("base")
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp_file:
-                tmp_file.write(audio)
-                tmp_file_path = tmp_file.name
 
-            result = model.transcribe(tmp_file_path)
-            os.remove(tmp_file_path)
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".mp3") as tmp:
+                tmp.write(decoded_audio)
+                tmp_path = tmp.name
+
+            result = model.transcribe(tmp_path)
+            os.remove(tmp_path)
             return result["text"]
         except Exception as e:
             return f"Transcription failed: {str(e)}"
 
 
+
 # --- Tool 3: Excel Reader Tool ---
+import base64
+import tempfile
+import pandas as pd
+import os
+
 class ExcelReaderTool(Tool):
     name = "excel_reader"
-    description = "Reads uploaded Excel file and summarizes sheet data."
+    description = "Reads uploaded Excel file (.xlsx) and summarizes the sheet data."
+    
     parameters = {
-    "type": "object",
-    "properties": {
-        "excel": {
-            "type": "string",  # Same as above, assume base64 input
-            "description": "The Excel file (.xlsx, base64-encoded)"
+        "type": "object",
+        "properties": {
+            "excel": {
+                "type": "string",
+                "description": "The Excel file in base64-encoded format"
             }
         },
         "required": ["excel"]
@@ -92,18 +111,19 @@ class ExcelReaderTool(Tool):
 
     output_type = "string"
 
-    def forward(self, excel: bytes) -> str:
+    def forward(self, excel: str) -> str:
         try:
-            with tempfile.NamedTemporaryFile(delete=False, suffix=".xlsx") as tmp_file:
-                tmp_file.write(excel)
-                tmp_file_path = tmp_file.name
-
-            df = pd.read_excel(tmp_file_path)
-            summary = df.describe(include="all").to_string()
-            os.remove(tmp_file_path)
-            return f"Summary statistics:\n{summary}"
+            decoded_excel = base64.b64decode(excel)
+            with tempfile.NamedTemporaryFile(delete=False, suffix=".xlsx") as tmp:
+                tmp.write(decoded_excel)
+                tmp_path = tmp.name
+
+            df = pd.read_excel(tmp_path)
+            os.remove(tmp_path)
+            return f"Summary:\n{df.describe(include='all').to_string()}"
         except Exception as e:
             return f"Failed to read Excel file: {str(e)}"
+
             
 excel_tool = ExcelReaderTool()
 wiki_tool = WikipediaTool()