trying other models

app.py

@@ -14,9 +14,7 @@ from youtube_transcript_api import YouTubeTranscriptApi
 
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-# Switched to a more reliable and fast model available on the free Inference API
 MODEL_ID = "mistralai/Mistral-7B-Instruct-v0.2"
-# Updated prompt template to match the Mistral format
 PROMPT_TEMPLATE = """<s>[INST]You are a helpful assistant designed to answer questions accurately. You have access to the following tools:
 
 {tools_description}
@@ -32,12 +30,15 @@ When you have the final answer, respond with:
 Thought: I have now found the final answer.
 Final Answer: The final answer.
 
-Do not use a tool if you are not sure about the parameters. Do not make up file names. If a tool is not available for a task (e.g., image analysis), state that you cannot answer.
+Important:
+- Do not use a tool if you are not sure about the parameters.
+- Do not make up file names.
+- If a tool is not available for a task (e.g., image analysis), state that you cannot answer.
+- If a tool returns an error, note it and try an alternative approach if possible.
 
 Question: {question}
 [/INST]{scratchpad}"""
 
-
 # --- Tool Definitions ---
 
 class WebSearchTool:
@@ -105,21 +106,24 @@ class FileReaderTool:
                 content = "\n".join(para.text for para in doc.paragraphs)
             elif file_name.endswith('.csv'):
                 df = pd.read_csv(file_content)
-                content = df.to_string()
+                content = df.to_json(orient='records')  # Return JSON for easier processing
             elif file_name.endswith('.json'):
                 data = json.load(file_content)
                 content = json.dumps(data, indent=2)
             elif file_name.endswith('.txt'):
                 content = file_content.read().decode('utf-8')
+            elif file_name.endswith('.xlsx'):
+                df = pd.read_excel(file_content, engine='openpyxl')
+                content = df.to_json(orient='records')  # Return JSON for easier processing
             else:
-                return f"Error: Unsupported file type for '{file_name}'. Supported types: .pdf, .docx, .csv, .json, .txt."
+                return f"Error: Unsupported file type for '{file_name}'. Supported types: .pdf, .docx, .csv, .json, .txt, .xlsx."
             return content if content else "File is empty."
         except Exception as e:
             return f"Error reading file '{file_name}': {e}"
 
     @property
     def description(self):
-        return 'file_reader(task_id: str, file_name: str) -> str - Reads content of text-based files (.pdf, .docx, .csv, .json, .txt). For audio, use audio_transcriber.'
+        return 'file_reader(task_id: str, file_name: str) -> str - Reads content of text-based files (.pdf, .docx, .csv, .json, .txt, .xlsx). For audio, use audio_transcriber.'
 
 class AudioTranscriptionTool:
     """A tool to transcribe audio files using the Hugging Face Inference API."""
@@ -134,8 +138,12 @@ class AudioTranscriptionTool:
             response = requests.get(file_url, timeout=30)
             response.raise_for_status()
             audio_data = response.content
-            transcription = self.client.automatic_speech_recognition(audio_data)
-            return transcription['text'] if transcription and 'text' in transcription else "Could not transcribe audio."
+            # Specify Whisper-large-v2 for accurate transcription
+            transcription = self.client.automatic_speech_recognition(audio_data, model="openai/whisper-large-v2")
+            if transcription and 'text' in transcription:
+                return transcription['text']
+            else:
+                return "Could not transcribe audio."
         except Exception as e:
             return f"Error during audio transcription: {e}"
 
@@ -161,7 +169,6 @@ class YouTubeTranscriptTool:
     def description(self):
         return 'youtube_transcript_fetcher(video_url: str) -> str - Fetches the transcript of a YouTube video. Use for questions about video content.'
 
-
 # --- GAIA Agent Definition ---
 class GaiaAgent:
     def __init__(self, hf_token: str, api_url: str, max_turns: int = 8):
@@ -291,7 +298,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         error_detail = f"Server responded with status {e.response.status_code}. Response: {e.response.text[:500]}" if e.response else str(e)
         return f"Submission Failed: {error_detail}", pd.DataFrame(results_log)
 
-
 # --- Gradio Interface ---
 with gr.Blocks() as demo:
     gr.Markdown("# GAIA Agent Evaluation Runner")