Spaces:
Sleeping
Sleeping
update the tools to check for temporary files and extract file paths
Browse files
app.py
CHANGED
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@@ -33,21 +33,26 @@ def describe_image(path: str) -> str:
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return image_captioner(path)[0]["generated_text"]
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@tool
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def audio_to_text_tool(
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"""Converts audio file to text. requires audio file path. return transcribed text.
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Args:
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audio_file_path: path of audio data file
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"""
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output = SpeechToTextTool()
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return output(audio_file_path)
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@tool
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def excel_reader(
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""" reads an excel file. Requires the
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Args:
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"""
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return f"Rows: {len(df)}, Columns: {list(df.columns)}, Description: {df.describe()}"
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class BasicAgent:
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@@ -67,7 +72,7 @@ class BasicAgent:
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planning_interval=None,
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name=None,
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description=None,
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additional_authorized_imports = [ 'cv2','PIL','time', 'math', 'stat', 're', 'queue', 'statistics', 'unicodedata', 'datetime', 'collections', 'itertools', 'random','json','numpy']
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)
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#self.model = InferenceClientModel(model= "Qwen/Qwen2.5-7B-Instruct",)
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@@ -88,10 +93,14 @@ CRITICAL RULES (Follow EXACTLY):
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6. For cities: full name, no abbreviations (Los Angeles, not LA)
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Important: Do not hallucinate. Try to keep your answers based on facts as much as you can. You will be asked a question, make sure you only give the answer asked in the question. Do a web search first and then wikipediasearch.
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-
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Question: {question}
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Respond with ONLY the
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output = self.agent.run(prompt)
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return str(output).strip()
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return image_captioner(path)[0]["generated_text"]
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@tool
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def audio_to_text_tool(directory: str = "/tmp") -> str:
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"""Converts audio file to text. requires audio file path. return transcribed text.
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Args:
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audio_file_path: path of audio data file
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"""
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files = os.listdir('/tmp')
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audio_file = [f for f in files if f.endswith('.mp3')][0]
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audio_file_path = f"/tmp/{audio_file}"
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output = SpeechToTextTool()
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return output(audio_file_path)
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@tool
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def excel_reader(directory: str = "/tmp") -> str:
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""" reads an excel file. Requires the temporary file. Return information on rows and columns and description of the file.
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Args:
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/tmp: file path as input
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"""
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files = os.listdir('/tmp')
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excel_file = [f for f in files if f.endswith('.xlsx')][0]
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df = pd.read_excel(f"/tmp/{excel_file}")
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return f"Rows: {len(df)}, Columns: {list(df.columns)}, Description: {df.describe()}"
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class BasicAgent:
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planning_interval=None,
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name=None,
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description=None,
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additional_authorized_imports = [ 'os','cv2','PIL','time', 'math', 'stat', 're', 'queue', 'statistics', 'unicodedata', 'datetime', 'collections', 'itertools', 'random','json','numpy']
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)
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#self.model = InferenceClientModel(model= "Qwen/Qwen2.5-7B-Instruct",)
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6. For cities: full name, no abbreviations (Los Angeles, not LA)
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Important: Do not hallucinate. Try to keep your answers based on facts as much as you can. You will be asked a question, make sure you only give the answer asked in the question. Do a web search first and then wikipediasearch.
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CRITICAL:
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1. GAIA files are at /tmp/task_*/filename
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2. List files: import os; print(os.listdir('/tmp'))
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3. Use REAL paths from os.listdir()
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4. Paths start with /tmp/task_"""
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Question: {question}
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Respond with ONLY the result."""
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output = self.agent.run(prompt)
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return str(output).strip()
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