Update crew.py
Browse files
crew.py
CHANGED
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@@ -48,268 +48,6 @@ tracer_provider = register(
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#CrewAIInstrumentor().instrument(tracer_provider=tracer_provider)
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@tool("Web Search Tool")
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def web_search_tool(question: str) -> str:
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"""Given a question only, search the web to answer the question.
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Args:
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question (str): Question to answer
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Returns:
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str: Answer to the question
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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response = client.models.generate_content(
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model=WEB_SEARCH_MODEL,
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contents=question,
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config=types.GenerateContentConfig(
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tools=[types.Tool(google_search=types.GoogleSearchRetrieval())]
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)
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Image Analysis Tool")
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def image_analysis_tool(question: str, file_path: str) -> str:
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"""Given a question and image file, analyze the image to answer the question.
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Args:
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question (str): Question about an image file
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file_path (str): The image file path
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Returns:
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str: Answer to the question about the image file
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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file = client.files.upload(file=file_path)
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response = client.models.generate_content(
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model=IMAGE_ANALYSIS_MODEL,
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contents=[file, question]
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Audio Analysis Tool")
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def audio_analysis_tool(question: str, file_path: str) -> str:
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"""Given a question and audio file, analyze the audio to answer the question.
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Args:
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question (str): Question about an audio file
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file_path (str): The audio file path
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Returns:
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str: Answer to the question about the audio file
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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file = client.files.upload(file=file_path)
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response = client.models.generate_content(
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model=AUDIO_ANALYSIS_MODEL,
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contents=[file, question]
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Video Analysis Tool")
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def video_analysis_tool(question: str, file_path: str) -> str:
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"""Given a question and video file, analyze the video to answer the question.
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Args:
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question (str): Question about a video file
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file_path (str): The video file path
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Returns:
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str: Answer to the question about the video file
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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file = client.files.upload(file=file_path)
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response = client.models.generate_content(
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model=VIDEO_ANALYSIS_MODEL,
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contents=[file, question]
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("YouTube Analysis Tool")
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def youtube_analysis_tool(question: str, url: str) -> str:
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"""Given a question and YouTube URL, analyze the video to answer the question.
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Args:
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question (str): Question about a YouTube video
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url (str): The YouTube URL
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Returns:
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str: Answer to the question about the YouTube video
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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return client.models.generate_content(
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model=YOUTUBE_ANALYSIS_MODEL,
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contents=types.Content(
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parts=[types.Part(file_data=types.FileData(file_uri=url)),
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types.Part(text=question)]
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)
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)
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Document Analysis Tool")
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def document_analysis_tool(question: str, file_path: str) -> str:
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"""Given a question and document file, analyze the document to answer the question.
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Args:
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question (str): Question about a document file
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file_path (str): The document file path
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Returns:
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str: Answer to the question about the document file
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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contents = []
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if is_ext(file_path, ".docx"):
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text_data = read_docx_text(file_path)
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contents = [f"{question}\n{text_data}"]
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print(f"=> Text data:\n{text_data}")
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elif is_ext(file_path, ".pptx"):
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text_data = read_pptx_text(file_path)
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contents = [f"{question}\n{text_data}"]
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print(f"=> Text data:\n{text_data}")
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else:
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file = client.files.upload(file=file_path)
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contents = [file, question]
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response = client.models.generate_content(
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model=DOCUMENT_ANALYSIS_MODEL,
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contents=contents
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Arithmetic Tool")
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def arithmetic_tool(question: str, a: float, b: float) -> float:
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"""Given a question and two numbers, perform the calculation to answer the question.
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Args:
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question (str): Question to answer
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a (float): First number
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b (float): Second number
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Returns:
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float: Result number
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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response = client.models.generate_content(
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model=ARITHMETIC_MODEL,
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contents=question,
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config=types.GenerateContentConfig(
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tools=[add, subtract, multiply, divide, modulus]
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)
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)
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return response.text
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Code Execution Tool")
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def code_execution_tool(question: str, file_path: str) -> str:
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"""Given a question and Python file, execute the file to answer the question.
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Args:
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question (str): Question to answer
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file_path (str): The Python file path
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Returns:
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str: Answer to the question
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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file = client.files.upload(file=file_path)
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response = client.models.generate_content(
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model=CODE_EXECUTION_MODEL,
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contents=[file, question],
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config=types.GenerateContentConfig(
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tools=[types.Tool(code_execution=types.ToolCodeExecution)]
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),
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)
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for part in response.candidates[0].content.parts:
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if part.code_execution_result is not None:
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return part.code_execution_result.output
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@tool("Code Generation Tool")
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def code_generation_tool(question: str, json_data: str) -> str:
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"""Given a question and JSON data, generate and execute code to answer the question.
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Args:
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question (str): Question to answer
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file_path (str): The JSON data
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Returns:
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str: Answer to the question
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Raises:
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RuntimeError: If processing fails"""
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try:
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client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
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response = client.models.generate_content(
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model=CODE_GENERATION_MODEL,
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contents=[f"{question}\n{json_data}"],
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config=types.GenerateContentConfig(
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tools=[types.Tool(code_execution=types.ToolCodeExecution)]
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),
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)
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for part in response.candidates[0].content.parts:
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if part.code_execution_result is not None:
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return part.code_execution_result.output
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except Exception as e:
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raise RuntimeError(f"Processing failed: {str(e)}")
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@CrewBase
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class GAIACrew():
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agents: List[BaseAgent]
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@@ -438,6 +176,268 @@ class GAIACrew():
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verbose=True
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)
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def run_crew(question, file_path):
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final_question = question
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#CrewAIInstrumentor().instrument(tracer_provider=tracer_provider)
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| 51 |
@CrewBase
|
| 52 |
class GAIACrew():
|
| 53 |
agents: List[BaseAgent]
|
|
|
|
| 176 |
verbose=True
|
| 177 |
)
|
| 178 |
|
| 179 |
+
@tool("Web Search Tool")
|
| 180 |
+
def web_search_tool(question: str) -> str:
|
| 181 |
+
"""Given a question only, search the web to answer the question.
|
| 182 |
+
|
| 183 |
+
Args:
|
| 184 |
+
question (str): Question to answer
|
| 185 |
+
|
| 186 |
+
Returns:
|
| 187 |
+
str: Answer to the question
|
| 188 |
+
|
| 189 |
+
Raises:
|
| 190 |
+
RuntimeError: If processing fails"""
|
| 191 |
+
try:
|
| 192 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 193 |
+
|
| 194 |
+
response = client.models.generate_content(
|
| 195 |
+
model=WEB_SEARCH_MODEL,
|
| 196 |
+
contents=question,
|
| 197 |
+
config=types.GenerateContentConfig(
|
| 198 |
+
tools=[types.Tool(google_search=types.GoogleSearchRetrieval())]
|
| 199 |
+
)
|
| 200 |
+
)
|
| 201 |
+
|
| 202 |
+
return response.text
|
| 203 |
+
except Exception as e:
|
| 204 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 205 |
+
|
| 206 |
+
@tool("Image Analysis Tool")
|
| 207 |
+
def image_analysis_tool(question: str, file_path: str) -> str:
|
| 208 |
+
"""Given a question and image file, analyze the image to answer the question.
|
| 209 |
+
|
| 210 |
+
Args:
|
| 211 |
+
question (str): Question about an image file
|
| 212 |
+
file_path (str): The image file path
|
| 213 |
+
|
| 214 |
+
Returns:
|
| 215 |
+
str: Answer to the question about the image file
|
| 216 |
+
|
| 217 |
+
Raises:
|
| 218 |
+
RuntimeError: If processing fails"""
|
| 219 |
+
try:
|
| 220 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 221 |
+
|
| 222 |
+
file = client.files.upload(file=file_path)
|
| 223 |
+
|
| 224 |
+
response = client.models.generate_content(
|
| 225 |
+
model=IMAGE_ANALYSIS_MODEL,
|
| 226 |
+
contents=[file, question]
|
| 227 |
+
)
|
| 228 |
+
|
| 229 |
+
return response.text
|
| 230 |
+
except Exception as e:
|
| 231 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 232 |
+
|
| 233 |
+
@tool("Audio Analysis Tool")
|
| 234 |
+
def audio_analysis_tool(question: str, file_path: str) -> str:
|
| 235 |
+
"""Given a question and audio file, analyze the audio to answer the question.
|
| 236 |
+
|
| 237 |
+
Args:
|
| 238 |
+
question (str): Question about an audio file
|
| 239 |
+
file_path (str): The audio file path
|
| 240 |
+
|
| 241 |
+
Returns:
|
| 242 |
+
str: Answer to the question about the audio file
|
| 243 |
+
|
| 244 |
+
Raises:
|
| 245 |
+
RuntimeError: If processing fails"""
|
| 246 |
+
try:
|
| 247 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 248 |
+
|
| 249 |
+
file = client.files.upload(file=file_path)
|
| 250 |
+
|
| 251 |
+
response = client.models.generate_content(
|
| 252 |
+
model=AUDIO_ANALYSIS_MODEL,
|
| 253 |
+
contents=[file, question]
|
| 254 |
+
)
|
| 255 |
+
|
| 256 |
+
return response.text
|
| 257 |
+
except Exception as e:
|
| 258 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 259 |
+
|
| 260 |
+
@tool("Video Analysis Tool")
|
| 261 |
+
def video_analysis_tool(question: str, file_path: str) -> str:
|
| 262 |
+
"""Given a question and video file, analyze the video to answer the question.
|
| 263 |
+
|
| 264 |
+
Args:
|
| 265 |
+
question (str): Question about a video file
|
| 266 |
+
file_path (str): The video file path
|
| 267 |
+
|
| 268 |
+
Returns:
|
| 269 |
+
str: Answer to the question about the video file
|
| 270 |
+
|
| 271 |
+
Raises:
|
| 272 |
+
RuntimeError: If processing fails"""
|
| 273 |
+
try:
|
| 274 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 275 |
+
|
| 276 |
+
file = client.files.upload(file=file_path)
|
| 277 |
+
|
| 278 |
+
response = client.models.generate_content(
|
| 279 |
+
model=VIDEO_ANALYSIS_MODEL,
|
| 280 |
+
contents=[file, question]
|
| 281 |
+
)
|
| 282 |
+
|
| 283 |
+
return response.text
|
| 284 |
+
except Exception as e:
|
| 285 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 286 |
+
|
| 287 |
+
@tool("YouTube Analysis Tool")
|
| 288 |
+
def youtube_analysis_tool(question: str, url: str) -> str:
|
| 289 |
+
"""Given a question and YouTube URL, analyze the video to answer the question.
|
| 290 |
+
|
| 291 |
+
Args:
|
| 292 |
+
question (str): Question about a YouTube video
|
| 293 |
+
url (str): The YouTube URL
|
| 294 |
+
|
| 295 |
+
Returns:
|
| 296 |
+
str: Answer to the question about the YouTube video
|
| 297 |
+
|
| 298 |
+
Raises:
|
| 299 |
+
RuntimeError: If processing fails"""
|
| 300 |
+
try:
|
| 301 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 302 |
+
|
| 303 |
+
return client.models.generate_content(
|
| 304 |
+
model=YOUTUBE_ANALYSIS_MODEL,
|
| 305 |
+
contents=types.Content(
|
| 306 |
+
parts=[types.Part(file_data=types.FileData(file_uri=url)),
|
| 307 |
+
types.Part(text=question)]
|
| 308 |
+
)
|
| 309 |
+
)
|
| 310 |
+
except Exception as e:
|
| 311 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 312 |
+
|
| 313 |
+
@tool("Document Analysis Tool")
|
| 314 |
+
def document_analysis_tool(question: str, file_path: str) -> str:
|
| 315 |
+
"""Given a question and document file, analyze the document to answer the question.
|
| 316 |
+
|
| 317 |
+
Args:
|
| 318 |
+
question (str): Question about a document file
|
| 319 |
+
file_path (str): The document file path
|
| 320 |
+
|
| 321 |
+
Returns:
|
| 322 |
+
str: Answer to the question about the document file
|
| 323 |
+
|
| 324 |
+
Raises:
|
| 325 |
+
RuntimeError: If processing fails"""
|
| 326 |
+
try:
|
| 327 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 328 |
+
|
| 329 |
+
contents = []
|
| 330 |
+
|
| 331 |
+
if is_ext(file_path, ".docx"):
|
| 332 |
+
text_data = read_docx_text(file_path)
|
| 333 |
+
contents = [f"{question}\n{text_data}"]
|
| 334 |
+
print(f"=> Text data:\n{text_data}")
|
| 335 |
+
elif is_ext(file_path, ".pptx"):
|
| 336 |
+
text_data = read_pptx_text(file_path)
|
| 337 |
+
contents = [f"{question}\n{text_data}"]
|
| 338 |
+
print(f"=> Text data:\n{text_data}")
|
| 339 |
+
else:
|
| 340 |
+
file = client.files.upload(file=file_path)
|
| 341 |
+
contents = [file, question]
|
| 342 |
+
|
| 343 |
+
response = client.models.generate_content(
|
| 344 |
+
model=DOCUMENT_ANALYSIS_MODEL,
|
| 345 |
+
contents=contents
|
| 346 |
+
)
|
| 347 |
+
|
| 348 |
+
return response.text
|
| 349 |
+
except Exception as e:
|
| 350 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 351 |
+
|
| 352 |
+
@tool("Arithmetic Tool")
|
| 353 |
+
def arithmetic_tool(question: str, a: float, b: float) -> float:
|
| 354 |
+
"""Given a question and two numbers, perform the calculation to answer the question.
|
| 355 |
+
|
| 356 |
+
Args:
|
| 357 |
+
question (str): Question to answer
|
| 358 |
+
a (float): First number
|
| 359 |
+
b (float): Second number
|
| 360 |
+
|
| 361 |
+
Returns:
|
| 362 |
+
float: Result number
|
| 363 |
+
|
| 364 |
+
Raises:
|
| 365 |
+
RuntimeError: If processing fails"""
|
| 366 |
+
try:
|
| 367 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 368 |
+
|
| 369 |
+
response = client.models.generate_content(
|
| 370 |
+
model=ARITHMETIC_MODEL,
|
| 371 |
+
contents=question,
|
| 372 |
+
config=types.GenerateContentConfig(
|
| 373 |
+
tools=[add, subtract, multiply, divide, modulus]
|
| 374 |
+
)
|
| 375 |
+
)
|
| 376 |
+
|
| 377 |
+
return response.text
|
| 378 |
+
except Exception as e:
|
| 379 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 380 |
+
|
| 381 |
+
@tool("Code Execution Tool")
|
| 382 |
+
def code_execution_tool(question: str, file_path: str) -> str:
|
| 383 |
+
"""Given a question and Python file, execute the file to answer the question.
|
| 384 |
+
|
| 385 |
+
Args:
|
| 386 |
+
question (str): Question to answer
|
| 387 |
+
file_path (str): The Python file path
|
| 388 |
+
|
| 389 |
+
Returns:
|
| 390 |
+
str: Answer to the question
|
| 391 |
+
|
| 392 |
+
Raises:
|
| 393 |
+
RuntimeError: If processing fails"""
|
| 394 |
+
try:
|
| 395 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 396 |
+
|
| 397 |
+
file = client.files.upload(file=file_path)
|
| 398 |
+
|
| 399 |
+
response = client.models.generate_content(
|
| 400 |
+
model=CODE_EXECUTION_MODEL,
|
| 401 |
+
contents=[file, question],
|
| 402 |
+
config=types.GenerateContentConfig(
|
| 403 |
+
tools=[types.Tool(code_execution=types.ToolCodeExecution)]
|
| 404 |
+
),
|
| 405 |
+
)
|
| 406 |
+
|
| 407 |
+
for part in response.candidates[0].content.parts:
|
| 408 |
+
if part.code_execution_result is not None:
|
| 409 |
+
return part.code_execution_result.output
|
| 410 |
+
except Exception as e:
|
| 411 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 412 |
+
|
| 413 |
+
@tool("Code Generation Tool")
|
| 414 |
+
def code_generation_tool(question: str, json_data: str) -> str:
|
| 415 |
+
"""Given a question and JSON data, generate and execute code to answer the question.
|
| 416 |
+
Args:
|
| 417 |
+
question (str): Question to answer
|
| 418 |
+
file_path (str): The JSON data
|
| 419 |
+
Returns:
|
| 420 |
+
str: Answer to the question
|
| 421 |
+
|
| 422 |
+
Raises:
|
| 423 |
+
RuntimeError: If processing fails"""
|
| 424 |
+
try:
|
| 425 |
+
client = genai.Client(api_key=os.environ["GEMINI_API_KEY"])
|
| 426 |
+
|
| 427 |
+
response = client.models.generate_content(
|
| 428 |
+
model=CODE_GENERATION_MODEL,
|
| 429 |
+
contents=[f"{question}\n{json_data}"],
|
| 430 |
+
config=types.GenerateContentConfig(
|
| 431 |
+
tools=[types.Tool(code_execution=types.ToolCodeExecution)]
|
| 432 |
+
),
|
| 433 |
+
)
|
| 434 |
+
|
| 435 |
+
for part in response.candidates[0].content.parts:
|
| 436 |
+
if part.code_execution_result is not None:
|
| 437 |
+
return part.code_execution_result.output
|
| 438 |
+
except Exception as e:
|
| 439 |
+
raise RuntimeError(f"Processing failed: {str(e)}")
|
| 440 |
+
|
| 441 |
def run_crew(question, file_path):
|
| 442 |
final_question = question
|
| 443 |
|