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| #!/usr/bin/env python | |
| # coding=utf-8 | |
| from typing import Optional | |
| from smolagents import Tool | |
| from smolagents.models import MessageRole, Model | |
| from .mdconvert import MarkdownConverter | |
| class TextInspectorTool(Tool): | |
| """ | |
| Tool for converting various file types to text and answering questions about their contents. | |
| Supported file types include: | |
| - Text documents (.txt, .md) | |
| - Web documents (.html, .htm) | |
| - Office documents (.docx, .xlsx, .pptx) | |
| - Audio files (.wav, .mp3, .flac) | |
| - PDF documents (.pdf) | |
| Images are not supported and should be processed with a visualizer tool instead. | |
| """ | |
| name = "view_file" | |
| description = """ | |
| You cannot load files yourself: instead call this tool to read a file as markdown text and ask questions about it. | |
| This tool handles the following file extensions: [".html", ".htm", ".md", ".txt", ".xlsx", ".pptx", ".wav", ".mp3", ".flac", ".pdf", ".docx"], and all other types of text files. IT DOES NOT HANDLE IMAGES. | |
| """ | |
| inputs = { | |
| "file_path": { | |
| "description": "The path to the file you want to read as text. Must be a '.something' file, like '.pdf'. If it is an image, use the visualizer tool instead! DO NOT use this tool for an HTML webpage: use the web_search tool instead!", | |
| "type": "string", | |
| }, | |
| "question": { | |
| "description": "[Optional]: Your question, as a natural language sentence. Provide as much context as possible. Do not pass this parameter if you just want to directly return the content of the file.", | |
| "type": "string", | |
| "nullable": True, | |
| }, | |
| } | |
| output_type = "string" | |
| md_converter = MarkdownConverter() | |
| def __init__(self, model: Model, text_limit: int): | |
| """ | |
| Initialize the TextInspectorTool with a model to use for generating text and a limit for the amount of text to generate. | |
| """ | |
| super().__init__() | |
| self.model = model | |
| self.text_limit = text_limit | |
| def forward_initial_exam_mode(self, file_path, question): | |
| """ | |
| This is used for generating code for the initial exam, and is not used for the final exam. | |
| """ | |
| result = self.md_converter.convert(file_path) | |
| if file_path[-4:] in [".png", ".jpg", ".webp"]: | |
| raise Exception( | |
| "Cannot use inspect_file_as_text tool with images: use visualizer instead!" | |
| ) | |
| if ".zip" in file_path: | |
| return result.text_content | |
| if not question: | |
| return result.text_content | |
| if len(result.text_content) < 4000: | |
| return "Document content: " + result.text_content | |
| messages = [ | |
| { | |
| "role": MessageRole.SYSTEM, | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Here is a file:\n### " | |
| + str(result.title) | |
| + "\n\n" | |
| + result.text_content[: self.text_limit], | |
| } | |
| ], | |
| }, | |
| { | |
| "role": MessageRole.USER, | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now please write a short, 5 sentence caption for this document, that could help someone asking this question: " | |
| + question | |
| + "\n\nDon't answer the question yourself! Just provide useful notes on the document", | |
| } | |
| ], | |
| }, | |
| ] | |
| return self.model(messages).content | |
| def forward(self, file_path: str, question: Optional[str] = None) -> str: | |
| """ | |
| Process a file and optionally answer a question about its contents. | |
| Args: | |
| file_path: Path to the file to be processed. Must be a supported file type. | |
| question: Optional question to answer about the file contents. | |
| If None, returns the raw file content. | |
| Returns: | |
| Either the raw file content if no question is provided, or the model's | |
| response to the question based on the file contents. | |
| Raises: | |
| Exception: If the file is an image file or has an unsupported format. | |
| """ | |
| result = self.md_converter.convert(file_path) | |
| if file_path[-4:] in [".png", ".jpg"]: | |
| raise Exception( | |
| "Cannot use inspect_file_as_text tool with images: use visualizer instead!" | |
| ) | |
| if ".zip" in file_path: | |
| return result.text_content | |
| if not question: | |
| return result.text_content | |
| messages = [ | |
| { | |
| "role": MessageRole.SYSTEM, | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "You will have to write a short caption for this file, then answer this question:" | |
| + question, | |
| } | |
| ], | |
| }, | |
| { | |
| "role": MessageRole.USER, | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Here is the complete file:\n### " | |
| + str(result.title) | |
| + "\n\n" | |
| + result.text_content[: self.text_limit], | |
| } | |
| ], | |
| }, | |
| { | |
| "role": MessageRole.USER, | |
| "content": [ | |
| { | |
| "type": "text", | |
| "text": "Now answer the question below. Use these three headings: '1. Short answer', '2. Extremely detailed answer', '3. Additional Context on the document and question asked'." | |
| + question, | |
| } | |
| ], | |
| }, | |
| ] | |
| return self.model(messages).content | |
| __all__ = ["TextInspectorTool"] | |