ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/gaia-experience/AWorld/examples/common/tools/document/__init__.py

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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.

chapter9/gaia-experience/AWorld/examples/common/tools/document/actions.py

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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.
+from examples.common.tools.tool_action import DocumentExecuteAction
+from aworld.core.tool.action_factory import ActionFactory
+from aworld.core.tool.action import ExecutableAction
+
+
+@ActionFactory.register(name=DocumentExecuteAction.DOCUMENT_ANALYSIS.value.name,
+                        desc=DocumentExecuteAction.DOCUMENT_ANALYSIS.value.desc,
+                        tool_name="document_analysis")
+class ExecuteAction(ExecutableAction):
+    """Only one action, define it, implemented can be omitted. Act in tool."""

chapter9/gaia-experience/AWorld/examples/common/tools/document/document.py

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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.
+
+import json
+import os
+import base64
+import tempfile
+import subprocess
+from pathlib import Path
+from typing import Any, Dict, Tuple
+from urllib.parse import urlparse
+
+from pydantic import BaseModel
+
+from aworld.config import ToolConfig
+from examples.common.tools.tool_action import DocumentExecuteAction
+from aworld.core.common import Observation, ActionModel, ActionResult
+from aworld.core.tool.base import ToolFactory, Tool
+from aworld.logs.util import logger
+from examples.common.tools.document.utils import encode_image_from_file, encode_image_from_url
+from aworld.utils import import_package, import_packages
+from aworld.tools.utils import build_observation
+
+
+class InputDocument(BaseModel):
+    document_path: str | None = None
+
+
+@ToolFactory.register(name="document_analysis",
+                      desc="document analysis",
+                      supported_action=DocumentExecuteAction,
+                      conf_file_name=f'document_analysis_tool.yaml',
+                      dir=f"{Path(__file__).parent.absolute()}")
+class DocumentTool(Tool):
+    def __init__(self, conf: ToolConfig, **kwargs) -> None:
+        """Init document tool."""
+        import_package('cv2', install_name='opencv-python')
+        import_packages(['xmltodict', 'pandas', 'docx2markdown', 'PyPDF2', 'numpy'])
+        super(DocumentTool, self).__init__(conf, **kwargs)
+        self.cur_observation = None
+        self.content = None
+        self.keyframes = []
+        self.init()
+        self.step_finished = True
+
+    def reset(self, *, seed: int | None = None, options: Dict[str, str] | None = None) -> Tuple[
+        Observation, dict[str, Any]]:
+        super().reset(seed=seed, options=options)
+
+        self.close()
+        self.step_finished = True
+        return build_observation(observer=self.name(),
+                                 ability=DocumentExecuteAction.DOCUMENT_ANALYSIS.value.name), {}
+
+    def init(self) -> None:
+        self.initialized = True
+
+    def close(self) -> None:
+        pass
+
+    def finished(self) -> bool:
+        return self.step_finished
+
+    def do_step(self, actions: list[ActionModel], **kwargs) -> Tuple[Observation, float, bool, bool, Dict[str, Any]]:
+        self.step_finished = False
+        reward = 0.
+        fail_error = ""
+        observation = build_observation(observer=self.name(),
+                                        ability=DocumentExecuteAction.DOCUMENT_ANALYSIS.value.name)
+        info = {}
+        try:
+            if not actions:
+                raise ValueError("actions is empty")
+            action = actions[0]
+            document_path = action.params.get("document_path", "")
+            if not document_path:
+                raise ValueError("document path invalid")
+            output, keyframes, error = self.document_analysis(document_path)
+            observation.content = output
+            observation.action_result.append(
+                ActionResult(is_done=True,
+                             success=False if error else True,
+                             content=f"{output}",
+                             error=f"{error}",
+                             keep=False))
+            info['key_frame'] = f"{keyframes}"
+            reward = 1.
+        except Exception as e:
+            fail_error = str(e)
+        finally:
+            self.step_finished = True
+        info["exception"] = fail_error
+        info.update(kwargs)
+        return (observation, reward, kwargs.get("terminated", False),
+                kwargs.get("truncated", False), info)
+
+    def document_analysis(self, document_path):
+        import xmltodict
+        error = None
+        # Initialize content to empty list to avoid None return
+        self.content = []
+        try:
+            if any(document_path.endswith(ext) for ext in [".jpg", ".jpeg", ".png"]):
+                parsed_url = urlparse(document_path)
+                is_url = all([parsed_url.scheme, parsed_url.netloc])
+                if not is_url:
+                    base64_image = encode_image_from_file(document_path)
+                else:
+                    base64_image = encode_image_from_url(document_path)
+                self.content = f"data:image/jpeg;base64,{base64_image}"
+
+            if any(document_path.endswith(ext) for ext in ["xls", "xlsx"]):
+                try:
+                    try:
+                        import pandas as pd
+                    except ImportError:
+                        error = "pandas library not found. Please install pandas: pip install pandas"
+                        return self.content, self.keyframes, error
+
+                    excel_data = {}
+
+                    with pd.ExcelFile(document_path) as xls:
+                        sheet_names = xls.sheet_names
+                        for sheet_name in sheet_names:
+                            df = pd.read_excel(xls, sheet_name=sheet_name)
+                            sheet_data = df.to_dict(orient='records')
+                            excel_data[sheet_name] = sheet_data
+
+                    self.content = json.dumps(excel_data, ensure_ascii=False)
+                    logger.info(f"Successfully processed Excel file: {document_path}")
+                    logger.info(f"Found {len(sheet_names)} sheets: {', '.join(sheet_names)}")
+
+                except Exception as excel_error:
+                    error = str(excel_error)
+
+            if any(document_path.endswith(ext) for ext in ["json", "jsonl", "jsonld"]):
+                with open(document_path, "r", encoding="utf-8") as f:
+                    self.content = json.load(f)
+                f.close()
+
+            if any(document_path.endswith(ext) for ext in ["xml"]):
+                data = None
+                with open(document_path, "r", encoding="utf-8") as f:
+                    data = f.read()
+                f.close()
+
+                try:
+                    self.content = xmltodict.parse(data)
+                    logger.info(f"The extracted xml data is: {self.content}")
+
+                except Exception as e:
+                    logger.info(f"The raw xml data is: {data}")
+                    error = str(e)
+                    self.content = data
+
+            if any(document_path.endswith(ext) for ext in ["doc", "docx"]):
+                from docx2markdown._docx_to_markdown import docx_to_markdown
+                file_name = os.path.basename(document_path)
+                md_file_path = f"{file_name}.md"
+                docx_to_markdown(document_path, md_file_path)
+                with open(md_file_path, "r") as f:
+                    self.content = f.read()
+                f.close()
+
+            if any(document_path.endswith(ext) for ext in ["pdf"]):
+                # try using pypdf to extract text from pdf
+                try:
+                    from PyPDF2 import PdfReader
+
+                    # Open file in binary mode for PdfReader
+                    f = open(document_path, "rb")
+                    reader = PdfReader(f)
+                    extracted_text = ""
+                    for page in reader.pages:
+                        extracted_text += page.extract_text()
+                    self.content = extracted_text
+                    f.close()
+                except Exception as pdf_error:
+                    error = str(pdf_error)
+
+            # audio
+            if any(document_path.endswith(ext.lower()) for ext in [".mp3", ".wav", ".wave"]):
+                try:
+                    # audio-> base64
+                    with open(document_path, "rb") as audio_file:
+                        audio_bytes = audio_file.read()
+                        audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
+
+                    # ext
+                    ext = os.path.splitext(document_path)[1].lower()
+                    mime_type = "audio/mpeg" if ext == ".mp3" else "audio/wav"
+
+                    # data URI
+                    self.content = f"data:{mime_type};base64,{audio_base64}"
+                except Exception as audio_error:
+                    error = str(audio_error)
+                    logger.error(f"Error processing audio file: {error}")
+
+            # video
+            if any(document_path.endswith(ext.lower()) for ext in [".mp4", ".avi", ".mov", ".mkv", ".flv", ".wmv"]):
+                try:
+                    try:
+                        import cv2
+                        import numpy as np
+                    except ImportError:
+                        error = "Required libraries not found. Please install opencv-python: pip install opencv-python"
+                        return None, None, error
+
+                    # create temp dir
+                    temp_dir = tempfile.mkdtemp()
+
+                    # 1.get audio -> base64
+                    audio_path = os.path.join(temp_dir, "extracted_audio.mp3")
+
+                    #  get audio by ffmpeg
+                    try:
+                        subprocess.run([
+                            "ffmpeg", "-i", document_path, "-q:a", "0",
+                            "-map", "a", audio_path, "-y"
+                        ], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+
+                        # audio->base64
+                        with open(audio_path, "rb") as audio_file:
+                            audio_bytes = audio_file.read()
+                            audio_base64 = base64.b64encode(audio_bytes).decode('utf-8')
+
+                        audio_data_uri = f"data:audio/mpeg;base64,{audio_base64}"
+                    except (subprocess.SubprocessError, FileNotFoundError) as e:
+                        logger.warning(f"Failed to extract audio: {str(e)}")
+                        audio_data_uri = None
+
+                    # 2. get keyframes
+                    cap = cv2.VideoCapture(document_path)
+
+                    if not cap.isOpened():
+                        raise ValueError(f"Could not open video file: {document_path}")
+
+                    # get video message
+                    fps = cap.get(cv2.CAP_PROP_FPS)
+                    frame_count = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
+                    duration = frame_count / fps if fps > 0 else 0
+
+                    # keyframes policy- per duration/10s，max 10
+                    keyframes_count = min(10, int(frame_count))
+                    frames_interval = max(1, int(frame_count / keyframes_count))
+
+                    self.keyframes = []
+                    frame_index = 0
+
+                    while True:
+                        ret, frame = cap.read()
+                        if not ret:
+                            break
+
+                        # per frames_interval save
+                        if frame_index % frames_interval == 0:
+                            # save JPEG -> base64
+                            _, buffer = cv2.imencode(".jpg", frame)
+                            img_base64 = base64.b64encode(buffer).decode('utf-8')
+                            time_position = frame_index / fps if fps > 0 else 0
+
+                            self.keyframes.append(f"data:image/jpeg;base64,{img_base64}")
+
+                            if len(self.keyframes) >= keyframes_count:
+                                break
+
+                        frame_index += 1
+
+                    cap.release()
+
+                    self.content = audio_data_uri
+                    logger.info(f"Successfully processed video file: {document_path}")
+                    logger.info(f"Extracted {len(self.keyframes)} keyframes and audio track")
+                    # clean tmp files
+                    try:
+                        os.remove(audio_path)
+                        os.rmdir(temp_dir)
+                    except Exception as cleanup_error:
+                        logger.warning(f"Error cleaning up temp files: {str(cleanup_error)}")
+
+                except Exception as video_error:
+                    error = str(video_error)
+                    logger.error(f"Error processing video file: {error}")
+
+            if any(document_path.endswith(ext) for ext in ["pptx"]):
+                try:
+                    # Initialize content list and empty keyframes
+                    self.content = []
+                    self.keyframes = []
+
+                    # Check if file exists
+                    if not os.path.exists(document_path):
+                        error = f"File does not exist: {document_path}"
+                        return self.content, self.keyframes, error
+
+                    # Check if file is readable
+                    if not os.access(document_path, os.R_OK):
+                        error = f"File is not readable: {document_path}"
+                        return self.content, self.keyframes, error
+
+                    # Check file size
+                    try:
+                        file_size = os.path.getsize(document_path)
+
+                        if file_size == 0:
+                            error = "File is empty"
+                            return self.content, self.keyframes, error
+                    except Exception as size_error:
+                        logger.warning(f"Cannot get file size: {str(size_error)}")
+
+                    try:
+                        # Import required libraries
+                        from pptx import Presentation
+                        from PIL import Image, ImageDraw, ImageFont
+                        import io
+                    except ImportError as import_error:
+                        error = f"Missing required libraries: {str(import_error)}. Please install: pip install python-pptx Pillow"
+                        return self.content, self.keyframes, error
+
+                    # Create temporary directory for images
+                    try:
+                        temp_dir = tempfile.mkdtemp()
+                    except Exception as temp_dir_error:
+                        error = f"Failed to create temporary directory: {str(temp_dir_error)}"
+                        return self.content, self.keyframes, error
+
+                    # Open presentation
+                    try:
+                        presentation = Presentation(document_path)
+                        # Get total slides count
+                        total_slides = len(presentation.slides)
+
+                        if total_slides == 0:
+                            error = "PPTX file does not contain any slides"
+                            return self.content, self.keyframes, error
+
+                        # Process each slide
+                        for i, slide in enumerate(presentation.slides):
+
+                            # Generate temporary file path for current slide
+                            img_path = os.path.join(temp_dir, f"slide_{i + 1}.jpg")
+
+                            # Get slide dimensions
+                            try:
+                                slide_width = presentation.slide_width
+                                slide_height = presentation.slide_height
+
+                                # PPTX dimensions are in EMU (English Metric Unit)
+                                # 1 inch = 914400 EMU, 1 cm = 360000 EMU
+                                # Convert to pixels (assuming 96 DPI)
+                                slide_width_px = int(slide_width / 914400 * 96 * 10)
+                                slide_height_px = int(slide_height / 914400 * 96 * 10)
+
+                                # Ensure dimensions are reasonable positive integers
+                                slide_width_px = max(1, min(slide_width_px, 4000))  # Limit max width to 4000px
+                                slide_height_px = max(1, min(slide_height_px, 3000))  # Limit max height to 3000px
+
+                            except Exception as size_error:
+                                # Use default dimensions
+                                slide_width_px = 960  # Default width 960px
+                                slide_height_px = 720  # Default height 720px
+
+                            # Create blank image
+                            try:
+                                # Log operation start
+
+                                # Create blank image
+                                try:
+                                    slide_img = Image.new('RGB', (slide_width_px, slide_height_px), 'white')
+                                    draw = ImageDraw.Draw(slide_img)
+                                except Exception as img_create_error:
+                                    logger.error(
+                                        f"Slide {i + 1} blank image creation failed: {str(img_create_error) or 'Unknown error'}")
+                                    raise
+
+                                # Draw slide number
+                                try:
+                                    font = ImageFont.load_default()
+                                    draw.text((20, 20), f"Slide {i + 1}/{total_slides}", fill="black", font=font)
+                                except Exception as font_error:
+                                    logger.warning(f"Failed to draw slide number: {str(font_error) or 'Unknown error'}")
+
+                                # Record shape count
+                                try:
+                                    shape_count = len(slide.shapes)
+                                except Exception as shape_count_error:
+                                    logger.warning(
+                                        f"Failed to get slide {i + 1} shape count: {str(shape_count_error) or 'Unknown error'}")
+                                    shape_count = 0
+
+                                # Try to render shapes on image
+                                shape_success_count = 0
+                                shape_fail_count = 0
+
+                                try:
+                                    for j, shape in enumerate(slide.shapes):
+                                        try:
+                                            shape_type = type(shape).__name__
+
+                                            # Process images
+                                            if hasattr(shape, 'image') and shape.image:
+                                                try:
+                                                    # Extract image from shape
+                                                    image_stream = io.BytesIO(shape.image.blob)
+                                                    img = Image.open(image_stream)
+
+                                                    # Calculate position
+                                                    left = shape.left
+                                                    top = shape.top
+
+                                                    # Paste image onto slide
+                                                    slide_img.paste(img, (left, top))
+                                                    shape_success_count += 1
+                                                except Exception as img_error:
+                                                    logger.warning(
+                                                        f"Failed to process image {j + 1} in slide {i + 1}: {str(img_error) or 'Unknown error'}")
+                                                    if not str(img_error):
+                                                        import traceback
+                                                        logger.warning(
+                                                            f"Image processing stack: {traceback.format_exc()}")
+                                                    shape_fail_count += 1
+
+                                            # Process text
+                                            elif hasattr(shape, 'text') and shape.text:
+                                                try:
+                                                    text = shape.text[:30] + "..." if len(
+                                                        shape.text) > 30 else shape.text
+                                                    # Simple text rendering
+                                                    text_left = shape.left
+                                                    text_top = shape.top
+                                                    draw.text((text_left, text_top), shape.text, fill="black",
+                                                              font=font)
+                                                    shape_success_count += 1
+                                                except Exception as text_error:
+                                                    logger.warning(
+                                                        f"Failed to process text {j + 1} in slide {i + 1}: {str(text_error) or 'Unknown error'}")
+                                                    if not str(text_error):
+                                                        import traceback
+                                                        logger.warning(
+                                                            f"Text processing stack: {traceback.format_exc()}")
+                                                    shape_fail_count += 1
+                                            else:
+                                                logger.info(
+                                                    f"Shape {j + 1} in slide {i + 1} is neither image nor text, skipping")
+                                        except Exception as shape_error:
+                                            if not str(shape_error):
+                                                import traceback
+                                                logger.warning(f"Shape processing stack: {traceback.format_exc()}")
+                                            shape_fail_count += 1
+                                except Exception as shapes_iteration_error:
+                                    logger.error(
+                                        f"Failed while iterating through shapes in slide {i + 1}: {str(shapes_iteration_error) or 'Unknown error'}")
+                                    if not str(shapes_iteration_error):
+                                        import traceback
+                                        logger.error(f"Shape iteration stack: {traceback.format_exc()}")
+
+                                # Save slide image
+                                try:
+                                    slide_img.save(img_path, 'JPEG')
+
+                                    # Check if image was saved successfully
+                                    if not os.path.exists(img_path):
+                                        raise ValueError(f"Saved image file does not exist: {img_path}")
+
+                                    file_size = os.path.getsize(img_path)
+                                    if file_size == 0:
+                                        raise ValueError(
+                                            f"Saved image file is empty: {img_path}, size: {file_size} bytes")
+
+                                    # Convert to base64
+                                    try:
+                                        base64_image = encode_image_from_file(img_path)
+                                        self.content.append(f"data:image/jpeg;base64,{base64_image}")
+                                    except Exception as base64_error:
+                                        error_msg = str(base64_error) or "Unknown base64 conversion error"
+                                        if not str(base64_error):
+                                            import traceback
+                                            logger.error(f"Base64 conversion stack: {traceback.format_exc()}")
+                                        raise ValueError(f"Base64 conversion error: {error_msg}")
+
+                                except Exception as save_error:
+                                    error_msg = str(save_error) or "Unknown save error"
+                                    logger.error(f"Failed to save slide {i + 1} as image: {error_msg}")
+                                    if not str(save_error):
+                                        import traceback
+                                        logger.error(f"Image save stack: {traceback.format_exc()}")
+                                    raise ValueError(f"Image save error: {error_msg}")
+
+                            except Exception as slide_render_error:
+                                error_msg = str(slide_render_error) or "Unknown rendering error"
+                                logger.error(f"Failed to render slide {i + 1}: {error_msg}")
+                                if not str(slide_render_error):
+                                    import traceback
+                                    logger.error(f"Slide rendering stack: {traceback.format_exc()}")
+                                # Continue processing next slide, don't interrupt the entire process
+                                continue
+
+                    except Exception as pptx_error:
+                        error = f"Failed to process PPTX file: {str(pptx_error)}"
+                        import traceback
+
+                    # Clean up temporary files
+                    try:
+                        for file in os.listdir(temp_dir):
+                            try:
+                                file_path = os.path.join(temp_dir, file)
+                                os.remove(file_path)
+                            except Exception as file_error:
+                                logger.warning(f"Failed to delete temporary file: {str(file_error)}")
+                        os.rmdir(temp_dir)
+                    except Exception as cleanup_error:
+                        logger.warning(f"Failed to clean up temporary files: {str(cleanup_error)}")
+
+                    if len(self.content) > 0:
+                        logger.info(f"Extracted {len(self.content)} slides")
+                    else:
+                        error = error or "Could not extract any slides from PPTX file"
+                        logger.error(error)
+
+                except Exception as outer_error:
+                    error = f"Error occurred during PPTX file processing: {str(outer_error)}"
+                    import traceback
+
+                return self.content, self.keyframes, error
+
+        finally:
+            pass
+
+        return self.content, self.keyframes, error

chapter9/gaia-experience/AWorld/examples/common/tools/document/document_analysis_tool.yaml

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+custom_executor: False
+enable_recording: False
+working_dir:
+max_retry: 3

chapter9/gaia-experience/AWorld/examples/common/tools/document/utils.py

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+# coding: utf-8
+# Copyright (c) 2025 inclusionAI.
+import base64
+from io import BytesIO
+
+
+def encode_image_from_url(image_url):
+    from aworld.utils.import_package import import_package
+    import_package("requests")
+
+    import requests
+    from PIL import Image
+
+    response = requests.get(image_url)
+    image = Image.open(BytesIO(response.content))
+
+    max_size = 1024
+    if max(image.size) > max_size:
+        ratio = max_size / max(image.size)
+        new_size = (int(image.size[0] * ratio), int(image.size[1] * ratio))
+        image = image.resize(new_size, Image.LANCZOS)
+
+    buffered = BytesIO()
+    image_format = image.format if image.format else 'JPEG'
+    image.save(buffered, format=image_format)
+    img_str = base64.b64encode(buffered.getvalue()).decode()
+    return img_str
+
+
+def encode_image_from_file(image_path):
+    with open(image_path, "rb") as image_file:
+        return base64.b64encode(image_file.read()).decode()