From 423b22214a849bd392b0180ec8970f663ab75c45 Mon Sep 17 00:00:00 2001 From: Zamil Majdy Date: Wed, 16 Jul 2025 20:00:40 +0800 Subject: [PATCH] feat(blocks): Add Excel support to ReadSpreadsheetBlock and introduced FileReadBlock (#10393) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit This PR adds Excel file support to CSV processing and enhances text file reading capabilities. ### Changes 🏗️ **ReadSpreadsheetBlock (formerly ReadCsvBlock):** - Renamed `ReadCsvBlock` to `ReadSpreadsheetBlock` for better clarity - Added Excel file support (.xlsx, .xls) with automatic conversion to CSV using pandas - Enhanced parameter `file_in` to `file_input` for consistency - Excel files are automatically detected by extension and converted to CSV format - Maintains all existing CSV processing functionality (delimiters, headers, etc.) - Graceful error handling when pandas library is not available **FileReadBlock:** - Enhanced text file reading with advanced chunking capabilities - Added parameters: `skip_size`, `skip_rows`, `row_limit`, `size_limit`, `delimiter` - Supports both character-based and row-based processing - Chunked output for large files based on size limits - Proper file handling with UTF-8 and latin-1 encoding fallbacks - Uses `store_media_file` for secure file processing (URLs, data URIs, local paths) - Fixed test input to use data URI instead of non-existent file **General Improvements:** - Consistent parameter naming across blocks (`file_input`) - Enhanced error handling and validation - Comprehensive test coverage - All existing functionality preserved ### Checklist 📋 #### For code changes: - [x] I have clearly listed my changes in the PR description - [x] I have made a test plan - [x] I have tested my changes according to the test plan: - [x] Both ReadSpreadsheetBlock and FileReadBlock instantiate correctly - [x] ReadSpreadsheetBlock processes CSV data with existing functionality - [x] FileReadBlock reads text files with data URI input - [x] All block tests pass (457 passed, 83 skipped) - [x] No linting errors in modified files - [x] Excel support gracefully handles missing pandas dependency #### For configuration changes: - [ ] `.env.example` is updated or already compatible with my changes - [ ] `docker-compose.yml` is updated or already compatible with my changes - [ ] I have included a list of my configuration changes in the PR description (under **Changes**) *Note: No configuration changes required for this PR.* --- .../backend/backend/blocks/csv.py | 97 +++++++++--- .../backend/backend/blocks/text.py | 140 ++++++++++++++++++ autogpt_platform/backend/poetry.lock | 96 +++++++++++- autogpt_platform/backend/pyproject.toml | 1 + .../backend/test/blocks/test_gmail.py | 2 - autogpt_platform/docker-compose.platform.yml | 2 + 6 files changed, 310 insertions(+), 28 deletions(-) diff --git a/autogpt_platform/backend/backend/blocks/csv.py b/autogpt_platform/backend/backend/blocks/csv.py index f69eeff4a9..f73c53469a 100644 --- a/autogpt_platform/backend/backend/blocks/csv.py +++ b/autogpt_platform/backend/backend/blocks/csv.py @@ -1,15 +1,24 @@ +from pathlib import Path + from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema from backend.data.model import ContributorDetails, SchemaField +from backend.util.file import get_exec_file_path, store_media_file +from backend.util.type import MediaFileType -class ReadCsvBlock(Block): +class ReadSpreadsheetBlock(Block): class Input(BlockSchema): - contents: str = SchemaField( - description="The contents of the CSV file to read", + contents: str | None = SchemaField( + description="The contents of the CSV/spreadsheet data to read", placeholder="a, b, c\n1,2,3\n4,5,6", + default=None, + ) + file_input: MediaFileType | None = SchemaField( + description="CSV or Excel file to read from (URL, data URI, or local path). Excel files are automatically converted to CSV", + default=None, ) delimiter: str = SchemaField( - description="The delimiter used in the CSV file", + description="The delimiter used in the CSV/spreadsheet data", default=",", ) quotechar: str = SchemaField( @@ -39,41 +48,89 @@ class ReadCsvBlock(Block): class Output(BlockSchema): row: dict[str, str] = SchemaField( - description="The data produced from each row in the CSV file" + description="The data produced from each row in the spreadsheet" ) - all_data: list[dict[str, str]] = SchemaField( - description="All the data in the CSV file as a list of rows" + rows: list[dict[str, str]] = SchemaField( + description="All the data in the spreadsheet as a list of rows" ) def __init__(self): super().__init__( id="acf7625e-d2cb-4941-bfeb-2819fc6fc015", - input_schema=ReadCsvBlock.Input, - output_schema=ReadCsvBlock.Output, - description="Reads a CSV file and outputs the data as a list of dictionaries and individual rows via rows.", + input_schema=ReadSpreadsheetBlock.Input, + output_schema=ReadSpreadsheetBlock.Output, + description="Reads CSV and Excel files and outputs the data as a list of dictionaries and individual rows. Excel files are automatically converted to CSV format.", contributors=[ContributorDetails(name="Nicholas Tindle")], categories={BlockCategory.TEXT, BlockCategory.DATA}, test_input={ "contents": "a, b, c\n1,2,3\n4,5,6", }, test_output=[ - ("row", {"a": "1", "b": "2", "c": "3"}), - ("row", {"a": "4", "b": "5", "c": "6"}), ( - "all_data", + "rows", [ {"a": "1", "b": "2", "c": "3"}, {"a": "4", "b": "5", "c": "6"}, ], ), + ("row", {"a": "1", "b": "2", "c": "3"}), + ("row", {"a": "4", "b": "5", "c": "6"}), ], ) - async def run(self, input_data: Input, **kwargs) -> BlockOutput: + async def run( + self, input_data: Input, *, graph_exec_id: str, **_kwargs + ) -> BlockOutput: import csv from io import StringIO - csv_file = StringIO(input_data.contents) + # Determine data source - prefer file_input if provided, otherwise use contents + if input_data.file_input: + stored_file_path = await store_media_file( + graph_exec_id=graph_exec_id, + file=input_data.file_input, + return_content=False, + ) + + # Get full file path + file_path = get_exec_file_path(graph_exec_id, stored_file_path) + if not Path(file_path).exists(): + raise ValueError(f"File does not exist: {file_path}") + + # Check if file is an Excel file and convert to CSV + file_extension = Path(file_path).suffix.lower() + + if file_extension in [".xlsx", ".xls"]: + # Handle Excel files + try: + from io import StringIO + + import pandas as pd + + # Read Excel file + df = pd.read_excel(file_path) + + # Convert to CSV string + csv_buffer = StringIO() + df.to_csv(csv_buffer, index=False) + csv_content = csv_buffer.getvalue() + + except ImportError: + raise ValueError( + "pandas library is required to read Excel files. Please install it." + ) + except Exception as e: + raise ValueError(f"Unable to read Excel file: {e}") + else: + # Handle CSV/text files + csv_content = Path(file_path).read_text(encoding="utf-8") + elif input_data.contents: + # Use direct string content + csv_content = input_data.contents + else: + raise ValueError("Either 'contents' or 'file_input' must be provided") + + csv_file = StringIO(csv_content) reader = csv.reader( csv_file, delimiter=input_data.delimiter, @@ -100,10 +157,8 @@ class ReadCsvBlock(Block): data[str(i)] = value.strip() if input_data.strip else value return data - all_data = [] - for row in reader: - processed_row = process_row(row) - all_data.append(processed_row) - yield "row", processed_row + rows = [process_row(row) for row in reader] - yield "all_data", all_data + yield "rows", rows + for processed_row in rows: + yield "row", processed_row diff --git a/autogpt_platform/backend/backend/blocks/text.py b/autogpt_platform/backend/backend/blocks/text.py index f4357a468c..2545facfa4 100644 --- a/autogpt_platform/backend/backend/blocks/text.py +++ b/autogpt_platform/backend/backend/blocks/text.py @@ -1,9 +1,12 @@ import re +from pathlib import Path from typing import Any from backend.data.block import Block, BlockCategory, BlockOutput, BlockSchema from backend.data.model import SchemaField from backend.util import json, text +from backend.util.file import get_exec_file_path, store_media_file +from backend.util.type import MediaFileType formatter = text.TextFormatter() @@ -303,3 +306,140 @@ class TextReplaceBlock(Block): async def run(self, input_data: Input, **kwargs) -> BlockOutput: yield "output", input_data.text.replace(input_data.old, input_data.new) + + +class FileReadBlock(Block): + class Input(BlockSchema): + file_input: MediaFileType = SchemaField( + description="The file to read from (URL, data URI, or local path)" + ) + delimiter: str = SchemaField( + description="Delimiter to split the content into rows/chunks (e.g., '\\n' for lines)", + default="", + advanced=True, + ) + size_limit: int = SchemaField( + description="Maximum size in bytes per chunk to yield (0 for no limit)", + default=0, + advanced=True, + ) + row_limit: int = SchemaField( + description="Maximum number of rows to process (0 for no limit, requires delimiter)", + default=0, + advanced=True, + ) + skip_size: int = SchemaField( + description="Number of characters to skip from the beginning of the file", + default=0, + advanced=True, + ) + skip_rows: int = SchemaField( + description="Number of rows to skip from the beginning (requires delimiter)", + default=0, + advanced=True, + ) + + class Output(BlockSchema): + content: str = SchemaField( + description="The full content of the file or a chunk based on delimiter/limits" + ) + chunk: str = SchemaField(description="Individual chunks when delimiter is used") + + def __init__(self): + super().__init__( + id="3735a31f-7e18-4aca-9e90-08a7120674bc", + input_schema=FileReadBlock.Input, + output_schema=FileReadBlock.Output, + description="Reads a file and returns its content as a string, with optional chunking by delimiter and size limits", + categories={BlockCategory.TEXT, BlockCategory.DATA}, + test_input={ + "file_input": "data:text/plain;base64,SGVsbG8gV29ybGQ=", + }, + test_output=[ + ("content", "Hello World"), + ], + ) + + async def run( + self, input_data: Input, *, graph_exec_id: str, **_kwargs + ) -> BlockOutput: + # Store the media file properly (handles URLs, data URIs, etc.) + stored_file_path = await store_media_file( + graph_exec_id=graph_exec_id, + file=input_data.file_input, + return_content=False, + ) + + # Get full file path + file_path = get_exec_file_path(graph_exec_id, stored_file_path) + + if not Path(file_path).exists(): + raise ValueError(f"File does not exist: {file_path}") + + # Read file content + try: + with open(file_path, "r", encoding="utf-8") as file: + content = file.read() + except UnicodeDecodeError: + # Try with different encodings + try: + with open(file_path, "r", encoding="latin-1") as file: + content = file.read() + except Exception as e: + raise ValueError(f"Unable to read file: {e}") + + # Apply skip_size (character-level skip) + if input_data.skip_size > 0: + content = content[input_data.skip_size :] + + # Split content into items (by delimiter or treat as single item) + items = ( + content.split(input_data.delimiter) if input_data.delimiter else [content] + ) + + # Apply skip_rows (item-level skip) + if input_data.skip_rows > 0: + items = items[input_data.skip_rows :] + + # Apply row_limit (item-level limit) + if input_data.row_limit > 0: + items = items[: input_data.row_limit] + + # Process each item and create chunks + def create_chunks(text, size_limit): + """Create chunks from text based on size_limit""" + if size_limit <= 0: + return [text] if text else [] + + chunks = [] + for i in range(0, len(text), size_limit): + chunk = text[i : i + size_limit] + if chunk: # Only add non-empty chunks + chunks.append(chunk) + return chunks + + # Process items and yield chunks + all_chunks = [] + for item in items: + if item: # Only process non-empty items + chunks = create_chunks(item, input_data.size_limit) + # Only yield as 'chunk' if we have a delimiter (multiple items) + if input_data.delimiter: + for chunk in chunks: + yield "chunk", chunk + all_chunks.extend(chunks) + + # Yield the processed content + if all_chunks: + full_content = ( + input_data.delimiter.join(items) + if input_data.delimiter + else "".join(items) + ) + + # Create chunks of the full content based on size_limit + content_chunks = create_chunks(full_content, input_data.size_limit) + for chunk in content_chunks: + yield "content", chunk + else: + yield "content", "" diff --git a/autogpt_platform/backend/poetry.lock b/autogpt_platform/backend/poetry.lock index 3129bfbd5f..a5ba8dbd05 100644 --- a/autogpt_platform/backend/poetry.lock +++ b/autogpt_platform/backend/poetry.lock @@ -1338,12 +1338,12 @@ files = [ 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"platform_system == \"Windows\"" files = [ {file = "tzdata-2025.2-py2.py3-none-any.whl", hash = "sha256:1a403fada01ff9221ca8044d701868fa132215d84beb92242d9acd2147f667a8"}, {file = "tzdata-2025.2.tar.gz", hash = "sha256:b60a638fcc0daffadf82fe0f57e53d06bdec2f36c4df66280ae79bce6bd6f2b9"}, @@ -6440,4 +6526,4 @@ cffi = ["cffi (>=1.11)"] [metadata] lock-version = "2.1" python-versions = ">=3.10,<3.13" -content-hash = "0f3dfd7fdfb50ffd9b9a046cce0be1b9f290d4e6055ff13c2fbda4faa610ba34" +content-hash = "a14329787353666e157a15352b3905782388566920e5825c9febb831123f0faf" diff --git a/autogpt_platform/backend/pyproject.toml b/autogpt_platform/backend/pyproject.toml index 80603c2c3f..bf4fc4ae3d 100644 --- a/autogpt_platform/backend/pyproject.toml +++ b/autogpt_platform/backend/pyproject.toml @@ -72,6 +72,7 @@ aiofiles = "^24.1.0" tiktoken = "^0.9.0" aioclamd = "^1.0.0" setuptools = "^80.9.0" +pandas = "^2.3.1" [tool.poetry.group.dev.dependencies] aiohappyeyeballs = "^2.6.1" diff --git a/autogpt_platform/backend/test/blocks/test_gmail.py b/autogpt_platform/backend/test/blocks/test_gmail.py index 38d6f8d8b1..6be1c914d4 100644 --- a/autogpt_platform/backend/test/blocks/test_gmail.py +++ b/autogpt_platform/backend/test/blocks/test_gmail.py @@ -1,8 +1,6 @@ import base64 from unittest.mock import Mock, patch -import pytest - from backend.blocks.google.gmail import GmailReadBlock diff --git a/autogpt_platform/docker-compose.platform.yml b/autogpt_platform/docker-compose.platform.yml index ca9a483b40..474c95fcb5 100644 --- a/autogpt_platform/docker-compose.platform.yml +++ b/autogpt_platform/docker-compose.platform.yml @@ -93,6 +93,7 @@ services: - SCHEDULER_HOST=scheduler_server - EXECUTIONMANAGER_HOST=executor - NOTIFICATIONMANAGER_HOST=rest_server + - CLAMAV_SERVICE_HOST=clamav - NEXT_PUBLIC_FRONTEND_BASE_URL=http://localhost:3000 - BACKEND_CORS_ALLOW_ORIGINS=["http://localhost:3000"] - ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw= # DO NOT USE IN PRODUCTION!! @@ -141,6 +142,7 @@ services: - PYRO_HOST=0.0.0.0 - AGENTSERVER_HOST=rest_server - NOTIFICATIONMANAGER_HOST=rest_server + - CLAMAV_SERVICE_HOST=clamav - ENCRYPTION_KEY=dvziYgz0KSK8FENhju0ZYi8-fRTfAdlz6YLhdB_jhNw= # DO NOT USE IN PRODUCTION!! ports: - "8002:8002"