File size: 8,523 Bytes
bdc5edd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 | """File / document / archive reading tools."""
import json
import os
import zipfile
from pathlib import Path
from langchain_core.tools import tool
@tool
def read_pdf(file_path: str) -> str:
"""
Extract text content from a PDF file.
Args:
file_path: Path to the PDF file to read.
Returns:
The text content of the PDF, with page separators.
"""
from pypdf import PdfReader
try:
reader = PdfReader(file_path)
text = []
for i, page in enumerate(reader.pages):
page_text = page.extract_text()
if page_text:
text.append(f"--- Page {i+1} ---\n{page_text}")
return "\n\n".join(text) if text else "[Empty PDF]"
except Exception as e:
return f"[read_pdf] failed to read PDF: {e}"
@tool
def read_docx(file_path: str) -> str:
"""
Extract text content from a Word document (.docx).
Args:
file_path: Path to the Word document to read.
Returns:
The text content of the document.
"""
from docx import Document
try:
doc = Document(file_path)
text_parts = []
paragraphs = [para.text for para in doc.paragraphs if para.text.strip()]
if paragraphs:
text_parts.append("\n".join(paragraphs))
for i, table in enumerate(doc.tables):
rows = [" | ".join(cell.text.strip() for cell in row.cells) for row in table.rows]
rows = [r for r in rows if r.strip()]
if rows:
text_parts.append(f"--- Table {i+1} ---\n" + "\n".join(rows))
return "\n\n".join(text_parts) if text_parts else "[Empty document]"
except Exception as e:
return f"[read_docx] failed to read DOCX: {e}"
@tool
def read_pptx(file_path: str) -> str:
"""
Extract text content from a PowerPoint presentation (.pptx).
Args:
file_path: Path to the PowerPoint file to read.
Returns:
The text content from all slides.
"""
from pptx import Presentation
try:
prs = Presentation(file_path)
text = []
for slide_num, slide in enumerate(prs.slides, 1):
slide_text = [f"--- Slide {slide_num} ---"]
for shape in slide.shapes:
if hasattr(shape, "text") and shape.text.strip():
slide_text.append(shape.text)
if len(slide_text) > 1:
text.append("\n".join(slide_text))
return "\n\n".join(text) if text else "[Empty presentation]"
except Exception as e:
return f"[read_pptx] failed to read PPTX: {e}"
@tool
def read_text_file(file_path: str) -> str:
"""
Read content from a plain text file (.txt).
Args:
file_path: Path to the text file to read.
Returns:
The content of the text file.
"""
try:
with open(file_path, 'r', encoding='utf-8', errors='replace') as f:
return f.read()
except Exception as e:
return f"[read_text_file] failed: {e}"
@tool
def read_csv(file_path: str) -> str:
"""
Read and analyze a CSV file using polars.
Args:
file_path: Path to the CSV file to read.
Returns:
Summary of the CSV including schema, row count, and data preview.
"""
import polars as pl
try:
df = pl.read_csv(file_path)
output = f"CSV File — {len(df)} rows, {len(df.columns)} columns\n"
output += f"Columns: {df.columns}\n\n"
output += f"Column Statistics:\n{df.describe()}\n\n"
output += f"Data (first 20 rows):\n{df.head(20)}"
if len(df) <= 50:
output += f"\n\nComplete data:\n{df}"
return output
except Exception as e:
return f"[read_csv] failed to read CSV: {e}"
@tool
def read_excel(file_path: str, sheet_id: int = 0) -> str:
"""
Read and analyze an Excel file (.xlsx) using polars.
Args:
file_path: Path to the Excel file to read.
sheet_id: The sheet index to read (0-based). Default is 0 (first sheet).
Returns:
Summary of the Excel sheet including schema, row count, and data preview.
"""
import polars as pl
import openpyxl
try:
wb = openpyxl.load_workbook(file_path, read_only=True)
sheet_names = wb.sheetnames
wb.close()
except Exception:
sheet_names = []
try:
df = pl.read_excel(file_path, sheet_id=sheet_id)
sheet_label = sheet_names[sheet_id] if sheet_id < len(sheet_names) else str(sheet_id)
output = f"Excel File — Available sheets: {sheet_names}\n\n"
output += f"Sheet {sheet_id} ('{sheet_label}') — {len(df)} rows, {len(df.columns)} columns\n"
output += f"Columns: {df.columns}\n\n"
output += f"Column Statistics:\n{df.describe()}\n\n"
output += f"Data (first 20 rows):\n{df.head(20)}"
if len(df) <= 50:
output += f"\n\nComplete data:\n{df}"
return output
except Exception as e:
return f"[read_excel] failed to read Excel: {e}"
@tool
def read_jsonld(file_path: str) -> str:
"""
Read and parse a JSON-LD file.
Args:
file_path: Path to the JSON-LD file to read.
Returns:
The formatted JSON content.
"""
try:
with open(file_path, 'r') as f:
data = json.load(f)
return f"JSON-LD Content:\n{json.dumps(data, indent=2)}"
except Exception as e:
return f"[read_jsonld] failed to read JSON-LD: {e}"
@tool
def read_pdb(file_path: str) -> str:
"""
Read and analyze a PDB (Protein Data Bank) file for protein structure analysis.
Args:
file_path: Path to the PDB file to read.
Returns:
Analysis of the protein structure including atoms, chains, and coordinates.
"""
from Bio.PDB import PDBParser
import numpy as np
try:
parser = PDBParser(QUIET=True)
structure = parser.get_structure("protein", file_path)
info = ["=== PDB Structure Analysis ==="]
atoms = list(structure.get_atoms())
info.append(f"Total atoms: {len(atoms)}")
for model in structure:
info.append(f"\nModel {model.id}:")
for chain in model:
residues = list(chain.get_residues())
info.append(f" Chain {chain.id}: {len(residues)} residues")
if len(atoms) >= 2:
info.append("\nFirst atoms (for distance calculations):")
for i, atom in enumerate(atoms[:5]):
coord = atom.get_coord()
info.append(
f" Atom {i+1}: {atom.get_name()} at "
f"[{coord[0]:.4f}, {coord[1]:.4f}, {coord[2]:.4f}]"
)
dist = np.linalg.norm(atoms[0].get_coord() - atoms[1].get_coord())
info.append(f"\nDistance between first two atoms: {dist:.4f} Angstroms")
return "\n".join(info)
except Exception as e:
return f"[read_pdb] failed to read PDB: {e}"
@tool
def read_python_file(file_path: str) -> str:
"""
Read a Python source code file.
Args:
file_path: Path to the Python file to read.
Returns:
The Python code content.
"""
try:
with open(file_path, 'r') as f:
code = f.read()
return f"Python Code:\n```python\n{code}\n```"
except Exception as e:
return f"[read_python_file] failed: {e}"
@tool
def extract_zip(file_path: str) -> str:
"""
Extract a ZIP archive and list its contents.
Args:
file_path: Path to the ZIP file to extract.
Returns:
List of files extracted from the archive with their paths.
"""
try:
extract_dir = Path(file_path).parent / Path(file_path).stem
extract_dir.mkdir(exist_ok=True)
with zipfile.ZipFile(file_path, 'r') as zip_ref:
zip_ref.extractall(extract_dir)
results = [f"ZIP Archive extracted to: {extract_dir}\n\nContents:"]
for root, dirs, files in os.walk(extract_dir):
for file in files:
full_path = os.path.join(root, file)
rel_path = os.path.relpath(full_path, extract_dir)
file_size = os.path.getsize(full_path)
results.append(f" - {rel_path} ({file_size} bytes)")
results.append(f"\nUse the appropriate read tool on the extracted files at: {extract_dir}/")
return "\n".join(results)
except Exception as e:
return f"[extract_zip] failed: {e}"
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