Code_to_dict

3 languages added, works well with python. Java and Js require additional revieving
pull/129/head
Pavel 2 years ago
parent 0fb28e5213
commit 2c364d3c00

@ -14,7 +14,11 @@ from langchain.text_splitter import RecursiveCharacterTextSplitter
from parser.file.bulk import SimpleDirectoryReader
from parser.schema.base import Document
from parser.open_ai_func import call_openai_api, get_user_permission
from parser.py2doc import get_classes, get_functions, transform_to_docs
from parser.py2doc import transform_to_docs
from parser.py2doc import extract_functions_and_classes as extract_py
from parser.js2doc import extract_functions_and_classes as extract_js
from parser.java2doc import extract_functions_and_classes as extract_java
dotenv.load_dotenv()
@ -83,27 +87,25 @@ def ingest(yes: bool = typer.Option(False, "-y", "--yes", prompt=False,
@app.command()
def convert():
ps = list(Path("inputs").glob("**/*.py"))
data = []
sources = []
for p in ps:
with open(p) as f:
data.append(f.read())
sources.append(p)
functions_dict = {}
classes_dict = {}
c1 = 0
for code in data:
functions = get_functions(ast.parse(code))
source = str(sources[c1])
functions_dict[source] = functions
classes = get_classes(code)
classes_dict[source] = classes
c1 += 1
transform_to_docs(functions_dict, classes_dict)
def convert(dir: Optional[str] = typer.Option("inputs",
help="""Path to directory to make documentation for.
E.g. --dir inputs """),
formats: Optional[str] = typer.Option("py",
help="""Required language.
py, js, java supported for now""")):
"""
Creates documentation linked to original functions from specified location.
By default /inputs folder is used, .py is parsed.
"""
if formats == 'py':
functions_dict, classes_dict = extract_py(dir)
elif formats == 'js':
functions_dict, classes_dict = extract_js(dir)
elif formats == 'java':
functions_dict, classes_dict = extract_java(dir)
else:
raise Exception("Sorry, language not supported yet")
transform_to_docs(functions_dict, classes_dict, formats, dir)
if __name__ == "__main__":
app()

@ -0,0 +1,61 @@
import os
import javalang
def find_files(directory):
files_list = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith('.java'):
files_list.append(os.path.join(root, file))
return files_list
def extract_functions(file_path):
with open(file_path, "r") as file:
java_code = file.read()
methods = {}
tree = javalang.parse.parse(java_code)
for _, node in tree.filter(javalang.tree.MethodDeclaration):
method_name = node.name
start_line = node.position.line - 1
end_line = start_line
brace_count = 0
for line in java_code.splitlines()[start_line:]:
end_line += 1
brace_count += line.count("{") - line.count("}")
if brace_count == 0:
break
method_source_code = "\n".join(java_code.splitlines()[start_line:end_line])
methods[method_name] = method_source_code
return methods
def extract_classes(file_path):
with open(file_path, 'r') as file:
source_code = file.read()
classes = {}
tree = javalang.parse.parse(source_code)
for class_decl in tree.types:
class_name = class_decl.name
declarations = []
methods = []
for field_decl in class_decl.fields:
field_name = field_decl.declarators[0].name
field_type = field_decl.type.name
declarations.append(f"{field_type} {field_name}")
for method_decl in class_decl.methods:
methods.append(method_decl.name)
class_string = "Declarations: " + ", ".join(declarations) + "\n Method name: " + ", ".join(methods)
classes[class_name] = class_string
return classes
def extract_functions_and_classes(directory):
files = find_files(directory)
functions_dict = {}
classes_dict = {}
for file in files:
functions = extract_functions(file)
if functions:
functions_dict[file] = functions
classes = extract_classes(file)
if classes:
classes_dict[file] = classes
return functions_dict, classes_dict

@ -0,0 +1,67 @@
import os
import esprima
import escodegen
def find_files(directory):
files_list = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith('.js'):
files_list.append(os.path.join(root, file))
return files_list
def extract_functions(file_path):
with open(file_path, 'r') as file:
source_code = file.read()
functions = {}
tree = esprima.parseScript(source_code)
for node in tree.body:
if node.type == 'FunctionDeclaration':
func_name = node.id.name if node.id else '<anonymous>'
functions[func_name] = escodegen.generate(node)
elif node.type == 'VariableDeclaration':
for declaration in node.declarations:
if declaration.init and declaration.init.type == 'FunctionExpression':
func_name = declaration.id.name if declaration.id else '<anonymous>'
functions[func_name] = escodegen.generate(declaration.init)
elif node.type == 'ClassDeclaration':
class_name = node.id.name
for subnode in node.body.body:
if subnode.type == 'MethodDefinition':
func_name = subnode.key.name
functions[func_name] = escodegen.generate(subnode.value)
elif subnode.type == 'VariableDeclaration':
for declaration in subnode.declarations:
if declaration.init and declaration.init.type == 'FunctionExpression':
func_name = declaration.id.name if declaration.id else '<anonymous>'
functions[func_name] = escodegen.generate(declaration.init)
return functions
def extract_classes(file_path):
with open(file_path, 'r') as file:
source_code = file.read()
classes = {}
tree = esprima.parseScript(source_code)
for node in tree.body:
if node.type == 'ClassDeclaration':
class_name = node.id.name
function_names = []
for subnode in node.body.body:
if subnode.type == 'MethodDefinition':
function_names.append(subnode.key.name)
classes[class_name] = ", ".join(function_names)
return classes
def extract_functions_and_classes(directory):
files = find_files(directory)
functions_dict = {}
classes_dict = {}
for file in files:
functions = extract_functions(file)
if functions:
functions_dict[file] = functions
classes = extract_classes(file)
if classes:
classes_dict[file] = classes
return functions_dict, classes_dict

@ -1,108 +1,87 @@
import os
import ast
import tiktoken
from pathlib import Path
from langchain.llms import OpenAI
from langchain.prompts import PromptTemplate
import dotenv
import ast
import typer
import tiktoken
dotenv.load_dotenv()
def get_functions(source_code):
tree = ast.parse(source_code)
functions = {}
for node in tree.body:
if isinstance(node, ast.FunctionDef):
functions[node.name] = ast.unparse(node)
def find_files(directory):
files_list = []
for root, dirs, files in os.walk(directory):
for file in files:
if file.endswith('.py'):
files_list.append(os.path.join(root, file))
return files_list
def extract_functions(file_path):
with open(file_path, 'r') as file:
source_code = file.read()
functions = {}
tree = ast.parse(source_code)
for node in ast.walk(tree):
if isinstance(node, ast.FunctionDef):
func_name = node.name
func_def = ast.get_source_segment(source_code, node)
functions[func_name] = func_def
return functions
def get_functions_names(node):
functions = []
for child in node.body:
if isinstance(child, ast.FunctionDef):
functions.append(child.name)
return functions
def get_classes(source_code):
tree = ast.parse(source_code)
classes = {}
for node in tree.body:
if isinstance(node, ast.ClassDef):
classes[node.name] = get_functions_names(node)
def extract_classes(file_path):
with open(file_path, 'r') as file:
source_code = file.read()
classes = {}
tree = ast.parse(source_code)
for node in ast.walk(tree):
if isinstance(node, ast.ClassDef):
class_name = node.name
function_names = []
for subnode in ast.walk(node):
if isinstance(subnode, ast.FunctionDef):
function_names.append(subnode.name)
classes[class_name] = ", ".join(function_names)
return classes
def get_functions_in_class(source_code, class_name):
tree = ast.parse(source_code)
functions = []
for node in tree.body:
if isinstance(node, ast.ClassDef):
if node.name == class_name:
for function in node.body:
if isinstance(function, ast.FunctionDef):
functions.append(function.name)
return functions
def parse_functions(functions_dict):
def extract_functions_and_classes(directory):
files = find_files(directory)
functions_dict = {}
classes_dict = {}
for file in files:
functions = extract_functions(file)
if functions:
functions_dict[file] = functions
classes = extract_classes(file)
if classes:
classes_dict[file] = classes
return functions_dict, classes_dict
def parse_functions(functions_dict, formats, dir):
c1 = len(functions_dict)
c2 = 0
for source, functions in functions_dict.items():
c2 += 1
print(f"Processing file {c2}/{c1}")
f1 = len(functions)
f2 = 0
source_w = source.replace("inputs/", "")
source_w = source_w.replace(".py", ".md")
# this is how we check subfolders
if "/" in source_w:
subfolders = source_w.split("/")
subfolders = subfolders[:-1]
subfolders = "/".join(subfolders)
if not Path(f"outputs/{subfolders}").exists():
Path(f"outputs/{subfolders}").mkdir(parents=True)
for name, function in functions.items():
f2 += 1
print(f"Processing function {f2}/{f1}")
for i, (source, functions) in enumerate(functions_dict.items(), start=1):
print(f"Processing file {i}/{c1}")
source_w = source.replace(dir+"/", "").replace("."+formats, ".md")
subfolders = "/".join(source_w.split("/")[:-1])
Path(f"outputs/{subfolders}").mkdir(parents=True, exist_ok=True)
for j, (name, function) in enumerate(functions.items(), start=1):
print(f"Processing function {j}/{len(functions)}")
prompt = PromptTemplate(
input_variables=["code"],
template="Code: \n{code}, \nDocumentation: ",
)
llm = OpenAI(temperature=0)
response = llm(prompt.format(code=function))
mode = "a" if Path(f"outputs/{source_w}").exists() else "w"
with open(f"outputs/{source_w}", mode) as f:
f.write(f"\n\n# Function name: {name} \n\nFunction: \n```\n{function}\n```, \nDocumentation: \n{response}")
if not Path(f"outputs/{source_w}").exists():
with open(f"outputs/{source_w}", "w") as f:
f.write(f"# Function name: {name} \n\nFunction: \n```\n{function}\n```, \nDocumentation: \n{response}")
else:
with open(f"outputs/{source_w}", "a") as f:
f.write(f"\n\n# Function name: {name} \n\nFunction: \n```\n{function}\n```, \nDocumentation: \n{response}")
def parse_classes(classes_dict):
def parse_classes(classes_dict, formats, dir):
c1 = len(classes_dict)
c2 = 0
for source, classes in classes_dict.items():
c2 += 1
print(f"Processing file {c2}/{c1}")
f1 = len(classes)
f2 = 0
source_w = source.replace("inputs/", "")
source_w = source_w.replace(".py", ".md")
if "/" in source_w:
subfolders = source_w.split("/")
subfolders = subfolders[:-1]
subfolders = "/".join(subfolders)
if not Path(f"outputs/{subfolders}").exists():
Path(f"outputs/{subfolders}").mkdir(parents=True)
for i, (source, classes) in enumerate(classes_dict.items()):
print(f"Processing file {i+1}/{c1}")
source_w = source.replace(dir+"/", "").replace("."+formats, ".md")
subfolders = "/".join(source_w.split("/")[:-1])
Path(f"outputs/{subfolders}").mkdir(parents=True, exist_ok=True)
for name, function_names in classes.items():
print(f"Processing Class {f2}/{f1}")
f2 += 1
print(f"Processing Class {i+1}/{c1}")
prompt = PromptTemplate(
input_variables=["class_name", "functions_names"],
template="Class name: {class_name} \nFunctions: {functions_names}, \nDocumentation: ",
@ -110,46 +89,25 @@ def parse_classes(classes_dict):
llm = OpenAI(temperature=0)
response = llm(prompt.format(class_name=name, functions_names=function_names))
if not Path(f"outputs/{source_w}").exists():
with open(f"outputs/{source_w}", "w") as f:
f.write(f"# Class name: {name} \n\nFunctions: \n{function_names}, \nDocumentation: \n{response}")
else:
with open(f"outputs/{source_w}", "a") as f:
f.write(f"\n\n# Class name: {name} \n\nFunctions: \n{function_names}, \nDocumentation: \n{response}")
with open(f"outputs/{source_w}", "a" if Path(f"outputs/{source_w}").exists() else "w") as f:
f.write(f"\n\n# Class name: {name} \n\nFunctions: \n{function_names}, \nDocumentation: \n{response}")
def transform_to_docs(functions_dict, classes_dict, formats, dir):
docs_content = ''.join([str(key) + str(value) for key, value in functions_dict.items()])
docs_content += ''.join([str(key) + str(value) for key, value in classes_dict.items()])
#User permission
def transform_to_docs(functions_dict, classes_dict):
# Function to ask user permission to call the OpenAI api and spend their OpenAI funds.
# Here we convert dicts to a string and calculate the number of OpenAI tokens the string represents.
docs_content = ""
for key, value in functions_dict.items():
docs_content += str(key) + str(value)
for key, value in classes_dict.items():
docs_content += str(key) + str(value)
encoding = tiktoken.get_encoding("cl100k_base")
num_tokens = len(encoding.encode(docs_content))
num_tokens = len(tiktoken.get_encoding("cl100k_base").encode(docs_content))
total_price = ((num_tokens / 1000) * 0.02)
# Here we print the number of tokens and the approx user cost with some visually appealing formatting.
print(f"Number of Tokens = {format(num_tokens, ',d')}")
print(f"Approx Cost = ${format(total_price, ',.2f')}")
#Here we check for user permission before calling the API.
user_input = input("Price Okay? (Y/N) \n").lower()
if user_input == "y":
if not Path("outputs").exists():
Path("outputs").mkdir()
parse_functions(functions_dict)
print("Functions done!")
parse_classes(classes_dict)
print("All done!")
elif user_input == "":
print(f"Number of Tokens = {num_tokens:,d}")
print(f"Approx Cost = ${total_price:,.2f}")
user_input = input("Price Okay? (Y/N)\n").lower()
if user_input == "y" or user_input == "":
if not Path("outputs").exists():
Path("outputs").mkdir()
parse_functions(functions_dict)
print("Functions done!")
parse_classes(classes_dict)
parse_functions(functions_dict, formats, dir)
parse_classes(classes_dict, formats, dir)
print("All done!")
else:
print("The API was not called. No money was spent.")
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