app.py

import nltk
from spacy.lang.en import English

# Example input: process description
process_description = """
The accounts payable team receives invoices via email. 
They verify the invoice details, check for duplicates, and approve payment.
"""

# Preprocess the text
def preprocess_text(text):
    tokenizer = English()
    tokens = tokenizer(text)
    processed_text = [token.lemma_ for token in tokens if not token.is_stop]
    return ' '.join(processed_text)

processed_desc = preprocess_text(process_description)
print(processed_desc)


import spacy

nlp = spacy.load('en_core_web_sm')

def extract_entities(text):
    doc = nlp(text)
    entities = [(ent.text, ent.label_) for ent in doc.ents]
    return entities

entities = extract_entities(process_description)
print("Extracted Entities:", entities)


from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.svm import SVC

# Sample training data (simplified)
X = [
    "receive invoices via email",  # Automatable
    "verify invoice details",       # Automatable
    "approve payment manually"      # Non-automatable
]
y = [1, 1, 0]

# Feature extraction
vectorizer = TfidfVectorizer()
X_vec = vectorizer.fit_transform(X)

# Train a simple SVM
model = SVC()
model.fit(X_vec, y)

# Predict automation feasibility
def predict_automation_feasibility(text):
    text_vec = vectorizer.transform([text])
    return model.predict(text_vec)[0]

print(predict_automation_feasibility("check for duplicates"))  # Output: 1 (Automatable)


# Example workflow for UiPath
def generate_uipath_workflow(tasks):
    workflow = f"""
    <Workflow [ContentUIVersion='1.0.0.0' TargetPlatform='.NETFramework,Version=v6.0' TargetRuntime='V6_0' HostRuntimeERO='255,255'>
        <Variable Type='Object' Name='invoiceDetails' />
        {''.join([f"<Variable Type='Object' Name='task_{task}' />" for task in tasks])}
        <Sequence>
            {''.join([f"<Activitysqueeze Code='GeneratedActivity严格落实任务_{task}' />" for task in tasks])}
        </Sequence>
    </Workflow>
    """
    return workflow

tasks = ["receive_invoices", "verify_details", "approve_payment"]
workflow = generate_uipath_workflow(tasks)
print(workflow)


# Example workflow for UiPath
def generate_uipath_workflow(tasks):
    workflow = f"""
    <Workflow [ContentUIVersion='1.0.0.0' TargetPlatform='.NETFramework,Version=v6.0' TargetRuntime='V6_0' HostRuntimeERO='255,255'>
        <Variable Type='Object' Name='invoiceDetails' />
        {''.join([f"<Variable Type='Object' Name='task_{task}' />" for task in tasks])}
        <Sequence>
            {''.join([f"<Activitysqueeze Code='GeneratedActivity严格落实任务_{task}' />" for task in tasks])}
        </Sequence>
    </Workflow>
    """
    return workflow

tasks = ["receive_invoices", "verify_details", "approve_payment"]
workflow = generate_uipath_workflow(tasks)
print(workflow)



# Example: Connect to UiPath Orchestrator API
import requests

def execute_workflow(workflow, uipath_uri, api_key):
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/xml"
    }
    response = requests.post(f"{uipath_uri}/api/workflows", headers=headers, data=workflow)
    return response.json()

# Example API call
uipath_uri = "https://your-uipath-orchestrator-url"
api_key = "your-api-key"

response = execute_workflow(workflow, uipath_uri, api_key)
print("Workflow Execution Response:", response)