import pandas as pd
import yaml

# Read the data from the CSV file
df = pd.read_csv(r"D:\livecode\Book1.csv")

# df['Question'] = df['Question'].replace('\n', ' ', regex=True)
# df['Question'] = df['Question'].str.strip()

# df['Answers'] = df['Answers'].replace('\n', ' ', regex=True)
# df['Answers'] = df['Answers'].str.strip()

# # Extract the columns from the dataframe
Question = df['Question'].tolist()
Example1 = df['Example1'].tolist()
Example2 = df['Example2'].tolist()
Example3 = df['Example3'].tolist()
uniqueid = df['uniqueid'].tolist()
Answers = df['Answers'].tolist()

question_cols = df.filter(regex='Example').columns
answer_cols = df.filter(regex='Answers').columns
#appending intents
import ruamel.yaml as yaml

# Load the domain YAML file
with open(r'C:\Users\Bizgaze\Desktop\fileupdation\trail_update\domain.yml', 'r') as f:
    domain = yaml.safe_load(f)
    for i in uniqueid:
        domain['intents'].append(i)
        with open(r'C:\Users\Bizgaze\Desktop\fileupdation\trail_update\domain.yml', 'w') as f:
            yaml.dump(domain, f, default_flow_style=False, allow_unicode=True)

#appending muitipal answers
from ruamel.yaml import YAML

# Create a YAML object that preserves the formatting of the original YAML file
yaml = YAML()
yaml.preserve_quotes = True
yaml.indent(mapping=2, sequence=4, offset=2)

# Read in the existing domain file
with open(r'C:\Users\Bizgaze\Desktop\fileupdation\trail_update\domain.yml', 'r') as file:
    domain = yaml.load(file)

# Generate the new YAML code for each row of data
new_content = {}
for index, row in df.iterrows():
    intent_name = row['uniqueid']
    examples = [row[col] for col in answer_cols ]
    separator = "_"
    for counter, example in enumerate(examples, start=1):
        #example=example.replace(':','')
        response_name = f"utter_{intent_name}{separator}{counter}"
        response_text = f"- text: {example}"
        if 'responses' not in new_content:
            new_content['responses'] = {}
        new_content['responses'][response_name] = yaml.load(response_text)

# Update the `responses` section of the domain dictionary with the new content
domain['responses'].update(new_content['responses'])

# Write the updated domain file back to disk, preserving the formatting of the original file
with open(r'C:\Users\Bizgaze\Desktop\fileupdation\trail_update\domain.yml', 'w') as file:
    yaml.dump(domain, file)

#appending multipal action for each rule
with open(r"C:\Users\Bizgaze\Desktop\fileupdation\trail_update\data\rules.yml", 'a') as f:
    for index, row in df.iterrows():
        intent_name = row['uniqueid']
        examples = [row[col] for col in question_cols]
        separator = "_"
        steps = {"intent": intent_name}
        gg=[]
        for counter, example in enumerate(examples, start=1):
            unique_id = f"{intent_name}{separator}{counter}"
            gg.append({"action": f"utter_{unique_id}"})

        output_str = "  \n  ".join([f"- action: {question['action'][:-1]}{i}" for i, question in enumerate(gg, start=1)])

        f.write(f""" 
- rule: Ticket{intent_name}
  steps:
  - intent: {steps['intent']}
  {output_str}
  
""")


# appending multipal question

with open(r'C:\Users\Bizgaze\Desktop\fileupdation\trail_update\data\nlu.yml', "a") as file:
    for index, row in df.iterrows():
        intent_name = row['uniqueid']
        examples = [row[col] for col in question_cols]
        file.write(f"""
- intent: {intent_name}
  examples: |
""")
        for example in examples:
            file.write(f"   - \"{example}\"\n")
        file.write("\n")


# filename = r"C:\Users\Bizgaze\Desktop\fileupdation\trail_update\data\nlu.yml"
# string_to_remove = '  - "nan"'

# with open(filename, "r") as f:
#     text = f.read()

# modified_text = text.replace(string_to_remove, "")

# with open(filename, "w") as f:
#     f.write(modified_text)

# filename = r"C:\Users\Bizgaze\Desktop\fileupdation\trail_update\data\domain.yml"
# string_to_remove = '  - "nan"'

# with open(filename, "r") as f:
#     text = f.read()

# modified_text = text.replace(string_to_remove, "")

# with open(filename, "w") as f:
#     f.write(modified_text)

# filename = r"C:\Users\Bizgaze\Desktop\fileupdation\trail_update\data\rules.yml"
# string_to_remove = '  - "nan"'

# with open(filename, "r") as f:
#     text = f.read()

# modified_text = text.replace(string_to_remove, "")

# with open(filename, "w") as f:
#     f.write(modified_text)