Upload files to 'chatbot'

Esse commit está contido em:
2023-05-01 04:50:41 +00:00
commit acb741f08b
+136
Ver Arquivo
@@ -0,0 +1,136 @@
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)