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import pandas as pd
from openai import OpenAI
import re
import time
import pickle

import pandas as pd from openai import OpenAI import re import time import pickle

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df = pd.read_csv('./dataset/raw.csv', )

df = pd.read_csv('./dataset/raw.csv', )

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df

df

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client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio")

client = OpenAI(base_url="http://localhost:1234/v1", api_key="lm-studio")

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def get_text_between_quotes(input_string):
    pattern = r'"([^"]*)"'
    matches = re.findall(pattern, input_string)
    try:
        return matches[0]
    except Exception as e:
        return input_string

def get_text_between_quotes(input_string): pattern = r'"([^"]*)"' matches = re.findall(pattern, input_string) try: return matches[0] except Exception as e: return input_string

Zero shot generate¶

Test¶

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promt = """
Generate formal script 1 paragraph to introduce with these information
- name: {}
- age: {}
- job: {}
"""

data = df.loc[0]
start_time = time.time()
completion = client.chat.completions.create(
  model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
  messages=[
    {"role": "system", "content": "Provide only answer don't repeat the question."},
    {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
  ],
  temperature=0,
)
content = completion.choices[0].message.content
text = get_text_between_quotes(content)
end_time = time.time()
print(f"Time use: {end_time - start_time} -- text: {text}")

promt = """ Generate formal script 1 paragraph to introduce with these information - name: {} - age: {} - job: {} """ data = df.loc[0] start_time = time.time() completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=0, ) content = completion.choices[0].message.content text = get_text_between_quotes(content) end_time = time.time() print(f"Time use: {end_time - start_time} -- text: {text}")

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promt = """
Generate informal script 1 paragraph to introduce with these information
- name: {}
- age: {}
- job: {}
"""

data = df.loc[0]
start_time = time.time()
completion = client.chat.completions.create(
  model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
  messages=[
    {"role": "system", "content": "Provide only answer don't repeat the question."},
    {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
  ],
  temperature=0,
)
content = completion.choices[0].message.content
text = get_text_between_quotes(content)
end_time = time.time()
print(f"Time use: {end_time - start_time} -- text: {text}")

promt = """ Generate informal script 1 paragraph to introduce with these information - name: {} - age: {} - job: {} """ data = df.loc[0] start_time = time.time() completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=0, ) content = completion.choices[0].message.content text = get_text_between_quotes(content) end_time = time.time() print(f"Time use: {end_time - start_time} -- text: {text}")

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promt = """
Generate 1 paragraph story which include following information 
- name: {}
- age: {}
- job: {}
"""

data = df.loc[0]
start_time = time.time()
completion = client.chat.completions.create(
  model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
  messages=[
    {"role": "system", "content": "Provide only answer don't repeat the question."},
    {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
  ],
  temperature=0,
)
content = completion.choices[0].message.content
text = get_text_between_quotes(content)
end_time = time.time()
print(f"Time use: {end_time - start_time} -- text: {text}")

promt = """ Generate 1 paragraph story which include following information - name: {} - age: {} - job: {} """ data = df.loc[0] start_time = time.time() completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=0, ) content = completion.choices[0].message.content text = get_text_between_quotes(content) end_time = time.time() print(f"Time use: {end_time - start_time} -- text: {text}")

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promt = """
Generate 1 paragraph story which include following information 
- name: {}
- age: {}
- job: {}
"""

data = df.loc[0]
start_time = time.time()
completion = client.chat.completions.create(
  model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
  messages=[
    {"role": "system", "content": "Provide only answer don't repeat the question."},
    {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
  ],
  temperature=0,
)
content = completion.choices[0].message.content
text = get_text_between_quotes(content)
end_time = time.time()
print(f"Time use: {end_time - start_time} -- text: {text}")

promt = """ Generate 1 paragraph story which include following information - name: {} - age: {} - job: {} """ data = df.loc[0] start_time = time.time() completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=0, ) content = completion.choices[0].message.content text = get_text_between_quotes(content) end_time = time.time() print(f"Time use: {end_time - start_time} -- text: {text}")

Generate zero shot¶

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formal_script = {}
# for temp in [0, 0.3, 0.8, 1.3]:
for temp in [0.8]:
    promt = """
    Generate formal script 1 paragraph to introduce with these information
    - name: {}
    - age: {}
    - job: {}
    """

    key = f"temp_{temp}"
    formal_script[key] = {}
    for _, data in df.iterrows():
        completion = client.chat.completions.create(
          model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
          messages=[
            {"role": "system", "content": "Provide only answer don't repeat the question."},
            {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
          ],
          temperature=temp,
        )
        content = completion.choices[0].message.content
        try:
            text = get_text_between_quotes(content)
        except Exception as e:
            text = content
        formal_script[key][data["uid"]] = text

formal_script = {} # for temp in [0, 0.3, 0.8, 1.3]: for temp in [0.8]: promt = """ Generate formal script 1 paragraph to introduce with these information - name: {} - age: {} - job: {} """ key = f"temp_{temp}" formal_script[key] = {} for _, data in df.iterrows(): completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=temp, ) content = completion.choices[0].message.content try: text = get_text_between_quotes(content) except Exception as e: text = content formal_script[key][data["uid"]] = text

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with open('./dataset/formal_script.pkl', 'wb') as fp:
    pickle.dump(formal_script, fp)

with open('./dataset/formal_script.pkl', 'wb') as fp: pickle.dump(formal_script, fp)

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informal_script = {}
# for temp in [0, 0.3, 0.8, 1.3]:
for temp in [0.8]:
    promt = """
    Generate informal script 1 paragraph to introduce with these information
    - name: {}
    - age: {}
    - job: {}
    """

    key = f"temp_{temp}"
    informal_script[key] = {}
    for _, data in df.iterrows():
        completion = client.chat.completions.create(
          model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
          messages=[
            {"role": "system", "content": "Provide only answer don't repeat the question."},
            {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
          ],
          temperature=temp,
        )
        content = completion.choices[0].message.content
        try:
            text = get_text_between_quotes(content)
        except Exception as e:
            text = content
        informal_script[key][data["uid"]] = text

informal_script = {} # for temp in [0, 0.3, 0.8, 1.3]: for temp in [0.8]: promt = """ Generate informal script 1 paragraph to introduce with these information - name: {} - age: {} - job: {} """ key = f"temp_{temp}" informal_script[key] = {} for _, data in df.iterrows(): completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=temp, ) content = completion.choices[0].message.content try: text = get_text_between_quotes(content) except Exception as e: text = content informal_script[key][data["uid"]] = text

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with open('./dataset/informal_script.pkl', 'wb') as fp:
    pickle.dump(informal_script, fp)

with open('./dataset/informal_script.pkl', 'wb') as fp: pickle.dump(informal_script, fp)

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novel_script = {}
# for temp in [0, 0.3, 0.8, 1.3]:
for temp in [0.8]:
    promt = """
    Generate 1 paragraph story which include following information 
    - name: {}
    - age: {}
    - job: {}
    """

    key = f"temp_{temp}"
    novel_script[key] = {}
    for _, data in df.iterrows():
        completion = client.chat.completions.create(
          model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF",
          messages=[
            {"role": "system", "content": "Provide only answer don't repeat the question."},
            {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])}
          ],
          temperature=temp,
        )
        content = completion.choices[0].message.content
        try:
            text = get_text_between_quotes(content)
        except Exception as e:
            text = content
        novel_script[key][data["uid"]] = text

novel_script = {} # for temp in [0, 0.3, 0.8, 1.3]: for temp in [0.8]: promt = """ Generate 1 paragraph story which include following information - name: {} - age: {} - job: {} """ key = f"temp_{temp}" novel_script[key] = {} for _, data in df.iterrows(): completion = client.chat.completions.create( model="lmstudio-community/Meta-Llama-3-8B-Instruct-GGUF", messages=[ {"role": "system", "content": "Provide only answer don't repeat the question."}, {"role": "user", "content": promt.format(data["name"], data["age"], data["job"])} ], temperature=temp, ) content = completion.choices[0].message.content try: text = get_text_between_quotes(content) except Exception as e: text = content novel_script[key][data["uid"]] = text

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with open('./dataset/novel_script.pkl', 'wb') as fp:
    pickle.dump(novel_script, fp)

with open('./dataset/novel_script.pkl', 'wb') as fp: pickle.dump(novel_script, fp)

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