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Initial updates to most recent openai api version.

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This commit is contained in:
Cristiano Ferreira
2024-05-19 14:37:50 +01:00
parent 070e8808b1
commit e568aff4e4
4 changed files with 162 additions and 205 deletions
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app.py
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@@ -239,17 +239,27 @@ def grade_writing_task_1():
}
}
else:
message = ("Evaluate the given Writing Task 1 response based on the IELTS grading system, ensuring a "
"strict assessment that penalizes errors. Deduct points for deviations from the task, and "
"assign a score of 0 if the response fails to address the question. Additionally, provide an "
"exemplary answer with a minimum of 150 words, along with a detailed commentary highlighting "
"both strengths and weaknesses in the response. Present your evaluation in JSON format with "
"the following structure: {'perfect_answer': 'example perfect answer', 'comment': "
"'comment about answer quality', 'overall': 0.0, 'task_response': {'Task Achievement': 0.0, "
"'Coherence and Cohesion': 0.0, 'Lexical Resource': 0.0, 'Grammatical Range and Accuracy': "
"0.0}}\n Question: '" + question + "' \n Answer: '" + answer + "'")
token_count = count_tokens(message)["n_tokens"]
response = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT, message, token_count,
messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"perfect_answer": "example perfect answer", "comment": '
'"comment about answer quality", "overall": 0.0, "task_response": '
'{"Task Achievement": 0.0, "Coherence and Cohesion": 0.0, '
'"Lexical Resource": 0.0, "Grammatical Range and Accuracy": 0.0 }')
},
{
"role": "user",
"content": ('Evaluate the given Writing Task 1 response based on the IELTS grading system, '
'ensuring a strict assessment that penalizes errors. Deduct points for deviations '
'from the task, and assign a score of 0 if the response fails to address the question. '
'Additionally, provide an exemplary answer with a minimum of 150 words, along with a '
'detailed commentary highlighting both strengths and weaknesses in the response. '
'\n Question: "' + question + '" \n Answer: "' + answer + '"')
}
]
token_count = count_total_tokens(messages)
response = make_openai_call(GPT_3_5_TURBO, messages, token_count,
["comment"],
GRADING_TEMPERATURE)
response["overall"] = fix_writing_overall(response["overall"], response["task_response"])
@@ -265,16 +275,29 @@ def get_writing_task_1_general_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics))
try:
gen_wt1_question = "Craft a prompt for an IELTS Writing Task 1 General Training exercise that instructs the " \
"student to compose a letter. The prompt should present a specific scenario or situation, " \
"based on the topic of '" + topic + "', " \
"requiring the student to provide information, advice, or instructions within the letter. " \
"Make sure that the generated prompt is of " + difficulty + " difficulty and does not contain forbidden subjects in muslim countries."
token_count = count_tokens(gen_wt1_question)["n_tokens"]
response = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT, gen_wt1_question, token_count, None,
messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"prompt": "prompt content"}')
},
{
"role": "user",
"content": ('Craft a prompt for an IELTS Writing Task 1 General Training exercise that instructs the '
'student to compose a letter. The prompt should present a specific scenario or situation, '
'based on the topic of "' + topic + '", requiring the student to provide information, '
'advice, or instructions within the letter. '
'Make sure that the generated prompt is '
'of ' + difficulty + 'difficulty and does not contain '
'forbidden subjects in muslim '
'countries.')
}
]
token_count = count_total_tokens(messages)
response = make_openai_call(GPT_3_5_TURBO, messages, token_count, "prompt",
GEN_QUESTION_TEMPERATURE)
return {
"question": response.strip(),
"question": response["prompt"].strip(),
"difficulty": difficulty,
"topic": topic
}
@@ -312,18 +335,27 @@ def grade_writing_task_2():
}
}
else:
message = ("Evaluate the given Writing Task 2 response based on the IELTS grading system, ensuring a "
"strict assessment that penalizes errors. Deduct points for deviations from the task, and "
"assign a score of 0 if the response fails to address the question. Additionally, provide an "
"exemplary answer with a minimum of 250 words, along with a detailed commentary highlighting "
"both strengths and weaknesses in the response. Present your evaluation in JSON format with "
"the following structure: {'perfect_answer': 'example perfect answer', 'comment': "
"'comment about answer quality', 'overall': 0.0, 'task_response': {'Task Achievement': 0.0, "
"'Coherence and Cohesion': 0.0, 'Lexical Resource': 0.0, 'Grammatical Range and Accuracy': "
"0.0}}\n Question: '" + question + "' \n Answer: '" + answer + "'")
token_count = count_tokens(message)["n_tokens"]
response = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT, message, token_count,
["comment"],
messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"perfect_answer": "example perfect answer", "comment": '
'"comment about answer quality", "overall": 0.0, "task_response": '
'{"Task Achievement": 0.0, "Coherence and Cohesion": 0.0, '
'"Lexical Resource": 0.0, "Grammatical Range and Accuracy": 0.0 }')
},
{
"role": "user",
"content": ('Evaluate the given Writing Task 2 response based on the IELTS grading system, ensuring a '
'strict assessment that penalizes errors. Deduct points for deviations from the task, and '
'assign a score of 0 if the response fails to address the question. Additionally, provide an '
'exemplary answer with a minimum of 250 words, along with a detailed commentary highlighting '
'both strengths and weaknesses in the response.'
'\n Question: "' + question + '" \n Answer: "' + answer + '"')
}
]
token_count = count_total_tokens(messages)
response = make_openai_call(GPT_4_O, messages, token_count, ["comment"],
GEN_QUESTION_TEMPERATURE)
response["overall"] = fix_writing_overall(response["overall"], response["task_response"])
response['fixed_text'] = get_fixed_text(answer)
@@ -345,16 +377,24 @@ def get_writing_task_2_general_question():
difficulty = request.args.get("difficulty", default=random.choice(difficulties))
topic = request.args.get("topic", default=random.choice(mti_topics))
try:
gen_wt2_question = "Craft a comprehensive question of " + difficulty + " difficulty for IELTS Writing Task 2 General Training that directs the candidate " \
"to delve into an in-depth analysis of contrasting perspectives on the topic of '" + topic + "'. The candidate " \
"should be asked to discuss the strengths and weaknesses of both viewpoints, provide evidence or " \
"examples, and present a well-rounded argument before concluding with their personal opinion on the " \
"subject."
token_count = count_tokens(gen_wt2_question)["n_tokens"]
response = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT, gen_wt2_question, token_count, None,
GEN_QUESTION_TEMPERATURE)
messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"prompt": "prompt content"}')
},
{
"role": "user",
"content": ('Craft a comprehensive question of ' + difficulty + 'difficulty like the ones for IELTS Writing Task 2 General Training that directs the candidate '
'to delve into an in-depth analysis of contrasting perspectives on the topic of "' + topic + '". '
'The candidate should be asked to discuss the strengths and weaknesses of both viewpoints, provide evidence or '
'examples, and present a well-rounded argument before concluding with their personal opinion on the subject.')
}
]
token_count = count_total_tokens(messages)
response = make_openai_call(GPT_4_O, messages, token_count, "prompt", GEN_QUESTION_TEMPERATURE)
return {
"question": response.strip(),
"question": response["prompt"].strip(),
"difficulty": difficulty,
"topic": topic
}
@@ -384,32 +424,50 @@ def grade_speaking_task_1():
logging.info("POST - speaking_task_1 - " + str(request_id) + " - Transcripted answer: " + answer)
if has_x_words(answer, 20):
message = ("Evaluate the given Speaking Part 1 response based on the IELTS grading system, ensuring a "
"strict assessment that penalizes errors. Deduct points for deviations from the task, and "
"assign a score of 0 if the response fails to address the question. Additionally, provide "
"detailed commentary highlighting both strengths and weaknesses in the response. Present your "
"evaluation in JSON format with "
"the following structure: {'comment': 'comment about answer quality', 'overall': 0.0, "
"'task_response': {'Fluency and Coherence': 0.0, 'Lexical Resource': 0.0, 'Grammatical Range "
"and Accuracy': 0.0, 'Pronunciation': 0.0}}\n Question: '" + question + "' \n Answer: '" + answer + "'")
token_count = count_tokens(message)["n_tokens"]
messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"comment": "comment about answer quality", "overall": 0.0, '
'"task_response": {"Fluency and Coherence": 0.0, "Lexical Resource": 0.0, '
'"Grammatical Range and Accuracy": 0.0, "Pronunciation": 0.0}}')
},
{
"role": "user",
"content": ('Evaluate the given Speaking Part 1 response based on the IELTS grading system, ensuring a '
'strict assessment that penalizes errors. Deduct points for deviations from the task, and '
'assign a score of 0 if the response fails to address the question. Additionally, provide '
'detailed commentary highlighting both strengths and weaknesses in the response.'
'\n Question: "'+ question + '" \n Answer: "'+ answer + '"')
}
]
token_count = count_total_tokens(messages)
logging.info("POST - speaking_task_1 - " + str(request_id) + " - Requesting grading of the answer.")
response = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT, message, token_count,
["comment"],
response = make_openai_call(GPT_3_5_TURBO, messages, token_count,["comment"],
GRADING_TEMPERATURE)
logging.info("POST - speaking_task_1 - " + str(request_id) + " - Answer graded: " + str(response))
perfect_answer_message = ("Provide a perfect answer according to ielts grading system to the following "
"Speaking Part 1 question: '" + question + "'")
token_count = count_tokens(perfect_answer_message)["n_tokens"]
perfect_answer_messages = [
{
"role": "system",
"content": ('You are a helpful assistant designed to output JSON on this format: '
'{"answer": "perfect answer"}')
},
{
"role": "user",
"content": (
'Provide a perfect answer according to ielts grading system to the following '
'Speaking Part 1 question: "' + question + '"')
}
]
token_count = count_total_tokens(perfect_answer_messages)
logging.info("POST - speaking_task_1 - " + str(request_id) + " - Requesting perfect answer.")
response['perfect_answer'] = make_openai_instruct_call(GPT_3_5_TURBO_INSTRUCT,
perfect_answer_message,
token_count,
None,
GEN_QUESTION_TEMPERATURE)
response['perfect_answer'] = make_openai_call(GPT_3_5_TURBO,
perfect_answer_messages,
token_count,
None,
GEN_QUESTION_TEMPERATURE)["answer"]
logging.info("POST - speaking_task_1 - " + str(
request_id) + " - Perfect answer: " + response['perfect_answer'])