Hi, I am actually trying to prompt Gemini to give me some gradings on students essay, however there is an error that states
Could not create `Blob`, expected `Blob`, `dict` or an `Image` type(`PIL.Image.Image` or `IPython.display.Image`). Got a: <class 'list'>
Hereby attached my code,
model = genai.GenerativeModel('gemini-1.5-pro')
def get_json_Gemini(file, prompt😞
start_time = time.time()
messages=[
{"role": "system", "parts": ["You are a teaching assistant."]},
{"role": "user", "parts": [prompt]},
],
response = model.generate_content(
contents=messages,
generation_config=genai.types.GenerationConfig(
temperature=0.9,
max_output_tokens=1600,
)
)
end_time = time.time()
print(f"API call for {file} took {end_time - start_time:.2f} seconds")
# Save the response to a JSON file
write_text_to_file(f"tmp/{file}.json", json.dumps(response))
tokens = response['usage']['total_tokens']
return json.loads(response['choices'][0]['message']['content']), tokens
def grade_answer(file, student_answer, marking_scheme😞
prompt = marking_scheme.replace("<ANSWER></ANSWER>", student_answer)
retry = 0
while True:
try:
content, tokens = get_json_Gemini(file, prompt)
break
except Exception as e:
if retry < 2:
retry += 1
print(e)
print("Retrying:", retry)
continue
return 0, "Error", 0, 0, True, 0, True
marks = content['marks']
comments = content['comments']
copyFromInternet = content['copyFromInternet']
generativeAI = content['generativeAI']
manualReview = content['manualReview']
return marks, comments, copyFromInternet, generativeAI, manualReview, tokens, False
def grade_answers(df_answers, marking_scheme😞
start_time = time.time()
for index, row in df_answers.iterrows():
file = row["FileName"]
print(f"Grading answer {index + 1}/{len(df_answers)}: {file}")
answer = row["Answers"]
marks, comments, copyFromInternet, generativeAI, manualReview, tokens, error = grade_answer(file, answer, marking_scheme)
df_answers.loc[index, "Marks"] = marks
df_answers.loc[index, "Comments"] = comments
df_answers.loc[index, "CopyFromInternet"] = copyFromInternet
df_answers.loc[index, "GenerativeAI"] = generativeAI
df_answers.loc[index, "GeminiTokens"] = tokens
df_answers.loc[index, "ManualReview"] = manualReview
df_answers.loc[index, "Error"] = error
end_time = time.time()
print(f"Grading all answers took {end_time - start_time:.2f} seconds")
return df_answers
marking_scheme = read_text_file("marking_scheme.txt")
marking_scheme
# Assuming df_answers is read from an Excel file
df_marked = grade_answers(df_answers, marking_scheme)
df_marked.to_excel("data/marks.xlsx", index=False)
print("Grading completed and results saved to data/marks.xlsx")
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