File size: 13,514 Bytes
daf1eaa
 
 
 
 
 
 
 
 
 
 
dea7766
 
 
daf1eaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d0d0b7b
daf1eaa
 
d0d0b7b
daf1eaa
 
d0d0b7b
 
 
 
daf1eaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
806da34
daf1eaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
793fb27
daf1eaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0192239
 
daf1eaa
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0192239
daf1eaa
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425

import json as js
import os
import streamlit as st
from mistralai.client import MistralClient
from mistralai.models.chat_completion import ChatMessage
import json
import base64
import torch
from transformers import pipeline
from diffusers import StableDiffusionPipeline
from sklearn.metrics.pairwise import cosine_similarity
from sentence_transformers import SentenceTransformer
from diffusers import StableDiffusionPipeline


import io
from gtts import gTTS
import ast
########################################
if 'sentence_model' not in st.session_state:
    st.session_state['sentence_model'] = SentenceTransformer('all-MiniLM-L6-v2')

sentence_model = st.session_state['sentence_model']

if 'pipeline' not in st.session_state:
    st.session_state['pipeline'] = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
    st.session_state['pipeline'].to("cuda")

pipeline = st.session_state['pipeline']


# Step 3: Function to get the embedding of the input sentence
def get_sentence_embedding(sentence):
    return sentence_model.encode(sentence)
# Step 4: Generate image using Stable Diffusion if needed
def generate_image(prompt):
    global pipeline
    pipeline.to("cuda" if torch.cuda.is_available() else "cpu")
    generated_image = pipeline(prompt).images[0]
    generated_image_path = "generated_image.png"
    generated_image.save(generated_image_path)
    return generated_image_path

# Step 5: Find the most reliable image
def find_most_reliable_image(folder_path, input_sentence, threshold=0.5):
    image_files = [f for f in os.listdir(folder_path) if f.endswith(('jpg', 'jpeg', 'png'))]
    sentence_embedding = get_sentence_embedding(input_sentence)
    
    max_similarity = -1
    most_reliable_image = None
    
    for image_file in image_files:
        filename_without_extension = os.path.splitext(image_file)[0]
        filename_embedding = get_sentence_embedding(filename_without_extension)
        similarity = cosine_similarity([sentence_embedding], [filename_embedding])[0][0]
        
        if similarity > max_similarity:
            max_similarity = similarity
            most_reliable_image = os.path.join(folder_path, image_file)
    
    if max_similarity < threshold:
        most_reliable_image = generate_image(input_sentence)
    
    return most_reliable_image

def findImg(input_sentence):
    folder_path = 'images_collection'
    threshold = 0.5
    most_reliable_image = find_most_reliable_image(folder_path, input_sentence, threshold)
    return most_reliable_image
########################################

@st.cache_data
def get_image(prompt: str) -> str:
    return findImg(prompt)
    #try:
    #    return findImg(prompt)
    #except:
    #    return "image.png"



prompt = """
you're an illiteracy tutot for illiterate people these people just learned the basic like they learn letters, your task is to:
-Generate a python lsit contians multiple-choice question with the following format, Create 10 questions:

- "question": The text of the question.
- "incorrect_answers": A list of possible answer choices which are incorrect.
- "correct_answer": The correct answer. :
- "image": description of image if needed, else keep it empty

Objective: Identify the correct letter to complete a word.

Objective: Match words with their correct images.

Objective: Identify the first and last letters of a word.

Objective: Identify whether the given letter is a vowel or a consonant.

Objective: Identify the word formed by blending given sounds.

Objective: Identify if the vowel in a word is short or long.

here's exemples:
[
{
  "question": "Complete the word: H__T (Hint: Something you wear on your head)",
  "incorrect_answers": ["A", "O", "U"],
  "correct_answer": "E",
  "image": ""
},
{
  "question": "Which word matches this picture?",
  "incorrect_answers": ["CAR", "BUS", "TRAIN"],
  "correct_answer": "BIKE",
  "image": "Picture of a Bike"
},
{
  "question": "What is the last letter of the word 'MONKEY'?",
  "incorrect_answers": ["M", "O", "K"],
  "correct_answer": "Y",
  "image": ""
},
{
  "question": "Is the vowel sound in 'HOP' short or long?",
  "incorrect_answers": ["Long"],
  "correct_answer": "Short",
  "image": ""
},
{
  "question": "Complete the word: B__L (Hint: A round object that bounces)",
  "incorrect_answers": ["A", "I", "U"],
  "correct_answer": "O",
  "image": ""
},
{
  "question": "Which word matches this picture?",
  "incorrect_answers": ["APPLE", "BANANA", "ORANGE"],
  "correct_answer": "PEAR",
  "image": "Picture of a Pear"
}
]
-generate a python list of 10 quizzes.
quizzes=

"""


QS=[
    {
        "question": "What is the beginning sound of the word 'apple'?",
        "incorrect_answers": ["m", "p", "r"],
        "correct_answer": "a"
    },
    {
        "question": "Which word has the same ending sound as 'sun'?",
        "incorrect_answers": ["moon", "run", "fun"],
        "correct_answer": "bun"
    },
    {
        "question": "Which word rhymes with 'ship'?",
        "incorrect_answers": ["dip", "rip", "sip"],
        "correct_answer": "tip"
    },
    {
        "question": "What is the long vowel sound in the word 'rain'?",
        "incorrect_answers": ["a", "e", "i"],
        "correct_answer": "ai"
    },
    {
        "question": "Which word has the same beginning sound as 'elephant'?",
        "incorrect_answers": ["igloo", "apple", "umbrella"],
        "correct_answer": "egg"
    },
    {
        "question": "Which word has the same ending sound as 'kite'?",
        "incorrect_answers": ["bike", "site", "dike"],
        "correct_answer": "light"
    },
    {
        "question": "What is the short vowel sound in the word 'dog'?",
        "incorrect_answers": ["a", "e", "i"],
        "correct_answer": "o"
    },
    {
        "question": "Which word has the same beginning sound as 'under'?",
        "incorrect_answers": ["apple", "egg", "umbrella"],
        "correct_answer": "up"
    },
    {
        "question": "Which word has the same ending sound as 'bat'?",
        "incorrect_answers": ["cat", "rat", "hat"],
        "correct_answer": "mat"
    },
    {
        "question": "What is the long vowel sound in the word 'boot'?",
        "incorrect_answers": ["a", "e", "i"],
        "correct_answer": "oo"
    }
]


import streamlit as st
def add_logo():
    st.markdown(
        """
        <style>
            [data-testid="stSidebarNav"] {
                /*background-image: url(http://placekitten.com/200/200);*/
                background-repeat: no-repeat;
                #padding-top: 120px;
                background-position: 20px 20px;
            }
            [data-testid="stSidebarNav"]::before {
                content: "MO3ALIMI sidebar";
                margin-left: 20px;
                margin-top: 20px;
                font-size: 29px;
                position: relative;
                top: 0px;
            }
        </style>
        """,
        unsafe_allow_html=True,
    )
add_logo()
@st.cache_data
def tts_predict(text="hello"):
    tts = gTTS(text=text, lang='en')
    with io.BytesIO() as audio_file:
        tts.write_to_fp(audio_file)
        audio_file.seek(0)
        audio_bytes = audio_file.read()
    return audio_bytes
@st.cache_data
def get_mistral_response_injson():
    global prompt
    api_key = "aOBApfmoJGuePYaDKeQbKjZRdN3et4hC"
    model = "mistral-small-latest"
    client = MistralClient(api_key=api_key)

    messages = [
        ChatMessage(role="user", content=prompt)
    ]

    chat_response = client.chat(
        model=model,
        response_format={"type": "json_object"},
        messages=messages,
    )

    output = chat_response.choices[0].message.content

    return output




@st.cache_data(ttl= 75, max_entries=1)
def get_questions():
    questions = ast.literal_eval(get_mistral_response_injson())
    return questions

def initialize_session_state():
    if 'current_question' not in st.session_state:
        st.session_state.current_question = 0
        # st.snow()
    if 'player_score' not in st.session_state:
        st.session_state.player_score = 0

def update_score(player_choice, correct_answer):
    if str(player_choice) == str(correct_answer):
        st.success("It was a correct answer! Great Job! 😁✌")
        st.session_state.player_score += 1
        #st.balloons()
    else:
        st.error("It was an incorrect answer! πŸ˜•")

if "page" not in st.session_state:
    st.session_state.page = 0
if "submit_key" in st.session_state and st.session_state.submit_key == True:
    st.session_state.running = True
else:
    st.session_state.running = False

if "running" not in st.session_state:
    st.session_state.running = False

def nextpage(): st.session_state.page += 1
def restart(): st.session_state.page = 0

# set_bg_hack_url()
st.markdown("""<style>description {color: Green;}

.st-emotion-cache-1y4p8pa {
    /* padding: none; */
}

            </style>""",unsafe_allow_html = True)

file_ = open("logo.png", "rb")
contents = file_.read()
data_url = base64.b64encode(contents).decode("utf-8")

st.markdown(f"""
    <div style="display: flex; align-items: center;">
  <img src="data:image/gif;base64,{data_url}" alt="Company Logo" style="height: 100px; width: auto; margin-right: 20px;">
  <h1 style="margin: 0;">MO3ALIMI</h1>
</div>
    """, unsafe_allow_html=True)

st.markdown("""
<style>
audio {
width: 300px;
height: 54px;
display: none;
}
</style>""", unsafe_allow_html=True)



initialize_session_state()

def calculate_score(player_choice):
    correct_answer = quiz_questions[st.session_state.current_question]["answer"]
    # st.write("inside calculate_score" + str(correct_answer))
    update_score(player_choice, correct_answer)
    st.session_state.current_question += 1


#if 'category'not in st.session_state:
#    st.session_state.category =None
#if st.sidebar.button('&nbsp;'*30+'Phonics'+'&nbsp;'*30, ):
#    st.session_state.category = 'phonics'
#if st.sidebar.button('&nbsp;'*27+'Numeracy'+'&nbsp;'*28, ):
#    st.session_state.category = 'numeracy'
#if st.sidebar.button('&nbsp;'*31+'Writing'+'&nbsp;'*31, ):
#    st.session_state.category = 'Writing'
#if st.sidebar.button('&nbsp;'*30+'Reading'+'&nbsp;'*30, ):
#    st.session_state.category = 'Reading'
#category = st.session_state.category

#category = st.sidebar.selectbox("Category: ", ['Phonics','Numeracy','Writing','Reading'], index= None, placeholder= "Select one: ", disabled=(st.session_state.running))

if 'img_path2' not in st.session_state:
    st.session_state['img_path2']="image.png"
# st.session_state.disable_opt = True
# category = st.sidebar.selectbox("Category: ", list(categories_option.keys()), index= None, placeholder= "Select one: ", disabled=(st.session_state.running))
col1, col2 = st.columns([0.6, 0.4],gap="medium")
with col1:
    QuestionList = get_questions()
    # st.write(QuestionList)
    len_response = len(QuestionList)
    if len_response == 0:
        st.error("Got no question! πŸ˜•πŸ˜”")
        st.stop()
    quiz_questions = []
    for item in range(len_response):
        temp_dict = dict()
        temp_dict['text'] = QuestionList[item].get("question")
        temp_dict['options'] = tuple(QuestionList[item].get("incorrect_answers") + [QuestionList[item].get("correct_answer")])
        temp_dict['answer'] = QuestionList[item].get("correct_answer")
        temp_dict['image'] = QuestionList[item].get("image")

        quiz_questions.append(temp_dict)
    placeholder = st.empty()
    ind = st.session_state.current_question
    if ind > len(quiz_questions):
        st.stop()
    else:



        current_question = quiz_questions[ind]
        st.subheader(quiz_questions[ind]["text"])

        audio_bytes = tts_predict(quiz_questions[ind]["text"])
        st.audio(audio_bytes, format='audio/wav', autoplay=True)

        if quiz_questions[ind]["image"]:
            st.session_state['img_prompt2']=quiz_questions[ind]["image"]


        def play_audio(choice):
            audio_bytes = tts_predict(choice)
            st.audio(audio_bytes, format='audio/wav', autoplay=True)




        player_choice = st.radio("Select your answer:",
                                 options=current_question["options"],
                                 key=f"question_{ind}",
                                 index=None,
                                 disabled=(st.session_state.running))

        try:
            play_audio(player_choice)
        except:
            pass

        submitted =  st.button("Submit", key="submit_key", disabled=(st.session_state.running))
        if submitted:
            calculate_score(player_choice)
            st.markdown("Correct Answer: "+ current_question["answer"])
        # st.empty()
            if st.button("Next",on_click=nextpage,disabled=(st.session_state.page >= 9)):
                if st.session_state.current_question < len(quiz_questions):
                    st.rerun()
            if st.session_state.current_question >= len(quiz_questions):
            # st.session_state.clear
                st.empty()
                st.success("Quiz Finished!")
                st.subheader(f"_Your_ _Score_: :blue[{st.session_state.player_score}] :sunglasses:")
                #st.snow()

with col2:
    if 'img_prompt2' in st.session_state:
        st.session_state['img_path2'] = get_image(st.session_state['img_prompt2'])
        del st.session_state['img_prompt2']

    st.image(st.session_state['img_path2'], caption="Generated Image", width=300)
st.markdown("---")