File size: 16,657 Bytes
8dec77d
 
 
 
 
 
 
 
 
 
 
 
 
38efa1b
8dec77d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12a78dd
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
8dec77d
38efa1b
 
 
 
 
 
 
 
 
 
 
 
 
 
8dec77d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
12a78dd
8dec77d
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
426
427
428
429
430
431
432
433
434
435
436
437
# listen.py
from flask import Flask, Blueprint, jsonify, send_file, abort, request, send_from_directory
from flask_cors import CORS
from moviepy.editor import VideoFileClip
from google.cloud import speech
import os
print(f"GOOGLE_APPLICATION_CREDENTIALS: {os.getenv('GOOGLE_APPLICATION_CREDENTIALS')}")
import uuid
import requests
from pydub import AudioSegment
import ffmpeg
import re
import io  # for streaming S3 bytes in HF/AWS mode
import json  # <-- added for JSON creds parsing

# Optional (only used in AWS mode)
try:
    import boto3
    from botocore.exceptions import BotoCoreError, ClientError
except Exception:
    boto3 = None
    BotoCoreError = ClientError = Exception

# ---------- Blueprint ----------
listen_bp = Blueprint("listen", __name__)

# ---------------------- storage mode helpers ----------------------
def _is_aws_video_mode() -> bool:
    """
    Switch to S3 on Hugging Face / prod. Local stays on disk.
    """
    if os.getenv("USE_AWS_VIDEO", "0") == "1":
        return True
    if os.getenv("SPACE_ID"):  # set on Hugging Face Spaces
        return True
    if os.getenv("ENV", "dev").lower() == "prod":
        return True
    return False

def _s3_clients():
    if boto3 is None:
        raise RuntimeError("boto3 is required in AWS video mode but not available")
    region = os.getenv("AWS_DEFAULT_REGION", "eu-north-1")
    s3 = boto3.client("s3", region_name=region)
    return s3

def _video_s3_bucket():
    bucket = os.getenv("S3_BUCKET_NAME")
    if not bucket:
        raise RuntimeError("S3_BUCKET_NAME is not set")
    return bucket

def _video_s3_key(filename: str) -> str:
    # Prefix under which listen.py stores videos in the same bucket
    prefix = os.getenv("LISTEN_S3_PREFIX", "listen")
    prefix = prefix.strip().strip("/")
    return f"{prefix}/{filename}"

# ---------- writable working directories ----------
# Base working dir: /tmp on HF/AWS; local stays under ./static (or override via LISTEN_WORKDIR)
_BASE_WORKDIR = os.getenv(
    "LISTEN_WORKDIR",
    "/tmp/listen" if _is_aws_video_mode() else os.path.abspath("static")
)

VIDEO_FOLDER = os.path.join(_BASE_WORKDIR, "videos")
AUDIO_FOLDER = os.path.join(_BASE_WORKDIR, "audio")
TRANSCRIPT_FOLDER = os.path.join(_BASE_WORKDIR, "transcripts")

# Ensure directories exist (with hard fallback to /tmp if needed)
for _pname in ("videos", "audio", "transcripts"):
    _p = os.path.join(_BASE_WORKDIR, _pname)
    try:
        os.makedirs(_p, exist_ok=True)
    except Exception:
        _fallback_base = "/tmp/listen"
        os.makedirs(os.path.join(_fallback_base, _pname), exist_ok=True)
        if _pname == "videos":
            VIDEO_FOLDER = os.path.join(_fallback_base, "videos")
        elif _pname == "audio":
            AUDIO_FOLDER = os.path.join(_fallback_base, "audio")
        else:
            TRANSCRIPT_FOLDER = os.path.join(_fallback_base, "transcripts")

# ---------------- Cohere configuration (migrated to v2 Chat) ----------------
COHERE_API_KEY = os.getenv("COHERE_API_KEY", "")
COHERE_API_URL = 'https://api.cohere.com/v2/chat'
# ---------------------------------------------------------------------------

# --- Google Cloud Speech-to-Text client init (prefers HF secret JSON) ---
def _make_speech_client():
    sa_json = os.getenv("GOOGLE_APPLICATION_CREDENTIALS_JSON")
    if sa_json:
        try:
            info = json.loads(sa_json)
            return speech.SpeechClient.from_service_account_info(info)
        except Exception as e:
            print(f"Failed to parse GOOGLE_APPLICATION_CREDENTIALS_JSON: {e}")
            # fall through to default ADC
    return speech.SpeechClient()

speech_client = _make_speech_client()
# -------------------------------------------------------------------------

# ------------- Cohere v2 helper (extract text from chat response) -------------
def _extract_text_v2(resp_json: dict) -> str:
    """
    Cohere v2 /chat returns:
      { "message": { "content": [ { "type": "text", "text": "..." }, ... ] } }
    This pulls the first text block.
    """
    msg = resp_json.get("message", {})
    content = msg.get("content", [])
    for block in content:
        if isinstance(block, dict) and block.get("type") == "text":
            text = (block.get("text") or "").strip()
            if text:
                return text
    return ""
# -----------------------------------------------------------------------------

# Convert video to audio
def convert_video_to_audio(video_path, audio_path):
    try:
        # Using moviepy to extract audio from video
        video = VideoFileClip(video_path)
        video.audio.write_audiofile(audio_path, codec='mp3')
        return audio_path
    except Exception as e:
        print(f"Error converting video to audio: {str(e)}")
        return None

# Re-encode MP3 to ensure proper format
def reencode_mp3(input_audio_path, output_audio_path):
    try:
        # Using pydub to convert and re-encode MP3 (ensuring correct encoding)
        audio = AudioSegment.from_mp3(input_audio_path)
        audio.export(output_audio_path, format="mp3", codec="libmp3lame", parameters=["-q:a", "0"])
        return output_audio_path
    except Exception as e:
        print(f"Error re-encoding MP3: {str(e)}")
        return None

# Helper function to convert audio to the proper MP3 encoding if necessary
def convert_audio_to_mp3(input_file_path, output_file_path):
    """
    Converts the audio file to a valid MP3 format with proper encoding.
    """
    try:
        ffmpeg.input(input_file_path).output(output_file_path, acodec='libmp3lame', audio_bitrate='128k').run()
        return True
    except Exception as e:
        print(f"Error during audio conversion: {e}")
        return False

# Function to compress audio dynamically
def compress_audio(input_file_path, output_file_path, target_bitrate="128k"):
    audio = AudioSegment.from_file(input_file_path)
    audio.export(output_file_path, format="mp3", bitrate=target_bitrate)
    return output_file_path

# ---------------------------- Routes (Blueprint) ----------------------------

@listen_bp.route('/', methods=['GET'])
def home():
    return "Welcome to the Flask app! The server is running."

@listen_bp.route('/videos', methods=['GET'])
def list_videos():
    """
    List available videos for users to watch.
    """
    # If you maintain a VIDEOS list elsewhere, return it here.
    # Returning empty list so the endpoint stays valid.
    return jsonify([]), 200

@listen_bp.route('/videos/<filename>')
def serve_video(filename):
    """
    Local: serve file from disk.
    HF/AWS: fetch object from S3 and stream bytes (no redirect).
    """
    if _is_aws_video_mode():
        try:
            s3 = _s3_clients()
            bucket = _video_s3_bucket()
            key = _video_s3_key(filename)
            obj = s3.get_object(Bucket=bucket, Key=key)
            data = obj["Body"].read()
            return send_file(
                io.BytesIO(data),
                mimetype="video/mp4",
                download_name=filename,
                as_attachment=False
            )
        except (BotoCoreError, ClientError, Exception) as e:
            print(f"S3 fetch failed for {filename}: {e}")
            abort(404)

    # Local
    video_path = os.path.join(VIDEO_FOLDER, filename)
    if not os.path.exists(video_path):
        print(f"Video file not found: {filename}")
        abort(404)

    return send_file(video_path, mimetype='video/mp4')

@listen_bp.route('/upload-video', methods=['POST'])
def upload_video():
    """
    Local: save to static/videos or /tmp/listen/videos (depending on mode).
    HF/AWS: upload to S3 (no local original).
    """
    print("Received upload request.")

    if 'video' not in request.files:
        print("No video file provided in the request.")
        return jsonify({'error': 'No video file provided'}), 400

    video = request.files['video']
    if video.filename == '':
        print("Empty filename detected.")
        return jsonify({'error': 'No selected file'}), 400

    try:
        filename = f"{uuid.uuid4()}.mp4"

        if _is_aws_video_mode():
            try:
                s3 = _s3_clients()
                bucket = _video_s3_bucket()
                key = _video_s3_key(filename)
                s3.put_object(
                    Bucket=bucket,
                    Key=key,
                    Body=video.stream.read(),
                    ContentType="video/mp4"
                )
                print(f"Uploaded to S3: s3://{bucket}/{key}")
            except (BotoCoreError, ClientError, Exception) as e:
                print(f"S3 upload error: {e}")
                return jsonify({'error': 'Failed to upload to S3'}), 500
        else:
            # Save locally
            video_path = os.path.join(VIDEO_FOLDER, filename)
            print(f"Saving video: {filename}")
            video.save(video_path)
            print(f"Video saved successfully at {video_path}")

        return jsonify({'message': 'Video uploaded successfully!', 'filename': filename}), 200

    except Exception as e:
        print(f"Error saving video: {str(e)}")
        return jsonify({'error': 'Failed to save video'}), 500

@listen_bp.route('/generate-questions-dynamicvideo', methods=['POST'])
def generate_questions():
    try:
        data = request.json
        video_filename = data.get('filename')

        if not video_filename:
            print("Error: No filename provided in request.")
            return jsonify({"error": "Filename is required"}), 400

        # Resolve a local readable path for processing
        video_path = os.path.join(VIDEO_FOLDER, video_filename)

        if _is_aws_video_mode():
            # Download object bytes to a local working file path
            try:
                s3 = _s3_clients()
                bucket = _video_s3_bucket()
                key = _video_s3_key(video_filename)
                obj = s3.get_object(Bucket=bucket, Key=key)
                data_bytes = obj["Body"].read()
                with open(video_path, "wb") as f:
                    f.write(data_bytes)
            except (BotoCoreError, ClientError, Exception) as e:
                print(f"S3 download error for {video_filename}: {e}")
                return jsonify({"error": "Video file not found"}), 404
        else:
            if not os.path.exists(video_path):
                print(f"Error: Video file {video_filename} not found at {video_path}")
                return jsonify({"error": "Video file not found"}), 404

        print(f"Processing video: {video_filename}")

        # Convert video to audio
        audio_filename = f"{uuid.uuid4()}.mp3"
        audio_path = os.path.join(AUDIO_FOLDER, audio_filename)
        
        if not convert_video_to_audio(video_path, audio_path):
            print("Error: Video to audio conversion failed.")
            return jsonify({"error": "Failed to convert video to audio"}), 500

        # Transcribe audio using Google Cloud Speech-to-Text
        with open(audio_path, 'rb') as audio_file:
            audio_content = audio_file.read()

        audio = speech.RecognitionAudio(content=audio_content)
        config = speech.RecognitionConfig(
            encoding=speech.RecognitionConfig.AudioEncoding.MP3,
            sample_rate_hertz=16000,
            language_code="en-US",
        )

        response = speech_client.recognize(config=config, audio=audio)
        transcripts = [result.alternatives[0].transcript for result in response.results]

        if not transcripts:
            print("Error: No transcription results found.")
            return jsonify({"error": "No transcription results found"}), 500

        transcription_text = " ".join(transcripts)
        print(f"Transcription successful: {transcription_text[:200]}...")  # Print first 200 chars

        # ---------------- Cohere v2 Chat call (minimal change) ----------------
        headers = {
            "Authorization": f"Bearer {COHERE_API_KEY}",
            "Content-Type": "application/json"
        }

        prompt_text = (
            "Generate exactly three multiple-choice questions based on this text:\n"
            f"{transcription_text}\n\n"
            "Rules:\n"
            "- Each question starts with a number and a period (e.g., 1.)\n"
            "- Each question has exactly four options labeled A., B., C., and D.\n"
            "- After the options, add a line 'Correct answer: <A|B|C|D>'\n"
            "- Output plain text only."
        )

        cohere_payload = {
            "model": "command-r-08-2024",
            "messages": [
                {"role": "user", "content": prompt_text}
            ],
            "max_tokens": 300,
            "temperature": 0.9
        }

        cohere_response = requests.post(
            COHERE_API_URL,
            json=cohere_payload,
            headers=headers,
            timeout=60
        )

        if cohere_response.status_code != 200:
            print(f"Error: Cohere API response failed: {cohere_response.text}")
            return jsonify({"error": "Failed to generate questions"}), 500

        raw_text = _extract_text_v2(cohere_response.json())
        if not raw_text:
            print("Error: No questions text returned by Cohere Chat API.")
            return jsonify({"error": "No questions generated"}), 500
        # ---------------------------------------------------------------------

        # Extract raw text and parse questions
        structured_questions = parse_questions(raw_text)

        return jsonify({"questions": structured_questions}), 200

    except Exception as e:
        print(f"Critical Error: {e}")
        return jsonify({"error": "An error occurred while generating questions"}), 500

def parse_questions(response_text):
    # Split the text into individual question blocks
    question_blocks = response_text.split("\n\n")
    questions = []

    # Process each question block
    for block in question_blocks:
        print("\nProcessing Block:", block)  # Debug: Log each question block

        # Split the block into lines
        lines = block.strip().split("\n")
        print("Split Lines:", lines)  # Debug: Log split lines of the block

        # Ensure the block contains a question
        if len(lines) < 2:
            print("Skipping Invalid Block")  # Debug: Log invalid blocks
            continue

        # Extract the question text
        question_line = lines[0]
        question_text = question_line.split(". ", 1)[1] if ". " in question_line else question_line
        print("Question Text:", question_text)  # Debug: Log extracted question text

        # Extract the options and find the correct answer
        options = []
        correct_answer_letter = None
        for line in lines[1:]:
            line = line.strip()
            # Handle A., B., C., D. and also a) / A) formats
            if line.lower().startswith("correct answer:"):
                correct_answer_letter = line.split(":")[-1].strip()
                continue
            match = re.match(r"^(?:[a-dA-D][\).]?\s)?(.+)$", line)
            if match:
                option_text = match.group(1).strip()
                # We already handled "Correct answer:" above, so only options get appended
                if not line.lower().startswith("correct answer:"):
                    options.append(option_text)

        print("Extracted Options:", options)  # Debug: Log extracted options
        print("Correct Answer Letter:", correct_answer_letter)  # Debug: Log the correct answer letter

        # Map the correct answer text
        correct_answer_text = ""
        if correct_answer_letter:
            option_index = ord(correct_answer_letter.upper()) - ord('A')  # Convert 'A'→0, 'B'→1, etc.
            if 0 <= option_index < len(options):
                correct_answer_text = options[option_index]
        print("Mapped Correct Answer Text:", correct_answer_text)  # Debug: Log mapped answer

        # Append the parsed question to the list
        if question_text and options:
            questions.append({
                "question": question_text,
                "options": options,
                "answer": correct_answer_text  # Use the full answer text
            })

    print("\nFinal Questions:", questions)  # Debug: Log final parsed questions
    return questions

# ---------- Standalone (local testing) ----------
if __name__ == '__main__':
    app = Flask(__name__)
    CORS(app)
    app.config["COHERE_API_KEY"] = os.getenv("COHERE_API_KEY", COHERE_API_KEY)
    app.register_blueprint(listen_bp, url_prefix='')
    app.run(host='0.0.0.0', port=5012, debug=True)