new version

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+bot.png filter=lfs diff=lfs merge=lfs -text
+user.png filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,7 +1,7 @@
 import time
 import gradio as gr
 import pandas as pd
-import openvino_genai
+import openvino_genai as ov_genai
 from huggingface_hub import snapshot_download
 from threading import Lock, Event
 import os
@@ -20,6 +20,11 @@ import textwrap
 from queue import Queue, Empty
 from concurrent.futures import ThreadPoolExecutor
 from typing import Generator
+import warnings
+from transformers import pipeline  # Added for Whisper
+
+# Suppress specific OpenVINO deprecation warning
+warnings.filterwarnings("ignore", category=DeprecationWarning, module="openvino.runtime")
 
 # Google API configuration
 GOOGLE_API_KEY = "AIzaSyAo-1iW5MEZbc53DlEldtnUnDaYuTHUDH4"
@@ -43,12 +48,15 @@ class UnifiedAISystem:
     def initialize_models(self):
         """Initialize all required models"""
         # Download models if not exists
-        if not os.path.exists("mistral-ov"):
-            snapshot_download(repo_id="OpenVINO/mistral-7b-instruct-v0.1-int8-ov", local_dir="mistral-ov")
-        if not os.path.exists("internvl-ov"):
-            snapshot_download(repo_id="OpenVINO/InternVL2-1B-int8-ov", local_dir="internvl-ov")
-        if not os.path.exists("whisper-ov-model"):
-            snapshot_download(repo_id="OpenVINO/whisper-tiny-fp16-ov", local_dir="whisper-ov-model")
+        model_paths = {
+            "mistral-ov": "OpenVINO/mistral-7b-instruct-v0.1-int8-ov",
+            "internvl-ov": "OpenVINO/InternVL2-1B-int8-ov"
+            # Removed distil-whisper download since we're using transformers version
+        }
+        
+        for local_dir, repo_id in model_paths.items():
+            if not os.path.exists(local_dir):
+                snapshot_download(repo_id=repo_id, local_dir=local_dir)
 
         # CPU-specific configuration
         cpu_features = cpuinfo.get_cpu_info()['flags']
@@ -59,16 +67,13 @@ class UnifiedAISystem:
             config_properties["INFERENCE_PRECISION_HINT"] = "f32"
 
         # Initialize Mistral model with updated configuration
-        self.mistral_pipe = openvino_genai.LLMPipeline(
+        self.mistral_pipe = ov_genai.LLMPipeline(
             "mistral-ov",
             device="CPU",
             PERFORMANCE_HINT="THROUGHPUT",
             **config_properties
         )
 
-        # Initialize Whisper for audio processing
-        self.whisper_pipe = openvino_genai.WhisperPipeline("whisper-ov-model", device="CPU")
-
     def load_data(self, file_path):
         """Load student data from file"""
         try:
@@ -119,7 +124,7 @@ class UnifiedAISystem:
         completion_event = Event()
         error = [None]  # Use list to capture exception from thread
 
-        optimized_config = openvino_genai.GenerationConfig(
+        optimized_config = ov_genai.GenerationConfig(
             max_new_tokens=max_tokens,
             temperature=0.3,
             top_p=0.9,
@@ -129,7 +134,7 @@ class UnifiedAISystem:
 
         def callback(tokens):  # Accepts multiple tokens
             response_queue.put("".join(tokens))
-            return openvino_genai.StreamingStatus.RUNNING
+            return ov_genai.StreamingStatus.RUNNING
 
         def generate():
             try:
@@ -223,7 +228,7 @@ class UnifiedAISystem:
 
             # Lazy initialize InternVL
             if self.internvl_pipe is None:
-                self.internvl_pipe = openvino_genai.VLMPipeline("internvl-ov", device="CPU")
+                self.internvl_pipe = ov_genai.VLMPipeline("internvl-ov", device="CPU")
 
             with self.pipe_lock:
                 self.internvl_pipe.start_chat()
@@ -282,7 +287,7 @@ class UnifiedAISystem:
             return np.array([], dtype=np.float32)
 
     def transcribe(self, audio):
-        """Transcribe audio using Whisper model with improved error handling"""
+        """Transcribe audio using OpenAI Whisper-small model"""
         if audio is None:
             return ""
         sr, data = audio
@@ -298,9 +303,17 @@ class UnifiedAISystem:
             if len(processed) < 8000:  # 0.5 seconds at 16kHz
                 return ""
 
-            # Use OpenVINO Whisper pipeline
-            result = self.whisper_pipe.generate(processed)
-            return result
+            # Lazy initialize Whisper - USING TRANSFORMERS PIPELINE
+            if self.whisper_pipe is None:
+                self.whisper_pipe = pipeline(
+                    "automatic-speech-recognition",
+                    model="openai/whisper-small",
+                    device="cpu"  # Use CPU for consistency
+                )
+
+            # Use transformers pipeline for transcription
+            result = self.whisper_pipe(processed, return_timestamps=False)
+            return result["text"]
         except Exception as e:
             print(f"Transcription error: {e}")
             return "❌ Transcription failed - please try again"

requirements.txt

@@ -1,15 +1,18 @@
-gradio==4.26.0
-openvino-genai>=1.0.0
-librosa==0.10.0
-numpy>=1.24.0
-scipy>=1.10.0
-huggingface_hub>=0.21.4
-google-api-python-client>=2.0.0
-pandas>=2.0.0
-requests>=2.31.0
-Pillow>=10.0.0
-py-cpuinfo>=9.0.0
-openvino>=2023.2.0
-PyPDF2>=3.0.0
-python-docx>=1.1.0
-soundfile>=0.12.0
+gradio==4.32.0
+openvino-genai==0.4.0
+huggingface_hub==0.23.2
+pandas==2.2.2
+numpy==1.26.4
+requests==2.32.3
+Pillow==10.3.0
+openvino==2024.1.0
+librosa==0.10.2.post1
+google-api-python-client==2.132.0
+PyPDF2==3.0.1
+python-docx==1.1.2
+transformers==4.41.2
+torch==2.3.0
+torchaudio==2.3.0
+ffmpeg-python==0.2.0
+soundfile==0.12.1
+py-cpuinfo==9.0.0