Traditional context-aware query response systems predominantly rely on textual information, often excluding multimedia content, which limits their effectiveness. Our system addresses this gap by incorporating advanced techniques for audio and visual context extraction, including audio-to-text conversion, video OCR, and Object Recognition. By seamlessly converting audio inputs to text and extracting text from video frames, our system enhances the processing of multimedia queries. This approach allows for more comprehensive context extraction and improved response generation, significantly elevating the accuracy and relevance of answers in multimedia settings. Ultimately, our system transforms query response mechanisms, enabling more dynamic and contextually aware interactions with multimedia content.