Gemini Live API
Use the Vertex AI Gemini Live API to create live voice-driven agentic applications. Businesses in all sectors want effective and aggressive solutions. Imagine frontline staff diagnosing problems, accessing critical information, and starting procedures in real time via voice commands and visual input. Developers can design next-generation, agentic industry apps with the help of the Gemini 2.0 Flash Live API.
These capabilities are extended to intricate industrial processes using this API. It uses multimodal data text, audio, and visual in a continuous livestream, in contrast to methods that only use one form of data. This makes it possible for intelligent assistants to genuinely comprehend and address the many needs of professionals in industries such as manufacturing, healthcare, energy, and logistics.
Use case for the Gemini 2.0 Flash Live API centered on industrial condition monitoring, particularly motor maintenance. Low-latency bidirectional phone and video communication with Gemini is made possible by the Live API. Through this API, one can give end users the experience of natural, human-like voice chats and give them the ability to use voice commands to stop the model’s responses. Text, audio, and video input can all be processed by the model, which can also produce text and audio output. The advantages of the API over traditional AI and its potential for strategic partnerships are demonstrated by this application.
A use case for condition monitoring that demonstrates multimodal intelligence
A live, bi-directional, multimodal streaming backend powered by the Gemini 2.0 Flash Live API is used in the presentation. It can process audio and visual data in real time, allowing for sophisticated reasoning and realistic dialogue. Building robust live multimodal systems with a streamlined, mobile-optimized user experience for factory floor operators is made possible by combining Google Cloud services with the API’s agentic and function calling capabilities. A motor with an obvious flaw serves as a real-world anchor for the presentation.
This is a condensed example of a smartphone flow:
- Real-time visual identification: Gemini recognises a motor by pointing the camera at it. It then rapidly summarises pertinent information from the manual, giving users rapid access to important equipment details.
- Real-time visual defect detection: Gemini listens to a spoken command such as “Inspect this motor for visual defects,” analyses the live video, locates the flaw, and provides an explanation of its cause.
- Simplified repair initiation: The system starts the repair procedure right away by automatically preparing and sending an email with the highlighted defect image and part details as soon as it detects a problem.
- Real-time identification of audio defects: Gemini uses pre-recorded audio of both healthy and defective motors to accurately identify the problematic one based on its sound profile and provides an explanation of its findings.
- Multimodal QA on operations: By aiming the camera at particular parts, operators can pose intricate queries on the motor. Gemini provides precise voice-based responses by cleverly fusing information from the motor manual with visual context.
The technical architecture
The Gemini Multimodal Livestreaming API on Google Cloud Vertex AI is used in the demonstration. While the standard Gemini API takes care of visual and audio feature extraction, the API controls the main workflow and agentic function calls.
The process includes:
- Agentic function calling: To ascertain the intended action, the API decodes user voice and visual input.
- Audio defect detection: The system collects motor sounds with the user’s permission, saves them in GCS, and then initiates a function that uses a prompt with samples of both healthy and defective sounds. The Gemini Flash 2.0 API then analyses the sounds to determine the motor’s condition.
- Visual inspection: The API employs the spatial knowledge of the Gemini Flash 2.0 API to identify and highlight faults by recognizing the intent to detect visual defects, capturing photos, and calling a function that performs zero-shot detection with a text prompt.
- Multimodal QA: The API determines the purpose of information retrieval when users ask questions, then applies RAG to the motor manual, integrates it with multimodal context, and leverages the Gemini API to deliver precise responses.
- Sending repair orders: The API automatically sends a repair order via email after identifying the intention to start a repair and extracting the part number and defect image using a pre-defined template.
Important features and business advantages with cross-sector use cases
The main features of the Gemini Multimodal Livestreaming API and their revolutionary industrial advantages are highlighted in this demonstration:
- Real-time multimodal processing: The API’s capacity to analyse live audio and video streams concurrently offers instant insights in dynamic settings, which is essential for maintaining operational continuity and avoiding downtime.
- Use case: A remote medical assistant might direct a field paramedic using live audio and video, getting real-time vital signs and visual data to offer knowledgeable assistance in an emergency.
- Advanced visual and auditory reasoning: Gemini’s advanced thinking deciphers minute auditory clues and intricate visual situations to provide precise diagnoses.
- Use Case: AI can reduce production interruptions in manufacturing by analysing the sounds and images of machinery to anticipate faults before they happen.
- Automated workflows through agentic function calling: The agentic nature of the API allows intelligent assistants to proactively initiate tasks, such as creating reports or starting procedures, which simplifies workflows.
- Use case: In logistics, an automated claim procedure and notification of the appropriate parties might be initiated by a voice command and visual confirmation of a damaged cargo.
- Scalability and seamless integration: The API’s interface with other Google Cloud services, which is based on Vertex AI, guarantees scalability and dependability for extensive deployments.
- Use case: Drones fitted with cameras and microphones might transmit real-time data to the API for agricultural applications such as insect detection and crop health analysis in real-time across large farmlands.
- Mobile-optimized user experience: Frontline workers may connect with the AI assistant at the time of need using devices they are accustomed to using due to the mobile-first design, which guarantees accessibility.
- Use case: Retail store employees might locate products, check inventories, and retrieve product information for customers right on the store floor by using speech and picture recognition.
- Proactive maintenance and efficiency gains: Industries can transition from reactive to predictive maintenance by providing real-time condition monitoring. This will minimise downtime, maximise asset utilisation, and boost overall sectoral efficiency.
- Use case: By using live audio and video streams, field technicians in the energy industry can utilise the API to diagnose problems with remote equipment, such as wind turbines, eliminating the need for expensive and time-consuming site visits.
Start now
This solution demonstrates state-of-the-art AI interaction with the Gemini Live API. Its codebase, which includes interruptible streaming audio, webcam/screen integration, low-latency voice, and a modular tool system through Cloud Functions, may be used as a solid foundation by developers. Create transformational, multimodal AI solutions that feel really conversational and aware by cloning the project, modifying its components, and starting to build them. The intelligent industry’s future is dynamic, multimodal, and accessible to all industries.
