Cohere Cohere Classify AI technology Top Builders

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Cohere classify

Cohere classify is a large language model that classify text content. Classify organizes information for more effective content moderation, analysis, and chatbot experiences.

General
Relese dateNovember 15, 2021
AuthorCohere
Documentationhttps://docs.cohere.ai/reference/classify
TypeAutoregressive, Transformer, Language model
Discordhttps://discord.gg/lablab-ai-877056448956346408

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    Gléssi-Tché

    Gléssi-Tché

    GLESSI-TCHE a le potentiel de révolutionner l'accès à l'information et aux services pour les agriculteurs béninois, en leur offrant une solution intégrée à l'IA et adaptée à leurs besoins uniques. Fonctionne dans les langues locales comme le Fon, le Yoruba et le Dendi, supprimant les barrières linguistiques. Accessible via des téléphones portables ou même des appareils simples et en combinant technologie avancée et sensibilité locale, GLESSI-TCHE peut jouer un rôle crucial dans l'autonomisation des agriculteurs et l'amélioration de la productivité agricole au Bénin. Les fonctionalités de GLESSI-TCHE: *Accès aux informations agricoles cruciales : Obtenez des réponses à vos questions sur la plantation, le choix des cultures, la lutte antiparasitaire, la gestion des sols, les prévisions météorologiques, les prix du marché, les techniques post-récolte. * Diagnostic des maladies et des parasites : Décrivez les symptômes ou prenez des photos pour qu'Agrispeaker diagnostique les problèmes potentiels et recommande des solutions. * Système d'alerte précoce : Recevez des alertes en temps réel sur les risques météorologiques tels que les sécheresses, les inondations et les invasions de parasites pour vous préparer et minimiser les pertes. * Optimisation de l'irrigation : Utilisez les recommandations d'Agrispeaker basées sur les données locales pour économiser l'eau et améliorer les rendements des cultures. * Accès au marché : Connectez-vous directement avec les acheteurs pour obtenir de meilleurs prix pour vos produits et réduire la dépendance vis-à-vis des intermédiaires.

    WeCare Caretaker Assistant

    WeCare Caretaker Assistant

    We have built a solution for agencies which provide the caretaker services for parents who are in search of babysitters for their child. When users call the agency after business hours or when agents are not available for assistance, we are routing them to leave a voicemail with their babysitter requirement and contact number. With this solution, agents can focus on more complex tasks rather than manually retrieving voicemails, analysing them and coming up with a resolution. When the caller dials the agency phone number during office closed hours or peak hours when agents are not available to serve them, we route the caller to the voicemail menu where we ask them to leave a voicemail with babysitting requirements and their contact details, etc. Once the voicemail is available, we extract it and convert this speech to text using OpenAI’s whisper API which gives us the voicemail transcription. After that, we meticulously perform the prompt engineering for ChatGPT API to provide us all the required information from voicemail like intent, sentiment, babysitting date and time, etc in JSON format. Using this information, we query the EmployeeSchedule table which is in the H2 database. Once we have the information about availability of babysitters, we query RedisJSON to get the employee profile information like employee name, contact details, date of birth, languages spoken, image, etc. We then build a PDF document using itext library. This PDF containing available babysitter information will be sent on the caller’s WhatsApp. After this, we send an SMS to the agency as an alert notification about the customer enquiry and ask them to get in touch with the customer. Github link - https://github.com/technocouple/technocouple-caretaker-assistant Video link - https://drive.google.com/drive/folders/1NBew2U0Xgtm04ubQszjLvZV92fowR6-D?usp=sharing Presentation - https://drive.google.com/file/d/1TBMSU5Ohyn1v2P2u_RqbZOpuCvWv1Crq/view?usp=share_link DEMO is at the end of the video.