diff --git a/README.md b/README.md index d23b4aa..fe8979b 100644 --- a/README.md +++ b/README.md @@ -1,26 +1,30 @@ -# Empowering-Investors-Hackathon - -## Submission Instruction: - 1. Fork this repository - 2. Create a folder with your Team Name - 3. Upload all the code and necessary files in the created folder - 4. Upload a **README.md** file in your folder with the below mentioned informations. - 5. Generate a Pull Request with your Team Name. (Example: submission-XYZ_team) - -## README.md must consist of the following information: - -#### Team Name - -#### Problem Statement - -#### Team Leader Email - +#### Team Name - Devesh +#### Problem Statement - Content Curation Education + Identifying Misleading Claims +#### Team Leader Email - devesh.xin@gmail.com ## A Brief of the Prototype: - This section must include UML Diagrams and prototype description +A WhatsApp chatbot catering to traders and investors, our solution empowers users to communicate and inquire in their regional languages. The chatbot offers versatile functionalities: +-->users can seek recommendations for topic-specific videos in natural language +-->ask questions specific to videos in their mother tongue (both by typing or in voice note) and can have interaction like ChatGPT +-->assess content authenticity by sharing links of youtube-videos, Instagram reels , articles, posts from telegram groups + ## Tech Stack: - List Down all technologies used to Build the prototype + We harness the power of Large Language models (LangChain&LLAMA) to efficiently analyze extensive online content. + +Integration with WhatsApp: Our solution seamlessly integrates processed data into chatbot,offering users easy access to insights. + +AWS Infrastructure: To handle complexity of model, we utilize AWS services(EC2), ensuring scalability. + +Data Storage: Results are stored in vector databases, optimizing data retrieval, providing quick access to relevant information. + +Automated Web Content Retrieval: Python scripts automate the process of fetching content from web, ensuring timely data acquisition. + +Streamlined Information Delivery: Through this synergy of technology & automation, we deliver reliable information to users in user-friendly format. ## Step-by-Step Code Execution Instructions: - This Section must contain a set of instructions required to clone and run the prototype so that it can be tested and deeply analyzed + To run this whatsapp bot along with crawwler You can dowload trained model from this [link](https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin). Also generating Twilio API key to integrate with python SDK. ## What I Learned: - Write about the biggest learning you had while developing the prototype + It was really exciting on working on problem of this magnitude and impact. We managed to come up with a very promising solution that leverages GenAL and Large Language Models + diff --git a/submission-Devesh/code__.zip b/submission-Devesh/code__.zip new file mode 100644 index 0000000..0a9c525 Binary files /dev/null and b/submission-Devesh/code__.zip differ diff --git a/submission-Devesh/readme.md b/submission-Devesh/readme.md new file mode 100644 index 0000000..fe8979b --- /dev/null +++ b/submission-Devesh/readme.md @@ -0,0 +1,30 @@ +#### Team Name - Devesh +#### Problem Statement - Content Curation Education + Identifying Misleading Claims +#### Team Leader Email - devesh.xin@gmail.com + +## A Brief of the Prototype: +A WhatsApp chatbot catering to traders and investors, our solution empowers users to communicate and inquire in their regional languages. The chatbot offers versatile functionalities: +-->users can seek recommendations for topic-specific videos in natural language +-->ask questions specific to videos in their mother tongue (both by typing or in voice note) and can have interaction like ChatGPT +-->assess content authenticity by sharing links of youtube-videos, Instagram reels , articles, posts from telegram groups + + +## Tech Stack: + We harness the power of Large Language models (LangChain&LLAMA) to efficiently analyze extensive online content. + +Integration with WhatsApp: Our solution seamlessly integrates processed data into chatbot,offering users easy access to insights. + +AWS Infrastructure: To handle complexity of model, we utilize AWS services(EC2), ensuring scalability. + +Data Storage: Results are stored in vector databases, optimizing data retrieval, providing quick access to relevant information. + +Automated Web Content Retrieval: Python scripts automate the process of fetching content from web, ensuring timely data acquisition. + +Streamlined Information Delivery: Through this synergy of technology & automation, we deliver reliable information to users in user-friendly format. + +## Step-by-Step Code Execution Instructions: + To run this whatsapp bot along with crawwler You can dowload trained model from this [link](https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin). Also generating Twilio API key to integrate with python SDK. + +## What I Learned: + It was really exciting on working on problem of this magnitude and impact. We managed to come up with a very promising solution that leverages GenAL and Large Language Models +