Project Info
This project did not submit a demo video on Devpost.
Inspiration
We were inspired by our friend's brother, a small business owner who spoke about the challenges of communicating with their many clients through Whatsapp. We decided to work on this idea to help small business owners all around the world who communicate with their customers directly.
What it does
We built a platform that helps small business owners interact with their customers using AI agents. We are the first to build an AI agent first WhatsApp/messaging application, that's personalized based on the customers' previous interests and wants.
How we built it
We built our tools using MonsterAPI for their LLM inference interface (using the Zephyr LLM model), Reflex.dev for their frontend in Python, and Fetch AI for creating an environments for our AI agents. We used RAG, for customer specific knowledge search.
Challenges we ran into
We ran into many issues with API calls and connecting our frontend to our backends. We used a lot of new and exciting technologies implemented in new libraries, in which there wasn't too much documentation for us to work off of. This likely slowed down our development speed.
Accomplishments we're proud of
We built a working AI agent framework for communication with real phone numbers!
What we learned
We learned a lot about the different tools used within the AI agent framework and interactions fro creating a full stack application.
What's next
for Agentic AI Marketing Platform The future of AI agents looks pretty bright! We used the newest tools for LLM inference and creation of agents, and we got a MVP working within about 24 hrs of focused work. We're really excited by the quick development speed enabled by these new frameworks!
Analysis
View
Metric
- 21
- 14
- 7
Figures cover GitHub contributors during the hackathon window. A co-authored commit counts in full for each author, so per-member totals add up to more than the whole-team figures.
Technology
- ExpressIn code
- FastAPIIn code
- HTMLIn code
- Hugging FaceIn code
- JavaScriptIn code
- LlamaIndexIn code
- OpenAIIn code
- PythonIn code
- PyTorchIn code
- RedisIn code
10 of 10 appear in the indexed code.
AI coding agents
No AI coding agent signals were found in this repository.
Detected from committed agent config files and commit authorship. Absence of a signal is not proof an agent was unused.
Codebase size
Source size
79 KB
Source files
30
Counts recognized source files only; vendored directories, binaries and lockfiles are excluded, so this is smaller than the repository on disk.
Repository
mikezhang25/The-Guild
72 files · 779 KB · @ 5649629
Structure
Interface
10 files · 14%Screens, components and styles rendered to the user.
Application logic
35 files · 49%Domain rules, services and shared utilities.
Supporting
Layers are inferred from where files sit in the tree, not from reading the code. A project that names its directories unconventionally will read oddly here — open the file browser to check anything the diagram implies.
Languages
- Python51%
- HTML43%
- JavaScript3%
- Markdown2%
- Shell1%
Share of indexed source by file size. Binary and vendored files are excluded.
Dependencies
requirements.txt
pypi · 120- aiohttp
- aiosignal
- alembic
- annotated-types
- anyio
- async-timeout
- attrs
- beautifulsoup4
- bidict
- bs4
- certifi
- charset-normalizer
- click
- cloudpickle
- dataclasses-json
- Deprecated
- dirtyjson
- distro
- +102 more
whatsapp/package.json
npm · 3- express
- qrcode-terminal
- whatsapp-web.js
reflex-chat/webui/requirements.txt
pypi · 2- openai
- reflex
Declared in the repository’s manifests at the indexed commit. A declared package is not proof it is used, and runtime dependencies are listed first.
This project’s features have not been analysed yet.
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