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2025-09-25 07:58:08 Kaushal Lamkhade: Updated project details
Projects/CRM System.md ..
@@ 39,3 39,104 @@
- **Containerization**: Docker
- **Background task runner**: Celery / RQ for async jobs (e.g., doc parsing)
- **Caching**: Redis for messages and sessions
+
+ # Client Communication Management Application – High-Level Overview
+
+ ## 1. Tech Stack
+ - **Backend (Python)**
+ - **FastAPI** (recommended for async, lightweight, API-first approach) or Django (if you want batteries-included features).
+ - **SQLAlchemy** or **Django ORM** (for database interactions).
+ - **Database**
+ - **PostgreSQL** (yes, perfectly suited for multi-tenant, relational data storage).
+ - **Frontend**
+ - React / Next.js (or Vue/Angular depending on preference).
+ - Admin dashboard + Client dashboard.
+ - **AI/ML Integrations**
+ - OpenAI API / Perplexity API / Custom AI connectors.
+ - Knowledge Base Indexing (e.g., **LangChain + Vector DB** like **Postgres pgvector**, **Weaviate**, or **Pinecone**).
+ - MCP Server (for tool orchestration + context passing).
+ - **Communication Channels**
+ - **Telegram Bot API** integration.
+ - **Email integration** (IMAP/SMTP or services like SendGrid/Mailgun).
+ - **Infrastructure**
+ - Docker for containerization.
+ - Nginx / Traefik for reverse proxy.
+ - Optional: Kubernetes for scaling.
+
+ ---
+
+ ## 2. Core Modules & Features
+
+ ### 🔹 Client Onboarding
+ - Form to capture client + project details.
+ - Generate dedicated project page for embedding AI bot.
+ - Multi-tenant user management (each client = tenant).
+
+ ### 🔹 Communication Channels
+ - Configurable options for each client:
+ - Telegram bot setup.
+ - Email inbox setup.
+ - Future: WhatsApp, Slack, etc.
+
+ ### 🔹 AI Model Connector
+ - Ability to select which AI model:
+ - ChatGPT (OpenAI).
+ - Perplexity.
+ - Others (pluggable architecture).
+ - Standardized response pipeline regardless of model.
+
+ ### 🔹 Knowledge Base
+ - Upload project docs (PDF, DOCX, TXT).
+ - Import from Drive links / Notion / Confluence.
+ - Store embeddings in **pgvector** (Postgres extension).
+ - Retrieval-Augmented Generation (RAG) for query responses.
+
+ ### 🔹 Query Processing
+ - Customer submits query → AI pipeline:
+ 1. Normalize input.
+ 2. Retrieve context from Knowledge Base.
+ 3. Feed context + query to chosen AI model.
+ 4. Return AI response.
+ - Option for admin override & monitoring.
+
+ ### 🔹 Monitoring & Admin Portal
+ - View all conversations per client/project.
+ - Override/edit AI responses.
+ - Track usage per channel/model.
+ - Analytics & logs.
+
+ ---
+
+ ## 3. Database Design (Postgres)
+
+ **Tables (example):**
+ - `clients` → Client info (name, domain, etc.)
+ - `projects` → Linked to clients (stores project metadata).
+ - `channels` → Configured communication channels.
+ - `ai_models` → Available model connectors.
+ - `knowledge_base` → Documents & embeddings.
+ - `queries` → User queries & responses.
+ - `users` → Client admins & internal admins.
+
+ Use **pgvector** for embeddings storage and similarity search.
+
+ ---
+
+ ## 4. External Integrations
+ - **Telegram Bot API** → Webhook for messages.
+ - **Email API** → IMAP/SMTP or SendGrid.
+ - **AI APIs** → OpenAI, Perplexity, etc.
+ - **Storage** → AWS S3 / GCP Storage for uploaded files.
+ - **Drive APIs** → Google Drive API (for fetching docs).
+ - **Authentication** → JWT or OAuth2 (multi-tenant).
+
+ ---
+
+ ## 5. Deployment & Scaling
+ - Containerize with Docker.
+ - CI/CD (GitHub Actions / GitLab CI).
+ - Cloud hosting (AWS/GCP/Azure/DigitalOcean).
+ - Use Postgres + pgvector for persistence + semantic search.
+ - Caching layer (Redis) for session storage & rate limiting.
+
+ ---
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