feat: add product support plugin using fast-graphrag

plugins/product_support_plugin/.dockerignore

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+.venv
+docs
+.env

plugins/product_support_plugin/.env.example

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+TELEGRAM_BOT_TOKEN=

plugins/product_support_plugin/.python-version

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+3.10

plugins/product_support_plugin/Dockerfile

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+FROM python:3.10.1-slim
+
+# Install build dependencies
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY --from=ghcr.io/astral-sh/uv:latest /uv /uvx /bin/
+WORKDIR /app
+
+# Copy project files
+COPY pyproject.toml .
+COPY . .
+RUN uv venv
+RUN uv sync --frozen
+# Run the application
+CMD ["uv", "run", "telegram_bot.py"]

plugins/product_support_plugin/README.md

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+# Product Support Plugin
+
+A RAG (Retrieval Augmented Generation) plugin for analyzing product support based on given documentation to identify key features, user interactions, data collection methods, and how different components of the platform work together.
+
+## Overview
+
+This plugin processes documentation from Mapeo, an offline-first mapping and monitoring platform, to provide insights about:
+
+- Key features and functionality
+- User interaction patterns 
+- Data collection methodologies
+- Component integrations
+- System architecture
+
+## Requirements
+
+- Python 3.10.1 or higher
+- uv package manager (recommended)
+- Dependencies listed in pyproject.toml
+
+## Installation
+
+1. Clone the repository:
+
+## Usage
+
+The plugin can be used in three ways:
+
+- As a CLI tool for direct queries
+- Through the Telegram bot interface
+- By importing and calling from your Python code
+
+To install dependencies with uv (recommended):
+
+### Docker
+
+To run the Awana Telegram Bot using Docker, you can use the following command:
+
+```bash
+docker run -v ./bot:/app/mapeo_docs -e TELEGRAM_BOT_TOKEN=xxx:xxx-xxx -e OPENAI_API_KEY=sk-proj-xxx communityfirst/awana_telegram_bot
+```

plugins/product_support_plugin/cli.py

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+from main import initialize_grag, query
+
+def main():
+    print("Welcome to Product Support Assistant!")
+    print("Ask questions about the product. Type 'exit' or 'quit' to end the session.")
+
+    # Initialize the GraphRAG once
+    grag = initialize_grag()
+
+    while True:
+        question = input("\nYour question: ").strip()
+
+        if question.lower() in ['exit', 'quit']:
+            print("Goodbye!")
+            break
+
+        if not question:
+            print("Please enter a valid question.")
+            continue
+
+        try:
+            response = query(question, grag)
+            print("\nAnswer:", response)
+        except Exception as e:
+            print(f"An error occurred: {str(e)}")
+
+if __name__ == "__main__":
+    main()