Add README and update CLAUDE.md with project docs

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## Overview
This is a new, empty project. Update this file as the codebase takes shape.
Telegram Channel Analyzer Bot — fetches public channel history via Telethon, analyzes with Claude AI (chunked summarization pipeline), delivers reports via aiogram bot.
## Stack
- **Python 3.12**, async throughout
- **aiogram 3** — Telegram bot interface (commands, inline keyboards, progress messages)
- **Telethon** — userbot client for reading public channel history
- **anthropic** (AsyncAnthropic) — Claude API with streaming
- **pydantic-settings** — config from environment variables
## Architecture
- Both aiogram and Telethon share one asyncio loop (no threads)
- Telethon client is attached to the bot instance in `__main__.py`
- Analysis pipeline: Fetch → Chunk (token-bounded) → Summarize each chunk → Synthesize final report
- Rate limit handling: semaphore(1), 60s cooldown between chunks, retry with backoff on 429
- Output: Markdown→HTML conversion, split on section boundaries at 4000 chars
## Key Files
- `bot/config.py` — all settings from env vars, `CLAUDE_MODEL` selects the model
- `bot/services/analyzer.py` — Claude API calls, adaptive thinking only for opus-4-6
- `bot/services/chunker.py``MAX_TOKENS_PER_CHUNK` and `CHARS_PER_TOKEN` control chunking
- `bot/prompts/` — prompt templates per report type (chunk_summary.py, synthesis.py)
## Running
- Container-based: `Containerfile` + `compose.yml`
- `--login` flag for interactive Telethon session creation
- Session persists in `data/` volume
- `.env` file must not have inline comments (Podman/Docker limitation)
## Common Tasks
- To change chunk size: edit `MAX_TOKENS_PER_CHUNK` in `bot/services/chunker.py`
- To add a report type: add to `ReportType` enum, add prompts in both `prompts/` files
- To change model: set `CLAUDE_MODEL` env var; thinking params auto-adapt in `analyzer.py`

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# Telegram Channel Analyzer Bot
Telegram bot that analyzes public channels using Claude AI. Fetches channel history via Telethon, chunks messages, summarizes with Claude, and delivers a report back in Telegram.
## Report Types
- **Content Analysis** — topics, tone, themes, content strategy
- **Content + Stats** — above + posting frequency, engagement patterns
- **Full Audit** — all above + sentiment, audience insights, recommendations
## Prerequisites
- Telegram Bot token from [@BotFather](https://t.me/BotFather)
- Telegram API credentials from [my.telegram.org](https://my.telegram.org)
- Anthropic API key from [console.anthropic.com](https://console.anthropic.com)
- Docker or Podman
## Setup
```bash
cp .env.example .env
# Edit .env with your credentials
```
`.env` values (no inline comments):
```
BOT_TOKEN=123456:ABC...
TELEGRAM_API_ID=12345678
TELEGRAM_API_HASH=abc123def456...
TELEGRAM_PHONE=+1234567890
ANTHROPIC_API_KEY=sk-ant-...
CLAUDE_MODEL=claude-haiku-4-5
```
Available models: `claude-opus-4-6`, `claude-sonnet-4-6`, `claude-haiku-4-5`
## Run with Docker
```bash
# Build
docker build -f Containerfile -t tg-analyzer .
# First run: interactive login to create Telethon session
docker run -it --env-file .env -v ./data:/app/data tg-analyzer python -m bot --login
# Run the bot
docker run -d --env-file .env -v ./data:/app/data --name tg-analyzer --restart unless-stopped tg-analyzer
```
## Run with Podman
```bash
# Build
podman build -t tg-analyzer .
# First run: interactive login
podman run -it --env-file .env -v ./data:/app/data tg-analyzer python -m bot --login
# Run the bot
podman run -d --env-file .env -v ./data:/app/data --name tg-analyzer tg-analyzer
```
## Run with Compose
```bash
# Login first (see above), then:
podman compose up -d
# or
docker compose up -d
```
## Usage
Send to your bot in Telegram:
```
/analyze @channel_username
```
Select a report type from the inline keyboard. The bot will show progress as it fetches and analyzes.
## Project Structure
```
bot/
├── __main__.py # Entrypoint: aiogram + Telethon on shared loop
├── config.py # pydantic-settings from env vars
├── models.py # ReportType enum, ChannelMessage dataclass
├── handlers/
│ ├── start.py # /start, /help
│ └── analyze.py # /analyze + report type selection + progress
├── services/
│ ├── fetcher.py # Telethon: read channel history
│ ├── chunker.py # Token-bounded message chunking
│ ├── analyzer.py # Claude API: chunk summaries → synthesis
│ └── formatter.py # Split report into Telegram-safe HTML messages
└── prompts/
├── chunk_summary.py # Per-chunk extraction prompts
└── synthesis.py # Final synthesis prompts
```
## Rate Limits
The bot respects Anthropic API rate limits with automatic retry and cooldown between chunks. On the free/low tier (30K input tokens/min), a large channel may take several minutes.