asxpi/tg-channel-analysis
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions
100% Made by Claude Opus 4.6 https://t.me/AISlopTest_bot
2 commits 1 branch 0 tags 39 KiB
  • Python 99.3%
  • Dockerfile 0.7%
Find a file
Exact
Sergei Poljanski 8a84145e15
 Add README and update CLAUDE.md with project docs
2026-02-22 23:00:23 +02:00
bot init 2026-02-22 21:33:23 +02:00
.containerignore init 2026-02-22 21:33:23 +02:00
.env.example init 2026-02-22 21:33:23 +02:00
.gitignore init 2026-02-22 21:33:23 +02:00
CLAUDE.md Add README and update CLAUDE.md with project docs 2026-02-22 23:00:23 +02:00
compose.yml init 2026-02-22 21:33:23 +02:00
Containerfile init 2026-02-22 21:33:23 +02:00
pyproject.toml init 2026-02-22 21:33:23 +02:00
README.md Add README and update CLAUDE.md with project docs 2026-02-22 23:00:23 +02:00

README.md

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

Setup

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

# 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

# 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

# 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.