zeph 0.21.4

Lightweight AI agent with hybrid inference, skills-first architecture, and multi-channel I/O
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# Zeph configuration for Telegram Test DC E2E testing.
# This template uses placeholder values — copy and fill before use:
#
#   cp config/telegram-test.toml .local/config/telegram-test.toml
#
# Then store the bot token in the vault:
#   cargo run --features full -- vault set ZEPH_TELEGRAM_TOKEN '<TOKEN>'
#
# Run Zeph with this config:
#   cargo run --features full -- --config .local/config/telegram-test.toml \
#       2>.local/testing/debug/telegram-session.log
#
# Notes:
#   - The bot token is obtained from @BotFather on the production Telegram.
#   - allowed_users must contain the Telegram username of the Telethon test account
#     created with get_session.py.

[agent]
name = "ZephTest"
max_tool_iterations = 10
auto_update_check = false

[[llm.providers]]
type = "openai"
model = "gpt-4o-mini"
max_tokens = 4096
embedding_model = "text-embedding-3-small"
default = true

[skills]
paths = [".local/testing/skills"]
max_active_skills = 5
prompt_mode = "auto"

[memory]
sqlite_path = ".local/testing/data/zeph-telegram-test.db"
history_limit = 50

[telegram]
# Token is injected via ZEPH_TELEGRAM_TOKEN env var (no token field needed in config).
# Replace with the Telegram username of your test account (created by get_session.py).
allowed_users = ["your_test_username"]
guest_mode = false
bot_to_bot = false
allowed_bots = []
max_bot_chain_depth = 1
stream_interval_ms = 3000

[tools]
enabled = true
summarize_output = true

[tools.shell]
timeout = 30
blocked_commands = []
allowed_commands = []
allowed_paths = []
allow_network = true

[vault]
backend = "age"

[debug]
enabled = true
output_dir = ".local/testing/debug"
format = "raw"

[security]
redact_secrets = true
autonomy_level = "full"

[cost]
enabled = true
max_daily_cents = 100