TGCore SDK
A fluent DSL framework for composing Telegram, APIs, and AI workflows.
Turn messy APIs into clean, composable chains.
Like Flutter for backend logic.
# Chain your backend, not JSON
result = await tg.app("groq.ai", tgmod=True)\
.model("moonshotai/kimi-k2-instruct-0905")\
.messages(
tg.user("Say test")
)\
.stream(False)\
.send()
print(result.text())
Framework TgCore |
TeamKillerX Docs IO |
TgCore API Docs |
Original Telegram API Docs
Security-focused Telegram Bot Framework.
- Getting Started
- Installation
- What makes TGCore different
- Chain & DSL
- AI Chain
- Traditional API
- TGCore Fluent Builder
- Ultra-fast with parallel
- System Benchmark
- payload DSL (domain-specific language)
- Clean architecture
- Authentication
- Usage
- Simple comparison
- New fluent chain API
- sendMessage
- Simple Call
- Builder Pattern
- Rest API & TGCore Bot
- Why TGCore?
- Compared to Native Telegram API
- License
- Contributing
- Status
- Author
What makes TGCore different
- Secure and scalable architecture
- Async-first design
- Fluent API builder pattern
- Supports Telegram bots, APIs, and AI workflows
- Designed for complex system composition
📦 Installation
pip install tgcore
Or install locally:
pip install -e .
Getting started
from tgcore import Client
tg = Client(api_key="YOUR_API_KEY")
await tg.raw.sendMessage()\
.chat_id(123456789)\
.text("Hello from TGCore")\
.send()
Chain & DSL
await tg.use.default\
.route("games", "chain")\
.user(
tg.where(
name="Randy Architect",
age="145",
hobi="all"
)
)\
.database(
tg.where(
mongodb=True,
redis=True,
sqlite=True
)
)\
.pretty()
AI Chain
msg = tg.msg.core("Hello")
res = await tg.ai.groq()\
.model("kimi-k2")\
.messages([msg])\
.send()
print(res.text())
Traditional API
send_message(
chat_id,
text,
parse_mode,
disable_notification,
reply_markup,
protect_content
)
TGCore Fluent Builder
send_message()\
.chat_id(id)\
.text("hello")\
.send()
Ultra-fast with parallel
Ultra-fast AES-256 cryptography for Telegram MTProto with hardware AES-NI acceleration.
- Mode:
tgcryptoorcryptg
tg.parallel(
install_type="tgcrypto",
debug=True
)
System Benchmark
Standardized routing layer across APIs
- API devs, etc
- Use
routerenums:/v1,/openai,/apior custom
from tgcore import Client
tg = Client(
bearer_token="gsk_xxxx",
base_url="https://api.groq.com",
is_bearer=True
)
await (
tg.app(
"v1/chat/completions",
router="/openai",
tgmod=False
)
.model("moonshotai/kimi-k2-instruct-0905")
.messages(tg.user("say test"))
).execute()
- TGCore (full control)
from tgcore import Client
tg = Client(api_key="xxxxxx")
result = await tg.app("groq.ai", tgmod=True)\
.model("moonshotai/kimi-k2-instruct-0905")\
.messages(
tg.user("Say test")
)\
.send()
print(result.text())
Simple comparison
❌ Regular Telegram
InlineKeyboardMarkup([
[InlineKeyboardButton("A", url="...")]
])
✅ tgcore (which you already use)
tg.kb.inline().url("A", "...").build()
payload DSL (domain-specific language)
JSON is the output, not the source of truth The architecture should absorb API changes
result = await tg.use.default\
.route("gemini", "gemini-2.5-flash")\
.contents(
[
tg.where(
parts=[tg.where(text="lu siapa?")]
)
]
)\
.system_instruction(
tg.where(
parts=[tg.where(text="kamu adalah TgCore komedi lucu")]
)
)\
.generationConfig(
tg.where(
temperature=1.0,
topP=0.8,
topK=10
)
)\
.send()
return result.text()
Clean architecture
- Architecture: clean
- Code: perfect
- Async: working
tg = Client(api_key="something", base_url="https://your_domain.com")
result = await tg.use.default\
.endpoint("/v1/chat/completions")\
.model("model")\
.messages([...])\
.stream(False)\
.send()
print(result)
🔑 Authentication
Create client instance:
from tgcore import Client
client = Client("fw_live_xxx")
await client.telegram.send_message(
chat_id="@channel",
text="hello"
)
👾 Usage
Platform Tools
resp = await tg.platform.facebook\
.download(url="https://facebook.com/...")\
.send()
New fluent chain API
Parameters can be chained (builder-style) without having to write long functions like send_message(...).
Example of using fluent chain API:
# version: 1.0.43+, 1.0.68+
async def full_code():
_ = await tg.fetch_post(
"/api/web/facebook/download",
url="https://www.facebook.com/groups/788889186033999/permalink/1325624742360438/?app=fbl",
check_errors=True
)
await tg.raw\
.sendVideo()\
.chat_id(chat_id)\
.video(_.data.video[0].url)\
.reply_markup(
tg.kb().copy_text(
"this SDK builder style",
"use a framework"
)
.build()
)\
.skip()
Example:
await tg.raw.sendMessage().chat_id(chat_id).text("tgcore").skip()
That's the concept of builder + fluent chain API.
sendMessage
# Latest version 1.0.16+, 1.0.68+
# Support Pyrogram/Kurigram (KeyboardBuilder)
from tgcore import Client, KeyboardBuilder
tg = Client()
async def send():
await (
tg.raw
.sendMessage(
chat_id=m.chat.id,
text="Testing",
reply_markup=(
KeyboardBuilder()
.url("This Url", "https://github.com/TeamKillerX/tgcore")
.style("This color", "danger", callback_data="#abc")
.build()
)
)
.execute()
)
New button
# old version: 1.0.14
from tgcore import Client, KeyboardBuilder
tg = Client()
async def use_pyrogram(m):
await tg.telegram.send_message(
chat_id=str(m.chat.id),
text="This Button",
reply_markup=(
KeyboardBuilder()
.row("GitHub", url="https://github.com")
.row("Docs", url="https://www.learnpython.org/")
.row("Pypi", url="https://pypi.org/project/tgcore/")
.build()
)
Simple Call
await client.telegram.send_message(
chat_id="@channel",
text="Hello world"
)
Builder Pattern
await (
client.telegram
.send_photo_call(chat_id="@channel", photo="https://img.jpg")
.execute()
)
Rest API & TgCore Bot
# Version: 1.0.68+
from tgcore import Client, KeyboardBuilder
tg = Client()
async def pinterest_images(q: str):
kw = await tg._post(
"/api/web/pinterest",
payload={"query": q}
)
like_ts = tg.to_obj(kw)
if not like_ts.ok or not like_ts.data:
return None
return like_ts.data.pins[1].media.images.orig.url
async def send_photo():
newurl = await pinterest_images("Real coding")
resp = await tg.raw.sendPhoto(
chat_id=-100123456789,
photo=newurl,
reply_markup=(
KeyboardBuilder()
.url("View Pinterest", newurl)
.url("Tgcore on PyPI", "https://pypi.org/project/tgcore/")
.row()
.url("Tgcore on NPMJS", "https://www.npmjs.com/package/@xtsea/tgcore-ts")
.build()
)
).execute()
return tg.to_obj(resp).ok
🔄 Token Rotation Support
The server supports storing encrypted tokens using AES-256-GCM. The SDK automatically uses the active token version.
🔒 Security Model
TgCoreSDK never exposes bot tokens to clients.
Flow:
Client → API Gateway → Decrypt → Telegram API
Benefits:
- prevents token leaks
- safe frontend usage
- safe monitoring dashboards
- supports IP restrictions
Why TGCore?
Unlike traditional Telegram SDKs, TGCore is built as a secure middleware layer that prevents token leaks, enforces API-key auth, and supports enterprise-grade scaling.
Designed for production, not demos.
Compared to Native Telegram API
| Feature | Telegram API | TGCore |
|---|---|---|
| Token Exposure | Yes | No |
| Auth Layer | None | API Key + Secret |
| Proxy Support | Manual | Built-in |
| Multi Bot | Limited | Yes |
| Webhook Security | Basic | Zero-Trust |
🧾 License
Licensed under Apache License 2.0
You may:
- use commercially
- modify
- distribute
- sublicense
🤝 Contributing
Pull requests welcome. For major changes, open an issue first to discuss what you would like to change.
🔥 Status
Production Ready
👑 Author
Built with ❤️ by Randy W
Metadata
Release files for tgcore 1.0.98
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|---|---|---|---|---|
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Total release size: 79.1 kB
Release files / tgcore-1.0.98.tar.gz
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| Tags | Source |
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Security for tgcore 1.0.98
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