nomyo-ai/nomyo
2
1
Fork 0
Code Issues Pull requests Projects Releases 8 Packages Wiki Activity Actions

Hello World!

Browse source
This commit is contained in:
Alpha Nerd 2025-12-17 16:03:20 +01:00 • committed by GitHub
commit 5c27f51941
No known key found for this signature in database
GPG key ID: B5690EEEBB952194
9 changed files with 1384 additions and 0 deletions
Download patch file Download diff file Expand all files Collapse all files

201
LICENSE Normal file
View file

@ -0,0 +1,201 @@
Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
1. Definitions.
"License" shall mean the terms and conditions for use, reproduction,
and distribution as defined by Sections 1 through 9 of this document.
"Licensor" shall mean the copyright owner or entity authorized by
the copyright owner that is granting the License.
"Legal Entity" shall mean the union of the acting entity and all
other entities that control, are controlled by, or are under common
control with that entity. For the purposes of this definition,
"control" means (i) the power, direct or indirect, to cause the
direction or management of such entity, whether by contract or
otherwise, or (ii) ownership of fifty percent (50%) or more of the
outstanding shares, or (iii) beneficial ownership of such entity.
"You" (or "Your") shall mean an individual or Legal Entity
exercising permissions granted by this License.
"Source" form shall mean the preferred form for making modifications,
including but not limited to software source code, documentation
source, and configuration files.
"Object" form shall mean any form resulting from mechanical
transformation or translation of a Source form, including but
not limited to compiled object code, generated documentation,
and conversions to other media types.
"Work" shall mean the work of authorship, whether in Source or
Object form, made available under the License, as indicated by a
copyright notice that is included in or attached to the work
(an example is provided in the Appendix below).
"Derivative Works" shall mean any work, whether in Source or Object
form, that is based on (or derived from) the Work and for which the
editorial revisions, annotations, elaborations, or other modifications
represent, as a whole, an original work of authorship. For the purposes
of this License, Derivative Works shall not include works that remain
separable from, or merely link (or bind by name) to the interfaces of,
the Work and Derivative Works thereof.
"Contribution" shall mean any work of authorship, including
the original version of the Work and any modifications or additions
to that Work or Derivative Works thereof, that is intentionally
submitted to Licensor for inclusion in the Work by the copyright owner
or by an individual or Legal Entity authorized to submit on behalf of
the copyright owner. For the purposes of this definition, "submitted"
means any form of electronic, verbal, or written communication sent
to the Licensor or its representatives, including but not limited to
communication on electronic mailing lists, source code control systems,
and issue tracking systems that are managed by, or on behalf of, the
Licensor for the purpose of discussing and improving the Work, but
excluding communication that is conspicuously marked or otherwise
designated in writing by the copyright owner as "Not a Contribution."
"Contributor" shall mean Licensor and any individual or Legal Entity
on behalf of whom a Contribution has been received by Licensor and
subsequently incorporated within the Work.
2. Grant of Copyright License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
copyright license to reproduce, prepare Derivative Works of,
publicly display, publicly perform, sublicense, and distribute the
Work and such Derivative Works in Source or Object form.
3. Grant of Patent License. Subject to the terms and conditions of
this License, each Contributor hereby grants to You a perpetual,
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
(except as stated in this section) patent license to make, have made,
use, offer to sell, sell, import, and otherwise transfer the Work,
where such license applies only to those patent claims licensable
by such Contributor that are necessarily infringed by their
Contribution(s) alone or by combination of their Contribution(s)
with the Work to which such Contribution(s) was submitted. If You
institute patent litigation against any entity (including a
cross-claim or counterclaim in a lawsuit) alleging that the Work
or a Contribution incorporated within the Work constitutes direct
or contributory patent infringement, then any patent licenses
granted to You under this License for that Work shall terminate
as of the date such litigation is filed.
4. Redistribution. You may reproduce and distribute copies of the
Work or Derivative Works thereof in any medium, with or without
modifications, and in Source or Object form, provided that You
meet the following conditions:
(a) You must give any other recipients of the Work or
Derivative Works a copy of this License; and
(b) You must cause any modified files to carry prominent notices
stating that You changed the files; and
(c) You must retain, in the Source form of any Derivative Works
that You distribute, all copyright, patent, trademark, and
attribution notices from the Source form of the Work,
excluding those notices that do not pertain to any part of
the Derivative Works; and
(d) If the Work includes a "NOTICE" text file as part of its
distribution, then any Derivative Works that You distribute must
include a readable copy of the attribution notices contained
within such NOTICE file, excluding those notices that do not
pertain to any part of the Derivative Works, in at least one
of the following places: within a NOTICE text file distributed
as part of the Derivative Works; within the Source form or
documentation, if provided along with the Derivative Works; or,
within a display generated by the Derivative Works, if and
wherever such third-party notices normally appear. The contents
of the NOTICE file are for informational purposes only and
do not modify the License. You may add Your own attribution
notices within Derivative Works that You distribute, alongside
or as an addendum to the NOTICE text from the Work, provided
that such additional attribution notices cannot be construed
as modifying the License.
You may add Your own copyright statement to Your modifications and
may provide additional or different license terms and conditions
for use, reproduction, or distribution of Your modifications, or
for any such Derivative Works as a whole, provided Your use,
reproduction, and distribution of the Work otherwise complies with
the conditions stated in this License.
5. Submission of Contributions. Unless You explicitly state otherwise,
any Contribution intentionally submitted for inclusion in the Work
by You to the Licensor shall be under the terms and conditions of
this License, without any additional terms or conditions.
Notwithstanding the above, nothing herein shall supersede or modify
the terms of any separate license agreement you may have executed
with Licensor regarding such Contributions.
6. Trademarks. This License does not grant permission to use the trade
names, trademarks, service marks, or product names of the Licensor,
except as required for reasonable and customary use in describing the
origin of the Work and reproducing the content of the NOTICE file.
7. Disclaimer of Warranty. Unless required by applicable law or
agreed to in writing, Licensor provides the Work (and each
Contributor provides its Contributions) on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
implied, including, without limitation, any warranties or conditions
of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
PARTICULAR PURPOSE. You are solely responsible for determining the
appropriateness of using or redistributing the Work and assume any
risks associated with Your exercise of permissions under this License.
8. Limitation of Liability. In no event and under no legal theory,
whether in tort (including negligence), contract, or otherwise,
unless required by applicable law (such as deliberate and grossly
negligent acts) or agreed to in writing, shall any Contributor be
liable to You for damages, including any direct, indirect, special,
incidental, or consequential damages of any character arising as a
result of this License or out of the use or inability to use the
Work (including but not limited to damages for loss of goodwill,
work stoppage, computer failure or malfunction, or any and all
other commercial damages or losses), even if such Contributor
has been advised of the possibility of such damages.
9. Accepting Warranty or Additional Liability. While redistributing
the Work or Derivative Works thereof, You may choose to offer,
and charge a fee for, acceptance of support, warranty, indemnity,
or other liability obligations and/or rights consistent with this
License. However, in accepting such obligations, You may act only
on Your own behalf and on Your sole responsibility, not on behalf
of any other Contributor, and only if You agree to indemnify,
defend, and hold each Contributor harmless for any liability
incurred by, or claims asserted against, such Contributor by reason
of your accepting any such warranty or additional liability.
END OF TERMS AND CONDITIONS
APPENDIX: How to apply the Apache License to your work.
To apply the Apache License to your work, attach the following
boilerplate notice, with the fields enclosed by brackets "[]"
replaced with your own identifying information. (Don't include
the brackets!) The text should be enclosed in the appropriate
comment syntax for the file format. We also recommend that a
file or class name and description of purpose be included on the
same "printed page" as the copyright notice for easier
identification within third-party archives.
Copyright 2025 OpenAI
Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at
http://www.apache.org/licenses/LICENSE-2.0
Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

3
MANIFEST.in Normal file
View file

@ -0,0 +1,3 @@
include README.md
include LICENSE
recursive-include nomyo *

341
README.md Normal file
View file

@ -0,0 +1,341 @@
# NOMYO Secure Python Chat Client
**OpenAI-compatible secure chat client with end-to-end encryption with NOMYO Inference Endpoints**
🔒 **All prompts and responses are automatically encrypted and decrypted**
🔑 **Uses hybrid encryption (AES-256-GCM + RSA-OAEP with 4096-bit keys)**
🔄 **Drop-in replacement for OpenAI's ChatCompletion API**
## 🚀 Quick Start
### 1. Install dependencies
```bash
pip install -r requirements.txt
```
### 2. Use the client (same API as OpenAI)
```python
import asyncio
from nomyo import SecureChatCompletion
async def main():
# Initialize client (defaults to http://api.nomyo.ai:12434)
client = SecureChatCompletion(base_url="http://api.nomyo.ai:12434")
# Simple chat completion
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "Hello! How are you today?"}
],
temperature=0.7
)
print(response['choices'][0]['message']['content'])
# Run the async function
asyncio.run(main())
```
### 3. Run tests
```bash
python3 test.py
```
## 🔐 Security Features
### Hybrid Encryption
- **Payload encryption**: AES-256-GCM (authenticated encryption)
- **Key exchange**: RSA-OAEP with SHA-256
- **Key size**: 4096-bit RSA keys
- **All communication**: End-to-end encrypted
### Key Management
- Automatic key generation and management
- Keys stored with restricted permissions (600 for private key)
- Optional password protection for private keys
- Key persistence across sessions
## 🔄 OpenAI Compatibility
The `SecureChatCompletion` class provides **exact API compatibility** with OpenAI's `ChatCompletion.create()` method.
### Supported Parameters
All standard OpenAI parameters are supported:
- `model`: Model identifier
- `messages`: List of message objects
- `temperature`: Sampling temperature (0-2)
- `max_tokens`: Maximum tokens to generate
- `top_p`: Nucleus sampling
- `frequency_penalty`: Frequency penalty
- `presence_penalty`: Presence penalty
- `stop`: Stop sequences
- `n`: Number of completions
- `stream`: Streaming (not yet implemented)
- `tools`: Tool definitions
- `tool_choice`: Tool selection strategy
- `user`: User identifier
- And more...
### Response Format
Responses follow the OpenAI format exactly, with an additional `_metadata` field for debugging and security information:
```python
{
"id": "chatcmpl-123",
"object": "chat.completion",
"created": 1234567890,
"model": "Qwen/Qwen3-0.6B",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"content": "Hello! I'm doing well, thank you for asking.",
"tool_calls": [...] # if tools were used
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 10,
"completion_tokens": 20,
"total_tokens": 30
},
"_metadata": {
"payload_id": "openai-compat-abc123", # Unique identifier for this request
"processed_at": 1765250382, # Timestamp when server processed the request
"is_encrypted": True, # Indicates this response was decrypted
"encryption_algorithm": "hybrid-aes256-rsa4096", # Encryption method used
"response_status": "success" # Status of the decryption/processing
}
}
```
The `_metadata` field contains security-related information about the encrypted communication and is automatically added to all responses.
## 🛠️ Usage Examples
### Basic Chat
```python
import asyncio
from nomyo import SecureChatCompletion
async def main():
client = SecureChatCompletion(base_url="http://api.nomyo.ai:12434")
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is the capital of France?"}
],
temperature=0.7
)
print(response['choices'][0]['message']['content'])
asyncio.run(main())
```
### With Tools
```python
import asyncio
from nomyo import SecureChatCompletion
async def main():
client = SecureChatCompletion(base_url="http://api.nomyo.ai:12434")
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "What's the weather in Paris?"}
],
tools=[
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather information",
"parameters": {
"type": "object",
"properties": {
"location": {"type": "string"}
},
"required": ["location"]
}
}
}
],
temperature=0.7
)
print(response['choices'][0]['message']['content'])
asyncio.run(main())
```
### Using acreate() Alias
```python
import asyncio
from nomyo import SecureChatCompletion
async def main():
client = SecureChatCompletion(base_url="http://api.nomyo.ai:12434")
response = await client.acreate(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "Hello!"}
],
temperature=0.7
)
print(response['choices'][0]['message']['content'])
asyncio.run(main())
```
## 📦 Dependencies
See `requirements.txt` for the complete list:
- `cryptography`: Cryptographic primitives (RSA, AES, etc.)
- `httpx`: Async HTTP client
- `anyio`: Async compatibility layer
## 🔧 Configuration
### Custom Base URL
```python
import asyncio
from nomyo import SecureChatCompletion
async def main():
client = SecureChatCompletion(base_url="http://NOMYO-Pro-Router:12434")
# ... rest of your code
asyncio.run(main())
```
### Key Management
Keys are automatically generated on first use and stored in `client_keys/` directory.
#### Generate Keys Manually
```python
import asyncio
from nomyo.SecureCompletionClient import SecureCompletionClient
async def main():
client = SecureCompletionClient()
await client.generate_keys(save_to_file=True, password="your-password")
asyncio.run(main())
```
#### Load Existing Keys
```python
import asyncio
from nomyo.SecureCompletionClient import SecureCompletionClient
async def main():
client = SecureCompletionClient()
await client.load_keys("client_keys/private_key.pem", "client_keys/public_key.pem", password="your-password")
asyncio.run(main())
```
## 🧪 Testing
Run the comprehensive test suite:
```bash
python3 test.py
```
Tests verify:
- ✅ OpenAI API compatibility
- ✅ Basic chat completion
- ✅ Tool usage
- ✅ All OpenAI parameters
- ✅ Async methods
- ✅ Error handling
## 📚 API Reference
### SecureChatCompletion
#### Constructor
```python
SecureChatCompletion(base_url: str = "http://api.nomyo.ai:12434")
```
#### Methods
- `create(model, messages, **kwargs)`: Create a chat completion
- `acreate(model, messages, **kwargs)`: Async alias for create()
### SecureCompletionClient
#### Constructor
```python
SecureCompletionClient(router_url: str = "http://api.nomyo.ai:12434")
```
#### Methods
- `generate_keys(save_to_file=False, key_dir="client_keys", password=None)`: Generate RSA key pair
- `load_keys(private_key_path, public_key_path=None, password=None)`: Load keys from files
- `fetch_server_public_key()`: Fetch server's public key
- `encrypt_payload(payload)`: Encrypt a payload
- `decrypt_response(encrypted_response, payload_id)`: Decrypt a response
- `send_secure_request(payload, payload_id)`: Send encrypted request and receive decrypted response
## 📝 Notes
### Security Best Practices
- Always use password protection for private keys in production
- Keep private keys secure (permissions set to 600)
- Never share your private key
- Verify server's public key fingerprint before first use
### Performance
- Key generation takes ~1-2 seconds (one-time operation)
- Encryption/decryption adds minimal overhead (~10-20ms per request)
### Compatibility
- Works with any OpenAI-compatible code
- No changes needed to existing OpenAI client code
- Simply replace `openai.ChatCompletion.create()` with `SecureChatCompletion.create()`
## 🤝 Contributing
Contributions are welcome! Please open issues or pull requests on the project repository.
## 📄 License
See LICENSE file for licensing information.
## 📞 Support
For questions or issues, please refer to the project documentation or open an issue.

382
nomyo/SecureCompletionClient.py Normal file
View file

@ -0,0 +1,382 @@
import json, base64, urllib.parse, httpx, os
from typing import Dict, Any, Optional
from cryptography.hazmat.primitives import serialization, hashes
from cryptography.hazmat.primitives.asymmetric import rsa, padding
from cryptography.hazmat.backends import default_backend
from cryptography.hazmat.primitives.ciphers import Cipher, algorithms, modes
from cryptography.hazmat.primitives.kdf.hkdf import HKDF
class SecureCompletionClient:
"""
Client for the /v1/chat/secure_completion endpoint.
Handles:
- Key generation and management
- Hybrid encryption/decryption
- API communication
- Response parsing
"""
def __init__(self, router_url: str = "http://api.nomyo.ai:12434"):
"""
Initialize the secure completion client.
Args:
router_url: Base URL of the NOMYO Router (e.g., "http://api.nomyo.ai:12434")
"""
self.router_url = router_url.rstrip('/')
self.private_key = None
self.public_key_pem = None
self.key_size = 4096 # RSA key size
async def generate_keys(self, save_to_file: bool = False, key_dir: str = "client_keys", password: Optional[str] = None) -> None:
"""
Generate RSA key pair for secure communication.
Args:
save_to_file: Whether to save keys to files
key_dir: Directory to save keys (if save_to_file is True)
password: Optional password to encrypt private key (recommended for production)
"""
print("🔑 Generating RSA key pair...")
# Generate private key
self.private_key = rsa.generate_private_key(
public_exponent=65537,
key_size=self.key_size,
backend=default_backend()
)
# Get public key
public_key = self.private_key.public_key()
# Serialize public key to PEM format
self.public_key_pem = public_key.public_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PublicFormat.SubjectPublicKeyInfo
).decode('utf-8')
print(f" ✓ Generated {self.key_size}-bit RSA key pair")
if save_to_file:
os.makedirs(key_dir, exist_ok=True)
# Save private key
if password:
# Encrypt private key with user-provided password
private_pem = self.private_key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.PKCS8,
encryption_algorithm=serialization.BestAvailableEncryption(password.encode('utf-8'))
)
print(f" ✓ Private key encrypted with password")
else:
# Save unencrypted for convenience (not recommended for production)
private_pem = self.private_key.private_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PrivateFormat.PKCS8,
encryption_algorithm=serialization.NoEncryption()
)
print(f" ⚠️ Private key saved UNENCRYPTED (not recommended for production)")
# Write private key with restricted permissions (readable only by owner)
private_key_path = os.path.join(key_dir, "private_key.pem")
with open(private_key_path, "wb") as f:
f.write(private_pem)
try:
os.chmod(private_key_path, 0o600) # Only owner can read/write
print(f" ✓ Private key permissions set to 600 (owner-only access)")
except Exception as e:
print(f" ⚠️ Could not set private key permissions: {e}")
# Save public key (always unencrypted, but with restricted permissions)
public_key_path = os.path.join(key_dir, "public_key.pem")
with open(public_key_path, "w") as f:
f.write(self.public_key_pem)
try:
os.chmod(public_key_path, 0o644) # Owner read/write, group/others read
print(f" ✓ Public key permissions set to 644")
except Exception as e:
print(f" ⚠️ Could not set public key permissions: {e}")
print(f" ✓ Keys saved to {key_dir}/")
async def load_keys(self, private_key_path: str, public_key_path: Optional[str] = None, password: Optional[str] = None) -> None:
"""
Load RSA keys from files.
Args:
private_key_path: Path to private key file
public_key_path: Path to public key file (optional, derived from private key if not provided)
password: Optional password for encrypted private key
"""
print(f"🔑 Loading keys from files...")
# Load private key
with open(private_key_path, "rb") as f:
private_pem = f.read()
# Try different password options
password_options = []
if password:
password_options.append(password.encode('utf-8'))
password_options.append(None) # Try without password
last_error = None
for pwd in password_options:
try:
self.private_key = serialization.load_pem_private_key(
private_pem,
password=pwd,
backend=default_backend()
)
print(f" ✓ Private key loaded {'with password' if pwd else 'without password'}")
break
except Exception as e:
last_error = e
continue
else:
raise ValueError(f"Failed to load private key. Tried all password options. Error: {last_error}")
# Get public key
public_key = self.private_key.public_key()
# Load public key from file if provided, otherwise derive from private key
if public_key_path:
with open(public_key_path, "r") as f:
self.public_key_pem = f.read().strip()
else:
self.public_key_pem = public_key.public_bytes(
encoding=serialization.Encoding.PEM,
format=serialization.PublicFormat.SubjectPublicKeyInfo
).decode('utf-8')
print(" ✓ Keys loaded successfully")
async def fetch_server_public_key(self) -> str:
"""
Fetch the server's public key from the /pki/public_key endpoint.
Returns:
Server's public key as PEM string
"""
print("🔑 Fetching server's public key...")
url = f"{self.router_url}/pki/public_key"
try:
async with httpx.AsyncClient(timeout=60.0) as client:
response = await client.get(url)
if response.status_code == 200:
server_public_key = response.text
print(" ✓ Server's public key fetched successfully")
return server_public_key
else:
raise ValueError(f"Failed to fetch server's public key: HTTP {response.status_code}")
except Exception as e:
raise ValueError(f"Failed to fetch server's public key: {e}")
async def encrypt_payload(self, payload: Dict[str, Any]) -> bytes:
"""
Encrypt a payload using hybrid encryption (AES-256-GCM + RSA-OAEP).
Args:
payload: Dictionary containing the chat completion request
Returns:
Encrypted payload as bytes
Raises:
Exception: If encryption fails
"""
print("🔒 Encrypting payload...")
try:
# Serialize payload to JSON
payload_json = json.dumps(payload).encode('utf-8')
print(f" Payload size: {len(payload_json)} bytes")
# Generate random AES key
aes_key = os.urandom(32) # 256-bit key
# Encrypt payload with AES-GCM using Cipher API (matching server implementation)
nonce = os.urandom(12) # 96-bit nonce for GCM
cipher = Cipher(
algorithms.AES(aes_key),
modes.GCM(nonce),
backend=default_backend()
)
encryptor = cipher.encryptor()
ciphertext = encryptor.update(payload_json) + encryptor.finalize()
tag = encryptor.tag
# Fetch server's public key for encrypting the AES key
server_public_key_pem = await self.fetch_server_public_key()
# Encrypt AES key with server's RSA-OAEP
server_public_key = serialization.load_pem_public_key(
server_public_key_pem.encode('utf-8'),
backend=default_backend()
)
encrypted_aes_key = server_public_key.encrypt(
aes_key,
padding.OAEP(
mgf=padding.MGF1(algorithm=hashes.SHA256()),
algorithm=hashes.SHA256(),
label=None
)
)
# Create encrypted package
encrypted_package = {
"version": "1.0",
"algorithm": "hybrid-aes256-rsa4096",
"encrypted_payload": {
"ciphertext": base64.b64encode(ciphertext).decode('utf-8'),
"nonce": base64.b64encode(nonce).decode('utf-8'),
"tag": base64.b64encode(tag).decode('utf-8')
},
"encrypted_aes_key": base64.b64encode(encrypted_aes_key).decode('utf-8'),
"key_algorithm": "RSA-OAEP-SHA256",
"payload_algorithm": "AES-256-GCM"
}
# Serialize package to JSON and return as bytes
package_json = json.dumps(encrypted_package).encode('utf-8')
print(f" ✓ Encrypted package size: {len(package_json)} bytes")
return package_json
except Exception as e:
raise Exception(f"Encryption failed: {str(e)}")
async def decrypt_response(self, encrypted_response: bytes, payload_id: str) -> Dict[str, Any]:
"""
Decrypt a response from the secure endpoint.
Args:
encrypted_response: Encrypted response bytes
payload_id: Payload ID for metadata verification
Returns:
Decrypted response dictionary
"""
print("🔓 Decrypting response...")
# Parse encrypted package
try:
package = json.loads(encrypted_response.decode('utf-8'))
except json.JSONDecodeError as e:
raise ValueError(f"Invalid encrypted package format: {e}")
# Validate package structure
required_fields = ["version", "algorithm", "encrypted_payload", "encrypted_aes_key"]
for field in required_fields:
if field not in package:
raise ValueError(f"Missing required field in encrypted package: {field}")
# Decrypt AES key with private key
encrypted_aes_key = base64.b64decode(package["encrypted_aes_key"])
aes_key = self.private_key.decrypt(
encrypted_aes_key,
padding.OAEP(
mgf=padding.MGF1(algorithm=hashes.SHA256()),
algorithm=hashes.SHA256(),
label=None
)
)
# Decrypt payload with AES-GCM using Cipher API (matching server implementation)
ciphertext = base64.b64decode(package["encrypted_payload"]["ciphertext"])
nonce = base64.b64decode(package["encrypted_payload"]["nonce"])
tag = base64.b64decode(package["encrypted_payload"]["tag"])
cipher = Cipher(
algorithms.AES(aes_key),
modes.GCM(nonce, tag),
backend=default_backend()
)
decryptor = cipher.decryptor()
plaintext = decryptor.update(ciphertext) + decryptor.finalize()
# Parse decrypted response
response = json.loads(plaintext.decode('utf-8'))
# Add metadata for debugging
if "_metadata" not in response:
response["_metadata"] = {}
response["_metadata"].update({
"payload_id": payload_id,
"processed_at": package.get("processed_at"),
"is_encrypted": True,
"encryption_algorithm": package["algorithm"]
})
print(f" ✓ Response decrypted successfully")
print(f" Response size: {len(plaintext)} bytes")
return response
async def send_secure_request(self, payload: Dict[str, Any], payload_id: str) -> Dict[str, Any]:
"""
Send a secure chat completion request to the router.
Args:
payload: Chat completion request payload
payload_id: Unique identifier for this request
Returns:
Decrypted response from the LLM
"""
print("\n📤 Sending secure chat completion request...")
# Step 1: Encrypt the payload
encrypted_payload = await self.encrypt_payload(payload)
# Step 2: Prepare headers
headers = {
"X-Payload-ID": payload_id,
"X-Public-Key": urllib.parse.quote(self.public_key_pem),
"Content-Type": "application/octet-stream"
}
# Step 3: Send request to router
url = f"{self.router_url}/v1/chat/secure_completion"
print(f" Target URL: {url}")
try:
async with httpx.AsyncClient(timeout=60.0) as client:
response = await client.post(
url,
headers=headers,
content=encrypted_payload
)
print(f" HTTP Status: {response.status_code}")
if response.status_code == 200:
# Step 4: Decrypt the response
encrypted_response = response.content
decrypted_response = await self.decrypt_response(encrypted_response, payload_id)
return decrypted_response
elif response.status_code == 400:
error = response.json()
raise ValueError(f"Bad request: {error.get('detail', 'Unknown error')}")
elif response.status_code == 404:
error = response.json()
raise ValueError(f"Endpoint not found: {error.get('detail', 'Secure inference not enabled')}")
elif response.status_code == 500:
error = response.json()
raise ValueError(f"Server error: {error.get('detail', 'Internal server error')}")
else:
raise ValueError(f"Unexpected status code: {response.status_code}")
except httpx.NetworkError as e:
raise ConnectionError(f"Failed to connect to router: {e}")
except Exception as e:
raise Exception(f"Request failed: {e}")

12
nomyo/__init__.py Normal file
View file

@ -0,0 +1,12 @@
"""
NOMYO Secure Python Chat Client
OpenAI-compatible secure chat client with end-to-end encryption.
"""
from .nomyo import SecureChatCompletion
__version__ = "0.1.0"
__author__ = "NOMYO AI"
__license__ = "Apache-2.0"
__all__ = ["SecureChatCompletion"]

161
nomyo/nomyo.py Normal file
View file

@ -0,0 +1,161 @@
import uuid
from typing import Dict, Any, List
from .SecureCompletionClient import SecureCompletionClient
class SecureChatCompletion:
"""
OpenAI-compatible secure chat completion client.
This class provides the same interface as OpenAI's ChatCompletion.create()
method, but automatically encrypts all requests and decrypts all responses
for secure communication with the NOMYO Router's /v1/chat/secure_completion
endpoint.
Usage:
```python
# Create a client instance
client = SecureChatCompletion(base_url="http://api.nomyo.ai:12434")
# Simple chat completion
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "What is the capital of France?"}
],
temperature=0.7
)
# With tools
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "What's the weather in Paris?"}
],
tools=[...],
temperature=0.7
)
```
"""
def __init__(self, base_url: str = "http://api.nomyo.ai:12434"):
"""
Initialize the secure chat completion client.
Args:
base_url: Base URL of the NOMYO Router (e.g., "http://api.nomyo.ai:12434")
This parameter is named 'base_url' for OpenAI compatibility.
"""
self.client = SecureCompletionClient(router_url=base_url)
self._keys_initialized = False
async def _ensure_keys(self):
"""Ensure keys are loaded or generated."""
if not self._keys_initialized:
# Try to load existing keys
try:
await self.client.load_keys("client_keys/private_key.pem", "client_keys/public_key.pem")
self._keys_initialized = True
except Exception:
# Generate new keys if loading fails
await self.client.generate_keys()
self._keys_initialized = True
async def create(self, model: str, messages: List[Dict[str, Any]], **kwargs) -> Dict[str, Any]:
"""
Creates a new chat completion for the provided messages and parameters.
This method provides the same interface as OpenAI's ChatCompletion.create()
but automatically handles encryption and decryption for secure communication.
Args:
model: The model to use for the chat completion.
messages: A list of message objects. Each message has a role ("system",
"user", or "assistant") and content.
**kwargs: Additional parameters that can be passed to the API.
Supported parameters include:
- temperature: float (0-2)
- max_tokens: int
- tools: List of tool definitions
- tool_choice: str ("auto", "none", or specific tool name)
- stop: Union[str, List[str]]
- presence_penalty: float
- frequency_penalty: float
- logit_bias: Dict[str, float]
- user: str
- base_url: str (alternative to initializing with router_url)
Returns:
A dictionary containing the chat completion response with the following structure:
{
"id": str,
"object": "chat.completion",
"created": int,
"model": str,
"choices": [
{
"index": int,
"message": {
"role": str,
"content": str,
"tool_calls": List[Dict] # if tools were used
},
"finish_reason": str
}
],
"usage": {
"prompt_tokens": int,
"completion_tokens": int,
"total_tokens": int
}
}
Raises:
ValueError: If required parameters are missing or invalid.
ConnectionError: If the connection to the router fails.
Exception: For other errors during the request.
"""
# Extract base_url if provided (OpenAI compatibility)
base_url = kwargs.pop("base_url", None)
# Use the instance's client unless base_url is explicitly overridden
if base_url is not None:
# Create a temporary client with overridden base_url
temp_client = type(self)(base_url=base_url)
instance = temp_client
else:
# Use the instance's existing client
instance = self
# Ensure keys are available
await instance._ensure_keys()
# Prepare payload in OpenAI format
payload = {
"model": model,
"messages": messages,
**kwargs
}
# Generate a unique payload ID
payload_id = f"openai-compat-{uuid.uuid4()}"
# Send secure request
response = await instance.client.send_secure_request(payload, payload_id)
return response
async def acreate(self, model: str, messages: List[Dict[str, Any]], **kwargs) -> Dict[str, Any]:
"""
Async alias for create() method.
This provides the same functionality as create() but with an explicit
async name, following OpenAI's naming conventions.
Args:
Same as create() method.
Returns:
Same as create() method.
"""
return await self.create(model, messages, **kwargs)

52
pyproject.toml Normal file
View file

@ -0,0 +1,52 @@
[build-system]
requires = ["hatchling>=1.0.0", "wheel"]
build-backend = "hatchling.build"
[project]
name = "nomyo"
version = "0.1.0"
description = "OpenAI-compatible secure chat client with end-to-end encryption for NOMYO Inference Endpoints"
authors = [
{name = "NOMYO.AI", email = "ichi@nomyo.ai"},
]
readme = "README.md"
license = {text = "Apache-2.0"}
classifiers = [
"Development Status :: 4 - Beta",
"Intended Audience :: Developers",
"Intended Audience :: Information Technology",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3",
"Programming Language :: Python :: 3.8",
"Programming Language :: Python :: 3.9",
"Programming Language :: Python :: 3.10",
"Programming Language :: Python :: 3.11",
"Programming Language :: Python :: 3.12",
"Topic :: Security :: Cryptography",
"Topic :: Software Development :: Libraries :: Python Modules",
"Topic :: Communications :: Chat",
"Operating System :: OS Independent",
]
requires-python = ">=3.8"
dependencies = [
"anyio==4.12.0",
"certifi==2025.11.12",
"cffi==2.0.0",
"cryptography==46.0.3",
"exceptiongroup==1.3.1",
"h11==0.16.0",
"httpcore==1.0.9",
"httpx==0.28.1",
"idna==3.11",
"pycparser==2.23",
"typing_extensions==4.15.0",
]
[project.urls]
Homepage = "https://nomyo.ai"
Documentation = "https://nomyo.ai/nomyo-docs"
Repository = "https://github.com/nomyo-ai/nomyo"
Issues = "https://github.com/nomyo-ai/nomyo/issues"
[tool.setuptools]
packages = ["nomyo"]

11
requirements.txt Normal file
View file

@ -0,0 +1,11 @@
anyio==4.12.0
certifi==2025.11.12
cffi==2.0.0
cryptography==46.0.3
exceptiongroup==1.3.1
h11==0.16.0
httpcore==1.0.9
httpx==0.28.1
idna==3.11
pycparser==2.23
typing_extensions==4.15.0

221
test.py Normal file
View file

@ -0,0 +1,221 @@
#!/usr/bin/env python3
"""
Test script to verify OpenAI compatibility of SecureChatCompletion.
This script demonstrates that the SecureChatCompletion class provides
the same interface as OpenAI's ChatCompletion.create() method.
"""
import asyncio
from nomyo import SecureChatCompletion
client = SecureChatCompletion(base_url="http://localhost:12434")
async def test_basic_chat():
"""Test basic chat completion with OpenAI-style API."""
print("=" * 70)
print("TEST 1: Basic Chat Completion (OpenAI-style API)")
print("=" * 70)
# This is how you would use OpenAI's client:
# response = await openai.ChatCompletion.create(
# model="gpt-3.5-turbo",
# messages=[...],
# temperature=0.7
# )
# Now with SecureChatCompletion (same API!):
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "What is the capital of France?"}
],
temperature=0.7,
)
# Verify response structure matches OpenAI format
assert "choices" in response, "Response missing 'choices' field"
assert len(response["choices"]) > 0, "No choices in response"
assert "message" in response["choices"][0], "Choice missing 'message' field"
assert "content" in response["choices"][0]["message"], "Message missing 'content' field"
assert "finish_reason" in response["choices"][0], "Choice missing 'finish_reason' field"
print("✅ Response structure matches OpenAI format")
print(f"✅ Model: {response.get('model')}")
print(f"✅ Finish Reason: {response['choices'][0].get('finish_reason')}")
print(f"✅ Content: {response['choices'][0]['message']['content']}...")
return True
async def test_chat_with_tools():
"""Test chat completion with tools (OpenAI-style API)."""
print("\n" + "=" * 70)
print("TEST 2: Chat with Tools (OpenAI-style API)")
print("=" * 70)
# This is how you would use OpenAI's client with tools:
# response = await openai.ChatCompletion.create(
# model="gpt-3.5-turbo",
# messages=[...],
# tools=[...],
# temperature=0.7
# )
# Now with SecureChatCompletion (same API!):
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "system", "content": "You are a helpful assistant with tools."},
{"role": "user", "content": "What's the weather in Paris?"}
],
tools=[
{
"type": "function",
"function": {
"name": "get_weather",
"description": "Get weather information for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name"
}
},
"required": ["location"]
}
}
}
],
temperature=0.7,
max_tokens=2000
)
# Verify response structure
assert "choices" in response, "Response missing 'choices' field"
assert "message" in response["choices"][0], "Choice missing 'message' field"
print("✅ Response structure matches OpenAI format")
print(f"✅ Model: {response.get('model')}")
print(f"✅ Content: {response['choices'][0]['message']['content']}...")
# Check for tool calls if present
if 'tool_calls' in response['choices'][0]['message']:
print("✅ Tool calls detected in response")
for tool_call in response['choices'][0]['message']['tool_calls']:
print(f" - Function: {tool_call['function']['name']}")
return True
async def test_all_openai_parameters():
"""Test that all common OpenAI parameters are supported."""
print("\n" + "=" * 70)
print("TEST 3: All OpenAI Parameters Support")
print("=" * 70)
# Test with various OpenAI parameters
response = await client.create(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "Hello!"}
],
temperature=0.7,
max_tokens=100,
top_p=0.9,
frequency_penalty=0.0,
presence_penalty=0.0,
stop=None,
n=1,
stream=False,
user="test_user"
)
print("✅ All OpenAI parameters accepted")
print(f"✅ Response received successfully")
return True
async def test_async_alias():
"""Test the acreate async alias method."""
print("\n" + "=" * 70)
print("TEST 4: Async Alias (acreate)")
print("=" * 70)
# Test using the acreate alias on the client instance
response = await client.acreate(
model="Qwen/Qwen3-0.6B",
messages=[
{"role": "user", "content": "Test message"}
],
temperature=0.7
)
print("✅ acreate() method works correctly")
print(f"✅ Response received: {response['choices'][0]['message']['content']}...")
return True
async def test_error_handling():
"""Test error handling."""
print("\n" + "=" * 70)
print("TEST 5: Error Handling")
print("=" * 70)
try:
# This should fail gracefully
response = await client.create(
model="nonexistent-model",
messages=[
{"role": "user", "content": "Test"}
]
)
print("⚠️ Expected error did not occur")
return False
except Exception as e:
print(f"✅ Error handled correctly: {type(e).__name__}")
return True
async def main():
"""Run all compatibility tests."""
print("=" * 70)
print("SECURE CHAT CLIENT - OpenAI Compatibility Tests")
print("=" * 70)
print("\nTesting that SecureChatCompletion provides the same API as")
print("openai.ChatCompletion.create() with end-to-end encryption...\n")
tests = [
test_basic_chat,
test_chat_with_tools,
test_all_openai_parameters,
test_async_alias,
test_error_handling,
]
results = []
for test in tests:
try:
result = await test()
results.append(result)
except Exception as e:
print(f"\n❌ Test failed with exception: {e}")
import traceback
traceback.print_exc()
results.append(False)
print("\n" + "=" * 70)
print("TEST SUMMARY")
print("=" * 70)
passed = sum(results)
total = len(results)
print(f"Passed: {passed}/{total}")
if passed == total:
print("\n🎉 ALL TESTS PASSED!")
print("\nThe SecureChatCompletion class is fully compatible with")
print("OpenAI's ChatCompletion.create() API while providing")
print("end-to-end encryption for secure communication.")
else:
print(f"\n⚠️ {total - passed} test(s) failed")
return passed == total
if __name__ == "__main__":
success = asyncio.run(main())
exit(0 if success else 1)