Comprehensive AI Framework with 50+ LLM Providers, Advanced Agents, Chains, Memory, RAG, and 100+ Tools
Project description
NeuralNode v3.1.0
NeuralNode is a Python AI framework focused on:
- real cloud providers that are implemented
- local model execution with Transformers, Ollama, llama.cpp, and Horus
- agents, memory, and RAG
- Replica TTS and speech recognition
- Telegram integration
Install
pip install neuralnode
pip install "neuralnode[all]"
Useful extras:
pip install "neuralnode[horus]"
pip install "neuralnode[telegram]"
pip install "neuralnode[replica]"
pip install "neuralnode[speech]"
pip install "neuralnode[turboquant]"
Quick Start
import neuralnode as nn
ai = nn.NeuralNode(
provider="groq",
model="llama-3.1-70b-versatile",
api_key="YOUR_GROQ_API_KEY",
)
print(ai.chat("Hello from NeuralNode"))
Horus
All Horus models use:
- unified chat template:
horus_unified - unified context window:
8192
import neuralnode as nn
model = nn.HorusModel(
model_id="tokenaii/horus/Horus-1.0-4B",
turboquant=True,
turboquant_bits=4,
).load()
response = model.chat([
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": "Explain Horus briefly."},
])
print(response.content)
Available Horus model IDs
from neuralnode import HorusModel
print(HorusModel.list_available_models())
Supported IDs currently include:
tokenaii/horustokenaii/horus/Horus-1.0-4Btokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q4_K_M.gguftokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q5_K_M.gguftokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q6_K.gguftokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-Q8_0.gguftokenaii/Hours-1.0-4B-GGUF/Horus-1.0-4B-F16.gguf
Replica TTS
Replica exposes 20 curated edge_tts voices through custom voice IDs.
import neuralnode as nn
print(nn.replica_voice_list())
tts = nn.ReplicaTTS(voice_id="replic-salma-language{ar-eg}")
tts.save_to_file("مرحبا من نيورال نود", "reply.mp3")
Voice mapping docs:
Horus + Replica
import neuralnode as nn
model = nn.HorusModel(
model_id="tokenaii/horus/Horus-1.0-4B",
enable_tts=True,
tts_voice_id="replic-salma-language{ar-eg}",
).load()
result = model.chat_and_speak(
[{"role": "user", "content": "قل لي جملة ترحيب قصيرة"}],
output_file="horus_reply.mp3",
)
print(result["response"].content)
print(result["audio_path"])
Telegram
Use a BotFather token to connect an agent to Telegram.
import neuralnode as nn
ai = nn.NeuralNode(provider="horus", model="tokenaii/horus/Horus-1.0-4B")
agent = ai.agent(agent_type="simple", thinking=False)
bot = nn.TelegramBot(
token="YOUR_BOTFATHER_TOKEN",
agent=agent,
config=nn.TelegramBotConfig(
token="YOUR_BOTFATHER_TOKEN",
enable_voice=True,
enable_documents=True,
reply_mode="both", # text | voice | both
voice_reply_voice_id="replic-aria-language{en-us}",
),
)
bot.start()
Telegram now supports:
- text chat
- voice transcription
- optional Replica voice replies
- document download and analysis
RAG
import neuralnode as nn
ai = nn.NeuralNode(provider="ollama", model="llama3.2")
rag = ai.rag(store="memory")
rag.add_documents(["notes.txt", "report.pdf"])
print(rag.query("Summarize the key findings"))
If the current LLM does not support embeddings, RAG automatically tries:
- a dedicated embedding provider
- sentence-transformers
- lexical fallback embeddings
Supported Provider Surface
Only implemented providers are exposed through the public provider registry.
Cloud chat providers:
anthropicgooglecoheremistralgroqdeepseekperplexityai21togetherfireworksbedrockvertexai
Local providers:
ollamallamacpptransformersllamafilekoboldcpptextgenwebuiexllamaautogptqautoawqvllmtgideepspeedrayservemlflowbentomltritonmlxhorus
TurboQuant
TurboQuant is integrated into:
HorusModel(..., turboquant=True, turboquant_bits=4)create_provider("transformers", turboquant=True, turboquant_bits=4, ...)
If the turboquant package is not installed or the backend cannot use it, NeuralNode falls back to normal generation automatically.
Notes
- OpenAI is intentionally blocked in NeuralNode.
- GGUF Horus models require
llama-cpp-python. - Horus downloads from Hugging Face require
huggingface_hub.
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