confamnode 0.1.2

The Nigerian AI inference gateway

ConfamNode

The Nigerian AI inference gateway. Access frontier AI models.

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Installation

Using pip

pip install confamnode

Using uv

uv add confamnode

Using virtualenv

# Create virtual environment
python -m venv venv

# Activate — Linux/Mac
source venv/bin/activate

# Activate — Windows
venv\Scripts\activate

# Install
pip install confamnode

Using uv with virtual environment

# Create project
uv init my-project
cd my-project

# Add confamnode
uv add confamnode

# Run your script
uv run python main.py

Using conda

# Create environment
conda create -n my-project python=3.10
conda activate my-project

# Install
pip install confamnode

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Quick Start

from confamnode import ConfamNode

client = ConfamNode(api_key="confam-sk-xxx")

ansa = client.gist(
    model="confam-speed",
    messages="How you dey?"
)

print(ansa.text)
print(f"Cost:   ₦{ansa.cost.naira:.6f}")
print(f"Tokens: {ansa.usage.total_tokens}")
print(f"ID:     {ansa.id}")

---

Streaming

from confamnode import ConfamNode

client = ConfamNode(api_key="confam-sk-xxx")

stream = client.gist(
    model="confam-speed",
    messages="Wetin be the capital of 9ja?",
    stream=True
)

# Print tokens as they arrive
for yarn in stream:
    content = yarn.choices[0].delta.content
    if content:
        print(content, end="", flush=True)

# Get full Ansa after stream completes
ansa = stream.get_ansa()
print(f"\nModel:  {ansa.model}")
print(f"Tokens: {ansa.usage.total_tokens}")
print(f"Cost:   ₦{ansa.cost.naira:.6f}")
if ansa.cost.dollars:
    print(f"${ansa.cost.dollars:.8f}")
print(f"ID: {ansa.id}")

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The Ansa Response Object

Every gist() call returns an Ansa object:

ansa = client.gist(model="confam-speed", messages="How far?")

# Response
ansa.text               # response text
ansa.model              # model that served the request
ansa.reasoning          # thinking trace (reasoning models only)
ansa.tools              # tool calls (agent models only)
ansa.citations          # citations (search models only)
ansa.finish_reason      # why generation stopped

# Usage
ansa.usage.prompt_tokens      # input tokens used
ansa.usage.completion_tokens  # output tokens used
ansa.usage.total_tokens       # total tokens used

# Cost — Naira first
ansa.cost.naira         # total cost in Naira ← primary
ansa.cost.naira_input   # input cost in Naira
ansa.cost.naira_output  # output cost in Naira
ansa.cost.dollars       # cost in USD (if available)

# Identity
ansa.is_local                # True — runs on Nigerian hardware
ansa.is_ngn_data_residency   # True — data never leaves Nigeria
ansa.id                      # unique request ID (confam-xxxx-xxxx)
ansa.raw                     # original LiteLLM response

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Models

Free Tier

Model	Description	Price
confam-lite	Light text and general chat	Free
confam-speed	Fast, high quality responses	Free
confam-reasoning	Standard reasoning and analysis	Free

Paid Tier

Model	Description	Input ₦/1M	Output ₦/1M	Input ₦/1K	Output ₦/1K
confam-intelligence	General smart tasks, 1M context	₦596	₦3,571	₦0.596	₦3.571
confam-deep-reasoning	Complex thinking, multi-step analysis	₦234	₦468	₦0.234	₦0.468
confam-code	Coding assistance, 1M context	₦234	₦468	₦0.234	₦0.468

Local Models — Nigeria Data Residency

Model	Description	Input ₦/1M	Output ₦/1M	Input ₦/1K	Output ₦/1K
confam-nano	Qwen3.5 4B on Jetson Orin Nano	₦500	₦1,500	₦0.500	₦1.500

Runs entirely on Nigerian hardware. Data never transmitted abroad.

Data never leaves Nigeria. Ideal for banks, fintechs, hospitals, law firms, and government agencies.

More models coming soon. Contact [e-mail] for early access.

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Pricing

All prices are in Nigerian Naira (₦). No USD. No conversion needed.

Tier	How it works
Free	Use immediately. No wallet needed. Shared capacity.
Paid	Contact us to get access. Pay in Naira. No subscription. No expiry.

Currently in private beta. To get API access: [e-mail]

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Rate Limits

Rate limits vary by plan. Contact [e-mail].

• Free tier — shared capacity with lower limits
• Paid tier — dedicated higher limits
• confam-nano — limited capacity, queue-based

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System Message

ConfamNode adds a default system message to every request giving the model a Nigerian identity and context. This is standard behaviour across all LLM providers and is counted in prompt_tokens.

# Use ConfamNode default identity (default)
ansa = client.gist(
    model="confam-speed",
    messages="Who are you?"
)
# "I am ConfamNode, Nigeria's AI inference gateway..."

# Override with your own system message
ansa = client.gist(
    model="confam-speed",
    messages="Who are you?",
    system="You are a helpful customer service agent for Konga."
)

# Disable system message entirely
ansa = client.gist(
    model="confam-speed",
    messages="Who you be?",
    system=None
)

---

Reasoning Models

Enable extended thinking for complex problems:

ansa = client.gist(
    model="confam-reasoning",
    messages="One trader buy goods for ₦50,000 sell am for ₦75,000. After e pay ₦5,000 for transport and ₦3,000 for market, wetin be the real profit? Show how you calculate am.",
    # Explicit reasoning control
    allowed_openai_params=["reasoning_effort"],
    rreasoning_effort={"effort": "low", "summary": "detailed"} # effort can be "low", "mid", "high", or "xhigh". summary can be "detailed", or "concise"
)

print(ansa.reasoning)   # thinking trace
print(ansa.text)        # final answer

Also available on confam-deep-reasoning for more complex multi-step problems:

ansa = client.gist(
    model="confam-deep-reasoning",
    messages="Analyse the financial risk of a Nigerian fintech expanding to Ghana...",
    # Explicit reasoning control
    allowed_openai_params=["reasoning_effort"],
    rreasoning_effort={"effort": "low", "summary": "detailed"} # effort can be "low", "mid", "high", or "xhigh". summary can be "detailed", or "concise"
)

print(ansa.reasoning)   # full thinking trace
print(ansa.text)        # final analysis

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RAG (Retrieval-Augmented Generation)

Best models for RAG

Model	Why	Context
confam-intelligence	General RAG, reliable, long context	1M tokens
confam-code	Code search, documentation RAG	1M tokens
confam-deep-reasoning	Complex RAG, multi-hop reasoning	1M tokens

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Data Residency

Nigerian businesses handling sensitive data can use local models that run entirely on Nigerian hardware — data is never transmitted abroad:

ansa = client.gist(
    model="confam-nano",
    messages="Analyse this sensitive document..."
)

print(ansa.is_local)                 # True — runs on Nigerian hardware
print(ansa.is_ngn_data_residency)    # True — data never leaves Nigeria
print(ansa.text)

Ideal for:

• Nigerian banks and fintechs
• Healthcare companies
• Law firms
• Government agencies
• Any business with strict data residency requirements

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Environment Variable

export CONFAMNODE_API_KEY="confam-sk-xxx"

# No need to pass api_key explicitly
client = ConfamNode()

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Custom Base URL

For enterprise clients running ConfamNode on private infrastructure:

client = ConfamNode(
    api_key="confam-sk-xxx",
    base_url="http://your-private-server:4000/v1"
)

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Error Handling

from confamnode import (
    ConfamAuthError,
    ConfamRateLimitError,
    ConfamModelError,
    ConfamNodeError
)

try:
    ansa = client.gist(
        model="confam-speed",
        messages="How you dey?"
    )
except ConfamAuthError:
    print("Check your API key")
except ConfamRateLimitError:
    print("You don reach your limit. Contact [e-mail]")
except ConfamModelError:
    print("Invalid model name")
except ConfamNodeError as e:
    print(f"Something went wrong: {e}")

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Private AI Deployment

Need Data-residential private AI on your own infrastructure?

JoTeq the First offers:

• On-premise deployment on Jetson devices and GPUs
• RTX 3090/4090 bare metal setup
• RAG pipelines and fine-tuning
• Dedicated hosted models
• SSH remote deployment

Contact: [e-mail]

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Links

• PyPI: pypi.org/project/confamnode
• GitHub: github.com/confamnodeai/confamnode
• General: [e-mail]
• Support: [e-mail]
• Billing: [e-mail]

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License

Apache 2.0

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