confamnode 0.2.4

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-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}")

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Streaming

from confamnode import ConfamNode

client = ConfamNode(api_key="confam-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}")
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 you dey?")

# 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 (includes system message)
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

# 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)

# Response metadata
ansa.raw                     # dict with id, finish_reason, usage
ansa.raw["id"]               # provider response ID
ansa.raw["finish_reason"]    # why generation stopped
ansa.raw["usage"]            # prompt and completion token counts

Note: prompt_tokens includes any system message tokens. This is standard behaviour across all LLM providers (OpenAI, Anthropic, etc.).

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Models

Free Tier

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

Paid Tier

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

Local Models — Nigerian Data Residency

Model	Description	Modality	Input ₦/1M	Output ₦/1M	Input ₦/1K	Output ₦/1K
confam-nano	Local model — data stays in Nigeria	Image-Text-to-Text	₦500	₦1,500	₦0.500	₦1.500

Runs entirely on Nigerian hardware. Data never transmitted abroad. 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
)

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Caching

Caching is controlled per request and is off by default — every call returns a fresh response, even when the request is identical. This keeps data-generation loops and any workflow that resends the same prompt from getting the same cached answer back each time.

Pass cache=True to read from and write to the cache — useful for idempotent lookups or to save cost on repeated queries:

# Default — caching off, fresh response every call
ansa = client.gist(
    model="confam-speed",
    messages="How you dey?"
)

# Enable caching — use a stored response when the request matches,
# and store this response for next time
ansa = client.gist(
    model="confam-speed",
    messages="How you dey?",
    cache=True
)

A cache hit is typically returned near-instantly and at little or no token cost — a quick way to confirm caching is active.

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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.",
    reasoning_effort="low"
    # one of: "xhigh", "high", "medium", "low", "minimal", "none"
)

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...",
    reasoning_effort="high"
)

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-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-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

• Website: confamnode.com
• 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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