tokenfactory

name

tokenfactory

description

Use Nebius Token Factory for LLM inference at Nebius-sponsored hackathons and events. Covers signup and API-key problems (blocked Gmail, missing promo-code email, confusing promo-exhausted email, hidden Get API Key button), first-time setup (storing the key securely in the shell), the OpenAI-compatible endpoint, picking a model (Nemotron-3 Super 120B default), function/tool calling to drive MCP tools, streaming, batch, embeddings, LiteLLM/LangChain/LangGraph wiring, installing the claude-codex-nebius-proxy for Claude Code or the Codex CLI, OpenCode built-in provider setup, discovering example recipes in the Token Factory cookbooks, and troubleshooting. Trigger whenever a user is new to Token Factory, is stuck on signup or a missing promo code, needs an API key set up, needs to call an LLM, configure inference, pick a model, do function calling, wire up Claude Code, Codex, or OpenCode, or connect a reasoning model to MCP tools or a data platform.

Nebius Token Factory — Skill

Token Factory is Nebius's managed inference platform. It serves open models behind an OpenAI-compatible API, so any agent framework that speaks OpenAI (or has a Nebius/OpenAI provider) can use it by changing three things: base URL, API key, and model name.

The core agent pattern:

Your model on Token Factory does the reasoning and tool-calling → your tools (often an MCP server) do the real work.

Your agent calls a Token Factory model; the model emits tool calls; your code dispatches those to your tools — local functions, APIs, or an MCP server's tools — and feeds results back. See reference/function-calling.md and reference/mcp-integration.md.

Helping a beginner ("vibe coder")? Assume no terminal fluency. Give one copy-paste block at a time and verify it worked before moving on (e.g. echo $NEBIUS_API_KEY after the export, the §1 curl after that). Don't assume they know what an environment variable or a base URL is — say what each step does in one plain sentence. Reassure them: only three things ever change vs. plain OpenAI — base URL, API key, model name.

1. Get access (do this first)

New to Token Factory? It's three steps: get a key → store it securely → make one test call. If the user doesn't have a key yet, walk them through this section before anything else.

Signup not going smoothly? (form won't load, Gmail rejected, no promo-code email, a confusing "promo code exhausted" email, can't find the Get API Key button) — every known signup gotcha and its workaround is in reference/signup-help.md.

1. Claim credits at https://dev.nebius.com/builders (apply early — approval can lag).

2. Log in to the Token Factory console — https://tokenfactory.nebius.com/ — and create/copy your API key.

3. Store it as an environment variable — never hardcode it in source code, never commit it:

   # Add an environment variable for your API key to store it locally.
   # Copy-paste this into your terminal and insert your API key:
   export NEBIUS_API_KEY="your-key-here"
   export NEBIUS_BASE_URL="https://api.tokenfactory.nebius.com/v1"
   
   # Persist across sessions:
   echo 'export NEBIUS_API_KEY="your-key-here"' >> ~/.zshrc    # macOS (default shell: zsh)
   echo 'export NEBIUS_API_KEY="your-key-here"' >> ~/.bashrc   # Linux (bash)
   # Then open a new terminal, or reload now: source ~/.zshrc  (or: source ~/.bashrc)
   

   Per-project alternative: cp .env.example .env and fill in the key — .env is gitignored here.

4. Verify it works (should print a JSON list of models):

   curl -s "$NEBIUS_BASE_URL/models" -H "Authorization: Bearer $NEBIUS_API_KEY" | head
   

   If it errors, see reference/troubleshooting.md (401 = key/credits issue, connection error = base URL).

Key safety: treat the key like a password. Don't paste it into chats, issues, or shared docs; don't commit it (this repo's .gitignore already excludes .env); if it leaks, revoke it in the dashboard and create a new one.

If a helper wants OPENAI_API_KEY / OPENAI_BASE_URL (many do), set those to the Nebius values.

2. First call (OpenAI SDK)

from openai import OpenAI
import os

client = OpenAI(
    base_url=os.environ["NEBIUS_BASE_URL"],
    api_key=os.environ["NEBIUS_API_KEY"],
)

resp = client.chat.completions.create(
    model="nvidia/nemotron-3-super-120b-a12b",   # recommended for agentic tool use
    messages=[{"role": "user", "content": "Say hello in one sentence."}],
)
print(resp.choices[0].message.content)

That's the whole integration surface. Everything else — streaming, tools, batch, embeddings — is standard OpenAI-shaped and documented in reference/api.md.

3. Which model?

New to this? Don't agonize — use the default below and move on; you can switch any time (it's just the model string). To see everything available on your account: curl -s "$NEBIUS_BASE_URL/models" -H "Authorization: Bearer $NEBIUS_API_KEY".

• Default for agents / tool use: nvidia/nemotron-3-super-120b-a12b (Nemotron-3 Super 120B, ~12B active, 1M context, native function calling).
• Token Factory hosts many open models (Llama, Qwen, DeepSeek, Kimi, etc.). Pick the smallest model that reliably tool-calls for your loop; scale up only if reasoning quality needs it.
• Full guidance + model IDs: reference/models.md.

4. Function calling → your tools

The whole game is: model proposes a tool call → you run the tool → return the result. Minimal loop: reference/function-calling.md and examples/function_calling.py. Tools on an MCP server: reference/mcp-integration.md and examples/langgraph_mcp_agent.py.

5. Identify the user's stack, then wire it

Before giving setup instructions, figure out which of these the user is on — ask if it isn't obvious from context ("Are you writing your own agent in Python/JS, or using Claude Code, the Codex CLI, or OpenCode?"). The setup differs:

Stack	Wiring
Own agent — OpenAI SDK (Python/JS)	No proxy needed. Set base_url + api_key from the env vars in §1 (snippet in §2).
Own agent — LiteLLM	model="nebius/nvidia/nemotron-3-super-120b-a12b", reads NEBIUS_API_KEY from env.
Own agent — LangChain / LangGraph	ChatOpenAI(base_url=..., api_key=..., model=...).
Claude Code	Claude Code speaks Anthropic's /v1/messages, not OpenAI — route through a local proxy. Install walkthrough: reference/proxy-setup.md; quick reference: reference/api.md → "CLI routing".
Codex CLI	Same proxy, plus ~/.codex/config.toml with wire_api = "responses". Install walkthrough: reference/proxy-setup.md.
OpenCode	No proxy needed — Nebius Token Factory is a built-in provider: run /connect, search "Nebius Token Factory", paste the key, then /models to pick one. Details: reference/api.md → "OpenCode".

Secure key handling on every path: the key lives in the NEBIUS_API_KEY environment variable (§1). CLI configs should reference it via env_key (Codex) or the proxy's environment — never paste the raw key into a config file, script, or repo.

Copy-paste snippets for each: reference/api.md. Runnable examples: examples/.

6. Find working examples (don't build from scratch)

Before writing anything from first principles, check the cookbooks — ~50 MIT-licensed recipes (agents on 7 frameworks, RAG, tool calling, integrations) that are usually two minutes from "adapt this":

• Browse without cloning: https://opencolin.github.io/nebius-ecosystem-cookbook/cookbook/ — every recipe rendered, notebooks with outputs visible, filter/search.
• Clone and run: https://github.com/nebius/token-factory-cookbook

Task-to-recipe map and more resources: reference/cookbooks.md.

7. When stuck — run the checklist

If a user is stuck and it's unclear where, walk this in order — each step verifies the one before it. Stop at the first "no" and fix there:

1. Signed up? With a non-Gmail address, promo code in hand → reference/signup-help.md
2. Right email? The Token Factory "here's your code" email — not the AI Cloud "exhausted" one → reference/signup-help.md
3. Key copied? From the dashboard (widen the window if the button is missing) → §1
4. Key stored? echo $NEBIUS_API_KEY prints it, and it's persisted in the shell profile → §1
5. Key works? curl -s "$NEBIUS_BASE_URL/models" -H "Authorization: Bearer $NEBIUS_API_KEY" returns a model list → §1; errors → reference/troubleshooting.md
6. Tool wired? Own agent → §2; Claude Code / Codex → reference/proxy-setup.md; OpenCode → reference/api.md § OpenCode
7. First call succeeded? If yes, stop debugging setup — start from a cookbook recipe (reference/cookbooks.md) instead of a blank file.

For specific errors (401, model-not-found, rate limits, tool-call JSON, context length): reference/troubleshooting.md.

Reference map

File	What's in it
reference/signup-help.md	Signup gotchas & workarounds: Gmail block, flaky form, promo emails, hidden key button
reference/api.md	Endpoints, auth, streaming, curl/Python/JS, LiteLLM, LangChain, OpenCode, CLI routing
reference/models.md	Recommended models, IDs, when to use which
reference/function-calling.md	Tool-calling loop, schema format, dispatching to your tools
reference/batch-and-embeddings.md	Batch API (evals) and embeddings (RAG over schema docs)
reference/mcp-integration.md	Driving MCP-server tools from a Token Factory model, end to end
reference/proxy-setup.md	Install claude-codex-nebius-proxy: TUI installer, agent-driven non-interactive install, Claude Code + Codex wiring
reference/cookbooks.md	Discover examples: cookbook task-to-recipe map, browsable mirror, awesome-nebius
reference/troubleshooting.md	Common errors and fixes
examples/	Runnable Python: quickstart, LiteLLM, function calling, LangGraph+MCP

Related resources

• Token Factory Cookbook — 50 recipes / 27 notebooks: https://github.com/nebius/token-factory-cookbook
• Browsable cookbook mirror (rendered notebooks + search): https://opencolin.github.io/nebius-ecosystem-cookbook/cookbook/
• awesome-nebius — curated Nebius resources: https://github.com/opencolin/awesome-nebius
• Claude Code / Codex → Nebius proxy — https://github.com/KiranChilledOut/claude-codex-nebius-proxy
• openclaw-nebius-plugin — https://github.com/opencolin/openclaw-nebius-plugin