relace-search
Relace Search explores a codebase by running 4–12 view_file and grep tools in parallel and returns the files relevant to a request. Unlike RAG, it searches the code agentically.
Precio: Entrada: 240 créditos / 1 M de tokens (≈ $1.20); salida: 720 créditos / 1 M de tokens (≈ $3.60).
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Relace Search API on ModelFold
Relace Search explores a codebase by running 4–12 view_file and grep tools in parallel and returns the files relevant to a request. Unlike RAG, it searches the code agentically. Try Relace Search in the ModelFold Playground, then call it from your own code through an OpenAI-compatible chat completions API.
What Is the Relace Search API
Relace Search at a glance
Relace Search is a chat model from Relace. It accepts text as input and returns text, with a context window of up to 256K tokens.
Use it without hosting anything
On ModelFold you call Relace Search with a single API key — no model weights to download and no inference servers to run. The same key also works for the other chat, image, video and audio models on ModelFold.
Core Capabilities of Relace Search
Up to 256K tokens of context
Keep long conversations, large documents and sizeable code in a single request, so the model can reason over the full material instead of fragments.
Function calling
Relace Search supports tool (function) calling: describe your functions in the request and the model returns structured calls your code can run — the basis for agents and integrations.
Structured outputs
Ask for JSON that follows a schema (response_format), which makes extraction, classification and system integrations more reliable.
How to Use Relace Search on ModelFold
- 1
Step 1: Try it in the Playground
Open the Playground at the top of this page, type a prompt and see how Relace Search responds before writing any code.
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Step 2: Create an API key
Sign in to ModelFold and create an API key in the console. Keep it secret and send it as a Bearer token.
- 3
Step 3: Send a request
Call POST https://modelfold.ai/v1/chat/completions with "model": "relace-search" and your messages. Existing OpenAI-compatible SDKs work by changing the base URL and key.
- ✓
Step 4: Ship and monitor
Integrate the response into your product and check token usage and spend for every call in the console logs.
What You Can Build with Relace Search
AI coding assistants
Generate, explain, debug and refactor code, review pull requests and work through multi-file changes in developer tools and IDE plugins.
Autonomous agents
Build agents that plan multi-step tasks, call your tools and APIs, and keep working toward a goal across long sessions.
Tool-calling backends
Route requests, call functions and chain API calls as the worker model inside larger agent systems.
Frequently Asked Questions
What is Relace Search?⌄
Relace Search explores a codebase by running 4–12 view_file and grep tools in parallel and returns the files relevant to a request. Unlike RAG, it searches the code agentically.
Which inputs does Relace Search support?⌄
Relace Search accepts text and returns text. Through ModelFold you send text messages; documents attached in the Playground are converted to text.
How long is the context window of Relace Search?⌄
Up to 256K tokens, shared between your input and the model’s output.
Does Relace Search support function calling?⌄
Yes. Relace Search supports tools / function calling through the standard tools parameter of the chat completions API.
How is Relace Search billed on ModelFold?⌄
Pay as you go by tokens: input and output tokens are charged at the per-million-token prices shown on this page. There is no monthly fee, and failed requests are not charged.
How do I call Relace Search through the API?⌄
Send a POST request to https://modelfold.ai/v1/chat/completions with "model": "relace-search", using your ModelFold API key as the Bearer token.
| Entrada | 240 créditos 1M tokens≈ $1.20 |
| Salida | 720 créditos 1M tokens≈ $3.60 |
Se cobra por token, con tarifas separadas para entrada y salida. Los tokens de razonamiento cuentan como salida. El entorno de pruebas aplica exactamente el mismo cálculo.
Leer la documentación de la API →AI Agents · Claude Code / Cursor / Trae →curl https://modelfold.ai/v1/chat/completions \
-H "Authorization: Bearer $MODELFOLD_API_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"relace-search","messages":[{"role":"user","content":"Hello"}]}'