RE

Relace: Relace Apply 3

Relace

Relace Apply 3 is a specialized code-patching LLM that merges AI-suggested edits straight into your source files. It can apply updates from GPT-4o, Claude, and others into your files at 10,000 tokens/sec on average. The model requires the prompt to be in the following format: <instruction>{instruction}</instruction> <code>{initial_code}</code> <update>{edit_snippet}</update> Zero Data Retention is enabled for Relace. Learn more about this model in their [documentation](https://docs.relace.ai/api-reference/instant-apply/apply)

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Specifications

Context Window256K
Modalitiestext
Statusavailable
Categorythird-party
Model IDrelace/relace-apply-3

Quick Start

TypeScript
import OpenAI from 'openai'

const client = new OpenAI({
  apiKey: process.env.HANZO_API_KEY,
  baseURL: 'https://api.hanzo.ai/v1'
})

const response = await client.chat.completions.create({
  model: 'relace/relace-apply-3',
  messages: [{ role: 'user', content: 'Hello!' }]
})

console.log(response.choices[0].message.content)
Python
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["HANZO_API_KEY"],
    base_url="https://api.hanzo.ai/v1"
)

response = client.chat.completions.create(
    model="relace/relace-apply-3",
    messages=[{"role": "user", "content": "Hello!"}]
)

print(response.choices[0].message.content)
cURL
curl https://api.hanzo.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $HANZO_API_KEY" \
  -d '{
    "model": "relace/relace-apply-3",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'
Go
package main

import (
    "context"
    "fmt"
    "os"

    "github.com/sashabaranov/go-openai"
)

func main() {
    cfg := openai.DefaultConfig(os.Getenv("HANZO_API_KEY"))
    cfg.BaseURL = "https://api.hanzo.ai/v1"
    client := openai.NewClientWithConfig(cfg)

    resp, _ := client.CreateChatCompletion(context.Background(),
        openai.ChatCompletionRequest{
            Model: "relace/relace-apply-3",
            Messages: []openai.ChatCompletionMessage{
                {Role: openai.ChatMessageRoleUser, Content: "Hello!"},
            },
        },
    )
    fmt.Println(resp.Choices[0].Message.Content)
}

More from Relace

Relace: Relace Search
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The relace-search model uses 4-12 `view_file` and `grep` tools in parallel to explore a codebase and return relevant files to the user request. In contrast to RAG, relace-search performs agentic multi-step reasoning to produce highly precise results 4x faster than any frontier model. It's designed to serve as a subagent that passes its findings to an "oracle" coding agent, who orchestrates/performs the rest of the coding task. To use relace-search you need to build an appropriate agent harness, and parse the response for relevant information to hand off to the oracle. Read more about it in the [Relace documentation](https://docs.relace.ai/docs/fast-agentic-search/agent).

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