> ## Documentation Index
> Fetch the complete documentation index at: https://www.edenai.co/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# OpenCode

> Configure OpenCode, the AI-powered terminal coding assistant, to use Eden AI for access to 500+ models.

export const TechArticleSchema = ({title, description, path, articleSection, about, proficiencyLevel = "Beginner", dependencies, keywords = [], datePublished, dateModified, image, inLanguage = "en"}) => {
  const baseUrl = "https://www.edenai.co/docs";
  const canonicalUrl = `${baseUrl}/${path}`.replace(/\/+$/, "");
  const ogParams = new URLSearchParams({
    division: articleSection || "",
    title: title || "",
    description: description || ""
  });
  const resolvedImage = image || `https://edenai.mintlify.app/_mintlify/api/og?${ogParams.toString()}`;
  const data = {
    "@context": "https://schema.org",
    "@type": "TechArticle",
    "@id": `${canonicalUrl}#techarticle`,
    mainEntityOfPage: {
      "@type": "WebPage",
      "@id": canonicalUrl
    },
    headline: title,
    name: title,
    description: description,
    url: canonicalUrl,
    inLanguage: inLanguage,
    isPartOf: {
      "@type": "WebSite",
      name: "Eden AI Documentation",
      url: baseUrl
    },
    author: [{
      "@type": "Organization",
      name: "Eden AI",
      url: "https://www.edenai.co/"
    }],
    publisher: {
      "@type": "Organization",
      name: "Eden AI",
      url: "https://www.edenai.co/",
      logo: {
        "@type": "ImageObject",
        url: "https://www.edenai.co/assets/logo.png"
      }
    }
  };
  if (articleSection) data.articleSection = articleSection;
  if (about) data.about = {
    "@type": "Thing",
    name: about
  };
  if (proficiencyLevel) data.proficiencyLevel = proficiencyLevel;
  if (dependencies) data.dependencies = dependencies;
  if (keywords && keywords.length) data.keywords = keywords;
  if (datePublished) data.datePublished = datePublished;
  if (dateModified) data.dateModified = dateModified;
  data.image = Array.isArray(resolvedImage) ? resolvedImage : [resolvedImage];
  const json = JSON.stringify(data);
  const schemaId = `techarticle-${canonicalUrl}`;
  React.useEffect(() => {
    if (typeof document === "undefined") return;
    document.querySelectorAll(`script[data-schema-id="${schemaId}"]`).forEach(n => n.remove());
    const script = document.createElement("script");
    script.type = "application/ld+json";
    script.dataset.schemaId = schemaId;
    script.textContent = json;
    document.head.appendChild(script);
    return () => script.remove();
  }, [json, schemaId]);
  return null;
};

<TechArticleSchema title={"OpenCode"} description={"Configure OpenCode, the AI-powered terminal coding assistant, to use Eden AI for access to 500+ models."} path="v3/integrations/opencode" articleSection="Coding Agents" about={"AI Coding Assistants"} proficiencyLevel="Intermediate" keywords={["Eden AI", "AI API", "OpenCode"]} datePublished="2026-05-06T00:00:00Z" dateModified="2026-05-07T00:00:00Z" />

Configure [OpenCode](https://opencode.ai), the AI-powered terminal coding assistant, to use Eden AI for access to 500+ models.

## Overview

OpenCode is a terminal-based AI coding assistant. By connecting it to Eden AI, you get:

* **500+ models**: Access OpenAI, Anthropic, Google, and more through a single API key
* **Auto-configured**: A script fetches Eden AI's full model catalog and writes your config automatically
* **Tool calling**: All models in the generated config support function calling, which OpenCode requires

## Setup

### 1. Install OpenCode

```bash theme={null}
npm install -g opencode-ai
```

### 2. Generate your config

Download the script and run it:

```bash theme={null}
python gen_opencode_config.py
```

This fetches all available Eden AI models and writes them directly to `~/.config/opencode/opencode.json`.

<CodeGroup>
  ```python gen_opencode_config.py theme={null}
  """Generate opencode.json from Eden AI's model catalog."""

  import json
  import requests
  from pathlib import Path

  MODELS_URL = "https://api.edenai.run/v3/models"
  BASE_URL = "https://api.edenai.run/v3"

  models = requests.get(MODELS_URL).json()["data"]

  def to_per_million(v):
      return round(v * 1_000_000, 6) if v else None

  model_entries = {}
  for m in models:
      caps = m.get("capabilities", {})
      if not caps.get("supports_function_calling"):
          continue  # opencode requires tool calling

      p = m.get("pricing", {})
      cost = {k: to_per_million(p.get(v)) for k, v in {
          "input": "input_cost_per_token",
          "output": "output_cost_per_token",
          "cache_read": "cache_read_input_token_cost",
          "cache_write": "cache_creation_input_token_cost",
      }.items() if p.get(v)}

      model_entries[m["id"]] = {
          **({"cost": cost} if cost else {}),
          **({"reasoning": True} if caps.get("supports_reasoning") else {}),
      }

  config = {
      "$schema": "https://opencode.ai/config.json",
      "provider": {
          "edenai": {
              "npm": "@ai-sdk/openai-compatible",
              "name": "Eden AI",
              "options": {"baseURL": BASE_URL},
              "models": model_entries,
          }
      },
  }

  output = Path.home() / ".config" / "opencode" / "opencode.json"
  output.parent.mkdir(parents=True, exist_ok=True)
  output.write_text(json.dumps(config, indent=2))

  print(f"Written {len(model_entries)} models to {output}")
  ```
</CodeGroup>

### 3. Connect your API key

Launch OpenCode, run `/connect`, select **Eden AI** from the list, and paste your API key when prompted.

Get your key from [app.edenai.run](https://app.edenai.run) → **API Keys**.

### 4. Start coding

```bash theme={null}
opencode
```

## Next Steps

* [Continue.dev](./continue-dev) - AI code assistant for VS Code and JetBrains
* [Claude Code](./claude-code) - Official Claude CLI