Use Black Eagle AI with OpenAI-compatible tools.

1. Test the endpoint first

Before configuring a framework, verify that your token, model id and base URL work with one small request.

curl https://api.blackeaglecambodia.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer sk-your-black-eagle-token" \
  -d '{
    "model": "deepseek-v4-flash",
    "messages": [{"role": "user", "content": "Say hello in one sentence."}]
  }'

2. OpenAI SDK

Use this when your application already uses the OpenAI Python or JavaScript client.

Python

from openai import OpenAI

client = OpenAI(
    api_key="sk-your-black-eagle-token",
    base_url="https://api.blackeaglecambodia.com/v1",
)

response = client.chat.completions.create(
    model="deepseek-v4-flash",
    messages=[{"role": "user", "content": "Draft a launch checklist."}],
)

print(response.choices[0].message.content)

Node.js

import OpenAI from "openai";

const client = new OpenAI({
  apiKey: "sk-your-black-eagle-token",
  baseURL: "https://api.blackeaglecambodia.com/v1",
});

const response = await client.chat.completions.create({
  model: "deepseek-v4-flash",
  messages: [{ role: "user", content: "Draft a launch checklist." }],
});

console.log(response.choices[0].message.content);

3. LiteLLM proxy

Use a custom OpenAI-compatible model route when you want LiteLLM to sit between your application and Black Eagle AI.

model_list:
  - model_name: black-eagle-deepseek-v4-flash
    litellm_params:
      model: openai/deepseek-v4-flash
      api_key: os.environ/BLACK_EAGLE_API_KEY
      api_base: https://api.blackeaglecambodia.com/v1

4. browser-use

For browser agents, start with text-only mode and a known chat model. Turn on vision or structured output only after the raw chat call works.

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="deepseek-v4-flash",
    api_key="sk-your-black-eagle-token",
    base_url="https://api.blackeaglecambodia.com/v1",
)

# If your model does not support vision, set the agent/browser-use
# configuration to text-only before debugging browser actions.

5. Browser Use / OpenAdapter fallback route

If your team already uses Browser Use or OpenAdapter, this guide gives the smallest useful Chinese-model test path without changing the rest of your workflow.

6. Qwen Code custom provider

When a tool supports OpenAI-compatible custom providers, keep each endpoint and model id explicit. If the same model name exists on multiple endpoints, use different display names.

{
  "$version": 3,
  "env": {
    "BLACK_EAGLE_API_KEY": "sk-your-black-eagle-token"
  },
  "security": {
    "auth": {
      "selectedType": "openai"
    }
  },
  "modelProviders": {
    "openai": [
      {
        "id": "deepseek-v4-flash-black-eagle",
        "name": "Black Eagle DeepSeek Chat",
        "envKey": "BLACK_EAGLE_API_KEY",
        "baseUrl": "https://api.blackeaglecambodia.com/v1"
      }
    ]
  }
}

7. Cline / OpenAI-compatible tools

For tools with a settings UI, choose the OpenAI-compatible provider and avoid stale OpenAI defaults after switching providers.

8. Debug checklist

1. Run a raw /chat/completions request before using a framework.
2. Confirm the final request host is api.blackeaglecambodia.com, not api.openai.com.
3. Keep model ids explicit; do not let a framework rewrite them silently.
4. Test streaming, tools, structured output and media endpoints separately.
5. For Qwen, Kimi, GLM, Kling or Seedance access, check the model catalog and submit a defined workload via the request template.