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docs: add DaoXE OpenAI-compatible base_url client example #1237

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37 changes: 37 additions & 0 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -198,6 +198,43 @@ llm = OpenAI(api_bese="http://localhost:3000/v1", model="meta-llama/Llama-3.2-1B

</details>

<details>

<summary>Remote OpenAI-compatible gateway (DaoXE)</summary>

The same OpenAI client works against any OpenAI-compatible base URL. For a multi-model multi-protocol cloud gateway (instead of a local OpenLLM server), point `base_url` at DaoXE:

```python
import os
from openai import OpenAI

client = OpenAI(
base_url="https://daoxe.com/v1",
api_key=os.environ["DAOXE_API_KEY"],
)

# Model IDs are account-scoped — list what your key can access:
# for m in client.models.list().data:
# print(m.id)

chat_completion = client.chat.completions.create(
model=os.environ["DAOXE_MODEL"], # e.g. an ID from GET /v1/models
messages=[
{
"role": "user",
"content": "Explain superconductors like I'm five years old",
}
],
stream=True,
)
for chunk in chat_completion:
print(chunk.choices[0].delta.content or "", end="")
```

DaoXE exposes OpenAI Chat Completions / Responses and Anthropic Messages among other protocols; this example uses the OpenAI Chat Completions path only. Replace the model ID with one available to your key ([catalog](https://daoxe.com/pricing)). Not available in mainland China. Site: [daoxe.com](https://daoxe.com).

</details>

## Chat UI

OpenLLM provides a chat UI at the `/chat` endpoint for the launched LLM server at http://localhost:3000/chat.
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37 changes: 37 additions & 0 deletions README.md.tpl
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -117,6 +117,43 @@ llm = OpenAI(api_bese="http://localhost:3000/v1", model="meta-llama/Llama-3.2-1B

</details>

<details>

<summary>Remote OpenAI-compatible gateway (DaoXE)</summary>

The same OpenAI client works against any OpenAI-compatible base URL. For a multi-model multi-protocol cloud gateway (instead of a local OpenLLM server), point `base_url` at DaoXE:

```python
import os
from openai import OpenAI

client = OpenAI(
base_url="https://daoxe.com/v1",
api_key=os.environ["DAOXE_API_KEY"],
)

# Model IDs are account-scoped — list what your key can access:
# for m in client.models.list().data:
# print(m.id)

chat_completion = client.chat.completions.create(
model=os.environ["DAOXE_MODEL"], # e.g. an ID from GET /v1/models
messages=[
{
"role": "user",
"content": "Explain superconductors like I'm five years old",
}
],
stream=True,
)
for chunk in chat_completion:
print(chunk.choices[0].delta.content or "", end="")
```

DaoXE exposes OpenAI Chat Completions / Responses and Anthropic Messages among other protocols; this example uses the OpenAI Chat Completions path only. Replace the model ID with one available to your key ([catalog](https://daoxe.com/pricing)). Not available in mainland China. Site: [daoxe.com](https://daoxe.com).

</details>

## Chat UI

OpenLLM provides a chat UI at the `/chat` endpoint for the launched LLM server at http://localhost:3000/chat.
Expand Down