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Unlimited gpt-oss api openai compatible

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# GPTOSS-Proxy OpenAI-Compatible

> ## Leave a ⭐ if this helped you

A tiny Cloudflare Worker that exposes a **single OpenAI-compatible endpoint**:

* `POST /v1/chat/completions` → supports `stream: true|false`, token streaming, and **reasoning** (CoT) as `reasoning_content`.
* `GET /v1/models` → lists available models: `gpt-oss-120b`, `gpt-oss-20b`.
* `GET /` → returns `{ success: true, discord, website, repo }`.

## 🚀 One-click deploy

[![Deploy to Cloudflare](https://deploy.workers.cloudflare.com/button)](https://deploy.workers.cloudflare.com/?url=https://github.com/junioralive/gptoss-proxy)

NOTE: You can [Join our Discord](https://discord.gg/cwDTVKyKJz) server if you face issues deploying.

## ✨ Features

* OpenAI-compatible `/v1/chat/completions` (streaming & non-stream)
* CoT **reasoning stream** → `choices[0].delta.reasoning_content`
* **Models**: `gpt-oss-120b` (larger) and `gpt-oss-20b` (faster)
* **Reasoning effort** control: `none | low | medium | high`
* **Thread persistence** via headers or payload metadata
* CORS enabled for browser clients

## ▶️ Endpoints

### `GET /`

Returns:

```json
{
  "success": true,
  "discord": "https://discord.gg/cwDTVKyKJz",
  "website": "https://ish.junioralive.in",
  "repo": "https://github.com/junioralive/gptoss-proxy"
}
```

### `GET /v1/models`

Lists supported models:

```json
{ "object":"list", "data":[
  {"id":"gpt-oss-120b","object":"model"},
  {"id":"gpt-oss-20b","object":"model"}
]}
```

### `POST /v1/chat/completions`

OpenAI-style body:

```json
{
  "model": "gpt-oss-20b",
  "messages": [
    {"role": "user", "content": "Say hi and then a space fact."}
  ],
  "stream": true,
  "metadata": {
    "gptoss_user_id": "u123",         // optional
    "gptoss_thread_id": "thr_456",    // optional
    "reasoning_effort": "medium"      // none|low|medium|high
  }
}
```

**Optional headers** (override metadata):

* `X-GPTOSS-User-Id: <uuid>`
* `X-GPTOSS-Thread-Id: thr_...`
* `X-Reasoning-Effort: none|low|medium|high`

**Streaming response:** OpenAI-style SSE

* token deltas → `choices[0].delta.content`
* reasoning updates → `choices[0].delta.reasoning_content`
* terminates with a chunk where `finish_reason = "stop"` then `data: [DONE]`

**Non-streaming:** standard `chat.completion` JSON.

## 🧪 Quick start (cURL)

**Streaming:**

```bash
curl -N https://<your-worker>.workers.dev/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "X-Reasoning-Effort: medium" \
  -d '{"model":"gpt-oss-120b","messages":[{"role":"user","content":"hello!"}],"stream":true}'
```

**Non-stream:**

```bash
curl https://<your-worker>.workers.dev/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{"model":"gpt-oss-20b","messages":[{"role":"user","content":"One short sentence."}],"stream":false}'
```

## 🐍 Python example

```python
import os, json, requests

BASE = "https://<your-worker>.workers.dev"

# stream
payload = {
    "model": "gpt-oss-120b",
    "messages": [{"role":"user","content":"Say hi, then a fun space fact."}],
    "stream": True,
    "metadata": {"reasoning_effort": "medium"}
}
with requests.post(f"{BASE}/v1/chat/completions",
                   headers={"Content-Type":"application/json"},
                   data=json.dumps(payload), stream=True, timeout=120) as r:
    r.raise_for_status()
    for line in r.iter_lines(decode_unicode=True):
        if not line: continue
        if line.startswith("data: "):
            data = line[6:].strip()
            if data == "[DONE]":
                print("\n[DONE]"); break
            obj = json.loads(data)
            delta = obj["choices"][0]["delta"]
            if "reasoning_content" in delta:
                print("\n[reasoning]", delta["reasoning_content"])
            if "content" in delta:
                print(delta["content"], end="", flush=True)

# non-stream
payload = {"model":"gpt-oss-20b","messages":[{"role":"user","content":"Now reply in one short sentence."}],"stream":False}
print("\n\nNon-stream result:")
print(requests.post(f"{BASE}/v1/chat/completions",
                    headers={"Content-Type":"application/json"},
                    json=payload, timeout=60).json())
```

## 🤝 Use with OpenAI SDKs

Point the SDK to your Worker:

**Python**

```python
from openai import OpenAI
client = OpenAI(base_url="https://<your-worker>.workers.dev/v1", api_key="dummy")
stream = client.chat.completions.create(
  model="gpt-oss-20b",
  messages=[{"role":"user","content":"hello!"}],
  stream=True,
  metadata={"reasoning_effort": "low"}
)
for chunk in stream:
    d = chunk.choices[0].delta
    if getattr(d, "reasoning_content", None): print("\n[reasoning]", d.reasoning_content)
    if getattr(d, "content", None): print(d.content, end="")
```

**Node**

```js
import OpenAI from "openai";
const client = new OpenAI({ baseURL: "https://<your-worker>.workers.dev/v1", apiKey: "dummy" });
const stream = await client.chat.completions.create({
  model: "gpt-oss-120b",
  messages: [{ role: "user", content: "hello!" }],
  stream: true,
  metadata: { reasoning_effort: "medium" }
});
for await (const chunk of stream) {
  const d = chunk.choices[0].delta;
  if (d.reasoning_content) console.log("\n[reasoning]", d.reasoning_content);
  if (d.content) process.stdout.write(d.content);
}
```

## ⚠️ Disclaimer

This script is provided **as a proof of concept**.
It is **not intended to cause harm or be misused**.

If you encounter any issues or have concerns, please contact:
📧 [support@junioralive.in](mailto:support@junioralive.in)
💬 [Join our Discord](https://discord.gg/cwDTVKyKJz)

## 🔧 Notes & tips

* **Models**: choose `gpt-oss-20b` for speed; `gpt-oss-120b` for quality.
* **Reasoning effort**: set via header or `metadata.reasoning_effort` (default `medium`).
* **Threads / Users**: pass `X-GPTOSS-Thread-Id` + `X-GPTOSS-User-Id` (or `metadata.gptoss_*`) to keep conversation history.
* **CORS**: enabled by default. If you add auth, include `authorization` in `access-control-allow-headers`.

gptoss-proxy

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