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AGENT_USAGE.md
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| 1 |
+
## AI Agent Integration Guide
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| 2 |
+
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| 3 |
+
This document explains how any AI agent (or app) should use the NVIDIA proxy API exposed by this service. The proxy keeps the real `NVIDIA_API_KEY` on the backend so that the agent never needs to handle or see the key directly.
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| 4 |
+
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+
---
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| 6 |
+
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+
### 1. Base URL
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| 8 |
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- **Local development**: `http://localhost:8000`
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| 10 |
+
- **Hugging Face Space** (production): `https://Rox-Turbo-API.hf.space`
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| 11 |
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+
All endpoints below are relative to this base URL.
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| 13 |
+
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| 14 |
+
---
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| 15 |
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+
### 2. Chat endpoint (recommended for applications)
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- **HTTP method**: `POST`
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- **Path**: `/chat`
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| 20 |
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- **Description**: General chat/completions endpoint, similar to OpenAI Chat Completions.
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| 21 |
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+
**Request JSON:**
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| 23 |
+
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```json
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| 25 |
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{
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| 26 |
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"messages": [
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| 27 |
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{ "role": "user", "content": "Your question here" }
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| 28 |
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],
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| 29 |
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"temperature": 1.0,
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| 30 |
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"top_p": 1.0,
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| 31 |
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"max_tokens": 1024
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| 32 |
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}
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| 33 |
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```
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| 34 |
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- `messages`:
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- Array of objects with `role` (`"user"`, `"assistant"`, `"system"`) and `content` (string).
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- The agent should include conversation history if it wants the model to be aware of context.
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- `temperature`, `top_p`, `max_tokens` are optional; if omitted, defaults are used.
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| 39 |
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| 40 |
+
**Response JSON:**
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| 41 |
+
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| 42 |
+
```json
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| 43 |
+
{
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| 44 |
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"content": "Model reply text..."
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| 45 |
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}
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```
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| 47 |
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- `content`: the full generated reply from the model as a single string.
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| 49 |
+
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| 50 |
+
**Notes for agents:**
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| 51 |
+
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| 52 |
+
- No API key or auth header is required; the proxy handles credentials.
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| 53 |
+
- Handle HTTP error codes:
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| 54 |
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- `400–499`: client-side issues (invalid body, etc.).
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| 55 |
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- `500`: internal error talking to upstream.
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| 56 |
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- `502`: bad response from upstream provider.
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| 57 |
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| 58 |
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---
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| 59 |
+
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### 3. Hugging Face–style endpoint (for HF tools)
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| 61 |
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| 62 |
+
- **HTTP method**: `POST`
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| 63 |
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- **Path**: `/hf/generate`
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| 64 |
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- **Description**: Hugging Face text-generation–style interface (`inputs` + `parameters`).
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| 65 |
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| 66 |
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**Request JSON:**
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| 67 |
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| 68 |
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```json
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| 69 |
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{
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| 70 |
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"inputs": "Prompt text here",
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| 71 |
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"parameters": {
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| 72 |
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"temperature": 0.7,
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| 73 |
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"top_p": 0.95,
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| 74 |
+
"max_new_tokens": 256
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| 75 |
+
}
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| 76 |
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}
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| 77 |
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```
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| 78 |
+
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| 79 |
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- `parameters` is optional; unspecified values fall back to sensible defaults.
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| 80 |
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| 81 |
+
**Response JSON:**
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| 82 |
+
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| 83 |
+
```json
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| 84 |
+
[
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| 85 |
+
{
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| 86 |
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"generated_text": "Model reply text..."
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| 87 |
+
}
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| 88 |
+
]
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| 89 |
+
```
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| 90 |
+
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| 91 |
+
- This shape matches what many Hugging Face clients expect from a text-generation endpoint.
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| 92 |
+
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| 93 |
+
---
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| 94 |
+
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| 95 |
+
### 4. Example usage from a browser (static frontend)
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| 96 |
+
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| 97 |
+
**JavaScript (fetch) example using `/chat`:**
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| 98 |
+
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| 99 |
+
```js
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| 100 |
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const API_URL = "https://Rox-Turbo-API.hf.space/chat";
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| 101 |
+
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| 102 |
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async function sendMessage(messageText) {
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| 103 |
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const body = {
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| 104 |
+
messages: [{ role: "user", content: messageText }],
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| 105 |
+
temperature: 1,
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| 106 |
+
top_p: 1,
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| 107 |
+
max_tokens: 1024
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| 108 |
+
};
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| 109 |
+
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| 110 |
+
const res = await fetch(API_URL, {
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| 111 |
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method: "POST",
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| 112 |
+
headers: { "Content-Type": "application/json" },
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| 113 |
+
body: JSON.stringify(body)
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| 114 |
+
});
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| 115 |
+
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| 116 |
+
if (!res.ok) {
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| 117 |
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throw new Error(`API error: ${res.status} ${await res.text()}`);
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| 118 |
+
}
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| 119 |
+
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| 120 |
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const data = await res.json();
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| 121 |
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return data.content; // model reply text
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| 122 |
+
}
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| 123 |
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```
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| 124 |
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| 125 |
+
---
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| 126 |
+
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| 127 |
+
### 5. Example usage from a Python agent
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| 128 |
+
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| 129 |
+
**Python example using `requests` and `/chat`:**
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| 130 |
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| 131 |
+
```python
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| 132 |
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import requests
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| 133 |
+
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| 134 |
+
BASE_URL = "https://Rox-Turbo-API.hf.space"
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| 135 |
+
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| 136 |
+
def ask_model(messages, temperature=1.0, top_p=1.0, max_tokens=1024):
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| 137 |
+
url = f"{BASE_URL}/chat"
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| 138 |
+
payload = {
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| 139 |
+
"messages": messages,
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| 140 |
+
"temperature": temperature,
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| 141 |
+
"top_p": top_p,
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| 142 |
+
"max_tokens": max_tokens,
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| 143 |
+
}
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| 144 |
+
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| 145 |
+
response = requests.post(url, json=payload, timeout=60)
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| 146 |
+
response.raise_for_status()
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| 147 |
+
data = response.json()
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| 148 |
+
return data["content"]
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| 149 |
+
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| 150 |
+
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| 151 |
+
if __name__ == "__main__":
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| 152 |
+
reply = ask_model([{"role": "user", "content": "Hello, who are you?"}])
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| 153 |
+
print("Model reply:", reply)
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| 154 |
+
```
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| 155 |
+
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| 156 |
+
---
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| 157 |
+
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| 158 |
+
### 6. Responsibilities and guarantees
|
| 159 |
+
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| 160 |
+
- The proxy:
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| 161 |
+
- Maintains and protects the `NVIDIA_API_KEY` on the server side.
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| 162 |
+
- Handles communication with the NVIDIA OpenAI-compatible endpoint.
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| 163 |
+
- Normalizes responses into simple JSON formats (`content` and `generated_text`).
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| 164 |
+
- The agent:
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| 165 |
+
- Only needs HTTPS access to the proxy.
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| 166 |
+
- Must handle standard HTTP errors and implement retries or fallback behavior as needed.
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| 167 |
+
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| 168 |
+
Use this document as the single source of truth for how your AI agent should call the NVIDIA proxy API in this project.
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| 169 |
+
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