# Send a Prompt

Use this guide to validate AI/LLM integration through the **Cloud and AI Gateway** after configuring your repository.

Unlike storage tests, AI tests use the repository's **OpenAI-compatible endpoint type** and an **AI LLM API key** generated for that repository.

{% hint style="info" %}
This is the AI equivalent of **Store An Object**: you confirm connectivity, authentication, routing, and response behavior before shipping production traffic.
{% endhint %}

## Prerequisites

Before running examples, make sure all of the following are complete:

1. At least one AI provider is configured in **AI → AI LLM**.
2. The AI resource is attached to your repository.
3. The repository endpoint type is **OPENAI**.
4. You created a repository **AI LLM API key**.

Related setup guides:

* [Configure an AI LLM](/guides/setup-the-cloud-and-ai-gateway/start-with-cloud-storage/create-a-bucket-1.md)
* [Create a Repository](/guides/setup-the-cloud-and-ai-gateway/start-with-cloud-storage-1/create-a-repository.md)
* [Configure a Repository](/guides/setup-the-cloud-and-ai-gateway/start-with-cloud-storage-1/program-with-flashback.md)

## Required endpoint and credentials

From your repository details, collect:

* **OpenAI-compatible base URL** (example: `https://openai-us-east-1-aws.flashback.tech/v1`)
* **AI API key** (Bearer token format)
* **Model identifier** available in your configured provider(s)

Then export them as environment variables:

```bash
export FB_OPENAI_BASE_URL="https://openai-us-east-1-aws.flashback.tech/v1"
export FB_OPENAI_API_KEY="YOUR_AI_API_KEY"
export FB_MODEL="gpt-4o-mini"
```

***

## Quick connectivity check (cURL)

Run a simple chat completion request through Flashback:

```bash
curl -sS "$FB_OPENAI_BASE_URL/chat/completions" \
  -H "Authorization: Bearer $FB_OPENAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "'"$FB_MODEL"'",
    "messages": [
      {"role": "system", "content": "You are a concise assistant."},
      {"role": "user", "content": "Explain in one sentence what Flashback Gateway does."}
    ],
    "temperature": 0.2
  }'
```

If successful, you should receive a JSON response containing `choices[0].message.content`.

***

## Python example

Install dependency:

```bash
pip install openai
```

```python
# send_prompt.py
import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["FB_OPENAI_API_KEY"],
    base_url=os.environ["FB_OPENAI_BASE_URL"],
)

response = client.chat.completions.create(
    model=os.environ.get("FB_MODEL", "gpt-4o-mini"),
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "List 3 benefits of using an API gateway for AI workloads."}
    ],
    temperature=0.3,
)

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

Run:

```bash
python send_prompt.py
```

## JavaScript example

Install dependency:

```bash
npm install openai
```

```javascript
// sendPrompt.mjs
import OpenAI from "openai";

const client = new OpenAI({
  apiKey: process.env.FB_OPENAI_API_KEY,
  baseURL: process.env.FB_OPENAI_BASE_URL,
});

const response = await client.chat.completions.create({
  model: process.env.FB_MODEL || "gpt-4o-mini",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Give me 3 best practices for AI key rotation." }
  ],
  temperature: 0.3,
});

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

Run:

```bash
node sendPrompt.mjs
```

## Gateway integration validation checklist

When the call succeeds, validate these integration points:

* Authentication works with the repository-level **AI LLM API key**.
* The request is routed through your Flashback Gateway endpoint (not directly to provider).
* The selected `model` is authorized and available in your provider configuration.
* The same app code can keep a stable OpenAI-compatible contract while backend provider/policy evolves in Flashback.

## Common errors and fixes

* **401 Unauthorized / 403 Forbidden**
  * Verify you are using an AI key (not a storage key).
  * Check key status and access mode in repository API keys.
* **404 Not Found**
  * Confirm `FB_OPENAI_BASE_URL` includes `/v1`.
  * Ensure repository endpoint type is OPENAI.
* **400 model not found / invalid model**
  * Use a model exposed by your configured provider(s).
  * Recheck provider mapping/policies in AI LLM configuration.
* **Timeout / network issues**
  * Validate DNS/network access to your Flashback endpoint.
  * Confirm bridge node health and connectivity.

## Next steps

After this test succeeds, you can:

* implement fallback and reliability patterns for multi-provider AI routing,
* apply governance/policy controls,
* move to production with key rotation and observability.

Explore practical patterns in [AI LLM Use Cases](/guides/explore-use-cases/ai-llm.md).


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.flashback.tech/guides/setup-the-cloud-and-ai-gateway/test-a-repository/program-with-flashback-1.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.