Cross-Language API Handler Implementation

While the example in this documentation uses JavaScript/Node.js (which is recommended), you can set up the API handler in any language or framework. For JavaScript, Monacopilot provides a built-in function that handles all the necessary steps, such as generating the prompt, sending it to the model, and processing the response. However, if you're using a different language, you'll need to implement these steps manually.

Implementation Steps

1. Create an endpoint that accepts POST requests (e.g., /code-completion).

2. The endpoint should expect a JSON body containing completion metadata.

3. Use the metadata to construct a prompt for your LLM.

4. Send the prompt to your chosen LLM and get the completion.

5. Return a JSON response with the following structure:

   {
       "completion": "Generated completion text"
   }

   Or in case of an error:

   {
       "completion": null,
       "error": "Error message"
   }

Key Considerations

• The prompt should instruct the model to return only the completion text, without any additional formatting or explanations.
• The completion text should be ready for direct insertion into the editor.

Check out the prompt.ts file to see how Monacopilot generates the prompt. This will give you an idea of how to structure the prompt for your LLM to achieve the best completions.

Metadata Overview

The request body's completionMetadata object contains essential information for crafting a prompt for the LLM to generate accurate completions. See the Completion Metadata section for more details.

Example Implementation (Python with FastAPI)

Here's a basic example using Python and FastAPI:

from fastapi import FastAPI, Request

app = FastAPI()

@app.post('/code-completion')
async def handle_completion(request: Request):
    try:
        body = await request.json()
        metadata = body['completionMetadata']

        prompt = f"""Please complete the following {metadata['language']} code:

{metadata['textBeforeCursor']}
<cursor>
{metadata['textAfterCursor']}

Use modern {metadata['language']} practices and hooks where appropriate. Please provide only the completed part of the
code without additional comments or explanations."""

        # Simulate a response from a model
        response = "Your model's response here"

        return {
            'completion': response,
            'error': None
        }
    except Exception as e:
        return {
            'completion': None,
            'error': str(e)
        }

Now, Monacopilot is set up to send completion requests to the /code-completion endpoint and receive completions in response.

registerCompletion(monaco, editor, {
    endpoint: 'https://my-python-api.com/code-completion',
    // ... other options
});