Document how to create completions using full notebook content

docs/source/developers/index.md

@@ -228,6 +228,94 @@ class MyCompletionProvider(BaseProvider, FakeListLLM):
         )
 ```
 
+
+#### Using the full notebook content for completions
+
+The `InlineCompletionRequest` contains the `path` of the current document (file or notebook).
+Inline completion providers can use this path to extract the content of the notebook from the disk,
+however such content may be outdated if the user has not saved the notebook recently.
+
+The accuracy of the suggestions can be slightly improved by combining the potentially outdated content of previous/following cells
+with the `prefix` and `suffix` which describe the up-to-date state of the current cell (identified by `cell_id`).
+
+Still, reading the full notebook from the disk may be slow for larger notebooks, which conflicts with the low latency requirement of inline completion.
+
+A better approach is to use the live copy of the notebook document that is persisted on the jupyter-server when *collaborative* document models are enabled.
+Two packages need to be installed to access the collaborative models:
+- `jupyter-server-ydoc` (>= 1.0) stores the collaborative models in the jupyter-server on runtime
+- `jupyter-docprovider` (>= 1.0) reconfigures JupyterLab/Notebook to use the collaborative models
+
+Both packages are automatically installed with `jupyter-collaboration` (in v3.0 or newer), however installing `jupyter-collaboration` is not required to take advantage of *collaborative* models.
+
+The snippet below demonstrates how to retrieve the content of all cells of a given type from the in-memory copy of the collaborative model (without additional disk reads).
+
+```python
+from jupyter_ydoc import YNotebook
+
+
+class MyCompletionProvider(BaseProvider, FakeListLLM):
+    id = "my_provider"
+    name = "My Provider"
+    model_id_key = "model"
+    models = ["model_a"]
+
+    def __init__(self, **kwargs):
+        kwargs["responses"] = ["This fake response will not be used for completion"]
+        super().__init__(**kwargs)
+
+    async def _get_prefix_and_suffix(self, request: InlineCompletionRequest):
+        prefix = request.prefix
+        suffix = request.suffix.strip()
+
+        server_ydoc = self.server_settings.get("jupyter_server_ydoc", None)
+        if not server_ydoc:
+            # fallback to prefix/suffix from single cell
+            return prefix, suffix
+
+        is_notebook = request.path.endswith("ipynb")
+        document = await server_ydoc.get_document(
+            path=request.path,
+            content_type="notebook" if is_notebook else "file",
+            file_format="json" if is_notebook else "text"
+        )
+        if not document or not isinstance(document, YNotebook):
+            return prefix, suffix
+
+        cell_type = "markdown" if request.language == "markdown" else "code"
+
+        is_before_request_cell = True
+        before = []
+        after = [suffix]
+
+        for cell in document.ycells:
+            if is_before_request_cell and cell["id"] == request.cell_id:
+                is_before_request_cell = False
+                continue
+            if cell["cell_type"] != cell_type:
+                continue
+            source = cell["source"].to_py()
+            if is_before_request_cell:
+                before.append(source)
+            else:
+                after.append(source)
+
+        before.append(prefix)
+        prefix = "\n\n".join(before)
+        suffix = "\n\n".join(after)
+        return prefix, suffix
+
+    async def generate_inline_completions(self, request: InlineCompletionRequest):
+        prefix, suffix = await self._get_prefix_and_suffix(request)
+
+        return InlineCompletionReply(
+            list=InlineCompletionList(items=[
+                {"insertText": your_llm_function(prefix, suffix)}
+            ]),
+            reply_to=request.number,
+        )
+```
+
+
 ## Prompt templates
 
 Each provider can define **prompt templates** for each supported format. A prompt

packages/jupyter-ai-magics/jupyter_ai_magics/providers.py

@@ -5,6 +5,7 @@
 import io
 import json
 from concurrent.futures import ThreadPoolExecutor
+from types import MappingProxyType
 from typing import (
     Any,
     AsyncIterator,
@@ -265,6 +266,13 @@ class Config:
     provider is selected.
     """
 
+    server_settings: ClassVar[Optional[MappingProxyType[str, Any]]] = None
+    """Settings passed on from jupyter-ai package.
+
+    The same server settings are shared between all providers.
+    Providers are not allowed to mutate this dictionary.
+    """
+
     @classmethod
     def chat_models(self):
         """Models which are suitable for chat."""

packages/jupyter-ai/jupyter_ai/extension.py

@@ -1,11 +1,12 @@
 import os
 import re
 import time
+import types
 
 from dask.distributed import Client as DaskClient
 from importlib_metadata import entry_points
 from jupyter_ai.chat_handlers.learn import Retriever
-from jupyter_ai_magics import JupyternautPersona
+from jupyter_ai_magics import BaseProvider, JupyternautPersona
 from jupyter_ai_magics.utils import get_em_providers, get_lm_providers
 from jupyter_server.extension.application import ExtensionApp
 from tornado.web import StaticFileHandler
@@ -202,6 +203,11 @@ def initialize_settings(self):
             defaults=defaults,
         )
 
+        # Expose a subset of settings as read-only to the providers
+        BaseProvider.server_settings = types.MappingProxyType(
+            self.serverapp.web_app.settings
+        )
+
         self.log.info("Registered providers.")
 
         self.log.info(f"Registered {self.name} server extension")