Add a plugin for llm

pyproject.toml

@@ -51,7 +51,7 @@ llama-index-readers-github = "^0.1.9"
 tiktoken = "^0.7.0"
 typer = "^0.12.3"
 rich = "^13.7.1"
-
+llm = { version="^0.14", optional=true }
 
 [tool.poetry.group.dev.dependencies]
 black = "^24.3.0"
@@ -74,6 +74,9 @@ azure = [
     "pulumi-azure-native",
     "azure-storage-file-share",
 ]
+llm_plugin = [
+    "llm",
+]
 
 [tool.poetry.scripts]
 reginald = "reginald.cli:cli"
@@ -82,6 +85,9 @@ reginald = "reginald.cli:cli"
 name = "PyPI"
 priority = "primary"
 
+[tool.poetry.plugins."llm"]
+reginald = "reginald.llm_reginald.llm_reginald"
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

reginald/llm_reginald/README.md

@@ -0,0 +1,19 @@
+# llm-reginald
+
+This module contains an [LLM](https://llm.datasette.io/) plugin for interacting with [Reginald](https://github.com/alan-turing-institute/reginald).
+
+The plugin is available to use immediately after reginald is installed, as long as the `llm_plugin` extra dependencies are selected when installing the package (either with `pip install .[llm_plugin]` or `poetry install --extras llm_plugin` or `poetry install --all-extras`).
+
+The plugin requires a running Reginald server to work.  By default this is assumed to be at `http://localhost:8000`.  Refer to the package README for instructions.
+
+Assuming [LLM](http://llm.datasette.io/) is installed, you can interact with Reginald like this:
+
+```
+llm -m reginald 'Who are you?'
+```
+
+Using a different server URL:
+
+```
+llm -m reginald -o server_url <server_url> ...
+```

reginald/llm_reginald/__init__.py

@@ -0,0 +1 @@
+from reginald.llm_reginald import *

reginald/llm_reginald/llm_reginald.py

@@ -0,0 +1,60 @@
+import uuid
+from typing import Optional
+from urllib.parse import urljoin
+
+import httpx
+import llm
+from pydantic import Field
+
+
+@llm.hookimpl
+def register_models(register):
+    register(Reginald())
+
+
+class Reginald(llm.Model):
+    model_id = "reginald"
+    can_stream = False
+
+    class Options(llm.Options):
+        server_url: str = Field(
+            default="http://localhost:8000",
+            title="Server URL",
+            description="The base URL of the Reginald server",
+        )
+
+        def direct_message_endpoint(self):
+            return urljoin(self.server_url, "direct_message")
+
+    def execute(self, prompt, stream, response, conversation):
+
+        message = prompt.prompt
+
+        # Reginald keeps a separate conversation history for each
+        # "user_id".  If 'conversation' is None (or doesn't have the
+        # user_id logged) start a new conversation by minting a new
+        # user_id history.  Otherwise, extract the logged user_id to
+        # continue that conversation.
+
+        try:
+            user_id = conversation.responses[0].response_json["user_id"]
+        except (TypeError, AttributeError, KeyError, IndexError) as e:
+            user_id = str(uuid.uuid4().int)
+
+        try:
+            with httpx.Client() as client:
+                reginald_reply = client.post(
+                    prompt.options.direct_message_endpoint(),
+                    json={"message": message, "user_id": user_id},
+                    timeout=None,
+                )
+            reginald_reply.raise_for_status()
+        except httpx.HTTPError as e:
+            # re-raise as an llm.ModelError for llm to report
+            raise llm.ModelError(
+                f"Could not connect to Reginald at {prompt.options.direct_message_endpoint()}.\n\nThe error was:\n    {e}.\n\nIs the model server running?"
+            )
+
+        yield reginald_reply.json()["message"]
+
+        response.response_json = {"user_id": user_id}