feat: Add a script to extract openapi.yaml

.gitignore

@@ -2,3 +2,4 @@
 __pycache__
 .env
 .vscode/
+openapi.yaml

dewy/common/db.py

@@ -30,7 +30,10 @@ async def init_pool(conn: asyncpg.Connection):
 
 
 def _pg_pool(request: Request) -> asyncpg.Pool:
-    return request.state.pg_pool
+    pg_pool = request.state.pg_pool
+    if pg_pool is None:
+        raise ValueError("DB not configured. Unable to get pool.")
+    return pg_pool
 
 
 PgPoolDep = Annotated[asyncpg.Pool, Depends(_pg_pool)]

dewy/config.py

@@ -1,8 +1,7 @@
 from typing import Any, Optional
 
 from fastapi.routing import APIRoute
-from pydantic import PostgresDsn, RedisDsn, ValidationInfo, field_validator
-from pydantic_core import Url
+from pydantic import PostgresDsn
 from pydantic_settings import BaseSettings, SettingsConfigDict
 
 from dewy.constants import Environment
@@ -21,8 +20,11 @@ class Config(BaseSettings):
     SERVE_ADMIN_UI: bool = True
     """If true, serve the admin UI."""
 
-    DB: PostgresDsn
-    """The Postgres database to connect to."""
+    DB: Optional[PostgresDsn] = None
+    """The Postgres database to connect to.
+
+    If not provided, none of the CRUD methods will work.
+    """
 
     APPLY_MIGRATIONS: bool = True
     """Whether migrations should be applied to the database.
@@ -34,73 +36,12 @@ class Config(BaseSettings):
     ENVIRONMENT: Environment = Environment.PRODUCTION
     """The environment the application is running in."""
 
-    REDIS: Optional[RedisDsn] = None
-    """The Redis service to use for queueing, indexing and document storage."""
-
-    EMBEDDING_MODEL: str = ""
-    """The embedding model to use.
-
-    This is a string of the form `<kind>[:<model>]` with the following options:
-
-    1. `local[:<path or repository>]` -- Run a model locally. If this is a path
-       it will attempt to load a model from that location. Otherwise, it should
-       be a Hugging Face repository from which to retrieve the model.
-    2. `openai[:<name>]` -- The named OpenAI model. `OPENAI_API_KEY` must be set.
-    3. `ollama:<name>` -- The named Ollama model. `OLLAMA_BASE_URL` must be set.
-
-    In each of these cases, you can omit the second part for the default model of the
-    given kind.
-
-    If unset, this will default to `"openai"` if an OpenAI API KEY is available and
-    otherwise will use `"local"`.
-
-    NOTE: Changing embedding models is not currently supported.
-    """
-
-    LLM_MODEL: str = ""
-    """The LLM model to use.
-
-    This is a string of the form `<kind>:<model>` with the following options:
-
-    1. `local[:<path or repository>]` -- Run a model locally. If this is a path
-       it will attempt to load a model from that location. Otherwise, it should
-       be a Hugging Face repository from which to retrieve the model.
-    2. `openai[:<name>]` -- The named OpenAI model. `OPENAI_API_KEY` must be set.
-    3. `ollama:<name>` -- The named Ollama model. `OLLAMA_BASE_URL` must be set.
-
-    In each of these cases, you can omit the second part for the default model of the
-    given kind.
-
-    If unset, this will default to `"openai"` if an OpenAI API KEY is available and
-    otherwise will use `"local"`.
-    """
-
     OPENAI_API_KEY: Optional[str] = None
     """ The OpenAI API Key to use for OpenAI models.
 
     This is required for using openai models.
     """
 
-    OLLAMA_BASE_URL: Optional[Url] = None
-    """The Base URL for Ollama.
-
-    This is required for using ollama models.
-    """
-
-    @field_validator("OLLAMA_BASE_URL")
-    def validate_ollama_base_url(cls, v, info: ValidationInfo):
-        MODELS = ["LLM_MODEL", "EMBEDDING_MODEL"]
-        if v is None:
-            for model in MODELS:
-                context = info.context
-                if context:
-                    value = context.get(model, "")
-                    if value.startswith("ollama"):
-                        raise ValueError(
-                            f"{info.field_name} must be set to use '{model}={value}'"
-                        )
-        return v
-
 
 settings = Config()
 

dewy/main.py

@@ -1,7 +1,7 @@
 import contextlib
 import os
 from pathlib import Path
-from typing import AsyncIterator, TypedDict
+from typing import AsyncIterator, Optional, TypedDict
 
 import asyncpg
 import uvicorn
@@ -17,7 +17,7 @@
 
 
 class State(TypedDict):
-    pg_pool: asyncpg.Pool
+    pg_pool: Optional[asyncpg.Pool]
 
 
 # Resolve paths, independent of PWD
@@ -30,17 +30,18 @@ class State(TypedDict):
 async def lifespan(_app: FastAPI) -> AsyncIterator[State]:
     """Function creating instances used during the lifespan of the service."""
 
-    # TODO: Look at https://gist.github.com/mattbillenstein/270a4d44cbdcb181ac2ed58526ae137d
-    # for simple migration scripts.
-    async with db.create_pool(settings.DB.unicode_string()) as pg_pool:
-        if settings.APPLY_MIGRATIONS:
-            async with pg_pool.acquire() as conn:
-                await apply_migrations(conn, migration_dir=migrations_path)
-
-        logger.info("Created database connection")
-        state = {
-            "pg_pool": pg_pool,
-        }
+    if settings.DB is not None:
+        async with db.create_pool(settings.DB.unicode_string()) as pg_pool:
+            if settings.APPLY_MIGRATIONS:
+                async with pg_pool.acquire() as conn:
+                    await apply_migrations(conn, migration_dir=migrations_path)
+
+            logger.info("Created database connection")
+            state = State(pg_pool=pg_pool)
+            yield state
+    else:
+        logger.warn("No database configured. CRUD methods will fail.")
+        state = State(pg_pool=None)
         yield state
 
 

example_notebook.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -15,17 +15,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'id': 1, 'name': 'my_collection', 'text_embedding_model': 'openai:text-embedding-ada-002', 'text_distance_metric': 'cosine'}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "response = client.put(f\"/collections/\",\n",
     "                      json = {\n",
@@ -39,17 +31,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'id': 1, 'collection_id': 1, 'url': 'https://arxiv.org/pdf/2305.14283.pdf', 'ingest_state': 'pending', 'ingest_error': None}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Add \"Query Rewriting for Retrieval-Augmented Large Language Models\"\n",
     "response = client.put(f\"/documents/\",\n",
@@ -64,17 +48,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "{'id': 1, 'collection_id': 1, 'url': 'https://arxiv.org/pdf/2305.14283.pdf', 'ingest_state': 'ingested', 'ingest_error': None}\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Report the status of the document ingestion.\n",
     "response = client.get(f\"/documents/{document_id}\")\n",
@@ -83,25 +59,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "JSONDecodeError",
-     "evalue": "Expecting value: line 1 column 1 (char 0)",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mJSONDecodeError\u001b[0m                           Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[7], line 9\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[38;5;66;03m# Retrieve 4 items with no summary.\u001b[39;00m\n\u001b[1;32m      2\u001b[0m results \u001b[38;5;241m=\u001b[39m client\u001b[38;5;241m.\u001b[39mpost(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/chunks/retrieve\u001b[39m\u001b[38;5;124m\"\u001b[39m,\n\u001b[1;32m      3\u001b[0m                       json \u001b[38;5;241m=\u001b[39m {\n\u001b[1;32m      4\u001b[0m                         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcollection_id\u001b[39m\u001b[38;5;124m\"\u001b[39m: collection_id,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m      7\u001b[0m                       },\n\u001b[1;32m      8\u001b[0m                       timeout \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[0;32m----> 9\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[43mresults\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjson\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m)\n\u001b[1;32m     10\u001b[0m results\u001b[38;5;241m.\u001b[39mraise_for_status()\n\u001b[1;32m     12\u001b[0m results\u001b[38;5;241m.\u001b[39mjson()\n",
-      "File \u001b[0;32m~/Library/Caches/pypoetry/virtualenvs/knowledge-7QbvxqGg-py3.11/lib/python3.11/site-packages/httpx/_models.py:762\u001b[0m, in \u001b[0;36mResponse.json\u001b[0;34m(self, **kwargs)\u001b[0m\n\u001b[1;32m    761\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mjson\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: typing\u001b[38;5;241m.\u001b[39mAny) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m typing\u001b[38;5;241m.\u001b[39mAny:\n\u001b[0;32m--> 762\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mjsonlib\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mloads\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcontent\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/__init__.py:346\u001b[0m, in \u001b[0;36mloads\u001b[0;34m(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)\u001b[0m\n\u001b[1;32m    341\u001b[0m     s \u001b[38;5;241m=\u001b[39m s\u001b[38;5;241m.\u001b[39mdecode(detect_encoding(s), \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msurrogatepass\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    343\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m (\u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m    344\u001b[0m         parse_int \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m parse_float \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m\n\u001b[1;32m    345\u001b[0m         parse_constant \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m object_pairs_hook \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m kw):\n\u001b[0;32m--> 346\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43m_default_decoder\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mdecode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    347\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mcls\u001b[39m \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    348\u001b[0m     \u001b[38;5;28mcls\u001b[39m \u001b[38;5;241m=\u001b[39m JSONDecoder\n",
-      "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/decoder.py:337\u001b[0m, in \u001b[0;36mJSONDecoder.decode\u001b[0;34m(self, s, _w)\u001b[0m\n\u001b[1;32m    332\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mdecode\u001b[39m(\u001b[38;5;28mself\u001b[39m, s, _w\u001b[38;5;241m=\u001b[39mWHITESPACE\u001b[38;5;241m.\u001b[39mmatch):\n\u001b[1;32m    333\u001b[0m \u001b[38;5;250m    \u001b[39m\u001b[38;5;124;03m\"\"\"Return the Python representation of ``s`` (a ``str`` instance\u001b[39;00m\n\u001b[1;32m    334\u001b[0m \u001b[38;5;124;03m    containing a JSON document).\u001b[39;00m\n\u001b[1;32m    335\u001b[0m \n\u001b[1;32m    336\u001b[0m \u001b[38;5;124;03m    \"\"\"\u001b[39;00m\n\u001b[0;32m--> 337\u001b[0m     obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mraw_decode\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43midx\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m_w\u001b[49m\u001b[43m(\u001b[49m\u001b[43ms\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mend\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    338\u001b[0m     end \u001b[38;5;241m=\u001b[39m _w(s, end)\u001b[38;5;241m.\u001b[39mend()\n\u001b[1;32m    339\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m end \u001b[38;5;241m!=\u001b[39m \u001b[38;5;28mlen\u001b[39m(s):\n",
-      "File \u001b[0;32m~/.pyenv/versions/3.11.4/lib/python3.11/json/decoder.py:355\u001b[0m, in \u001b[0;36mJSONDecoder.raw_decode\u001b[0;34m(self, s, idx)\u001b[0m\n\u001b[1;32m    353\u001b[0m     obj, end \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mscan_once(s, idx)\n\u001b[1;32m    354\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m err:\n\u001b[0;32m--> 355\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m JSONDecodeError(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpecting value\u001b[39m\u001b[38;5;124m\"\u001b[39m, s, err\u001b[38;5;241m.\u001b[39mvalue) \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    356\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m obj, end\n",
-      "\u001b[0;31mJSONDecodeError\u001b[0m: Expecting value: line 1 column 1 (char 0)"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# Retrieve 4 items with no summary.\n",
     "results = client.post(f\"/chunks/retrieve\",\n",

pyproject.toml

@@ -13,6 +13,34 @@ include = [
 [tool.poetry.scripts]
 dewy = "dewy.main:run"
 
+[tool.poe.tasks.check-ruff]
+help = "Check ruff formatting and checks."
+sequence = ["check-ruff-format", "check-ruff-checks"]
+
+[tool.poe.tasks.fix-ruff]
+help = "Fix ruff formatting and checks."
+sequence = ["fix-ruff-format", "fix-ruff-checks"]
+
+[tool.poe.tasks.check-ruff-checks]
+cmd = "ruff check"
+
+[tool.poe.tasks.check-ruff-format]
+cmd = "ruff format --check"
+
+[tool.poe.tasks.fix-ruff-checks]
+cmd = "ruff check --fix"
+
+[tool.poe.tasks.fix-ruff-format]
+cmd = "ruff format"
+
+[tool.poe.tasks.test]
+help = "Run unit and feature tests"
+cmd  = "pytest"
+
+[tool.poe.tasks.extract-openapi]
+help = "Update openapi.toml from the swagger docs"
+cmd = "python scripts/extract_openapi.py dewy.main:app"
+
 [tool.poetry.dependencies]
 python = "^3.11"
 pydantic = "^2.5.3"