feat: support pagination on spans resolver

app/schema.graphql

@@ -508,7 +508,6 @@ type PageInfo {
   hasPreviousPage: Boolean!
   startCursor: String
   endCursor: String
-  totalCount: Int!
 }
 
 enum PerformanceMetric {

integration-tests/pagination_queries.ipynb

@@ -0,0 +1,220 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Example Queries for Cursor-Based Pagination"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from phoenix.db import models\n",
+    "from sqlalchemy import and_, create_engine, select\n",
+    "from sqlalchemy.orm import aliased, sessionmaker"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "PostgresSession = sessionmaker(\n",
+    "    create_engine(\n",
+    "        \"postgresql+psycopg://localhost:5432/postgres?user=postgres&password=mysecretpassword\",\n",
+    "        echo=True,\n",
+    "    ),\n",
+    "    expire_on_commit=False,\n",
+    ")\n",
+    "SqliteSession = sessionmaker(\n",
+    "    create_engine(\"sqlite:////Users/xandersong/.phoenix/phoenix.db\", echo=True),\n",
+    "    expire_on_commit=False,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- filter: None\n",
+    "- sort: None\n",
+    "- after: None\n",
+    "- before: None\n",
+    "- first: 10\n",
+    "- last: None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "page_size = 10\n",
+    "with SqliteSession() as session:\n",
+    "    span_ids = session.scalars(select(models.Span.id).limit(page_size)).all()\n",
+    "span_ids"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- filter: None\n",
+    "- sort: None\n",
+    "- after: 5\n",
+    "- before: None\n",
+    "- first: 10\n",
+    "- last: None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cursor = 10\n",
+    "page_size = 10\n",
+    "with SqliteSession() as session:\n",
+    "    span_ids = session.scalars(\n",
+    "        select(models.Span.id).where(models.Span.id >= cursor).limit(page_size)\n",
+    "    ).all()\n",
+    "span_ids"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- filter: \"\"\"span_kind == 'LLM'\"\"\"\n",
+    "- sort: None\n",
+    "- after: 10\n",
+    "- before: None\n",
+    "- first: 10\n",
+    "- last: None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cursor = 10\n",
+    "page_size = 10\n",
+    "with SqliteSession() as session:\n",
+    "    span_ids = session.scalars(\n",
+    "        select(models.Span.id)\n",
+    "        .where(models.Span.span_kind == \"LLM\")\n",
+    "        .where(models.Span.id >= cursor)\n",
+    "        .limit(page_size)\n",
+    "    ).all()\n",
+    "span_ids"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- filter: None\n",
+    "- sort: prompt token count\n",
+    "- after: 10\n",
+    "- before: None\n",
+    "- first: 10\n",
+    "- last: None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cursor = 100\n",
+    "page_size = 10\n",
+    "with SqliteSession() as session:\n",
+    "    prompt_tokens = models.Span.attributes[[\"llm\", \"token_count\", \"prompt\"]]\n",
+    "    for index, span in enumerate(\n",
+    "        session.execute(\n",
+    "            select(models.Span.id, prompt_tokens)\n",
+    "            .where(models.Span.id >= cursor)\n",
+    "            .order_by(prompt_tokens, models.Span.id)\n",
+    "            .limit(page_size)\n",
+    "        )\n",
+    "    ):\n",
+    "        print(f\"{index=} {span=}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "- filter: attributes[\"llm.prompt.tokens] < 50\n",
+    "- sort: evals[\"Q&A Correctness\"].score DESC\n",
+    "- after: 10\n",
+    "- before: None\n",
+    "- first: 10\n",
+    "- last: None"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "span"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "span.attributes[\"llm\"]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cursor = 100\n",
+    "page_size = 10\n",
+    "A = aliased(models.SpanAnnotation, name=\"A\")\n",
+    "with SqliteSession() as session:\n",
+    "    for index, (span, score) in enumerate(\n",
+    "        session.execute(\n",
+    "            select(models.Span, A.score)\n",
+    "            .join(\n",
+    "                A,\n",
+    "                onclause=and_(\n",
+    "                    A.span_rowid == models.Span.id,\n",
+    "                    A.name == \"Q&A Correctness\",\n",
+    "                    A.annotator_kind == \"LLM\",\n",
+    "                ),\n",
+    "            )\n",
+    "            .where(models.Span.id >= cursor)\n",
+    "            .order_by(A.score.desc(), models.Span.id)\n",
+    "        )\n",
+    "    ):\n",
+    "        print(f\"{index=} {span.id=} {score=}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}