refactor(sessions): add dataloaders for session queries

scripts/fixtures/multi-turn_chat_sessions.ipynb

@@ -7,7 +7,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%pip install -Uqqq datasets openinference-instrumentation-openai openai-responses openai tiktoken langchain langchain-openai llama-index llama-index-llms-openai faker mdgen"
+    "%pip install -Uqqq datasets openinference-semantic-conventions openinference-instrumentation-openai faker openai-responses openai tiktoken"
    ]
   },
   {
@@ -25,7 +25,6 @@
     "import pandas as pd\n",
     "from datasets import load_dataset\n",
     "from faker import Faker\n",
-    "from mdgen import MarkdownPostProvider\n",
     "from openai_responses import OpenAIMock\n",
     "from openinference.instrumentation import using_session, using_user\n",
     "from openinference.instrumentation.openai import OpenAIInstrumentor\n",
@@ -39,8 +38,7 @@
     "import phoenix as px\n",
     "from phoenix.trace.span_evaluations import SpanEvaluations\n",
     "\n",
-    "fake = Faker(\"ja_JP\")\n",
-    "fake.add_provider(MarkdownPostProvider)"
+    "fake = Faker([\"ja_JP\", \"vi_VN\", \"ko_KR\", \"zh_CN\", \"th_TH\", \"bn_BD\"])"
    ]
   },
   {
@@ -104,7 +102,7 @@
     "    if p < 0.1:\n",
     "        return \":\" * randint(1, 5)\n",
     "    if p < 0.9:\n",
-    "        return Faker([\"ja_JP\", \"vi_VN\", \"ko_KR\", \"zh_CN\"]).address()\n",
+    "        return fake.address()\n",
     "    return int(abs(random()) * 1_000_000_000)\n",
     "\n",
     "\n",
@@ -113,15 +111,17 @@
     "    if p < 0.1:\n",
     "        return \":\" * randint(1, 5)\n",
     "    if p < 0.9:\n",
-    "        return Faker([\"ja_JP\", \"vi_VN\", \"ko_KR\", \"zh_CN\"]).name()\n",
+    "        return fake.name()\n",
     "    return int(abs(random()) * 1_000_000_000)\n",
     "\n",
     "\n",
-    "def export_spans():\n",
+    "def export_spans(prob_drop_root):\n",
     "    \"\"\"Export spans in random order for receiver testing\"\"\"\n",
     "    spans = list(in_memory_span_exporter.get_finished_spans())\n",
     "    shuffle(spans)\n",
     "    for span in spans:\n",
+    "        if span.parent is None and random() < prob_drop_root:\n",
+    "            continue\n",
     "        otlp_span_exporter.export([span])\n",
     "    in_memory_span_exporter.clear()\n",
     "    session_count = len({id_ for span in spans if (id_ := span.attributes.get(\"session.id\"))})\n",
@@ -147,7 +147,7 @@
     "        return\n",
     "    has_yielded = False\n",
     "    with tracer.start_as_current_span(\n",
-    "        Faker(\"ja_JP\").kana_name(),\n",
+    "        fake.city(),\n",
     "        attributes=dict(rand_span_kind()),\n",
     "        end_on_exit=False,\n",
     "    ) as root:\n",
@@ -185,6 +185,7 @@
    "source": [
     "session_count = randint(5, 10)\n",
     "tree_complexity = 4  # set to 0 for single span under root\n",
+    "prob_drop_root = 0.0  # probability that a root span gets dropped\n",
     "\n",
     "\n",
     "def simulate_openai():\n",
@@ -237,7 +238,7 @@
     "        simulate_openai()\n",
     "finally:\n",
     "    OpenAIInstrumentor().uninstrument()\n",
-    "spans = export_spans()\n",
+    "spans = export_spans(prob_drop_root)\n",
     "\n",
     "# Annotate root spans\n",
     "root_span_ids = pd.Series(\n",

src/phoenix/server/api/context.py

@@ -31,12 +31,16 @@
     MinStartOrMaxEndTimeDataLoader,
     ProjectByNameDataLoader,
     RecordCountDataLoader,
+    SessionIODataLoader,
+    SessionNumTracesDataLoader,
+    SessionTokenUsagesDataLoader,
     SpanAnnotationsDataLoader,
     SpanDatasetExamplesDataLoader,
     SpanDescendantsDataLoader,
     SpanProjectsDataLoader,
     TokenCountDataLoader,
     TraceByTraceIdsDataLoader,
+    TraceRootSpansDataLoader,
     UserRolesDataLoader,
     UsersDataLoader,
 )
@@ -68,12 +72,17 @@ class DataLoaders:
     latency_ms_quantile: LatencyMsQuantileDataLoader
     min_start_or_max_end_times: MinStartOrMaxEndTimeDataLoader
     record_counts: RecordCountDataLoader
+    session_first_inputs: SessionIODataLoader
+    session_last_outputs: SessionIODataLoader
+    session_num_traces: SessionNumTracesDataLoader
+    session_token_usages: SessionTokenUsagesDataLoader
     span_annotations: SpanAnnotationsDataLoader
     span_dataset_examples: SpanDatasetExamplesDataLoader
     span_descendants: SpanDescendantsDataLoader
     span_projects: SpanProjectsDataLoader
     token_counts: TokenCountDataLoader
     trace_by_trace_ids: TraceByTraceIdsDataLoader
+    trace_root_spans: TraceRootSpansDataLoader
     project_by_name: ProjectByNameDataLoader
     users: UsersDataLoader
     user_roles: UserRolesDataLoader

src/phoenix/server/api/dataloaders/__init__.py

@@ -19,12 +19,16 @@
 from .min_start_or_max_end_times import MinStartOrMaxEndTimeCache, MinStartOrMaxEndTimeDataLoader
 from .project_by_name import ProjectByNameDataLoader
 from .record_counts import RecordCountCache, RecordCountDataLoader
+from .session_io import SessionIODataLoader
+from .session_num_traces import SessionNumTracesDataLoader
+from .session_token_usages import SessionTokenUsagesDataLoader
 from .span_annotations import SpanAnnotationsDataLoader
 from .span_dataset_examples import SpanDatasetExamplesDataLoader
 from .span_descendants import SpanDescendantsDataLoader
 from .span_projects import SpanProjectsDataLoader
 from .token_counts import TokenCountCache, TokenCountDataLoader
 from .trace_by_trace_ids import TraceByTraceIdsDataLoader
+from .trace_root_spans import TraceRootSpansDataLoader
 from .user_roles import UserRolesDataLoader
 from .users import UsersDataLoader
 
@@ -45,11 +49,15 @@
     "LatencyMsQuantileDataLoader",
     "MinStartOrMaxEndTimeDataLoader",
     "RecordCountDataLoader",
+    "SessionIODataLoader",
+    "SessionNumTracesDataLoader",
+    "SessionTokenUsagesDataLoader",
     "SpanDatasetExamplesDataLoader",
     "SpanDescendantsDataLoader",
     "SpanProjectsDataLoader",
     "TokenCountDataLoader",
     "TraceByTraceIdsDataLoader",
+    "TraceRootSpansDataLoader",
     "ProjectByNameDataLoader",
     "SpanAnnotationsDataLoader",
     "UsersDataLoader",

src/phoenix/server/api/dataloaders/session_io.py

@@ -0,0 +1,75 @@
+from functools import cached_property
+from typing import Literal, Optional, cast
+
+from openinference.semconv.trace import SpanAttributes
+from sqlalchemy import Select, func, select
+from strawberry.dataloader import DataLoader
+from typing_extensions import TypeAlias, assert_never
+
+from phoenix.db import models
+from phoenix.server.types import DbSessionFactory
+from phoenix.trace.schemas import MimeType, SpanIOValue
+
+Key: TypeAlias = int
+Result: TypeAlias = Optional[SpanIOValue]
+
+Kind = Literal["first_input", "last_output"]
+
+
+class SessionIODataLoader(DataLoader[Key, Result]):
+    def __init__(self, db: DbSessionFactory, kind: Kind) -> None:
+        super().__init__(load_fn=self._load_fn)
+        self._db = db
+        self._kind = kind
+
+    @cached_property
+    def _subq(self) -> Select[tuple[Optional[int], str, str, int]]:
+        stmt = (
+            select(models.Trace.project_session_rowid.label("id_"))
+            .join_from(models.Span, models.Trace)
+            .where(models.Span.parent_id.is_(None))
+        )
+        if self._kind == "first_input":
+            stmt = stmt.add_columns(
+                models.Span.attributes[INPUT_VALUE].label("value"),
+                models.Span.attributes[INPUT_MIME_TYPE].label("mime_type"),
+                func.row_number()
+                .over(
+                    partition_by=models.Trace.project_session_rowid,
+                    order_by=[models.Trace.start_time.asc(), models.Trace.id.asc()],
+                )
+                .label("rank"),
+            )
+        elif self._kind == "last_output":
+            stmt = stmt.add_columns(
+                models.Span.attributes[OUTPUT_VALUE].label("value"),
+                models.Span.attributes[OUTPUT_MIME_TYPE].label("mime_type"),
+                func.row_number()
+                .over(
+                    partition_by=models.Trace.project_session_rowid,
+                    order_by=[models.Trace.start_time.desc(), models.Trace.id.desc()],
+                )
+                .label("rank"),
+            )
+        else:
+            assert_never(self._kind)
+        return cast(Select[tuple[Optional[int], str, str, int]], stmt)
+
+    def _stmt(self, *keys: Key) -> Select[tuple[int, str, str]]:
+        subq = self._subq.where(models.Trace.project_session_rowid.in_(keys)).subquery()
+        return select(subq.c.id_, subq.c.value, subq.c.mime_type).filter_by(rank=1)
+
+    async def _load_fn(self, keys: list[Key]) -> list[Result]:
+        async with self._db() as session:
+            result: dict[Key, SpanIOValue] = {
+                id_: SpanIOValue(value=value, mime_type=MimeType(mime_type))
+                async for id_, value, mime_type in await session.stream(self._stmt(*keys))
+                if id_ is not None
+            }
+        return [result.get(key) for key in keys]
+
+
+INPUT_VALUE = SpanAttributes.INPUT_VALUE.split(".")
+INPUT_MIME_TYPE = SpanAttributes.INPUT_MIME_TYPE.split(".")
+OUTPUT_VALUE = SpanAttributes.OUTPUT_VALUE.split(".")
+OUTPUT_MIME_TYPE = SpanAttributes.OUTPUT_MIME_TYPE.split(".")

src/phoenix/server/api/dataloaders/session_num_traces.py

@@ -0,0 +1,30 @@
+from sqlalchemy import func, select
+from strawberry.dataloader import DataLoader
+from typing_extensions import TypeAlias
+
+from phoenix.db import models
+from phoenix.server.types import DbSessionFactory
+
+Key: TypeAlias = int
+Result: TypeAlias = int
+
+
+class SessionNumTracesDataLoader(DataLoader[Key, Result]):
+    def __init__(self, db: DbSessionFactory) -> None:
+        super().__init__(load_fn=self._load_fn)
+        self._db = db
+
+    async def _load_fn(self, keys: list[Key]) -> list[Result]:
+        stmt = (
+            select(
+                models.Trace.project_session_rowid.label("id_"),
+                func.count(models.Trace.id).label("value"),
+            )
+            .group_by(models.Trace.project_session_rowid)
+            .where(models.Trace.project_session_rowid.in_(keys))
+        )
+        async with self._db() as session:
+            result: dict[Key, int] = {
+                id_: value async for id_, value in await session.stream(stmt) if id_ is not None
+            }
+        return [result.get(key, 0) for key in keys]

src/phoenix/server/api/dataloaders/session_token_usages.py

@@ -0,0 +1,41 @@
+from sqlalchemy import func, select
+from sqlalchemy.sql.functions import coalesce
+from strawberry.dataloader import DataLoader
+from typing_extensions import TypeAlias
+
+from phoenix.db import models
+from phoenix.server.types import DbSessionFactory
+from phoenix.trace.schemas import TokenUsage
+
+Key: TypeAlias = int
+Result: TypeAlias = TokenUsage
+
+
+class SessionTokenUsagesDataLoader(DataLoader[Key, Result]):
+    def __init__(self, db: DbSessionFactory) -> None:
+        super().__init__(load_fn=self._load_fn)
+        self._db = db
+
+    async def _load_fn(self, keys: list[Key]) -> list[Result]:
+        stmt = (
+            select(
+                models.Trace.project_session_rowid.label("id_"),
+                func.sum(coalesce(models.Span.cumulative_llm_token_count_prompt, 0)).label(
+                    "prompt"
+                ),
+                func.sum(coalesce(models.Span.cumulative_llm_token_count_completion, 0)).label(
+                    "completion"
+                ),
+            )
+            .join_from(models.Span, models.Trace)
+            .where(models.Span.parent_id.is_(None))
+            .where(models.Trace.project_session_rowid.in_(keys))
+            .group_by(models.Trace.project_session_rowid)
+        )
+        async with self._db() as session:
+            result: dict[Key, TokenUsage] = {
+                id_: TokenUsage(prompt=prompt, completion=completion)
+                async for id_, prompt, completion in await session.stream(stmt)
+                if id_ is not None
+            }
+        return [result.get(key, TokenUsage()) for key in keys]

src/phoenix/server/api/dataloaders/trace_by_trace_ids.py

@@ -7,10 +7,7 @@
 from phoenix.db import models
 from phoenix.server.types import DbSessionFactory
 
-TraceId: TypeAlias = str
-Key: TypeAlias = TraceId
-TraceRowId: TypeAlias = int
-ProjectRowId: TypeAlias = int
+Key: TypeAlias = str
 Result: TypeAlias = Optional[models.Trace]
 
 
@@ -22,5 +19,7 @@ def __init__(self, db: DbSessionFactory) -> None:
     async def _load_fn(self, keys: List[Key]) -> List[Result]:
         stmt = select(models.Trace).where(models.Trace.trace_id.in_(keys))
         async with self._db() as session:
-            result = {trace.trace_id: trace for trace in await session.scalars(stmt)}
+            result: dict[Key, models.Trace] = {
+                trace.trace_id: trace async for trace in await session.stream_scalars(stmt)
+            }
         return [result.get(trace_id) for trace_id in keys]

src/phoenix/server/api/dataloaders/trace_root_spans.py

@@ -0,0 +1,32 @@
+from typing import List, Optional
+
+from sqlalchemy import select
+from sqlalchemy.orm import contains_eager
+from strawberry.dataloader import DataLoader
+from typing_extensions import TypeAlias
+
+from phoenix.db import models
+from phoenix.server.types import DbSessionFactory
+
+Key: TypeAlias = int
+Result: TypeAlias = Optional[models.Span]
+
+
+class TraceRootSpansDataLoader(DataLoader[Key, Result]):
+    def __init__(self, db: DbSessionFactory) -> None:
+        super().__init__(load_fn=self._load_fn)
+        self._db = db
+
+    async def _load_fn(self, keys: List[Key]) -> List[Result]:
+        stmt = (
+            select(models.Span)
+            .join(models.Trace)
+            .where(models.Span.parent_id.is_(None))
+            .where(models.Trace.id.in_(keys))
+            .options(contains_eager(models.Span.trace).load_only(models.Trace.trace_id))
+        )
+        async with self._db() as session:
+            result: dict[Key, models.Span] = {
+                span.trace_rowid: span async for span in await session.stream_scalars(stmt)
+            }
+        return [result.get(key) for key in keys]