diff --git a/.github/ISSUE_TEMPLATE/bug-report.md b/.github/ISSUE_TEMPLATE/bug-report.md index 4a921f130..1b535e0ac 100644 --- a/.github/ISSUE_TEMPLATE/bug-report.md +++ b/.github/ISSUE_TEMPLATE/bug-report.md @@ -4,7 +4,7 @@ about: Thanks for taking the time to fill out this bug report! Please complete t following form to help us assist you. title: "[BUG]" labels: bug -assignees: sfc-gh-jreini +assignees: sfc-gh-pdharmana --- diff --git a/.github/ISSUE_TEMPLATE/feature_request.md b/.github/ISSUE_TEMPLATE/feature_request.md index 7666d8a2e..38354fcfd 100644 --- a/.github/ISSUE_TEMPLATE/feature_request.md +++ b/.github/ISSUE_TEMPLATE/feature_request.md @@ -4,7 +4,7 @@ about: Thanks for taking the time to fill out this feature request! Please compl the following form to help us assist you. title: "[FEAT] " labels: enhancement -assignees: sfc-gh-jreini +assignees: sfc-gh-pdharmana --- diff --git a/examples/quickstart/snowflake_ai_observability_example.ipynb b/examples/quickstart/snowflake_ai_observability_example.ipynb new file mode 100644 index 000000000..0f5c8e346 --- /dev/null +++ b/examples/quickstart/snowflake_ai_observability_example.ipynb @@ -0,0 +1,269 @@ +{ + "cells": [ + { + "attachments": { + "image-2.png": { + "image/png": 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" + } + }, + "cell_type": "markdown", + "id": "2d9ee223", + "metadata": {}, + "source": [ + "### Quickstart Guides\n", + "#### Tutorial: AI Observability for RAG using Cortex Search and Cortex LLMs\n", + "This tutorial will show you how to use AI observability with Snowflake on a RAG application built\n", + "using [Cortex Search](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/cortex-search-overview) and LLMs using [Cortex Complete function](https://docs.snowflake.com/en/sql-reference/functions/complete-snowflake-cortex) . Before adding observability,\n", + "you will need to create an application to observe. To do so, start with [Cortex Search Tutorial 3](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/tutorials/cortex-search-tutorial-3-chat-advanced),\n", + "completing through step 4. Once you have created the cortex search service following the\n", + "tutorial, return here to finish building the RAG and add observability.\n", + "\n", + "**Introduction**\n", + "\n", + "This tutorial describes how to add observability to a simple RAG application.\n", + "**What you will learn**\n", + "\n", + "- Add observability to a RAG application built with Cortex Search & Cortex & LLMs\n", + "- Compute evaluation metrics using Cortex LLMs running in the warehouse\n", + "- Log evaluation metrics and traces to Snowflake\n", + "\n", + "**Prerequisites**\n", + "\n", + "The following prerequisites are required to complete this tutorial:\n", + "\n", + "- You have a Snowflake account and user with a role that grants the necessary privileges\n", + "to create a database, tables, virtual warehouse objects, Cortex Search services, call\n", + "Cortex LLMs and use Snowflake Notebooks. Refer to the [Snowflake in 20 minutes](https://docs.snowflake.com/en/user-guide/tutorials/snowflake-in-20minutes) for\n", + "instructions to meet these requirements.\n", + "\n", + "- You have already created a Cortex Search Service using [Cortex Search Tutorial 3](https://docs.snowflake.com/en/user-guide/snowflake-cortex/cortex-search/tutorials/cortex-search-tutorial-3-chat-advanced).\n", + "\n", + "**Step 1: Setup**\n", + "\n", + "1. Create a new schema in the Cortex Search Tutorial Database created in the prerequisites.\n", + "\n", + "SQL\n", + "```\n", + "USE CORTEX_SEARCH_TUTORIAL_DB;\n", + "CREATE OR REPLACE SCHEMA AI_OBSERVABILITY_SCHEMA;\n", + "```\n", + "This creates a new schema to store the traces and evaluation results needed for observability.\n", + "\n", + "2. Create a Snowflake notebook using `CORTEX_SEARCH_TUTORIAL_DB` database,\n", + "`AI_OBSERVABILITY_SCHEMA`, and `CORTEX_SEARCH_TUTORIAL_WH` warehouse.\n", + "![image.png](attachment:image.png)\n", + "\n", + "3. Add the following Trulens and Snowflake ML python packages to the snowflake notebook.\n", + "\n", + "- `trulens-core`\n", + "- `trulens-feedback`\n", + "- `trulens-connectors-snowflake`\n", + "- `trulens-providers-cortex`\n", + "- `snowflake-ml-python`\n", + "\n", + "![image-2.png](attachment:image-2.png)\n", + "\n", + "**Step 2: Set up RAG application and add instrumentation for tracing**\n", + "\n", + "\n", + "Now that we've set up the components we need from Snowflake Cortex, we can build our RAG.\n", + "We'll do this by creating a custom python class with methods for retrieval generation and chaining.\n", + "We'll also add TruLens instrumentation with the `@instrument` decorator to each method in our app\n", + "we’d like to record.\n", + "The first thing we need to do is to set the database connection to Snowflake where we'll log the\n", + "traces and evaluation results from our application. Since we’re already working in a Snowflake\n", + "notebook, we’ll do this by creating a connector for TruLens to Snowflake with the active Snowpark\n", + "Session." + ] + }, + { + "cell_type": "markdown", + "id": "9342d4bc", + "metadata": {}, + "source": [ + "### This example quickstart is assumed to be run within Snowflake notebook runtime" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3775908f-ca36-4846-8f38-5adca39217f2", + "metadata": {}, + "outputs": [], + "source": [ + "from snowflake.snowpark.context import get_active_session\n", + "from trulens.connectors.snowflake import SnowflakeConnector\n", + "from trulens.core import TruSession\n", + "\n", + "# Get Snowflake session\n", + "snowpark_session = get_active_session()\n", + "\n", + "# Create database connection\n", + "tru_snowflake_connector = SnowflakeConnector(snowpark_session=snowpark_session)\n", + "tru_session = TruSession(connector=tru_snowflake_connector)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "974dc779-dae9-477d-a3ae-0ec1161cd74d", + "metadata": {}, + "outputs": [], + "source": [ + "from typing import List\n", + "\n", + "from snowflake.core import Root\n", + "from snowflake.cortex import Complete\n", + "from snowflake.snowpark.context import get_active_session\n", + "from trulens.apps.custom import instrument\n", + "\n", + "\n", + "# Create RAG application with Cortex Search and Cortex Complete function\n", + "class RAG:\n", + " def __init__(self, database, schema, search_service, limit_to_retrieve):\n", + " self.database = database\n", + " self.schema = schema\n", + " self.search_service = search_service\n", + " self.limit_to_retrieve = limit_to_retrieve\n", + " self.session = get_active_session()\n", + " self.session.use_schema(schema)\n", + " svc_search_col = self.session.sql(\n", + " f\"DESC CORTEX SEARCH SERVICE {search_service};\"\n", + " ).collect()[0][\"search_column\"]\n", + " service_metadata = {\n", + " \"name\": search_service,\n", + " \"search_column\": svc_search_col,\n", + " }\n", + " self.service_metadata = service_metadata\n", + "\n", + " @instrument\n", + " def retrieve(self, query: str) -> List[str]:\n", + " cortex_search_service = (\n", + " Root(self.session)\n", + " .databases[self.database]\n", + " .schemas[self.schema]\n", + " .cortex_search_services[self.search_service]\n", + " )\n", + " context_documents = cortex_search_service.search(\n", + " query,\n", + " columns=[self.service_metadata[\"search_column\"]],\n", + " limit=self.limit_to_retrieve,\n", + " )\n", + " return context_documents.results\n", + "\n", + " @instrument\n", + " def generate_completion(self, query: str, context_documents: list) -> str:\n", + " \"\"\"\n", + " Generate answer from context.\n", + " \"\"\"\n", + " prompt = f\"\"\"\n", + " You are an expert assistant extracting information from context\n", + " provided.\n", + " Answer the question based on the context. Be concise and do not\n", + " hallucinate.\n", + " If you don ́t have the information just say so.\n", + " Context: {context_documents}\n", + " Question:\n", + " {query}\n", + " Answer: \"\"\"\n", + " return Complete(\"mistral-large2\", prompt)\n", + "\n", + " def query(self, query: str) -> str:\n", + " context_str = self.retrieve(query)\n", + " return self.generate_completion(query, context_str)\n", + "\n", + "\n", + "rag = RAG(\n", + " database=\"CORTEX_SEARCH_TUTORIAL_DB\",\n", + " schema=\"PUBLIC\",\n", + " search_service=\"FOMC_MEETING\",\n", + " limit_to_retrieve=4,\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "e072db19-0072-4098-acd5-b2121ef78f68", + "metadata": {}, + "outputs": [], + "source": [ + "import numpy as np\n", + "from trulens.core import Feedback\n", + "from trulens.core import Select\n", + "from trulens.providers.cortex.provider import Cortex\n", + "\n", + "provider = Cortex(snowpark_session.connection, \"llama3.1-8b\")\n", + "f_context_relevance = (\n", + " Feedback(provider.context_relevance, name=\"Context Relevance\")\n", + " .on(Select.RecordCalls.retrieve.args.query)\n", + " .on(Select.RecordCalls.retrieve.rets.collect())\n", + " .aggregate(np.mean)\n", + ")\n", + "f_answer_relevance = (\n", + " Feedback(provider.relevance, name=\"Answer Relevance\")\n", + " .on(Select.RecordCalls.retrieve.args.query)\n", + " .on_output()\n", + " .aggregate(np.mean)\n", + ")\n", + "# For Snowflake notebook, sentence tokenizer needs to be set to false for groundedness evaluation.\n", + "f_groundedness = (\n", + " Feedback(\n", + " lambda source,\n", + " statement: provider.groundedness_measure_with_cot_reasons(\n", + " source=source, statement=statement, use_sent_tokenize=False\n", + " ),\n", + " name=\"Groundedness\",\n", + " )\n", + " .on(Select.RecordCalls.retrieve.rets[:].collect())\n", + " .on_output()\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "c16bf847-a90e-4918-ac49-63398a6320dc", + "metadata": {}, + "outputs": [], + "source": [ + "from trulens.apps.custom import TruCustomApp\n", + "\n", + "tru_rag = TruCustomApp(\n", + " rag,\n", + " app_name=\"RAG\",\n", + " app_version=\"simple\",\n", + " feedbacks=[f_answer_relevance, f_context_relevance],\n", + " # feedbacks=[f_groundedness, f_answer_relevance, f_context_relevance],\n", + ")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "7cbafc19-b93f-46c5-a8ae-3b72741792bd", + "metadata": {}, + "outputs": [], + "source": [ + "prompts = [\n", + " \"What was GDP Growth in 2024 Q3\",\n", + " \"What was Janet Yellen's opinion on the growth outlook for 2025?\",\n", + "]\n", + "with tru_rag as recording:\n", + " for prompt in prompts:\n", + " rag.query(prompt)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Streamlit Notebook", + "name": "streamlit" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/poetry.lock b/poetry.lock index ebaf7640a..ecfd18734 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.8.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.8.4 and should not be changed by hand. 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-9420,7 +9420,7 @@ url = "src/apps/nemo" [[package]] name = "trulens-benchmark" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9436,7 +9436,7 @@ url = "src/benchmark" [[package]] name = "trulens-connectors-snowflake" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1,<3.12" @@ -9454,7 +9454,7 @@ url = "src/connectors/snowflake" [[package]] name = "trulens-core" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9486,7 +9486,7 @@ url = "src/core" [[package]] name = "trulens-dashboard" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1,!=3.9.7" @@ -9515,7 +9515,7 @@ url = "src/dashboard" [[package]] name = "trulens-eval" -version = "1.2.9" +version = "1.2.10" description = "Backwards-compatibility package for API of trulens_eval<1.0.0 using API of trulens-*>=1.0.0." optional = false python-versions = "^3.8.1,!=3.9.7" @@ -9533,7 +9533,7 @@ url = "src/trulens_eval" [[package]] name = "trulens-feedback" -version = "1.2.9" +version = "1.2.10" description = "A TruLens extension package implementing feedback functions for LLM App evaluation." optional = false python-versions = "^3.8.1" @@ -9561,7 +9561,7 @@ url = "src/feedback" [[package]] name = "trulens-otel-semconv" -version = "1.2.9" +version = "1.2.10" description = "Semantic conventions for spans produced by TruLens." optional = false python-versions = "^3.8.1,!=3.9.7" @@ -9577,7 +9577,7 @@ url = "src/otel/semconv" [[package]] name = "trulens-providers-bedrock" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9596,7 +9596,7 @@ url = "src/providers/bedrock" [[package]] name = "trulens-providers-cortex" -version = "1.2.9" +version = "1.2.10" description = "A TruLens extension package adding Snowflake Cortex support for LLM App evaluation." optional = false python-versions = "^3.8.1,<3.12" @@ -9617,7 +9617,7 @@ url = "src/providers/cortex" [[package]] name = "trulens-providers-huggingface" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9645,7 +9645,7 @@ url = "src/providers/huggingface" [[package]] name = "trulens-providers-langchain" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9663,7 +9663,7 @@ url = "src/providers/langchain" [[package]] name = "trulens-providers-litellm" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" @@ -9681,7 +9681,7 @@ url = "src/providers/litellm" [[package]] name = "trulens-providers-openai" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." optional = false python-versions = "^3.8.1" diff --git a/pyproject.toml b/pyproject.toml index a677533c0..d750d260e 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/apps/langchain/pyproject.toml b/src/apps/langchain/pyproject.toml index 44cc8ee4d..b92efe656 100644 --- a/src/apps/langchain/pyproject.toml +++ b/src/apps/langchain/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-apps-langchain" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/apps/langchain/trulens/apps/langchain/langchain.py b/src/apps/langchain/trulens/apps/langchain/langchain.py index 2ec6a0745..6992ebc6a 100644 --- a/src/apps/langchain/trulens/apps/langchain/langchain.py +++ b/src/apps/langchain/trulens/apps/langchain/langchain.py @@ -4,9 +4,8 @@ example classes: """ -from typing import Type - from trulens.core import app as core_app +from trulens.core._utils.pycompat import Type from trulens.core.utils import pyschema as pyschema_utils from trulens.core.utils import serial as serial_utils diff --git a/src/apps/llamaindex/pyproject.toml b/src/apps/llamaindex/pyproject.toml index 4426b264a..b72d794ac 100644 --- a/src/apps/llamaindex/pyproject.toml +++ b/src/apps/llamaindex/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-apps-llamaindex" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/apps/llamaindex/trulens/apps/llamaindex/llama.py b/src/apps/llamaindex/trulens/apps/llamaindex/llama.py index e8ef09ba0..9f91cd035 100644 --- a/src/apps/llamaindex/trulens/apps/llamaindex/llama.py +++ b/src/apps/llamaindex/trulens/apps/llamaindex/llama.py @@ -6,9 +6,8 @@ nodes via a threshold on a specified feedback function. """ -from typing import Type - from trulens.core import app as core_app +from trulens.core._utils.pycompat import Type from trulens.core.utils import pyschema as pyschema_utils from trulens.core.utils import serial as serial_utils diff --git a/src/apps/nemo/pyproject.toml b/src/apps/nemo/pyproject.toml index d8454d98f..ef2323bbc 100644 --- a/src/apps/nemo/pyproject.toml +++ b/src/apps/nemo/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-apps-nemo" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/benchmark/pyproject.toml b/src/benchmark/pyproject.toml index 97ced3ecc..c52b09053 100644 --- a/src/benchmark/pyproject.toml +++ b/src/benchmark/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-benchmark" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/connectors/snowflake/meta.yaml b/src/connectors/snowflake/meta.yaml index ba1fbf168..6f0e6d867 100644 --- a/src/connectors/snowflake/meta.yaml +++ b/src/connectors/snowflake/meta.yaml @@ -1,5 +1,5 @@ {% set name = "trulens-connectors-snowflake" %} -{% set version = "1.2.9" %} +{% set version = "1.2.10" %} package: name: {{ name|lower }} @@ -7,7 +7,7 @@ package: source: url: https://pypi.org/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz - sha256: 34439f15d462570e7f20bb89f207e92f5d80a8f4f4657c87005f14e1ae53b241 + sha256: 28e43abcf966047915722233fde18cac6600d302f076de1b1d50528dc776dd79 build: noarch: python diff --git a/src/connectors/snowflake/pyproject.toml b/src/connectors/snowflake/pyproject.toml index 02d122282..ef2cb2b7a 100644 --- a/src/connectors/snowflake/pyproject.toml +++ b/src/connectors/snowflake/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-connectors-snowflake" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/core/meta.yaml b/src/core/meta.yaml index 6e7ead4be..7e3f40189 100644 --- a/src/core/meta.yaml +++ b/src/core/meta.yaml @@ -1,5 +1,5 @@ {% set name = "trulens-core" %} -{% set version = "1.2.9" %} +{% set version = "1.2.10" %} package: name: {{ name|lower }} @@ -7,7 +7,7 @@ package: source: url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz - sha256: 7ce766eae1befe2de895a8bb46a049fbcdd4b56c7f4d395bf8cb3a7771e2371a + sha256: 597a2ac350450330daeb7326e012c62389ba246d88d02db64832b97f837d2b32 build: noarch: python diff --git a/src/core/pyproject.toml b/src/core/pyproject.toml index c6466898f..406ecdcb3 100644 --- a/src/core/pyproject.toml +++ b/src/core/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-core" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/core/trulens/core/_utils/pycompat.py b/src/core/trulens/core/_utils/pycompat.py index ae2317f39..c8c75dabb 100644 --- a/src/core/trulens/core/_utils/pycompat.py +++ b/src/core/trulens/core/_utils/pycompat.py @@ -18,14 +18,15 @@ from typing import ( Any, Generic, - Type, TypeVar, ) +import weakref import typing_extensions TypeAliasType = typing_extensions.TypeAliasType TypeAlias = typing_extensions.TypeAlias +Type = typing_extensions.Type if sys.version_info >= (3, 11): getmembers_static = inspect.getmembers_static @@ -60,6 +61,20 @@ def getmembers_static(obj, predicate=None): `Generic[A]` is used instead. """ + WeakSet = weakref.WeakSet + """Alias for [weakref.WeakSet][] . + + In python < 3.9, a subclass of [weakref.WeakSet][] with + `Generic[A]` is used instead. + """ + + ReferenceType = weakref.ReferenceType + """Alias for [weakref.ReferenceType][] . + + In python < 3.9, a subclass of [weakref.ReferenceType][] with + `Generic[A]` is used instead. + """ + else: # Fake classes which can have type args. In python earlier than 3.9, the # classes imported above cannot have type args which is annoying for type @@ -83,6 +98,20 @@ class Queue(Generic[A], queue.Queue): `Generic[A]` is used instead. """ + class WeakSet(Generic[A], weakref.WeakSet): + """Alias for [weakref.WeakSet][] . + + In python < 3.9, a subclass of [weakref.WeakSet][] with + `Generic[A]` is used instead. + """ + + class ReferenceType(Generic[A], weakref.ReferenceType): + """Alias for [weakref.ReferenceType][] . + + In python < 3.9, a subclass of [weakref.ReferenceType][] with + `Generic[A]` is used instead. + """ + class EmptyType(type): """A type that cannot be instantiated or subclassed.""" diff --git a/src/core/trulens/core/instruments.py b/src/core/trulens/core/instruments.py index 0c27f0cc6..4ce31e533 100644 --- a/src/core/trulens/core/instruments.py +++ b/src/core/trulens/core/instruments.py @@ -37,6 +37,7 @@ import pydantic from pydantic.v1 import BaseModel as v1BaseModel from trulens.core import experimental as core_experimental +from trulens.core._utils.pycompat import WeakSet from trulens.core.feedback import endpoint as core_endpoint from trulens.core.feedback import feedback as core_feedback from trulens.core.schema import base as base_schema @@ -931,7 +932,7 @@ def rewrap(rets): # recorder/app gets garbage collected, it will be evicted from this set. # NOTE(piotrm): __repr__.__self__ undoes weakref.proxy . - apps = weakref.WeakSet([self.app.__repr__.__self__]) + apps = WeakSet([self.app.__repr__.__self__]) # Indicate that the wrapper is an instrumented method so that we dont # further instrument it in another layer accidentally. diff --git a/src/core/trulens/core/utils/python.py b/src/core/trulens/core/utils/python.py index fa0e547d2..24fe368d1 100644 --- a/src/core/trulens/core/utils/python.py +++ b/src/core/trulens/core/utils/python.py @@ -37,6 +37,7 @@ import weakref import pydantic +from trulens.core._utils.pycompat import ReferenceType T = TypeVar("T") @@ -190,6 +191,9 @@ def safe_getattr(obj: Any, k: str, get_prop: bool = True) -> Any: if not get_prop: raise ValueError(f"{k} is a property") + if v.fget is None: + raise ValueError(f"{k} property does not have a getter.") + try: v = v.fget(obj) return v @@ -577,10 +581,10 @@ class WeakWrapper(Generic[T]): otherwise not weakly referenceable. The goal of this class is to generalize weakref.ref to work with any object.""" - obj: weakref.ReferenceType[Union[_Wrap[T], T]] + obj: ReferenceType[Union[_Wrap[T], T]] - def __init__(self, obj: Union[weakref.ReferenceType[T], WeakWrapper[T], T]): - if isinstance(obj, weakref.ReferenceType): + def __init__(self, obj: Union[ReferenceType[T], WeakWrapper[T], T]): + if isinstance(obj, ReferenceType): self.obj = obj else: @@ -813,18 +817,16 @@ def with_context(context_vars: Optional[ContextVarsOrValues] = None): variables to set to their current value. """ - tokens = set_context_vars_or_values(context_vars) - try: + tokens = set_context_vars_or_values(context_vars) yield finally: for cv, v in tokens.items(): try: cv.reset(v) - except Exception: - # TODO: Figure out if this is bad. - pass + except Exception as e: + logger.warning("Context reset failed: %s", e) @asynccontextmanager @@ -838,18 +840,16 @@ async def awith_context(context_vars: Optional[ContextVarsOrValues] = None): variables to set to their current value. """ - tokens = set_context_vars_or_values(context_vars) - try: + tokens = set_context_vars_or_values(context_vars) yield finally: for cv, v in tokens.items(): try: cv.reset(v) - except Exception: - # TODO: Figure out if this is bad. - pass + except Exception as e: + logger.warning("Context reset failed: %s", e) def wrap_awaitable( @@ -1232,9 +1232,9 @@ def delete_singleton_by_name(cls, name: str): class InstanceRefMixin: """Mixin for classes that need to keep track of their instances.""" - _instance_refs: Dict[ - Type, List[weakref.ReferenceType[InstanceRefMixin]] - ] = defaultdict(list) + _instance_refs: Dict[Type, List[ReferenceType[InstanceRefMixin]]] = ( + defaultdict(list) + ) def __init__(self, register_instance: bool = True): if register_instance: diff --git a/src/core/trulens/core/utils/trulens.py b/src/core/trulens/core/utils/trulens.py index 581291b08..dff93147c 100644 --- a/src/core/trulens/core/utils/trulens.py +++ b/src/core/trulens/core/utils/trulens.py @@ -3,9 +3,8 @@ Currently organizes all such components as "Other". """ -from typing import Type - from trulens.core import app +from trulens.core._utils.pycompat import Type from trulens.core.utils import pyschema as pyschema_utils diff --git a/src/dashboard/meta.yaml b/src/dashboard/meta.yaml index f16539f27..6a772f361 100644 --- a/src/dashboard/meta.yaml +++ b/src/dashboard/meta.yaml @@ -1,5 +1,5 @@ {% set name = "trulens-dashboard" %} -{% set version = "1.2.9" %} +{% set version = "1.2.10" %} package: name: {{ name|lower }} @@ -7,7 +7,7 @@ package: source: url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz - sha256: 3a784770d596a45bbe7e858911925e70b9363b0f6813881ca440a7dfca3767f8 + sha256: 46fb841f48238cc3c75f9d434296e3efe1e4bdd2758daa13fc8cb360cb928754 build: noarch: python diff --git a/src/dashboard/pyproject.toml b/src/dashboard/pyproject.toml index 3b613c01f..d005beee7 100644 --- a/src/dashboard/pyproject.toml +++ b/src/dashboard/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-dashboard" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/feedback/meta.yaml b/src/feedback/meta.yaml index d014324a0..5de185458 100644 --- a/src/feedback/meta.yaml +++ b/src/feedback/meta.yaml @@ -1,5 +1,5 @@ {% set name = "trulens-feedback" %} -{% set version = "1.2.9" %} +{% set version = "1.2.10" %} package: name: {{ name|lower }} @@ -7,7 +7,7 @@ package: source: url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz - sha256: db5564acc7ca2526d8d89573dca950c5e41e6cc689283d834268fac7be93597c + sha256: b6a3e2a7dbd00649aa2c1283af52c0182939d0cc7c78c4d17012ca2cc0ff0386 build: noarch: python diff --git a/src/feedback/pyproject.toml b/src/feedback/pyproject.toml index 6bbcff749..8bdc07cf1 100644 --- a/src/feedback/pyproject.toml +++ b/src/feedback/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-feedback" -version = "1.2.9" +version = "1.2.10" description = "A TruLens extension package implementing feedback functions for LLM App evaluation." authors = [ "Snowflake Inc. ", diff --git a/src/otel/semconv/meta.yaml b/src/otel/semconv/meta.yaml new file mode 100644 index 000000000..e5a8e8e43 --- /dev/null +++ b/src/otel/semconv/meta.yaml @@ -0,0 +1,42 @@ +{% set name = "trulens-otel-semconv" %} +{% set version = "1.2.10" %} + +package: + name: {{ name|lower }} + version: {{ version }} + +source: + url: https://pypi.org/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz + sha256: ef567fc7ac238c1789b070a30bb374b394072c5a13145e6fb6ca8112cd4d9e3e + +build: + noarch: python + script: {{ PYTHON }} -m pip install . -vv --no-deps --no-build-isolation + number: 0 + +requirements: + host: + - python >=3.8.1,<3.12 + - poetry-core + - pip + run: + - python >=3.8.1,<3.12 + - opentelemetry-semantic-conventions >=0.36b0 + +test: + imports: + - trulens.otel.semconv + commands: + - pip check + requires: + - pip + +about: + home: https://trulens.org/ + summary: Library to systematically track and evaluate LLM based applications. + license: MIT + +extra: + recipe-maintainers: + - sfc-gh-srudenko + - sfc-gh-chu diff --git a/src/otel/semconv/pyproject.toml b/src/otel/semconv/pyproject.toml index 28eb3c3ad..de31e7689 100644 --- a/src/otel/semconv/pyproject.toml +++ b/src/otel/semconv/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-otel-semconv" -version = "1.2.9" +version = "1.2.10" description = "Semantic conventions for spans produced by TruLens." authors = [ "Snowflake Inc. ", @@ -29,6 +29,6 @@ classifiers = [ [tool.poetry.dependencies] python = "^3.8.1,!=3.9.7" # This package only has pre-releases: -opentelemetry-semantic-conventions = { version = ">=0.48b0", allow-prereleases = true } +opentelemetry-semantic-conventions = { version = ">=0.36b0", allow-prereleases = true } # This package requires python 3.9 so we are avoiding using it for now: # opentelemetry-semantic-conventions-ai = { version = ">=0.4.2", allow-prereleases=true } diff --git a/src/otel/semconv/trulens/otel/semconv/__init__.py b/src/otel/semconv/trulens/otel/semconv/__init__.py index 5d556a1a9..9367f60fc 100644 --- a/src/otel/semconv/trulens/otel/semconv/__init__.py +++ b/src/otel/semconv/trulens/otel/semconv/__init__.py @@ -1,7 +1,17 @@ from importlib.metadata import version +import sys -from trulens.core.utils import imports as import_utils -__version__ = version( - import_utils.safe_importlib_package_name(__package__ or __name__) -) +def safe_importlib_package_name(package_name: str) -> str: + """Convert a package name that may have periods in it to one that uses + hyphens for periods but only if the python version is old. + Copied from trulens-core to avoid a circular dependency.""" + + return ( + package_name + if sys.version_info >= (3, 10) + else package_name.replace(".", "-") + ) + + +__version__ = version(safe_importlib_package_name(__package__ or __name__)) diff --git a/src/providers/bedrock/pyproject.toml b/src/providers/bedrock/pyproject.toml index 8d78ff78e..6c3b22726 100644 --- a/src/providers/bedrock/pyproject.toml +++ b/src/providers/bedrock/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-bedrock" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/providers/cortex/meta.yaml b/src/providers/cortex/meta.yaml index 0938a7db4..ca55b2273 100644 --- a/src/providers/cortex/meta.yaml +++ b/src/providers/cortex/meta.yaml @@ -1,5 +1,5 @@ {% set name = "trulens-providers-cortex" %} -{% set version = "1.2.9" %} +{% set version = "1.2.10" %} package: name: {{ name|lower }} @@ -7,7 +7,7 @@ package: source: url: https://pypi.io/packages/source/{{ name[0] }}/{{ name }}/{{ name.replace('-', '_') }}-{{ version }}.tar.gz - sha256: 9368c88ec0315d1c333aaf8ecce479f869a19686d3b53eaf9d0dcb63d24eb466 + sha256: 75b3b963940dde7064a2f7d58166bb99d706b8e7db326c958ef872387c297352 build: noarch: python diff --git a/src/providers/cortex/pyproject.toml b/src/providers/cortex/pyproject.toml index 3f23b3054..746c1c2c3 100644 --- a/src/providers/cortex/pyproject.toml +++ b/src/providers/cortex/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-cortex" -version = "1.2.9" +version = "1.2.10" description = "A TruLens extension package adding Snowflake Cortex support for LLM App evaluation." authors = [ "Snowflake Inc. ", diff --git a/src/providers/huggingface/pyproject.toml b/src/providers/huggingface/pyproject.toml index e9db0761e..3c50fc2a8 100644 --- a/src/providers/huggingface/pyproject.toml +++ b/src/providers/huggingface/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-huggingface" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/providers/langchain/pyproject.toml b/src/providers/langchain/pyproject.toml index 35255bbe7..987026b57 100644 --- a/src/providers/langchain/pyproject.toml +++ b/src/providers/langchain/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-langchain" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/providers/litellm/pyproject.toml b/src/providers/litellm/pyproject.toml index c1ab1196f..552b91648 100644 --- a/src/providers/litellm/pyproject.toml +++ b/src/providers/litellm/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-litellm" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/providers/openai/pyproject.toml b/src/providers/openai/pyproject.toml index 842b76b11..65237b018 100644 --- a/src/providers/openai/pyproject.toml +++ b/src/providers/openai/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens-providers-openai" -version = "1.2.9" +version = "1.2.10" description = "Library to systematically track and evaluate LLM based applications." authors = [ "Snowflake Inc. ", diff --git a/src/providers/openai/trulens/providers/openai/endpoint.py b/src/providers/openai/trulens/providers/openai/endpoint.py index c71f9b016..0e9e8e93d 100644 --- a/src/providers/openai/trulens/providers/openai/endpoint.py +++ b/src/providers/openai/trulens/providers/openai/endpoint.py @@ -67,7 +67,7 @@ openai.types.create_embedding_response.CreateEmbeddingResponse, openai.types.moderation.Moderation, ] -"""Types that openai respones can attain, or at least the ones we handle in cost tracking.""" +"""Types that openai responses can attain, or at least the ones we handle in cost tracking.""" TOpenAIResponse = TOpenAIReturn diff --git a/src/trulens_eval/pyproject.toml b/src/trulens_eval/pyproject.toml index e0311e129..faca87294 100644 --- a/src/trulens_eval/pyproject.toml +++ b/src/trulens_eval/pyproject.toml @@ -6,7 +6,7 @@ requires = [ [tool.poetry] name = "trulens_eval" -version = "1.2.9" +version = "1.2.10" description = "Backwards-compatibility package for API of trulens_eval<1.0.0 using API of trulens-*>=1.0.0." authors = [ "Snowflake Inc. ", diff --git a/tests/test.py b/tests/test.py index 8ffe4a7e4..729afa099 100644 --- a/tests/test.py +++ b/tests/test.py @@ -26,10 +26,10 @@ ) import unittest from unittest import TestCase -import weakref import pydantic from pydantic import BaseModel +from trulens.core._utils.pycompat import ReferenceType from trulens.core.utils import python as python_utils from trulens.core.utils import serial as serial_utils import yaml @@ -553,7 +553,7 @@ def env_true(var: str) -> bool: "on", ] - def assertCollected(self, ref: weakref.ReferenceType[T], msg=None): + def assertCollected(self, ref: ReferenceType[T], msg=None): """Check that the object referenced by `ref` has been garbage collected. diff --git a/tests/utils.py b/tests/utils.py index d9a161ad4..0415212af 100644 --- a/tests/utils.py +++ b/tests/utils.py @@ -29,6 +29,7 @@ from tqdm.auto import tqdm from trulens.core._utils import pycompat as pycompat_utils +from trulens.core._utils.pycompat import ReferenceType from trulens.core.utils import python as python_utils from trulens.core.utils import serial as serial_utils from trulens.core.utils import text as text_utils @@ -616,7 +617,7 @@ class RefLike(Generic[T]): def __init__( self, ref_id: Optional[int] = None, - obj: Optional[Union[weakref.ReferenceType[T], T]] = None, + obj: Optional[Union[ReferenceType[T], T]] = None, ): if ref_id is None: assert obj is not None @@ -642,7 +643,7 @@ def __init__( def get(self) -> T: try: - if weakref.ReferenceType.__instancecheck__(self.ref_or_val): + if ReferenceType.__instancecheck__(self.ref_or_val): return self.ref_or_val() except Exception: return None