forked from Archives/langchain
Use Run object from SDK (#6067)
Update the Run object in the tracer to extend that in the SDK to include the parameters necessary for tracking/tracing
This commit is contained in:
parent
cde1e8739a
commit
0c52275bdb
@ -11,7 +11,11 @@ from uuid import UUID
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from langchainplus_sdk import LangChainPlusClient
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from langchain.callbacks.tracers.base import BaseTracer
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from langchain.callbacks.tracers.schemas import Run, RunTypeEnum, TracerSession
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from langchain.callbacks.tracers.schemas import (
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Run,
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RunTypeEnum,
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TracerSession,
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)
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from langchain.env import get_runtime_environment
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from langchain.schema import BaseMessage, messages_to_dict
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@ -2,13 +2,13 @@
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from __future__ import annotations
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import datetime
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from enum import Enum
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from typing import Any, Dict, List, Optional
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from uuid import UUID
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from langchainplus_sdk.schemas import RunBase as BaseRunV2
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from langchainplus_sdk.schemas import RunTypeEnum
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from pydantic import BaseModel, Field, root_validator
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from langchain.env import get_runtime_environment
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from langchain.schema import LLMResult
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@ -88,36 +88,11 @@ class ToolRun(BaseRun):
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# Begin V2 API Schemas
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class RunTypeEnum(str, Enum):
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"""Enum for run types."""
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class Run(BaseRunV2):
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"""Run schema for the V2 API in the Tracer."""
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tool = "tool"
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chain = "chain"
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llm = "llm"
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class RunBase(BaseModel):
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"""Base Run schema."""
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id: Optional[UUID]
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start_time: datetime.datetime = Field(default_factory=datetime.datetime.utcnow)
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end_time: datetime.datetime = Field(default_factory=datetime.datetime.utcnow)
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extra: Optional[Dict[str, Any]] = None
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error: Optional[str]
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execution_order: int
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child_execution_order: Optional[int]
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serialized: dict
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inputs: dict
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outputs: Optional[dict]
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reference_example_id: Optional[UUID]
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run_type: RunTypeEnum
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parent_run_id: Optional[UUID]
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class Run(RunBase):
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"""Run schema when loading from the DB."""
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name: str
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child_execution_order: int
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child_runs: List[Run] = Field(default_factory=list)
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@root_validator(pre=True)
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@ -131,26 +106,19 @@ class Run(RunBase):
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return values
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class RunCreate(RunBase):
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name: str
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session_name: Optional[str] = None
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@root_validator(pre=True)
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def add_runtime_env(cls, values: Dict[str, Any]) -> Dict[str, Any]:
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"""Add env info to the run."""
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extra = values.get("extra", {})
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extra["runtime"] = get_runtime_environment()
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values["extra"] = extra
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return values
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class RunUpdate(BaseModel):
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end_time: Optional[datetime.datetime]
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error: Optional[str]
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outputs: Optional[dict]
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parent_run_id: Optional[UUID]
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reference_example_id: Optional[UUID]
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ChainRun.update_forward_refs()
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ToolRun.update_forward_refs()
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__all__ = [
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"BaseRun",
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"ChainRun",
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"LLMRun",
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"Run",
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"RunTypeEnum",
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"ToolRun",
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"TracerSession",
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"TracerSessionBase",
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"TracerSessionV1",
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"TracerSessionV1Base",
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"TracerSessionV1Create",
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]
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18
poetry.lock
generated
18
poetry.lock
generated
@ -1,4 +1,4 @@
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# This file is automatically @generated by Poetry and should not be changed by hand.
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# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
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[[package]]
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name = "absl-py"
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@ -4058,14 +4058,14 @@ tests = ["pytest", "pytest-mock"]
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[[package]]
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name = "langchainplus-sdk"
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version = "0.0.7"
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version = "0.0.9"
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description = "Client library to connect to the LangChainPlus LLM Tracing and Evaluation Platform."
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category = "main"
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optional = false
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python-versions = ">=3.8.1,<4.0"
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files = [
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{file = "langchainplus_sdk-0.0.7-py3-none-any.whl", hash = "sha256:aefc471058648bf9fc51f659117d33ef905d25a304d5a021f7e32c30f5921076"},
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{file = "langchainplus_sdk-0.0.7.tar.gz", hash = "sha256:b58565bdcaf301d2e6e7dd8898f0b8ccf549a35476258e0c14d871d6de02d210"},
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{file = "langchainplus_sdk-0.0.9-py3-none-any.whl", hash = "sha256:4fe1a60f28c93ae0e145dcd53e4dc5293374ed0a8518abcc51e201081809bf0b"},
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{file = "langchainplus_sdk-0.0.9.tar.gz", hash = "sha256:bbfdc54c64df5ca4334068ab2d7b89d3a894f313b1285939b4c4532fea62eeb7"},
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]
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[package.dependencies]
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@ -11472,13 +11472,13 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
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cffi = ["cffi (>=1.11)"]
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[extras]
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all = ["anthropic", "cohere", "openai", "nlpcloud", "huggingface_hub", "jina", "manifest-ml", "elasticsearch", "opensearch-py", "google-search-results", "faiss-cpu", "sentence-transformers", "transformers", "spacy", "nltk", "wikipedia", "beautifulsoup4", "tiktoken", "torch", "jinja2", "pinecone-client", "pinecone-text", "pymongo", "weaviate-client", "redis", "google-api-python-client", "google-auth", "wolframalpha", "qdrant-client", "tensorflow-text", "pypdf", "networkx", "nomic", "aleph-alpha-client", "deeplake", "pgvector", "psycopg2-binary", "pyowm", "pytesseract", "html2text", "atlassian-python-api", "gptcache", "duckduckgo-search", "arxiv", "azure-identity", "clickhouse-connect", "azure-cosmos", "lancedb", "langkit", "lark", "pexpect", "pyvespa", "O365", "jq", "docarray", "steamship", "pdfminer-six", "lxml", "requests-toolbelt", "neo4j", "openlm", "azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech", "momento", "singlestoredb", "tigrisdb", "nebula3-python", "awadb"]
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azure = ["azure-identity", "azure-cosmos", "openai", "azure-core", "azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech", "azure-search-documents"]
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all = ["O365", "aleph-alpha-client", "anthropic", "arxiv", "atlassian-python-api", "awadb", "azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech", "azure-cosmos", "azure-identity", "beautifulsoup4", "clickhouse-connect", "cohere", "deeplake", "docarray", "duckduckgo-search", "elasticsearch", "faiss-cpu", "google-api-python-client", "google-auth", "google-search-results", "gptcache", "html2text", "huggingface_hub", "jina", "jinja2", "jq", "lancedb", "langkit", "lark", "lxml", "manifest-ml", "momento", "nebula3-python", "neo4j", "networkx", "nlpcloud", "nltk", "nomic", "openai", "openlm", "opensearch-py", "pdfminer-six", "pexpect", "pgvector", "pinecone-client", "pinecone-text", "psycopg2-binary", "pymongo", "pyowm", "pypdf", "pytesseract", "pyvespa", "qdrant-client", "redis", "requests-toolbelt", "sentence-transformers", "singlestoredb", "spacy", "steamship", "tensorflow-text", "tigrisdb", "tiktoken", "torch", "transformers", "weaviate-client", "wikipedia", "wolframalpha"]
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azure = ["azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech", "azure-core", "azure-cosmos", "azure-identity", "azure-search-documents", "openai"]
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cohere = ["cohere"]
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docarray = ["docarray"]
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embeddings = ["sentence-transformers"]
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extended-testing = ["beautifulsoup4", "bibtexparser", "chardet", "jq", "pdfminer-six", "pypdf", "pymupdf", "pypdfium2", "tqdm", "lxml", "atlassian-python-api", "beautifulsoup4", "pandas", "telethon", "psychicapi", "zep-python", "gql", "requests-toolbelt", "html2text", "py-trello", "scikit-learn", "pyspark", "openai"]
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llms = ["anthropic", "cohere", "openai", "openlm", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
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extended-testing = ["atlassian-python-api", "beautifulsoup4", "beautifulsoup4", "bibtexparser", "chardet", "gql", "html2text", "jq", "lxml", "openai", "pandas", "pdfminer-six", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "requests-toolbelt", "scikit-learn", "telethon", "tqdm", "zep-python"]
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llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "openlm", "torch", "transformers"]
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openai = ["openai", "tiktoken"]
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qdrant = ["qdrant-client"]
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text-helpers = ["chardet"]
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@ -11486,4 +11486,4 @@ text-helpers = ["chardet"]
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[metadata]
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lock-version = "2.0"
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python-versions = ">=3.8.1,<4.0"
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content-hash = "17e9c7a2ae2d0ef7cf45bc232ebeb7fd3eee2760bb2a19b34a63dcddafd3e4ad"
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content-hash = "b4a782d8223ccc19b2dfb777978c3ad636b11a79cc58a5c45e4dcdb0fe5e29c1"
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@ -105,7 +105,7 @@ singlestoredb = {version = "^0.6.1", optional = true}
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pyspark = {version = "^3.4.0", optional = true}
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tigrisdb = {version = "^1.0.0b6", optional = true}
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nebula3-python = {version = "^3.4.0", optional = true}
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langchainplus-sdk = ">=0.0.7"
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langchainplus-sdk = ">=0.0.9"
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awadb = {version = "^0.3.2", optional = true}
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azure-search-documents = {version = "11.4.0a20230509004", source = "azure-sdk-dev", optional = true}
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@ -203,8 +203,10 @@ def test_callback_manager_inheritance() -> None:
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assert child_manager2.inheritable_handlers == [handler1]
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def test_callback_manager_configure() -> None:
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def test_callback_manager_configure(monkeypatch: pytest.MonkeyPatch) -> None:
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"""Test callback manager configuration."""
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monkeypatch.setenv("LANGCHAIN_TRACING_V2", "false")
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monkeypatch.setenv("LANGCHAIN_TRACING", "false")
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handler1, handler2, handler3, handler4 = (
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FakeCallbackHandler(),
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FakeCallbackHandler(),
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27
tests/unit_tests/callbacks/test_schemas.py
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27
tests/unit_tests/callbacks/test_schemas.py
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import langchain.callbacks.tracers.schemas as schemas
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from langchain.callbacks.tracers.schemas import __all__ as schemas_all
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def test_public_api() -> None:
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"""Test for changes in the public API."""
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expected_all = [
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"BaseRun",
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"ChainRun",
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"LLMRun",
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"Run",
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"RunTypeEnum",
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"ToolRun",
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"TracerSession",
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"TracerSessionBase",
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"TracerSessionV1",
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"TracerSessionV1Base",
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"TracerSessionV1Create",
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]
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assert sorted(schemas_all) == expected_all
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# Assert that the object is actually present in the schema module
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for module_name in expected_all:
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assert (
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hasattr(schemas, module_name) and getattr(schemas, module_name) is not None
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)
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