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Use LCP Client in Tracer (#5908)

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Move the LCP calls to the client.
searx_updates
Zander Chase 11 months ago committed by GitHub
parent 3ec6400d70
commit 77c286cf02
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GPG Key ID: 4AEE18F83AFDEB23
5 changed files with 32 additions and 110 deletions
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110
langchain/callbacks/tracers/langchain.py
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@ -8,61 +8,16 @@ from datetime import datetime
from typing import Any, Dict, List, Optional, Union
from uuid import UUID
import requests
from requests.exceptions import HTTPError
from tenacity import (
before_sleep_log,
retry,
retry_if_exception_type,
stop_after_attempt,
wait_exponential,
)
from langchainplus_sdk import LangChainPlusClient
from langchain.callbacks.tracers.base import BaseTracer
from langchain.callbacks.tracers.schemas import (
Run,
RunCreate,
RunTypeEnum,
RunUpdate,
TracerSession,
)
from langchain.callbacks.tracers.schemas import Run, RunTypeEnum, TracerSession
from langchain.env import get_runtime_environment
from langchain.schema import BaseMessage, messages_to_dict
logger = logging.getLogger(__name__)
def get_headers() -> Dict[str, Any]:
"""Get the headers for the LangChain API."""
headers: Dict[str, Any] = {"Content-Type": "application/json"}
if os.getenv("LANGCHAIN_API_KEY"):
headers["x-api-key"] = os.getenv("LANGCHAIN_API_KEY")
return headers
def get_endpoint() -> str:
return os.getenv("LANGCHAIN_ENDPOINT", "http://localhost:1984")
class LangChainTracerAPIError(Exception):
"""An error occurred while communicating with the LangChain API."""
class LangChainTracerUserError(Exception):
"""An error occurred while communicating with the LangChain API."""
class LangChainTracerError(Exception):
"""An error occurred while communicating with the LangChain API."""
retry_decorator = retry(
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=4, max=10),
retry=retry_if_exception_type(LangChainTracerAPIError),
before_sleep=before_sleep_log(logger, logging.WARNING),
)
class LangChainTracer(BaseTracer):
"""An implementation of the SharedTracer that POSTS to the langchain endpoint."""
@ -70,19 +25,19 @@ class LangChainTracer(BaseTracer):
self,
example_id: Optional[Union[UUID, str]] = None,
session_name: Optional[str] = None,
client: Optional[LangChainPlusClient] = None,
**kwargs: Any,
) -> None:
"""Initialize the LangChain tracer."""
super().__init__(**kwargs)
self.session: Optional[TracerSession] = None
self._endpoint = get_endpoint()
self._headers = get_headers()
self.example_id = (
UUID(example_id) if isinstance(example_id, str) else example_id
)
self.session_name = session_name or os.getenv("LANGCHAIN_SESSION", "default")
# set max_workers to 1 to process tasks in order
self.executor = ThreadPoolExecutor(max_workers=1)
self.client = client or LangChainPlusClient()
def on_chat_model_start(
self,
@ -114,60 +69,19 @@ class LangChainTracer(BaseTracer):
def _persist_run(self, run: Run) -> None:
"""The Langchain Tracer uses Post/Patch rather than persist."""
@retry_decorator
def _persist_run_single(self, run: Run) -> None:
"""Persist a run."""
if run.parent_run_id is None:
run.reference_example_id = self.example_id
run_dict = run.dict()
del run_dict["child_runs"]
run_create = RunCreate(**run_dict, session_name=self.session_name)
response = None
try:
# TODO: Add retries when async
response = requests.post(
f"{self._endpoint}/runs",
data=run_create.json(),
headers=self._headers,
)
response.raise_for_status()
except HTTPError as e:
if response is not None and response.status_code == 500:
raise LangChainTracerAPIError(
f"Failed to upsert persist run to LangChain API. {e}"
)
else:
raise LangChainTracerUserError(
f"Failed to persist run to LangChain API. {e}"
)
except Exception as e:
raise LangChainTracerError(
f"Failed to persist run to LangChain API. {e}"
) from e
@retry_decorator
run_dict = run.dict(exclude={"child_runs"})
extra = run_dict.get("extra", {})
extra["runtime"] = get_runtime_environment()
run_dict["extra"] = extra
run = self.client.create_run(**run_dict, session_name=self.session_name)
def _update_run_single(self, run: Run) -> None:
"""Update a run."""
run_update = RunUpdate(**run.dict())
response = None
try:
response = requests.patch(
f"{self._endpoint}/runs/{run.id}",
data=run_update.json(),
headers=self._headers,
)
response.raise_for_status()
except HTTPError as e:
if response is not None and response.status_code == 500:
raise LangChainTracerAPIError(
f"Failed to update run to LangChain API. {e}"
)
else:
raise LangChainTracerUserError(f"Failed to run to LangChain API. {e}")
except Exception as e:
raise LangChainTracerError(
f"Failed to update run to LangChain API. {e}"
) from e
self.client.update_run(run.id, **run.dict())
def _on_llm_start(self, run: Run) -> None:
"""Persist an LLM run."""

11
langchain/callbacks/tracers/langchain_v1.py
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@ -2,12 +2,11 @@ from __future__ import annotations
import logging
import os
from typing import Any, Optional, Union
from typing import Any, Dict, Optional, Union
import requests
from langchain.callbacks.tracers.base import BaseTracer
from langchain.callbacks.tracers.langchain import get_headers
from langchain.callbacks.tracers.schemas import (
ChainRun,
LLMRun,
@ -21,6 +20,14 @@ from langchain.schema import get_buffer_string
from langchain.utils import raise_for_status_with_text
def get_headers() -> Dict[str, Any]:
"""Get the headers for the LangChain API."""
headers: Dict[str, Any] = {"Content-Type": "application/json"}
if os.getenv("LANGCHAIN_API_KEY"):
headers["x-api-key"] = os.getenv("LANGCHAIN_API_KEY")
return headers
def _get_endpoint() -> str:
return os.getenv("LANGCHAIN_ENDPOINT", "http://localhost:8000")

1
langchain/env.py
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@ -10,6 +10,7 @@ def get_runtime_environment() -> dict:
return {
"library_version": __version__,
"library": "langchain",
"platform": platform.platform(),
"runtime": "python",
"runtime_version": platform.python_version(),

18
poetry.lock generated
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@ -1,4 +1,4 @@
# This file is automatically @generated by Poetry and should not be changed by hand.
# This file is automatically @generated by Poetry 1.4.2 and should not be changed by hand.
[[package]]
name = "absl-py"
@ -4005,14 +4005,14 @@ tests = ["pytest", "pytest-mock"]
[[package]]
name = "langchainplus-sdk"
version = "0.0.6"
version = "0.0.7"
description = "Client library to connect to the LangChainPlus LLM Tracing and Evaluation Platform."
category = "main"
optional = false
python-versions = ">=3.8.1,<4.0"
files = [
{file = "langchainplus_sdk-0.0.6-py3-none-any.whl", hash = "sha256:43fe01c66442b88403c969b8812f6be81e023c0d2a6d5d3572a8d87961438658"},
{file = "langchainplus_sdk-0.0.6.tar.gz", hash = "sha256:c911a98fd2d02baa48f742b7d700fd6a55f11c9a545ee5d66b08825940c9a32e"},
{file = "langchainplus_sdk-0.0.7-py3-none-any.whl", hash = "sha256:aefc471058648bf9fc51f659117d33ef905d25a304d5a021f7e32c30f5921076"},
{file = "langchainplus_sdk-0.0.7.tar.gz", hash = "sha256:b58565bdcaf301d2e6e7dd8898f0b8ccf549a35476258e0c14d871d6de02d210"},
]
[package.dependencies]
@ -11340,13 +11340,13 @@ cffi = {version = ">=1.11", markers = "platform_python_implementation == \"PyPy\
cffi = ["cffi (>=1.11)"]
[extras]
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"]
azure = ["azure-identity", "azure-cosmos", "openai", "azure-core", "azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech"]
all = ["O365", "aleph-alpha-client", "anthropic", "arxiv", "atlassian-python-api", "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"]
azure = ["azure-ai-formrecognizer", "azure-ai-vision", "azure-cognitiveservices-speech", "azure-core", "azure-cosmos", "azure-identity", "openai"]
cohere = ["cohere"]
docarray = ["docarray"]
embeddings = ["sentence-transformers"]
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"]
llms = ["anthropic", "cohere", "openai", "openlm", "nlpcloud", "huggingface_hub", "manifest-ml", "torch", "transformers"]
extended-testing = ["atlassian-python-api", "beautifulsoup4", "beautifulsoup4", "bibtexparser", "chardet", "gql", "html2text", "jq", "lxml", "pandas", "pdfminer-six", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "requests-toolbelt", "scikit-learn", "telethon", "tqdm", "zep-python"]
llms = ["anthropic", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "openlm", "torch", "transformers"]
openai = ["openai", "tiktoken"]
qdrant = ["qdrant-client"]
text-helpers = ["chardet"]
@ -11354,4 +11354,4 @@ text-helpers = ["chardet"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.8.1,<4.0"
content-hash = "0da3585d7f3216764f396c162c8f9456423b9f80a6dc9af46040c3e5eec0b79e"
content-hash = "dbbaa2907bf2ac09ed111ce712772bba0fe56901627f41c53aef71ae5a38d1c6"

2
pyproject.toml
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@ -105,7 +105,7 @@ singlestoredb = {version = "^0.6.1", optional = true}
pyspark = {version = "^3.4.0", optional = true}
tigrisdb = {version = "^1.0.0b6", optional = true}
nebula3-python = {version = "^3.4.0", optional = true}
langchainplus-sdk = ">=0.0.6"
langchainplus-sdk = ">=0.0.7"
[tool.poetry.group.docs.dependencies]

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