langchain/libs/community/tests/integration_tests/callbacks/test_wandb_tracer.py
Bagatur ed58eeb9c5
community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)
Moved the following modules to new package langchain-community in a backwards compatible fashion:

```
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
```

Moved the following to core
```
mv langchain/langchain/utils/json_schema.py core/langchain_core/utils
mv langchain/langchain/utils/html.py core/langchain_core/utils
mv langchain/langchain/utils/strings.py core/langchain_core/utils
cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py
rm langchain/langchain/utils/env.py
```

See .scripts/community_split/script_integrations.sh for all changes
2023-12-11 13:53:30 -08:00

124 lines
3.6 KiB
Python

"""Integration tests for the langchain tracer module."""
import asyncio
import os
from aiohttp import ClientSession
from langchain_community.callbacks import wandb_tracing_enabled
from langchain_community.llms import OpenAI
questions = [
(
"Who won the US Open men's final in 2019? "
"What is his age raised to the 0.334 power?"
),
(
"Who is Olivia Wilde's boyfriend? "
"What is his current age raised to the 0.23 power?"
),
(
"Who won the most recent formula 1 grand prix? "
"What is their age raised to the 0.23 power?"
),
(
"Who won the US Open women's final in 2019? "
"What is her age raised to the 0.34 power?"
),
("Who is Beyonce's husband? " "What is his age raised to the 0.19 power?"),
]
def test_tracing_sequential() -> None:
from langchain.agents import AgentType, initialize_agent, load_tools
os.environ["LANGCHAIN_WANDB_TRACING"] = "true"
os.environ["WANDB_PROJECT"] = "langchain-tracing"
for q in questions[:3]:
llm = OpenAI(temperature=0)
tools = load_tools(
["llm-math", "serpapi"],
llm=llm,
)
agent = initialize_agent(
tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
agent.run(q)
def test_tracing_session_env_var() -> None:
from langchain.agents import AgentType, initialize_agent, load_tools
os.environ["LANGCHAIN_WANDB_TRACING"] = "true"
llm = OpenAI(temperature=0)
tools = load_tools(
["llm-math", "serpapi"],
llm=llm,
)
agent = initialize_agent(
tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
agent.run(questions[0])
async def test_tracing_concurrent() -> None:
from langchain.agents import AgentType, initialize_agent, load_tools
os.environ["LANGCHAIN_WANDB_TRACING"] = "true"
aiosession = ClientSession()
llm = OpenAI(temperature=0)
async_tools = load_tools(
["llm-math", "serpapi"],
llm=llm,
aiosession=aiosession,
)
agent = initialize_agent(
async_tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
tasks = [agent.arun(q) for q in questions[:3]]
await asyncio.gather(*tasks)
await aiosession.close()
def test_tracing_context_manager() -> None:
from langchain.agents import AgentType, initialize_agent, load_tools
llm = OpenAI(temperature=0)
tools = load_tools(
["llm-math", "serpapi"],
llm=llm,
)
agent = initialize_agent(
tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
if "LANGCHAIN_WANDB_TRACING" in os.environ:
del os.environ["LANGCHAIN_WANDB_TRACING"]
with wandb_tracing_enabled():
agent.run(questions[0]) # this should be traced
agent.run(questions[0]) # this should not be traced
async def test_tracing_context_manager_async() -> None:
from langchain.agents import AgentType, initialize_agent, load_tools
llm = OpenAI(temperature=0)
async_tools = load_tools(
["llm-math", "serpapi"],
llm=llm,
)
agent = initialize_agent(
async_tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True
)
if "LANGCHAIN_WANDB_TRACING" in os.environ:
del os.environ["LANGCHAIN_TRACING"]
# start a background task
task = asyncio.create_task(agent.arun(questions[0])) # this should not be traced
with wandb_tracing_enabled():
tasks = [agent.arun(q) for q in questions[1:4]] # these should be traced
await asyncio.gather(*tasks)
await task