langchain/docs/extras/integrations/providers/log10.mdx
arjunbansal a2681f950d
add instructions on integrating Log10 (#8938)
- Description: Instruction for integration with Log10: an [open
source](https://github.com/log10-io/log10) proxiless LLM data management
and application development platform that lets you log, debug and tag
your Langchain calls
  - Tag maintainer: @baskaryan
  - Twitter handle: @log10io @coffeephoenix

Several examples showing the integration included
[here](https://github.com/log10-io/log10/tree/main/examples/logging) and
in the PR
2023-08-08 19:15:31 -07:00

105 lines
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Plaintext

# Log10
This page covers how to use the [Log10](https://log10.io) within LangChain.
## What is Log10?
Log10 is an [open source](https://github.com/log10-io/log10) proxiless LLM data management and application development platform that lets you log, debug and tag your Langchain calls.
## Quick start
1. Create your free account at [log10.io](https://log10.io)
2. Add your `LOG10_TOKEN` and `LOG10_ORG_ID` from the Settings and Organization tabs respectively as environment variables.
3. Also add `LOG10_URL=https://log10.io` and your usual LLM API key: for e.g. `OPENAI_API_KEY` or `ANTHROPIC_API_KEY` to your environment
## How to enable Log10 data management for Langchain
Integration with log10 is a simple one-line `log10_callback` integration as shown below:
```python
from langchain.chat_models import ChatOpenAI
from langchain.schema import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config
log10_callback = Log10Callback(log10_config=Log10Config())
messages = [
HumanMessage(content="You are a ping pong machine"),
HumanMessage(content="Ping?"),
]
llm = ChatOpenAI(model_name="gpt-3.5-turbo", callbacks=[log10_callback])
```
[Log10 + Langchain + Logs docs](https://github.com/log10-io/log10/blob/main/logging.md#langchain-logger)
[More details + screenshots](https://log10.io/docs/logs) including instructions for self-hosting logs
## How to use tags with Log10
```python
from langchain import OpenAI
from langchain.chat_models import ChatAnthropic
from langchain.chat_models import ChatOpenAI
from langchain.schema import HumanMessage
from log10.langchain import Log10Callback
from log10.llm import Log10Config
log10_callback = Log10Callback(log10_config=Log10Config())
messages = [
HumanMessage(content="You are a ping pong machine"),
HumanMessage(content="Ping?"),
]
llm = ChatOpenAI(model_name="gpt-3.5-turbo", callbacks=[log10_callback], temperature=0.5, tags=["test"])
completion = llm.predict_messages(messages, tags=["foobar"])
print(completion)
llm = ChatAnthropic(model="claude-2", callbacks=[log10_callback], temperature=0.7, tags=["baz"])
llm.predict_messages(messages)
print(completion)
llm = OpenAI(model_name="text-davinci-003", callbacks=[log10_callback], temperature=0.5)
completion = llm.predict("You are a ping pong machine.\nPing?\n")
print(completion)
```
You can also intermix direct OpenAI calls and Langchain LLM calls:
```python
import os
from log10.load import log10, log10_session
import openai
from langchain import OpenAI
log10(openai)
with log10_session(tags=["foo", "bar"]):
# Log a direct OpenAI call
response = openai.Completion.create(
model="text-ada-001",
prompt="Where is the Eiffel Tower?",
temperature=0,
max_tokens=1024,
top_p=1,
frequency_penalty=0,
presence_penalty=0,
)
print(response)
# Log a call via Langchain
llm = OpenAI(model_name="text-ada-001", temperature=0.5)
response = llm.predict("You are a ping pong machine.\nPing?\n")
print(response)
```
## How to debug Langchain calls
[Example of debugging](https://log10.io/docs/prompt_chain_debugging)
[More Langchain examples](https://github.com/log10-io/log10/tree/main/examples#langchain)