LLM applications
in productionOptimize LLM applications by tuning prompts and models
AI-powered LLMOps for developers
From development to production across data management, evals & fine-tuning.
Use our Prompt Engineering Copilot to get to more accurate prompts faster via AI-powered tuning of prompts and models
Integrate Log10's llmeval tool to iterate even faster during development & continuously monitor the accuracy of your LLM apps in production
Scale human review of LLM outputs with the power of Log10's AutoFeedback solution. Read the technical details
Debug, compare and improve prompts & models
Logs
Metrics
Playgrounds
Evaluations
Easy programmatic integration
Just call log10(openai) and use the OpenAI client library as before
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import openai
from log10.load import log10
log10(openai)
client = openai.OpenAI()
completion = client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{
"role": "system",
"content": "You are the most knowledgable Star Wars guru on the planet",
},
{
"role": "user",
"content": "Write the time period of all the Star Wars movies and spinoffs?",
},
],
)
print(completion.choices[0].message)