Observability tools for LLMs in Python Intro: As LLMs have become popular in the past two years, more companies have adopted their usage differently to meet business needs; the need to also be able to monitor the use and performance of these LLMs has become important too, and these talk will be focused on shedding light on how this can be done with best (or good practices in mind).

The Talk will address the following: - What Observability is - What LLMs are - The usage of LLM - Why Observability is needed in LLMs - Summarized intro into LLMOps - The actual need for observability - How observability can be done using python - Touch on specific tools: - Helicone - Portkey - Langfuse - Details on each tool - Comparison of each tool - Current challenges in the ecosystem - Future of Observability in LLMOps - Conclusion

Talk Objective: At the end of this talk, the audience should have gained knowledge on : - What observability is - Why it is needed for LLMs? - How it can be done with some tools in Python