Jonymusky litellm integration (#36)

* feat: LiteLLM integration

* update

* chore: make start-dev

feedback from: https://github.com/temporal-community/temporal-ai-agent/issues/31

* bump dependencies

* clean up setup.md

* setup update

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Co-authored-by: Jonathan Muszkat <muskys@gmail.com>
This commit is contained in:
Steve Androulakis
2025-05-26 14:37:14 -07:00
committed by GitHub
parent 847f4bbaef
commit 7bb6688797
9 changed files with 1344 additions and 918 deletions

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@@ -2,7 +2,13 @@
This demo shows a multi-turn conversation with an AI agent running inside a Temporal workflow. The purpose of the agent is to collect information towards a goal, running tools along the way. There's a simple DSL input for collecting information (currently set up to use mock functions to search for public events, search for flights around those events, then create a test Stripe invoice for the trip).
The AI will respond with clarifications and ask for any missing information to that goal. You can configure it to use [ChatGPT 4o](https://openai.com/index/hello-gpt-4o/), [Anthropic Claude](https://www.anthropic.com/claude), [Google Gemini](https://gemini.google.com), [Deepseek-V3](https://www.deepseek.com/), [Grok](https://docs.x.ai/docs/overview) or a local LLM of your choice using [Ollama](https://ollama.com).
The AI will respond with clarifications and ask for any missing information to that goal. You can configure it to use any LLM supported by [LiteLLM](https://docs.litellm.ai/docs/providers), including:
- OpenAI models (GPT-4, GPT-3.5)
- Anthropic Claude models
- Google Gemini models
- Deepseek models
- Ollama models (local)
- And many more!
It's really helpful to [watch the demo (5 minute YouTube video)](https://www.youtube.com/watch?v=GEXllEH2XiQ) to understand how interaction works.
@@ -28,7 +34,11 @@ These are the key elements of an agentic framework:
For a deeper dive into this, check out the [architecture guide](./architecture.md).
## Setup and Configuration
See [the Setup guide](./setup.md).
See [the Setup guide](./setup.md) for detailed instructions. The basic configuration requires just two environment variables:
```bash
LLM_MODEL=openai/gpt-4o # or any other model supported by LiteLLM
LLM_KEY=your-api-key-here
```
## Customizing Interaction & Tools
See [the guide to adding goals and tools](./adding-goals-and-tools.md).