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.env.example
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.env.example
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OPENAI_API_KEY=sk-proj-...
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RAPIDAPI_KEY=9df2cb5...
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RAPIDAPI_HOST=sky-scrapper.p.rapidapi.com
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This demo shows a multi-turn conversation with an AI agent running inside a Temporal workflow. The goal is to collect information towards a goal. There's a simple DSL input for collecting information (currently set up to use mock functions to search for events, book flights around those events then generate an invoice for those flights, see `send_message.py`). The AI will respond with clarifications and ask for any missing information to that goal. It uses a local LLM via Ollama.
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## Setup
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* Install [Ollama](https://ollama.com) and the [Qwen2.5 14B](https://ollama.com/library/qwen2.5) model (`ollama run qwen2.5:14b`). (note this model is about 9GB to download).
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* Requires an OpenAI key for the gpt-4o model. Set this in the `OPENAI_API_KEY` environment variable in .env
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* Requires a rapidapi key for sky-scrapper (how we find flights). Set this in the `RAPIDAPI_KEY` environment variable in .env
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* If you're lazy go to `tools/search_flights.py` and replace the `get_flights` function with the mock `search_flights_example` that exists in the same file.
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* See .env_example for the required environment variables.
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* Install and run Temporal. Follow the instructions in the [Temporal documentation](https://learn.temporal.io/getting_started/python/dev_environment/#set-up-a-local-temporal-service-for-development-with-temporal-cli) to install and run the Temporal server.
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* Install the dependencies: `poetry install`
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Deprecated:
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* Install [Ollama](https://ollama.com) and the [Qwen2.5 14B](https://ollama.com/library/qwen2.5) model (`ollama run qwen2.5:14b`). (note this model is about 9GB to download).
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* Local LLM is disabled as ChatGPT 4o was better for this use case. To use Ollama, examine `./activities/tool_activities.py` and rename the functions.
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## Running the example
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From the /scripts directory:
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