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Steve Androulakis
2025-01-01 17:10:48 -08:00
parent 443401ba83
commit f1f9e9e5c9
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README.md
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@@ -1,6 +1,6 @@
# AI Agent execution using Temporal # AI Agent execution using Temporal
Work in progress (very early!). Work in progress.
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. 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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workflows/tool_workflow.py
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@@ -179,7 +179,7 @@ class ToolWorkflow:
"Chat ended. Conversation summary:\n" "Chat ended. Conversation summary:\n"
+ f"{self.conversation_summary}" + f"{self.conversation_summary}"
) )
return f"{self.conversation_history}" return f"{self.conversation_summary}"
@workflow.signal @workflow.signal
async def user_prompt(self, prompt: str) -> None: async def user_prompt(self, prompt: str) -> None: