initial progress

README.md

@@ -1,9 +1,11 @@
-# Multi-turn chat with Ollama Entity Workflow
+# AI Agent execution using Temporal
 
-Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless explicitly ended. The workflow continues as new after a configurable number of chat turns to keep the prompt size small and the Temporal event history small. Each continued-as-new workflow receives a summary of the conversation history so far for context.
+Work in progress (very early!).
+
+This demo shows a multi-turn conversation with an AI agent running inside a Temporal Entity Workflow. The goal is to collect information towards a goal. There's a simple DSL input for collecting information (currently set up to search for flights). The AI will respond with clarifications and ask for any missing information (e.g., origin city, destination, travel dates). It uses a local LLM via Ollama.
 
 ## Setup
-* Install [Ollama](https://ollama.com) and the Mistral model (`ollama run mistral`).
+* Install [Ollama](https://ollama.com) and the Mistral model (`ollama run qwen2.5:14b`). (note this model is more than 10GB to download).
 * 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.
 * Install the dependencies: `poetry install`
 
@@ -12,13 +14,24 @@ Multi-Turn Chat using an Entity Workflow. The workflow runs forever unless expli
 1. Run the worker: `poetry run python run_worker.py`
 2. In another terminal run the client with a prompt.
 
-    Example: `poetry run python send_message.py 'What animals are marsupials?'`
+    Example: `poetry run python send_message.py 'I want to book a flight'`
 
 3. View the worker's output for the response.
 4. Give followup prompts by signaling the workflow.
 
-    Example: `poetry run python send_message.py 'Do they lay eggs?'`
+    Example: `poetry run python send_message.py 'From San Francisco'`
 5. Get the conversation history summary by querying the workflow.
     
     Example: `poetry run python get_history.py`
 6. To end the chat session, run `poetry run python end_chat.py`
+
+The chat session will end if it has collected enough information to complete the task or if the user explicitly ends the chat session.
+
+Run query get_tool_data to see the data the tool has collected so far.
+
+## TODO
+- This is currently a good single tool workflow. It could be a child as part of a planning workflow (multiple tools).
+- I should integrate another tool. Perhaps something that consumes web sites hunting for destinations to go to in the first place.
+- I should make this workflow execute a Search for flights as right now it will finish without doing anything.
+- I need to add a human in the loop confirmation step before it executes tools.
+- I need to build a chat interface so it's not cli-controlled. Also want to show some 'behind the scenes' of the agents being used as they run.