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fixing docs - duplicates, clarifying

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Joshua Smith
2025-03-28 14:57:56 -04:00
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38
adding-goals-and-tools.md
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@@ -68,41 +68,3 @@ Example:
if tool_name == "CurrentPTO":
return current_pto
```
### Existing Travel Goals
The agent can be configured to pursue different goals using the `AGENT_GOAL` environment variable in your `.env` file.
#### Goal: Find an event in Australia / New Zealand, book flights to it and invoice the user for the cost
- `AGENT_GOAL=goal_event_flight_invoice` (default) - Helps users find events, book flights, and arrange train travel with invoice generation
- This is the scenario in the [original video](https://www.youtube.com/watch?v=GEXllEH2XiQ)
#### Goal: Find a Premier League match, book train tickets to it and invoice the user for the cost
- `AGENT_GOAL=goal_match_train_invoice` - Focuses on Premier League match attendance with train booking and invoice generation
- This is a new goal that is part of the [Replay 2025 talk](https://www.youtube.com/watch?v=YDxAWrIBQNE).
If not specified, the agent defaults to all goals. Each goal, including these, comes with its own set of tools and conversation flows designed for specific use cases. You can examine `tools/goal_registry.py` to see the detailed configuration of each goal.
See the next section for tool configuration for these goals.
#### Configuring Travel Goal Tools
##### Agent Goal: goal_event_flight_invoice (default)
* The agent uses a mock function to search for events. This has zero configuration.
* By default the agent uses a mock function to search for flights.
* If you want to use the real flights API, go to `tools/search_flights.py` and replace the `search_flights` function with `search_flights_real_api` that exists in the same file.
* It's free to sign up at [RapidAPI](https://rapidapi.com/apiheya/api/sky-scrapper)
* This api might be slow to respond, so you may want to increase the start to close timeout, `TOOL_ACTIVITY_START_TO_CLOSE_TIMEOUT` in `workflows/workflow_helpers.py`
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.
##### Agent Goal: goal_match_train_invoice
* Finding a match requires a key from [Football Data](https://www.football-data.org). Sign up for a free account, then see the 'My Account' page to get your API token. Set `FOOTBALL_DATA_API_KEY` to this value.
* If you're lazy go to `tools/search_fixtures.py` and replace the `search_fixtures` function with the mock `search_fixtures_example` that exists in the same file.
* We use a mock function to search for trains. Start the train API server to use the real API: `python thirdparty/train_api.py`
* * The train activity is 'enterprise' so it's written in C# and requires a .NET runtime. See the [.NET backend](#net-(enterprise)-backend) section for details on running it.
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.

81
setup.md
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@@ -17,41 +17,7 @@ SHOW_CONFIRM=True
The agent can be configured to pursue different goals using the `AGENT_GOAL` environment variable in your `.env` file.
#### Goal: Find an event in Australia / New Zealand, book flights to it and invoice the user for the cost
- `AGENT_GOAL=goal_event_flight_invoice` (default) - Helps users find events, book flights, and arrange train travel with invoice generation
- This is the scenario in the video above
#### Goal: Find a Premier League match, book train tickets to it and invoice the user for the cost
- `AGENT_GOAL=goal_match_train_invoice` - Focuses on Premier League match attendance with train booking and invoice generation
- This goal was part of [Temporal's Replay 2025 conference keynote demo](https://www.youtube.com/watch?v=YDxAWrIBQNE)
- Note, there is failure built in to this demo (the train booking step) to show how the agent can handle failures and retry. See Tool Configuration below for details.
If not specified, the agent defaults to `goal_event_flight_invoice`. Each goal comes with its own set of tools and conversation flows designed for specific use cases. You can examine `tools/goal_registry.py` to see the detailed configuration of each goal.
See the next section for tool configuration for each goal.
### Tool Configuration
#### Agent Goal: goal_event_flight_invoice (default)
* The agent uses a mock function to search for events. This has zero configuration.
* By default the agent uses a mock function to search for flights.
* If you want to use the real flights API, go to `tools/search_flights.py` and replace the `search_flights` function with `search_flights_real_api` that exists in the same file.
* It's free to sign up at [RapidAPI](https://rapidapi.com/apiheya/api/sky-scrapper)
* This api might be slow to respond, so you may want to increase the start to close timeout, `TOOL_ACTIVITY_START_TO_CLOSE_TIMEOUT` in `workflows/workflow_helpers.py`
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* Set permissions for read-write on: `Credit Notes, Invoices, Customers and Customer Sessions`
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.
#### Agent Goal: goal_match_train_invoice
NOTE: This goal was developed for an on-stage demo and has failure (and its resolution) built in to show how the agent can handle failures and retry.
* Finding a match requires a key from [Football Data](https://www.football-data.org). Sign up for a free account, then see the 'My Account' page to get your API token. Set `FOOTBALL_DATA_API_KEY` to this value.
* If you're lazy go to `tools/search_fixtures.py` and replace the `search_fixtures` function with the mock `search_fixtures_example` that exists in the same file.
* We use a mock function to search for trains. Start the train API server to use the real API: `python thirdparty/train_api.py`
* * The train activity is 'enterprise' so it's written in C# and requires a .NET runtime. See the [.NET backend](#net-(enterprise)-backend) section for details on running it.
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.
See the section Goal-Specific Tool Configuration below for tool configuration for specific goals.
### LLM Provider Configuration
@@ -156,7 +122,40 @@ npx vite
```
Access the UI at `http://localhost:5173`
### Python Search Trains API
## Goal-Specific Tool Configuration
Here is configuration guidance for specific goals. `travel,fin` goals have configuration & setup as below.
### Goal: Find an event in Australia / New Zealand, book flights to it and invoice the user for the cost
- `AGENT_GOAL=goal_event_flight_invoice` - Helps users find events, book flights, and arrange train travel with invoice generation
- This is the scenario in the [original video](https://www.youtube.com/watch?v=GEXllEH2XiQ)
#### Configuring Agent Goal: goal_event_flight_invoice
* The agent uses a mock function to search for events. This has zero configuration.
* By default the agent uses a mock function to search for flights.
* If you want to use the real flights API, go to `tools/search_flights.py` and replace the `search_flights` function with `search_flights_real_api` that exists in the same file.
* It's free to sign up at [RapidAPI](https://rapidapi.com/apiheya/api/sky-scrapper)
* This api might be slow to respond, so you may want to increase the start to close timeout, `TOOL_ACTIVITY_START_TO_CLOSE_TIMEOUT` in `workflows/workflow_helpers.py`
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* Set permissions for read-write on: `Credit Notes, Invoices, Customers and Customer Sessions`
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.
### Goal: Find a Premier League match, book train tickets to it and invoice the user for the cost (Replay 2025 Keynote)
- `AGENT_GOAL=goal_match_train_invoice` - Focuses on Premier League match attendance with train booking and invoice generation
- This goal was part of [Temporal's Replay 2025 conference keynote demo](https://www.youtube.com/watch?v=YDxAWrIBQNE)
- Note, there is failure built in to this demo (the train booking step) to show how the agent can handle failures and retry. See Tool Configuration below for details.
#### Configuring Agent Goal: goal_match_train_invoice
NOTE: This goal was developed for an on-stage demo and has failure (and its resolution) built in to show how the agent can handle failures and retry.
* Finding a match requires a key from [Football Data](https://www.football-data.org). Sign up for a free account, then see the 'My Account' page to get your API token. Set `FOOTBALL_DATA_API_KEY` to this value.
* If you're lazy go to `tools/search_fixtures.py` and replace the `search_fixtures` function with the mock `search_fixtures_example` that exists in the same file.
* We use a mock function to search for trains. Start the train API server to use the real API: `python thirdparty/train_api.py`
* * The train activity is 'enterprise' so it's written in C# and requires a .NET runtime. See the [.NET backend](#net-(enterprise)-backend) section for details on running it.
* Requires a Stripe key for the `create_invoice` tool. Set this in the `STRIPE_API_KEY` environment variable in .env
* It's free to sign up and get a key at [Stripe](https://stripe.com/)
* If you're lazy go to `tools/create_invoice.py` and replace the `create_invoice` function with the mock `create_invoice_example` that exists in the same file.
##### Python Search Trains API
> Agent Goal: goal_match_train_invoice only
Required to search and book trains!
@@ -167,7 +166,7 @@ poetry run python thirdparty/train_api.py
# http://localhost:8080/api/search?from=london&to=liverpool&outbound_time=2025-04-18T09:00:00&inbound_time=2025-04-20T09:00:00
```
### Python Train Legacy Worker
##### Python Train Legacy Worker
> Agent Goal: goal_match_train_invoice only
These are Python activities that fail (raise NotImplemented) to show how Temporal handles a failure. You can run these activities with.
@@ -178,7 +177,7 @@ poetry run python thirdparty/train_api.py
The activity will fail and be retried infinitely. To rescue the activity (and its corresponding workflows), kill the worker and run the .NET one in the section below.
### .NET (enterprise) Worker ;)
##### .NET (enterprise) Worker ;)
We have activities written in C# to call the train APIs.
```bash
cd enterprise
@@ -187,14 +186,14 @@ dotnet run
```
If you're running your train API above on a different host/port then change the API URL in `Program.cs`. Otherwise, be sure to run it using `python thirdparty/train_api.py`.
### Money Movement Scenario
This scenario _can_ initiate a secondary workflow to move money. Check out [this repo](https://github.com/temporal-sa/temporal-money-transfer-java) - you'll need to get the worker running and connected to the same account as the agentic worker.
#### Goals: Money Movement
- `AGENT_GOAL=goal_fin_move_money` - This scenario _can_ initiate a secondary workflow to move money. Check out [this repo](https://github.com/temporal-sa/temporal-money-transfer-java) - you'll need to get the worker running and connected to the same account as the agentic worker.
By default it will _not_ make a real workflow, it'll just fake it. If you get the worker running and want to start a workflow, in your [.env](./.env):
```bash
FIN_START_REAL_WORKFLOW=FALSE #set this to true to start a real workflow
```
## Customizing the Agent
## Customizing the Agent Further
- `tool_registry.py` contains the mapping of tool names to tool definitions (so the AI understands how to use them)
- `goal_registry.py` contains descriptions of goals and the tools used to achieve them
- The tools themselves are defined in their own files in `/tools`