start prompt comes from back-end

README.md

@@ -142,6 +142,7 @@ Access the UI at `http://localhost:5173`
 # TODO for this branch
 ## Agent
 - We'll have to figure out which matches are where. No use going to Manchester for a match that isn't there.
+- The use of `###` in prompts I want excluded from the conversation history is a bit of a hack.
 
 ## Validator function
 - Probably keep data types, but move the activity and workflow code for the demo

api/main.py

@@ -132,3 +132,26 @@ async def end_chat():
         print(e)
         # Workflow not found; return an empty response
         return {}
+
+
+@app.post("/start-workflow")
+async def start_workflow():
+    # Create combined input
+    combined_input = CombinedInput(
+        tool_params=ToolWorkflowParams(None, None),
+        agent_goal=goal_event_flight_invoice,
+    )
+
+    workflow_id = "agent-workflow"
+
+    # Start the workflow with the starter prompt from the goal
+    await temporal_client.start_workflow(
+        ToolWorkflow.run,
+        combined_input,
+        id=workflow_id,
+        task_queue=TEMPORAL_TASK_QUEUE,
+        start_signal="user_prompt",
+        start_signal_args=["### " + goal_event_flight_invoice.starter_prompt],
+    )
+
+    return {"message": f"Workflow started with goal's starter prompt: {goal_event_flight_invoice.starter_prompt}."}

frontend/src/pages/App.jsx

@@ -167,7 +167,7 @@ export default function App() {
         try {
             setError(INITIAL_ERROR_STATE);
             setLoading(true);
-            await apiService.sendMessage("I'd like to travel for an event.");
+            await apiService.startWorkflow();
             setConversation([]);
             setLastMessage(null);
         } catch (err) {

frontend/src/services/api.js

@@ -56,6 +56,26 @@ export const apiService = {
         }
     },
 
+    async startWorkflow() {
+        try {
+            const res = await fetch(
+                `${API_BASE_URL}/start-workflow`,
+                { 
+                    method: 'POST',
+                    headers: {
+                        'Content-Type': 'application/json'
+                    }
+                }
+            );
+            return handleResponse(res);
+        } catch (error) {
+            throw new ApiError(
+                'Failed to start workflow',
+                error.status || 500
+            );
+        }
+    },
+
     async confirm() {
         try {
             const res = await fetch(`${API_BASE_URL}/confirm`, { 

models/tool_definitions.py

@@ -20,6 +20,7 @@ class ToolDefinition:
 class AgentGoal:
     tools: List[ToolDefinition]
     description: str = "Description of the tools purpose and overall goal"
+    starter_prompt: str = "Initial prompt to start the conversation"
     example_conversation_history: str = (
         "Example conversation history to help the AI agent understand the context of the conversation"
     )

tools/goal_registry.py

@@ -11,6 +11,7 @@ goal_event_flight_invoice = AgentGoal(
     "1. FindFixtures: Find fixtures for a team in a given month "
     "2. SearchFlights: search for a flight around the event dates "
     "3. CreateInvoice: Create a simple invoice for the cost of that flight ",
+    starter_prompt="Welcome me, give me a description of what you can do, then ask me for the details you need to do your job",
     example_conversation_history="\n ".join(
         [
             "user: I'd like to travel to a football match",

workflows/tool_workflow.py

@@ -151,23 +151,23 @@ class ToolWorkflow:
                 if not prompt.startswith("###"):
                     self.add_message("user", prompt)
                 
-                # Validate the prompt before proceeding
-                validation_input = ValidationInput(
-                    prompt=prompt,
-                    conversation_history=self.conversation_history,
-                    agent_goal=agent_goal,
-                )
-                validation_result = await workflow.execute_activity(
-                    ToolActivities.validate_llm_prompt,
-                    args=[validation_input],
-                    schedule_to_close_timeout=LLM_ACTIVITY_TIMEOUT,
-                    retry_policy=RetryPolicy(initial_interval=timedelta(seconds=5)),
-                )
+                    # Validate the prompt before proceeding
+                    validation_input = ValidationInput(
+                        prompt=prompt,
+                        conversation_history=self.conversation_history,
+                        agent_goal=agent_goal,
+                    )
+                    validation_result = await workflow.execute_activity(
+                        ToolActivities.validate_llm_prompt,
+                        args=[validation_input],
+                        schedule_to_close_timeout=LLM_ACTIVITY_TIMEOUT,
+                        retry_policy=RetryPolicy(initial_interval=timedelta(seconds=5)),
+                    )
 
-                if not validation_result.validationResult:
-                    # Handle validation failure
-                    self.add_message("agent", validation_result.validationFailedReason)
-                    continue  # Skip to the next iteration
+                    if not validation_result.validationResult:
+                        # Handle validation failure
+                        self.add_message("agent", validation_result.validationFailedReason)
+                        continue  # Skip to the next iteration
 
                 # Proceed with generating the context and prompt