refactors and ui enhancements

README.md

@@ -7,6 +7,7 @@ This demo shows a multi-turn conversation with an AI agent running inside a Temp
 ## Setup
 * Requires an OpenAI key for the gpt-4o model. Set this in the `OPENAI_API_KEY` environment variable in .env
 * Requires a rapidapi key for sky-scrapper (how we find flights). Set this in the `RAPIDAPI_KEY` environment variable in .env
+    * It's free to sign up and get a key at [RapidAPI](https://rapidapi.com/apiheya/api/sky-scrapper)
     * 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.
 * See .env_example for the required environment variables.
 * 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.

api/main.py

@@ -1,15 +1,10 @@
 from fastapi import FastAPI
 from temporalio.client import Client
 from workflows.tool_workflow import ToolWorkflow
-from models.data_types import CombinedInput, ToolsData, ToolWorkflowParams
+from models.data_types import CombinedInput, ToolWorkflowParams
+from tools.goal_registry import goal_event_flight_invoice
 from temporalio.exceptions import TemporalError
 from fastapi.middleware.cors import CORSMiddleware
-from tools.tool_registry import (
-    find_events_tool,
-    search_flights_tool,
-    create_invoice_tool,
-)
-
 
 app = FastAPI()
 
@@ -68,40 +63,10 @@ async def get_conversation_history():
 async def send_prompt(prompt: str):
     client = await Client.connect("localhost:7233")
 
-    # Build the ToolsData
-    tools_data = ToolsData(
-        tools=[find_events_tool, search_flights_tool, create_invoice_tool],
-        description="Help the user gather args for these tools in order: "
-        "1. FindEvents: Find an event to travel to "
-        "2. SearchFlights: search for a flight around the event dates "
-        "3. GenerateInvoice: Create a simple invoice for the cost of that flight ",
-        example_conversation_history="\n ".join(
-            [
-                "user: I'd like to travel to an event",
-                "agent: Sure! Let's start by finding an event you'd like to attend. Could you tell me which city and month you're interested in?",
-                "user: In Sao Paulo, Brazil, in February",
-                "agent: Great! Let's find an events in Sao Paulo, Brazil in February.",
-                "user_confirmed_tool_run: <user clicks confirm on FindEvents tool>",
-                "tool_result: { 'event_name': 'Carnival', 'event_date': '2023-02-25' }",
-                "agent: Found an event! There's Carnival on 2023-02-25, ending on 2023-02-28. Would you like to search for flights around these dates?",
-                "user: Yes, please",
-                "agent: Let's search for flights around these dates. Could you provide your departure city?",
-                "user: New York",
-                "agent: Thanks, searching for flights from New York to Sao Paulo around 2023-02-25 to 2023-02-28.",
-                "user_confirmed_tool_run: <user clicks confirm on SearchFlights tool>"
-                'tool_result: results including {"flight_number": "CX101", "return_flight_number": "CX102", "price": 850.0}',
-                "agent: Found some flights! The cheapest is CX101 for $850. Would you like to generate an invoice for this flight?",
-                "user_confirmed_tool_run: <user clicks confirm on CreateInvoice tool>",
-                'tool_result: { "status": "success", "invoice": { "flight_number": "CX101", "amount": 850.0 }, invoiceURL: "https://example.com/invoice" }',
-                "agent: Invoice generated! Here's the link: https://example.com/invoice",
-            ]
-        ),
-    )
-
     # Create combined input
     combined_input = CombinedInput(
         tool_params=ToolWorkflowParams(None, None),
-        tools_data=tools_data,
+        agent_goal=goal_event_flight_invoice,
     )
 
     workflow_id = "agent-workflow"

frontend/src/components/ConfirmInline.jsx

@@ -1,5 +1,4 @@
 import React from "react";
-import LoadingIndicator from "./LoadingIndicator";
 
 export default function ConfirmInline({ data, confirmed, onConfirm }) {
   const { args, tool } = data || {};

frontend/src/components/LLMResponse.jsx

@@ -32,6 +32,16 @@ export default function LLMResponse({ data, onConfirm, isLastMessage }) {
           onConfirm={handleConfirm}
         />
       )}
+      {!requiresConfirm && data.tool && data.next === "confirm" && (
+        <div className="text-sm text-center  text-green-600 dark:text-green-400">
+          <div>
+            Agent ran tool: <strong>{data.tool ?? "Unknown"}</strong>
+          </div>
+          {/* <div>
+            {JSON.stringify(data, null, 2)}
+          </div> */}
+        </div>
+      )}
     </div>
   );
 }

models/data_types.py

@@ -1,6 +1,6 @@
 from dataclasses import dataclass
 from typing import Optional, Deque
-from models.tool_definitions import ToolsData
+from models.tool_definitions import AgentGoal
 
 
 @dataclass
@@ -12,4 +12,4 @@ class ToolWorkflowParams:
 @dataclass
 class CombinedInput:
     tool_params: ToolWorkflowParams
-    tools_data: ToolsData
+    agent_goal: AgentGoal

models/tool_definitions.py

@@ -17,7 +17,7 @@ class ToolDefinition:
 
 
 @dataclass
-class ToolsData:
+class AgentGoal:
     tools: List[ToolDefinition]
     description: str = "Description of the tools purpose and overall goal"
     example_conversation_history: str = (

prompts/agent_prompt_generators.py

@@ -1,10 +1,10 @@
-from models.tool_definitions import ToolsData
+from models.tool_definitions import AgentGoal
 from typing import Optional
 import json
 
 
 def generate_genai_prompt(
-    tools_data: ToolsData, conversation_history: str, raw_json: Optional[str] = None
+    agent_goal: AgentGoal, conversation_history: str, raw_json: Optional[str] = None
 ) -> str:
     """
     Generates a concise prompt for producing or validating JSON instructions
@@ -28,22 +28,22 @@ def generate_genai_prompt(
     prompt_lines.append("END CONVERSATION HISTORY")
     prompt_lines.append("")
 
-    # Example Conversation History (from tools_data)
+    # Example Conversation History (from agent_goal)
-    if tools_data.example_conversation_history:
+    if agent_goal.example_conversation_history:
         prompt_lines.append("=== Example Conversation With These Tools ===")
         prompt_lines.append(
             "Use this example to understand how tools are invoked and arguments are gathered."
         )
         prompt_lines.append("BEGIN EXAMPLE")
-        prompt_lines.append(tools_data.example_conversation_history)
+        prompt_lines.append(agent_goal.example_conversation_history)
         prompt_lines.append("END EXAMPLE")
         prompt_lines.append("")
 
     # Tools Definitions
     prompt_lines.append("=== Tools Definitions ===")
-    prompt_lines.append(f"There are {len(tools_data.tools)} available tools:")
+    prompt_lines.append(f"There are {len(agent_goal.tools)} available tools:")
-    prompt_lines.append(", ".join([t.name for t in tools_data.tools]))
+    prompt_lines.append(", ".join([t.name for t in agent_goal.tools]))
-    prompt_lines.append(f"Goal: {tools_data.description}")
+    prompt_lines.append(f"Goal: {agent_goal.description}")
     prompt_lines.append(
         "Gather the necessary information for each tool in the sequence described above."
     )
@@ -51,7 +51,7 @@ def generate_genai_prompt(
         "Only ask for arguments listed below. Do not add extra arguments."
     )
     prompt_lines.append("")
-    for tool in tools_data.tools:
+    for tool in agent_goal.tools:
         prompt_lines.append(f"Tool name: {tool.name}")
         prompt_lines.append(f"  Description: {tool.description}")
         prompt_lines.append("  Required args:")

scripts/send_message.py

@@ -2,14 +2,14 @@ import asyncio
 import sys
 from temporalio.client import Client
 
-from models.data_types import CombinedInput, ToolsData, ToolWorkflowParams
+from models.data_types import CombinedInput, AgentGoal, ToolWorkflowParams
 from tools.tool_registry import event_travel_tools
 from workflows.tool_workflow import ToolWorkflow
 
 
 async def main(prompt: str):
-    # Build the ToolsData
+    # Build the AgentGoal
-    tools_data = ToolsData(
+    agent_goal = AgentGoal(
         tools=event_travel_tools,
         description="Helps the user find an event to travel to, search flights, and create an invoice for those flights.",
     )
@@ -17,7 +17,7 @@ async def main(prompt: str):
     # 2) Create combined input
     combined_input = CombinedInput(
         tool_params=ToolWorkflowParams(None, None),
-        tools_data=tools_data,
+        agent_goal=agent_goal,
     )
 
     # 3) Connect to Temporal and start or signal the workflow

tools/goal_registry.py

@@ -0,0 +1,35 @@
+from models.tool_definitions import AgentGoal
+from tools.tool_registry import (
+    find_events_tool,
+    search_flights_tool,
+    create_invoice_tool,
+)
+
+goal_event_flight_invoice = AgentGoal(
+    tools=[find_events_tool, search_flights_tool, create_invoice_tool],
+    description="Help the user gather args for these tools in order: "
+    "1. FindEvents: Find an event to travel to "
+    "2. SearchFlights: search for a flight around the event dates "
+    "3. GenerateInvoice: Create a simple invoice for the cost of that flight ",
+    example_conversation_history="\n ".join(
+        [
+            "user: I'd like to travel to an event",
+            "agent: Sure! Let's start by finding an event you'd like to attend. Could you tell me which city and month you're interested in?",
+            "user: In Sao Paulo, Brazil, in February",
+            "agent: Great! Let's find an events in Sao Paulo, Brazil in February.",
+            "user_confirmed_tool_run: <user clicks confirm on FindEvents tool>",
+            "tool_result: { 'event_name': 'Carnival', 'event_date': '2023-02-25' }",
+            "agent: Found an event! There's Carnival on 2023-02-25, ending on 2023-02-28. Would you like to search for flights around these dates?",
+            "user: Yes, please",
+            "agent: Let's search for flights around these dates. Could you provide your departure city?",
+            "user: New York",
+            "agent: Thanks, searching for flights from New York to Sao Paulo around 2023-02-25 to 2023-02-28.",
+            "user_confirmed_tool_run: <user clicks confirm on SearchFlights tool>"
+            'tool_result: results including {"flight_number": "CX101", "return_flight_number": "CX102", "price": 850.0}',
+            "agent: Found some flights! The cheapest is CX101 for $850. Would you like to generate an invoice for this flight?",
+            "user_confirmed_tool_run: <user clicks confirm on CreateInvoice tool>",
+            'tool_result: { "status": "success", "invoice": { "flight_number": "CX101", "amount": 850.0 }, invoiceURL: "https://example.com/invoice" }',
+            "agent: Invoice generated! Here's the link: https://example.com/invoice",
+        ]
+    ),
+)

tools/search_flights.py

@@ -40,7 +40,7 @@ def search_airport(query: str) -> list:
         return []
 
 
-def search_flights(args: dict) -> dict:
+def search_flights_realapi(args: dict) -> dict:
     """
     1) Looks up airport/city codes via search_airport.
     2) Finds the first matching skyId/entityId for both origin & destination.
@@ -169,26 +169,31 @@ def search_flights(args: dict) -> dict:
     }
 
 
-def search_flights_example(args: dict) -> dict:
+def search_flights(args: dict) -> dict:
     """
-    Example function for searching flights.
+    Returns example flight search results in the requested JSON format.
-    Currently just prints/returns the passed args,
-    but you can add real flight search logic later.
     """
-    # date_depart = args.get("dateDepart")
-    # date_return = args.get("dateReturn")
     origin = args.get("origin")
     destination = args.get("destination")
 
-    flight_search_results = {
+    return {
-        "origin": f"{origin}",
-        "destination": f"{destination}",
         "currency": "USD",
+        "destination": f"{destination}",
+        "origin": f"{origin}",
         "results": [
-            {"flight_number": "CX101", "return_flight_number": "CX102", "price": 850.0},
+            {
-            {"flight_number": "QF30", "return_flight_number": "QF29", "price": 920.0},
+                "operating_carrier": "American Airlines",
-            {"flight_number": "MH129", "return_flight_number": "MH128", "price": 780.0},
+                "outbound_flight_code": "AA203",
+                "price": 1262.51,
+                "return_flight_code": "AA202",
+                "return_operating_carrier": "American Airlines",
+            },
+            {
+                "operating_carrier": "Air New Zealand",
+                "outbound_flight_code": "NZ488",
+                "price": 1396.00,
+                "return_flight_code": "NZ527",
+                "return_operating_carrier": "Air New Zealand",
+            },
         ],
     }
-
-    return flight_search_results

workflows/tool_workflow.py

@@ -30,7 +30,7 @@ class ToolWorkflow:
     @workflow.run
     async def run(self, combined_input: CombinedInput) -> str:
         params = combined_input.tool_params
-        tools_data = combined_input.tools_data
+        agent_goal = combined_input.agent_goal
         tool_data = None
 
         if params and params.conversation_summary:
@@ -97,10 +97,10 @@ class ToolWorkflow:
 
                 # Pass entire conversation + Tools to LLM
                 context_instructions = generate_genai_prompt(
-                    tools_data, self.conversation_history, self.tool_data
+                    agent_goal, self.conversation_history, self.tool_data
                 )
 
-                # tools_list = ", ".join([t.name for t in tools_data.tools])
+                # tools_list = ", ".join([t.name for t in agent_goal.tools])
 
                 prompt_input = ToolPromptInput(
                     prompt=prompt,
@@ -121,7 +121,7 @@ class ToolWorkflow:
                 current_tool = self.tool_data.get("tool")
 
                 if next_step == "confirm" and current_tool:
-                    # tmp arg check
+                    # todo make this less awkward
                     args = self.tool_data.get("args")
 
                     # check each argument for null values
@@ -132,8 +132,6 @@ class ToolWorkflow:
                             missing_args.append(key)
 
                     if missing_args:
-                        # self.add_message("response_confirm_missing_args", tool_data)
-
                         # Enqueue a follow-up prompt for the LLM
                         self.prompt_queue.append(
                             f"### INSTRUCTIONS set next='question', combine this response response='{tool_data.get('response')}' and following missing arguments for tool {current_tool}: {missing_args}. "
@@ -184,7 +182,7 @@ class ToolWorkflow:
                                     conversation_summary=self.conversation_summary,
                                     prompt_queue=self.prompt_queue,
                                 ),
-                                tools_data=tools_data,
+                                agent_goal=agent_goal,
                             )
                         ]
                     )