ui enhancements, model tuning

frontend/src/components/ChatWindow.jsx

@@ -19,6 +19,7 @@ export default function ChatWindow({ conversation, loading, onConfirm }) {
   }
 
   const filtered = conversation.filter((msg) => {
+    console.log(conversation[conversation.length - 1].actor)
     const { actor, response } = msg;
   
     if (actor === "user") {
@@ -61,6 +62,11 @@ export default function ChatWindow({ conversation, loading, onConfirm }) {
           <LoadingIndicator />
         </div>
       )}
+      {conversation.length > 0 && conversation[conversation.length - 1].actor === "tool_result_to_llm" && (
+        <div className="flex justify-center">
+          <LoadingIndicator />
+        </div>
+      )}
     </div>
   );
 }

frontend/src/components/ConfirmInline.jsx

@@ -4,8 +4,6 @@ import LoadingIndicator from "./LoadingIndicator";
 export default function ConfirmInline({ data, confirmed, onConfirm }) {
   const { args, tool } = data || {};
 
-  console.log("ConfirmInline rendered with confirmed:", confirmed);
-
   if (confirmed) {
     // Once confirmed, show "Running..." state in the same container
     return (

frontend/src/components/LoadingIndicator.jsx

@@ -2,7 +2,7 @@ import React from "react";
 
 export default function LoadingIndicator() {
   return (
-    <div className="flex items-center justify-center space-x-2">
+    <div className="flex items-center justify-center space-x-2 pb-4">
       <div className="w-2 h-2 rounded-full bg-blue-600 animate-ping"></div>
       <div className="w-2 h-2 rounded-full bg-blue-600 animate-ping delay-100"></div>
       <div className="w-2 h-2 rounded-full bg-blue-600 animate-ping delay-200"></div>

frontend/src/pages/App.jsx

@@ -60,7 +60,7 @@ export default function App() {
         try {
             await fetch("http://127.0.0.1:8000/end-chat", { method: "POST" });
             // sleep for a bit to allow the server to process the end-chat request
-            await new Promise((resolve) => setTimeout(resolve, 4000)); // todo make less dodgy
+            await new Promise((resolve) => setTimeout(resolve, 1000)); // todo make less dodgy
             await fetch(
                 `http://127.0.0.1:8000/send-prompt?prompt=${encodeURIComponent("I'd like to travel to an event.")}`,
                 { method: "POST" }
@@ -71,6 +71,12 @@ export default function App() {
         }
     };
 
+    const handleKeyPress = (e) => {
+        if (e.key === "Enter") {
+            handleSendMessage();
+        }
+    };
+
     return (
         <div className="flex flex-col min-h-screen">
             <NavBar title="Temporal AI Agent" />
@@ -91,6 +97,7 @@ export default function App() {
                             placeholder="Type your message..."
                             value={userInput}
                             onChange={(e) => setUserInput(e.target.value)}
+                            onKeyPress={handleKeyPress}
                         />
                         <button
                             onClick={handleSendMessage}

prompts/agent_prompt_generators.py

@@ -73,8 +73,10 @@ def generate_genai_prompt(
     prompt_lines.append(
         "6. Use 'next': 'question' if you lack any required arguments based on the history and prompt. "
         "Use 'next': 'confirm' only if NO arguments are missing. "
-        "Use 'next': 'done' and tool: 'null' if you have successfully completed all tools."
+        "Use 'next': 'done' and tool: 'null' if you have successfully completed all tools "
         "Don't offer any additional tools beyond the tools listed. "
+        "DON'T editorialize or add extra information to a 'done' response. "
+        "Example done response: {'response': 'All tools completed.', 'next': 'done', 'tool': 'null', 'args': {}} "
     )
     prompt_lines.append(
         "7. Keep 'response' user-friendly with no extra commentary. Stick to valid JSON syntax. "

workflows/tool_workflow.py

@@ -1,6 +1,6 @@
 from collections import deque
 from datetime import timedelta
-from typing import Dict, Any, Union, List, Optional, Tuple, Deque
+from typing import Dict, Any, Union, List, Optional, Deque
 from temporalio.common import RetryPolicy
 
 from temporalio import workflow
@@ -25,6 +25,7 @@ class ToolWorkflow:
         self.tool_data = None
         self.max_turns_before_continue: int = 250
         self.confirm = False
+        self.tool_results: List[Dict[str, Any]] = []
 
     @workflow.run
     async def run(self, combined_input: CombinedInput) -> str:
@@ -50,22 +51,9 @@ class ToolWorkflow:
 
             # 1) If chat_ended was signaled, handle end and return
             if self.chat_ended:
-                # possibly do a summary if multiple turns
+
-                if len(self.conversation_history["messages"]) > 1:
+                workflow.logger.info("Chat ended.")
-                    summary_context, summary_prompt = self.prompt_summary_with_history()
+                return f"{self.conversation_history}"
-                    summary_input = ToolPromptInput(
-                        prompt=summary_prompt, context_instructions=summary_context
-                    )
-                    self.conversation_summary = await workflow.start_activity_method(
-                        ToolActivities.prompt_llm,
-                        summary_input,
-                        schedule_to_close_timeout=timedelta(seconds=20),
-                    )
-                workflow.logger.info(
-                    "Chat ended. Conversation summary:\n"
-                    + f"{self.conversation_summary}"
-                )
-                return f"{self.conversation_summary}"
 
             # 2) If we received a confirm signal:
             if self.confirm and waiting_for_confirm and current_tool:
@@ -86,13 +74,15 @@ class ToolWorkflow:
                     schedule_to_close_timeout=timedelta(seconds=20),
                 )
                 dynamic_result["tool"] = current_tool
-                self.add_message(f"tool_result", dynamic_result)
+                self.add_message(
+                    "tool_result", {"tool": current_tool, "result": dynamic_result}
+                )
 
                 # Enqueue a follow-up prompt for the LLM
                 self.prompt_queue.append(
                     f"### The '{current_tool}' tool completed successfully with {dynamic_result}. "
                     "INSTRUCTIONS: Use this tool result, and the conversation history to figure out next steps. "
-                    "IMPORTANT: If all listed tools have run, you are up to the final step. Mark 'next':'done' and respond with your final confirmation."
+                    "IMPORTANT: If all listed tools have run, you are up to the final step. Mark 'next':'done' and respond with 'All tools run' or similar."
                 )
                 # Loop around again
                 continue