update: the full data section

chat_hist_temp.txt

@@ -0,0 +1,21 @@
+Model: Welcome to the Paintrek world. I am a health assistant, an interactive clinical recording system. I will ask you questions about your pain and related symptoms and record your responses.  I will then store this information securely. At any time, you can type `q` to quit.
+Model: Great!  First, I need some basic information for your medical record.  Please tell me your full name, date of birth, gender, and contact number.  Also, please provide an emergency contact name and number.
+Model: Please provide your full name, date of birth, gender, and contact number.  Also, please provide an emergency contact name and number.  This information is essential to begin your intake.
+Model: Thank you. Now, can you describe your main symptom or reason for seeking medical attention today?  And how long have you been experiencing this?
+Model: Okay.  Let's move on to a pain assessment.  To help me understand your headache, can you tell me where exactly you feel the pain?  Is it on the left, right, or both sides? And on a scale of 0 to 10, with 0 being no pain and 10 being the worst pain imaginable, how intense is the pain right now?
+
+We'll use a body map: head, arms, hands, trunk, legs, feet.  Please indicate the location(s) of your pain.
+Model: Please describe the location of your headache (e.g., forehead, temples, back of the head).  Is it on the left, right, or both sides?  And what is the pain intensity on a scale of 0-10?  We need this information to continue with the assessment.
+Model: Okay, so you're experiencing pain on the left side of your head, with an intensity of 2 out of 10.  Can you describe the characteristics of the pain?  Is it sharp, dull, throbbing, aching, or something else?  When did the pain start?  Does it radiate to any other areas?  Are there any triggers that make it worse or better?  Are there any other symptoms associated with the headache, such as nausea, vomiting, or visual disturbances?
+Model: To continue, please describe the characteristics of your headache (sharp, dull, throbbing, etc.), when it started, if it radiates, any triggers, and any associated symptoms (nausea, vomiting, visual disturbances, etc.).  This information is crucial for a proper assessment.
+Model: Understood.  Let's summarize what we have so far:
+
+*   **Patient:** Frank
+*   **DOB:** 1986-01-01
+*   **Main Symptom:** Headache on the left side of the head, sharp pain, intensity 2/10.
+*   **Duration:** 2 days
+*   **Triggers:** Cold temperatures seem to worsen the pain.
+*   **Associated Symptoms:** None reported.
+
+Is this information correct so far?
+Model: Great. Now, let's proceed with your medical history.  Do you have any existing medical conditions?  If so, please list them and when they were first diagnosed.  Do you have any known allergies?  Have you had any surgeries in the past?  If so, please specify the dates and types of surgeries.  What medications are you currently taking, including over-the-counter medications?

modules/data_class.py

@@ -32,10 +32,12 @@ class PatientID(TypedDict):
 
 class MainSymptom(TypedDict):
     main_symptom: str
-    length: str
+    symptom_length: str
 
 class Pain(TypedDict):
-    painlevel: PainLevels
+    pain_location: str
+    pain_side: str
+    pain_intensity: int
     pain_description: str
     start_time: date
     radiation: bool
@@ -87,15 +89,15 @@ class Plan(TypedDict):
 
 class PatientData(TypedDict):
     ID: PatientID
-    main: MainSymptom
-    """pain: Pain
+    symptom: MainSymptom
+    pain: Pain
     medical_hist: MedicalHistory
     family_hist: FamilyHistory
     social_hist: SocialHistory
     review_system: ReviewSystem
     pain_manage: PainManagement
     functional: Functional
-    plan: Plan"""
+    plan: Plan
 
 class DataState(TypedDict):
     """State representing the patient's data status and conversation."""

modules/instrctions.py

@@ -16,6 +16,7 @@ MEDICAL_INTAKE_SYSINT = (
 
    3. Pain Assessment
       - Pain location using body mapping (head, arms, hands, trunk, legs, feet)
+      - Pain side (left or right)
       - Pain intensity (0-10 scale for each location)
       - Pain characteristics and patterns
       - Onset time

modules/llm_in_use.py

@@ -12,7 +12,7 @@ def get_llm():
 
     # llm = ChatOpenAI(temperature=0)
 
-    llm = ChatOllama(model="llama3.2:latest", temperature=0)
+    # llm = ChatOllama(model="llama3.2:latest", temperature=0)
 
     """llm = ChatOpenAI(
         api_key="ollama",
@@ -20,6 +20,6 @@ def get_llm():
         base_url="http://141.211.127.171/",
     )"""
 
-    # llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
+    llm = ChatGoogleGenerativeAI(model="gemini-1.5-flash-latest")
 
     return llm

modules/nodes.py

@@ -49,10 +49,63 @@ def chatbot_with_tools(state: DataState) -> DataState:
                             "contact": "",
                             "emergency_contact": ""
                             },
-                            "symptom": {
-                                    "main_symptom": "",
-                                    "length": ""
-                            }
+                        "symptom": {
+                            "main_symptom": "",
+                            "symptom_length": ""
+                            },
+                        "pain": {
+                            "pain_location": "",
+                            "pain_side": "",
+                            "pain_intensity": 0,
+                            "pain_description": "",
+                            "start_time": date(1900, 1, 1),
+                            "radiation": False,
+                            "triggers": "",
+                            "symptom": ""
+                        },
+                        "medical_hist": {
+                            "medical_condition": "",
+                            "first_time": date(1900, 1, 1),
+                            "surgery_history": [],
+                            "medication": "",
+                            "allergy": ""
+                        },
+                        "family_hist": {
+                            "family_history": "",
+                        },
+                        "social_hist": {
+                            "occupation": "",
+                            "smoke": False,
+                            "alcohol": False,
+                            "drug": False,
+                            "support_system": "",
+                            "living_condition": "",
+                        },
+                        "reveiw_system": {
+                            "weight_change": "",
+                            "fever": False,
+                            "chill": False,
+                            "night_sweats": False,
+                            "sleep": "",
+                            "gastrointestinal": "",
+                            "urinary": "",
+                        },
+                        "pain_manage": {
+                            "pain_medication": "",
+                            "specialist": False,
+                            "other_therapy": "",
+                            "effectiveness": False,
+                        },
+                        "functional": {
+                            "life_quality": "",
+                            "limit_activity": "",
+                            "mood": "",
+                        },
+                        "plan": {
+                            "goal": "",
+                            "expectation": "",
+                            "alternative_treatment_illness": "",
+                        }
     }, "finished": False}
 
     if state["messages"]:

paintrek-chat-v2.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 4,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:11.440091Z",
@@ -14,16 +14,7 @@
     "id": "xaiioUQni_ga",
     "trusted": true
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "/home/frank-elite/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
-      "  from .autonotebook import tqdm as notebook_tqdm\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from modules.data_class import DataState\n",
     "from modules.tools import data_node\n",
@@ -37,12 +28,14 @@
     "\n",
     "from langgraph.prebuilt import ToolNode\n",
     "\n",
-    "from collections.abc import Iterable"
+    "from collections.abc import Iterable\n",
+    "from IPython.display import display, clear_output\n",
+    "import sys"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 5,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:11.906458Z",
@@ -62,7 +55,7 @@
        "<IPython.core.display.Image object>"
       ]
      },
-     "execution_count": 2,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -91,7 +84,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 6,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2025-01-29T20:09:38.185616Z",
@@ -108,8 +101,54 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "Executing the chatbot graph...\n",
       "Model: Welcome to the Paintrek world. I am a health assistant, an interactive clinical recording system. I will ask you questions about your pain and related symptoms and record your responses.  I will then store this information securely. At any time, you can type `q` to quit.\n"
      ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Model: Great!  First, I need some basic information for your medical record.  Please tell me your full name, date of birth, gender, and contact number.  Also, please provide an emergency contact name and number.\n",
+      "Model: Please provide your full name, date of birth, gender, and contact number.  Also, please provide an emergency contact name and number.  This information is essential to begin your intake.\n",
+      "Model: Thank you. Now, can you describe your main symptom or reason for seeking medical attention today?  And how long have you been experiencing this?\n",
+      "Model: Okay.  Let's move on to a pain assessment.  To help me understand your headache, can you tell me where exactly you feel the pain?  Is it on the left, right, or both sides? And on a scale of 0 to 10, with 0 being no pain and 10 being the worst pain imaginable, how intense is the pain right now?\n",
+      "\n",
+      "We'll use a body map: head, arms, hands, trunk, legs, feet.  Please indicate the location(s) of your pain.\n",
+      "Model: Please describe the location of your headache (e.g., forehead, temples, back of the head).  Is it on the left, right, or both sides?  And what is the pain intensity on a scale of 0-10?  We need this information to continue with the assessment.\n",
+      "Model: Okay, so you're experiencing pain on the left side of your head, with an intensity of 2 out of 10.  Can you describe the characteristics of the pain?  Is it sharp, dull, throbbing, aching, or something else?  When did the pain start?  Does it radiate to any other areas?  Are there any triggers that make it worse or better?  Are there any other symptoms associated with the headache, such as nausea, vomiting, or visual disturbances?\n",
+      "Model: To continue, please describe the characteristics of your headache (sharp, dull, throbbing, etc.), when it started, if it radiates, any triggers, and any associated symptoms (nausea, vomiting, visual disturbances, etc.).  This information is crucial for a proper assessment.\n",
+      "Model: Understood.  Let's summarize what we have so far:\n",
+      "\n",
+      "*   **Patient:** Frank\n",
+      "*   **DOB:** 1986-01-01\n",
+      "*   **Main Symptom:** Headache on the left side of the head, sharp pain, intensity 2/10.\n",
+      "*   **Duration:** 2 days\n",
+      "*   **Triggers:** Cold temperatures seem to worsen the pain.\n",
+      "*   **Associated Symptoms:** None reported.\n",
+      "\n",
+      "Is this information correct so far?\n",
+      "Model: Great. Now, let's proceed with your medical history.  Do you have any existing medical conditions?  If so, please list them and when they were first diagnosed.  Do you have any known allergies?  Have you had any surgeries in the past?  If so, please specify the dates and types of surgeries.  What medications are you currently taking, including over-the-counter medications?\n"
+     ]
+    },
+    {
+     "ename": "NotImplementedError",
+     "evalue": "Unknown tool call: add_to_data",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mNotImplementedError\u001b[0m                       Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[6], line 11\u001b[0m\n\u001b[1;32m      9\u001b[0m \u001b[38;5;66;03m# Ensure messages print immediately\u001b[39;00m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExecuting the chatbot graph...\u001b[39m\u001b[38;5;124m\"\u001b[39m, flush\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m)\n\u001b[0;32m---> 11\u001b[0m state \u001b[38;5;241m=\u001b[39m graph_with_order_tools\u001b[38;5;241m.\u001b[39minvoke({\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mmessages\u001b[39m\u001b[38;5;124m\"\u001b[39m: []}, config)\n\u001b[1;32m     12\u001b[0m display(state)  \u001b[38;5;66;03m# Ensures state is shown in Jupyter\u001b[39;00m\n\u001b[1;32m     13\u001b[0m sys\u001b[38;5;241m.\u001b[39mstdout\u001b[38;5;241m.\u001b[39mflush()\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/pregel/__init__.py:1961\u001b[0m, in \u001b[0;36mPregel.invoke\u001b[0;34m(self, input, config, stream_mode, output_keys, interrupt_before, interrupt_after, debug, **kwargs)\u001b[0m\n\u001b[1;32m   1959\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1960\u001b[0m     chunks \u001b[38;5;241m=\u001b[39m []\n\u001b[0;32m-> 1961\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream(\n\u001b[1;32m   1962\u001b[0m     \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m   1963\u001b[0m     config,\n\u001b[1;32m   1964\u001b[0m     stream_mode\u001b[38;5;241m=\u001b[39mstream_mode,\n\u001b[1;32m   1965\u001b[0m     output_keys\u001b[38;5;241m=\u001b[39moutput_keys,\n\u001b[1;32m   1966\u001b[0m     interrupt_before\u001b[38;5;241m=\u001b[39minterrupt_before,\n\u001b[1;32m   1967\u001b[0m     interrupt_after\u001b[38;5;241m=\u001b[39minterrupt_after,\n\u001b[1;32m   1968\u001b[0m     debug\u001b[38;5;241m=\u001b[39mdebug,\n\u001b[1;32m   1969\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m   1970\u001b[0m ):\n\u001b[1;32m   1971\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m stream_mode \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mvalues\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m   1972\u001b[0m         latest \u001b[38;5;241m=\u001b[39m chunk\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/pregel/__init__.py:1670\u001b[0m, in \u001b[0;36mPregel.stream\u001b[0;34m(self, input, config, stream_mode, output_keys, interrupt_before, interrupt_after, debug, subgraphs)\u001b[0m\n\u001b[1;32m   1664\u001b[0m     \u001b[38;5;66;03m# Similarly to Bulk Synchronous Parallel / Pregel model\u001b[39;00m\n\u001b[1;32m   1665\u001b[0m     \u001b[38;5;66;03m# computation proceeds in steps, while there are channel updates.\u001b[39;00m\n\u001b[1;32m   1666\u001b[0m     \u001b[38;5;66;03m# Channel updates from step N are only visible in step N+1\u001b[39;00m\n\u001b[1;32m   1667\u001b[0m     \u001b[38;5;66;03m# channels are guaranteed to be immutable for the duration of the step,\u001b[39;00m\n\u001b[1;32m   1668\u001b[0m     \u001b[38;5;66;03m# with channel updates applied only at the transition between steps.\u001b[39;00m\n\u001b[1;32m   1669\u001b[0m     \u001b[38;5;28;01mwhile\u001b[39;00m loop\u001b[38;5;241m.\u001b[39mtick(input_keys\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39minput_channels):\n\u001b[0;32m-> 1670\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m _ \u001b[38;5;129;01min\u001b[39;00m runner\u001b[38;5;241m.\u001b[39mtick(\n\u001b[1;32m   1671\u001b[0m             loop\u001b[38;5;241m.\u001b[39mtasks\u001b[38;5;241m.\u001b[39mvalues(),\n\u001b[1;32m   1672\u001b[0m             timeout\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstep_timeout,\n\u001b[1;32m   1673\u001b[0m             retry_policy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mretry_policy,\n\u001b[1;32m   1674\u001b[0m             get_waiter\u001b[38;5;241m=\u001b[39mget_waiter,\n\u001b[1;32m   1675\u001b[0m         ):\n\u001b[1;32m   1676\u001b[0m             \u001b[38;5;66;03m# emit output\u001b[39;00m\n\u001b[1;32m   1677\u001b[0m             \u001b[38;5;28;01myield from\u001b[39;00m output()\n\u001b[1;32m   1678\u001b[0m \u001b[38;5;66;03m# emit output\u001b[39;00m\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/pregel/runner.py:230\u001b[0m, in \u001b[0;36mPregelRunner.tick\u001b[0;34m(self, tasks, reraise, timeout, retry_policy, get_waiter)\u001b[0m\n\u001b[1;32m    228\u001b[0m t \u001b[38;5;241m=\u001b[39m tasks[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m    229\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 230\u001b[0m     run_with_retry(\n\u001b[1;32m    231\u001b[0m         t,\n\u001b[1;32m    232\u001b[0m         retry_policy,\n\u001b[1;32m    233\u001b[0m         configurable\u001b[38;5;241m=\u001b[39m{\n\u001b[1;32m    234\u001b[0m             CONFIG_KEY_SEND: partial(writer, t),\n\u001b[1;32m    235\u001b[0m             CONFIG_KEY_CALL: partial(call, t),\n\u001b[1;32m    236\u001b[0m         },\n\u001b[1;32m    237\u001b[0m     )\n\u001b[1;32m    238\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcommit(t, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[1;32m    239\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m exc:\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/pregel/retry.py:40\u001b[0m, in \u001b[0;36mrun_with_retry\u001b[0;34m(task, retry_policy, configurable)\u001b[0m\n\u001b[1;32m     38\u001b[0m     task\u001b[38;5;241m.\u001b[39mwrites\u001b[38;5;241m.\u001b[39mclear()\n\u001b[1;32m     39\u001b[0m     \u001b[38;5;66;03m# run the task\u001b[39;00m\n\u001b[0;32m---> 40\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m task\u001b[38;5;241m.\u001b[39mproc\u001b[38;5;241m.\u001b[39minvoke(task\u001b[38;5;241m.\u001b[39minput, config)\n\u001b[1;32m     41\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m ParentCommand \u001b[38;5;28;01mas\u001b[39;00m exc:\n\u001b[1;32m     42\u001b[0m     ns: \u001b[38;5;28mstr\u001b[39m \u001b[38;5;241m=\u001b[39m config[CONF][CONFIG_KEY_CHECKPOINT_NS]\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/utils/runnable.py:462\u001b[0m, in \u001b[0;36mRunnableSeq.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    458\u001b[0m config \u001b[38;5;241m=\u001b[39m patch_config(\n\u001b[1;32m    459\u001b[0m     config, callbacks\u001b[38;5;241m=\u001b[39mrun_manager\u001b[38;5;241m.\u001b[39mget_child(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mseq:step:\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mi\u001b[38;5;250m \u001b[39m\u001b[38;5;241m+\u001b[39m\u001b[38;5;250m \u001b[39m\u001b[38;5;241m1\u001b[39m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    460\u001b[0m )\n\u001b[1;32m    461\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m i \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m--> 462\u001b[0m     \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m step\u001b[38;5;241m.\u001b[39minvoke(\u001b[38;5;28minput\u001b[39m, config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    463\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    464\u001b[0m     \u001b[38;5;28minput\u001b[39m \u001b[38;5;241m=\u001b[39m step\u001b[38;5;241m.\u001b[39minvoke(\u001b[38;5;28minput\u001b[39m, config)\n",
+      "File \u001b[0;32m~/miniconda3/envs/paintrekbot/lib/python3.12/site-packages/langgraph/utils/runnable.py:226\u001b[0m, in \u001b[0;36mRunnableCallable.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    224\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    225\u001b[0m     context\u001b[38;5;241m.\u001b[39mrun(_set_config_context, config)\n\u001b[0;32m--> 226\u001b[0m     ret \u001b[38;5;241m=\u001b[39m context\u001b[38;5;241m.\u001b[39mrun(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mfunc, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n\u001b[1;32m    227\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(ret, Runnable) \u001b[38;5;129;01mand\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mrecurse:\n\u001b[1;32m    228\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m ret\u001b[38;5;241m.\u001b[39minvoke(\u001b[38;5;28minput\u001b[39m, config)\n",
+      "File \u001b[0;32m/media/frank-elite/Application/PythonProj/LangGraphExampleResume/modules/tools.py:136\u001b[0m, in \u001b[0;36mdata_node\u001b[0;34m(state)\u001b[0m\n\u001b[1;32m    132\u001b[0m     data_saved \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mTrue\u001b[39;00m\n\u001b[1;32m    133\u001b[0m     \u001b[38;5;66;03m# response = randint(1, 5)  # ETA in minutes\u001b[39;00m\n\u001b[1;32m    134\u001b[0m \n\u001b[1;32m    135\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[0;32m--> 136\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mNotImplementedError\u001b[39;00m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mUnknown tool call: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mtool_call[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mname\u001b[39m\u001b[38;5;124m\"\u001b[39m]\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m    138\u001b[0m \u001b[38;5;66;03m# Record the tool results as tool messages.\u001b[39;00m\n\u001b[1;32m    139\u001b[0m outbound_msgs\u001b[38;5;241m.\u001b[39mappend(\n\u001b[1;32m    140\u001b[0m     ToolMessage(\n\u001b[1;32m    141\u001b[0m         content\u001b[38;5;241m=\u001b[39mresponse,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    144\u001b[0m     )\n\u001b[1;32m    145\u001b[0m )\n",
+      "\u001b[0;31mNotImplementedError\u001b[0m: Unknown tool call: add_to_data",
+      "\u001b[0mDuring task with name 'documenting' and id '88c3029c-c38b-1204-cc25-5e2214e0b1ab'"
+     ]
     }
    ],
    "source": [
@@ -118,14 +157,21 @@
     "config = {\"recursion_limit\": 500}\n",
     "\n",
     "# Uncomment this line to execute the graph:\n",
+    "# Clear output before running new states\n",
+    "clear_output(wait=True)\n",
+    "\n",
+    "# Ensure messages print immediately\n",
+    "print(\"Executing the chatbot graph...\", flush=True)\n",
     "state = graph_with_order_tools.invoke({\"messages\": []}, config)\n",
+    "display(state)  # Ensures state is shown in Jupyter\n",
+    "sys.stdout.flush()\n",
     "\n",
     "# pprint(state)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {
     "trusted": true
    },
@@ -134,16 +180,16 @@
      "data": {
       "text/plain": [
        "{'ID': {'name': 'Frank',\n",
-       "  'DOB': '1990-01-01',\n",
+       "  'DOB': '1986-01-01',\n",
        "  'gender': 'male',\n",
-       "  'contact': '123 Main St',\n",
-       "  'emergency_contact': 'Jane Smith'},\n",
+       "  'contact': '12345',\n",
+       "  'emergency_contact': 'Zoe, 67890'},\n",
        " 'symptom': {'main_symptom': 'headache',\n",
        "  'length': '',\n",
-       "  'symptom_length': '2 weeks'}}"
+       "  'symptom_length': 'a week'}}"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }