diff --git "a/Modules/PoseEstimation/pose_estimation.ipynb" "b/Modules/PoseEstimation/pose_estimation.ipynb"
--- "a/Modules/PoseEstimation/pose_estimation.ipynb"
+++ "b/Modules/PoseEstimation/pose_estimation.ipynb"
@@ -2,9 +2,18 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 22,
+   "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/theorousseaux/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
+      "  warnings.warn(\n"
+     ]
+    }
+   ],
    "source": [
     "from ultralytics import YOLO\n",
     "import numpy as np"
@@ -12,7 +21,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -38,13 +47,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
     "model = YOLO('yolov8n-pose.pt')\n",
     "\n",
-    "def get_keypoints_from_keypoints(model, video_path):\n",
+    "def get_keypoints_from_keypoints(video_path, model=YOLO('yolov8n-pose.pt')):\n",
     "\n",
     "    keypoints = []\n",
     "    results = model(video_path, save=True, show_conf=False, show_boxes=False)\n",
@@ -56,7 +65,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -74,414 +83,428 @@
       "        boxes = r.boxes  # Boxes object for bbox outputs\n",
       "        masks = r.masks  # Masks object for segment masks outputs\n",
       "        probs = r.probs  # Class probabilities for classification outputs\n",
-      "\n",
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-      "video 1/1 (frame 2/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 269.2ms\n",
-      "video 1/1 (frame 3/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 137.3ms\n",
-      "video 1/1 (frame 4/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 177.4ms\n",
-      "video 1/1 (frame 5/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 156.0ms\n",
-      "video 1/1 (frame 6/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 182.3ms\n",
-      "video 1/1 (frame 7/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 187.9ms\n",
-      "video 1/1 (frame 8/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 326.9ms\n",
-      "video 1/1 (frame 9/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 194.0ms\n",
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-      "Speed: 7.5ms preprocess, 156.2ms inference, 1.5ms postprocess per image at shape (1, 3, 640, 576)\n",
-      "Results saved to \u001b[1m/Users/theorousseaux/Documents/Hackathon/FitnessEquation/runs/pose/predict\u001b[0m\n"
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Users/theorousseaux/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/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"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
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+      "video 1/1 (frame 396/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 120.3ms\n",
+      "video 1/1 (frame 397/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 120.0ms\n",
+      "video 1/1 (frame 398/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 157.0ms\n",
+      "video 1/1 (frame 399/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 112.3ms\n",
+      "video 1/1 (frame 400/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 142.3ms\n",
+      "video 1/1 (frame 401/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 145.3ms\n",
+      "video 1/1 (frame 402/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 126.9ms\n",
+      "video 1/1 (frame 403/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 130.2ms\n",
+      "video 1/1 (frame 404/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 139.4ms\n",
+      "video 1/1 (frame 405/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 115.2ms\n",
+      "Speed: 6.9ms preprocess, 162.9ms inference, 6.5ms postprocess per image at shape (1, 3, 640, 576)\n",
+      "Results saved to \u001b[1m/Users/theorousseaux/Documents/Hackathon/FitnessEquation/runs/pose/predict5\u001b[0m\n"
      ]
     }
    ],
@@ -491,7 +514,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 32,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -579,7 +602,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 33,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -593,16 +616,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "[<matplotlib.lines.Line2D at 0x12f346820>]"
+       "[<matplotlib.lines.Line2D at 0x1363b3be0>]"
       ]
      },
-     "execution_count": 34,
+     "execution_count": 7,
      "metadata": {},
      "output_type": "execute_result"
     },
@@ -622,6 +645,773 @@
     "\n",
     "plt.plot(angles)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "AIMessage(content=\"Who's there?\\n\\n(Please provide the next line of the knock-knock joke.)\", response_metadata={'token_usage': {'prompt_tokens': 5, 'total_tokens': 26, 'completion_tokens': 21}, 'model': 'mistral-large-latest', 'finish_reason': 'stop'}, id='run-f72f8b00-6073-439e-9b82-cc50101f0809-0')"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from langchain_core.messages import HumanMessage\n",
+    "from langchain_mistralai.chat_models import ChatMistralAI\n",
+    "\n",
+    "# If api_key is not passed, default behavior is to use the `MISTRAL_API_KEY` environment variable.\n",
+    "llm = ChatMistralAI(model='mistral-large-latest', api_key=\"i5jSJkCFNGKfgIztloxTMjfckiFbYBj4\")\n",
+    "messages = [HumanMessage(content=\"knock knock\")]\n",
+    "llm.invoke(messages)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 83,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Import things that are needed generically\n",
+    "from langchain.pydantic_v1 import BaseModel, Field\n",
+    "from langchain.tools import tool\n",
+    "\n",
+    "@tool\n",
+    "def compute_right_knee_angle(pose: list) -> float:\n",
+    "\n",
+    "    \"\"\"\n",
+    "    Computes the knee angle.\n",
+    "\n",
+    "    Args:\n",
+    "        pose (list): list of keypoints\n",
+    "\n",
+    "    Returns:\n",
+    "        knee_angle (float): knee angle\n",
+    "    \"\"\"\n",
+    "\n",
+    "    right_hip = pose[joints_id_dict['right_hip']]\n",
+    "    right_knee = pose[joints_id_dict['right_knee']]\n",
+    "    right_ankle = pose[joints_id_dict['right_ankle']]\n",
+    "\n",
+    "    knee_angle = calculate_angle(right_hip, right_knee, right_ankle)\n",
+    "\n",
+    "    print(knee_angle)\n",
+    "\n",
+    "    return str(knee_angle)\n",
+    "\n",
+    "@tool\n",
+    "def get_keypoints_from_path(video_path: str):\n",
+    "    \"\"\"\n",
+    "    Get keypoints from a video.\n",
+    "\n",
+    "    Args:\n",
+    "        video_path (str): path to the video\n",
+    "        model (YOLO): model to use\n",
+    "\n",
+    "    Returns:\n",
+    "        keypoints (list): list of keypoints\n",
+    "    \"\"\"\n",
+    "\n",
+    "    keypoints = []\n",
+    "    results = model(video_path, save=True, show_conf=False, show_boxes=False)\n",
+    "    for frame in results:\n",
+    "        tensor = frame.keypoints.xy[0]\n",
+    "        keypoints.append(tensor.tolist())\n",
+    "\n",
+    "    return keypoints"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 84,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "WARNING ⚠️ inference results will accumulate in RAM unless `stream=True` is passed, causing potential out-of-memory\n",
+      "errors for large sources or long-running streams and videos. See https://docs.ultralytics.com/modes/predict/ for help.\n",
+      "\n",
+      "Example:\n",
+      "    results = model(source=..., stream=True)  # generator of Results objects\n",
+      "    for r in results:\n",
+      "        boxes = r.boxes  # Boxes object for bbox outputs\n",
+      "        masks = r.masks  # Masks object for segment masks outputs\n",
+      "        probs = r.probs  # Class probabilities for classification outputs\n",
+      "\n",
+      "video 1/1 (frame 1/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 140.3ms\n",
+      "video 1/1 (frame 2/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 160.4ms\n",
+      "video 1/1 (frame 3/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 222.3ms\n",
+      "video 1/1 (frame 4/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 156.6ms\n",
+      "video 1/1 (frame 5/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 190.2ms\n",
+      "video 1/1 (frame 6/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 190.0ms\n",
+      "video 1/1 (frame 7/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 166.8ms\n",
+      "video 1/1 (frame 8/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 187.1ms\n",
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+      "video 1/1 (frame 383/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 140.6ms\n",
+      "video 1/1 (frame 384/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 161.2ms\n",
+      "video 1/1 (frame 385/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 138.9ms\n",
+      "video 1/1 (frame 386/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 144.6ms\n",
+      "video 1/1 (frame 387/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 130.0ms\n",
+      "video 1/1 (frame 388/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 150.8ms\n",
+      "video 1/1 (frame 389/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 134.0ms\n",
+      "video 1/1 (frame 390/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 131.6ms\n",
+      "video 1/1 (frame 391/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 162.0ms\n",
+      "video 1/1 (frame 392/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 134.1ms\n",
+      "video 1/1 (frame 393/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 141.6ms\n",
+      "video 1/1 (frame 394/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 238.5ms\n",
+      "video 1/1 (frame 395/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 158.1ms\n",
+      "video 1/1 (frame 396/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 121.8ms\n",
+      "video 1/1 (frame 397/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 396.2ms\n",
+      "video 1/1 (frame 398/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 463.3ms\n",
+      "video 1/1 (frame 399/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 278.9ms\n",
+      "video 1/1 (frame 400/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 211.4ms\n",
+      "video 1/1 (frame 401/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 163.1ms\n",
+      "video 1/1 (frame 402/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 163.2ms\n",
+      "video 1/1 (frame 403/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 125.6ms\n",
+      "video 1/1 (frame 404/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 163.0ms\n",
+      "video 1/1 (frame 405/465) /Users/theorousseaux/Documents/Hackathon/FitnessEquation/Modules/PoseEstimation/../../data/pose/squat.mp4: 640x576 1 person, 162.2ms\n",
+      "Speed: 6.6ms preprocess, 152.9ms inference, 1.3ms postprocess per image at shape (1, 3, 640, 576)\n",
+      "Results saved to \u001b[1m/Users/theorousseaux/Documents/Hackathon/FitnessEquation/runs/pose/predict5\u001b[0m\n"
+     ]
+    }
+   ],
+   "source": [
+    "sequence = get_keypoints_from_path('../../data/pose/squat.mp4')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "compute_right_knee_angle\n",
+      "compute_right_knee_angle(pose: list) -> float - Computes the knee angle.\n",
+      "\n",
+      "    Args:\n",
+      "        pose (list): list of keypoints\n",
+      "\n",
+      "    Returns:\n",
+      "        knee_angle (float): knee angle\n",
+      "{'pose': {'title': 'Pose', 'type': 'array', 'items': {}}}\n",
+      "False\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(compute_right_knee_angle.name)\n",
+    "print(compute_right_knee_angle.description)\n",
+    "print(compute_right_knee_angle.args)\n",
+    "print(compute_right_knee_angle.return_direct)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 85,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.agents import AgentExecutor, create_tool_calling_agent\n",
+    "from langchain_community.tools.tavily_search import TavilySearchResults\n",
+    "from langchain_core.prompts import ChatPromptTemplate\n",
+    "\n",
+    "tools = [compute_right_knee_angle]\n",
+    "\n",
+    "prompt = ChatPromptTemplate.from_messages(\n",
+    "    [\n",
+    "        (\n",
+    "            \"system\",\n",
+    "            \"You are a helpful assistant. Make sure to use the compute_right_knee_angle tool for information.\",\n",
+    "        ),\n",
+    "        (\"placeholder\", \"{chat_history}\"),\n",
+    "        (\"human\", \"{input}\"),\n",
+    "        (\"placeholder\", \"{agent_scratchpad}\"),\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "# Construct the Tools agent\n",
+    "agent = create_tool_calling_agent(llm, tools, prompt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 91,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n",
+      "\u001b[32;1m\u001b[1;3m\n",
+      "Invoking: `compute_right_knee_angle` with `{'pose': [[705.0933227539062, 159.55224609375], [0.0, 0.0], [688.4795532226562, 135.9303436279297], [0.0, 0.0], [628.56689453125, 150.44094848632812], [603.4036254882812, 295.99420166015625], [619.6266479492188, 305.51202392578125], [0.0, 0.0], [629.2274780273438, 532.8370361328125], [0.0, 0.0], [665.978515625, 716.4405517578125], [634.9310302734375, 684.9545288085938], [642.503173828125, 691.6080932617188], [633.3930053710938, 1001.8157958984375], [649.4693603515625, 1014.472900390625], [601.3526611328125, 1321.026123046875], [580.6210327148438, 1337.936279296875]]}`\n",
+      "\n",
+      "\n",
+      "\u001b[0m166.748027626137\n",
+      "\u001b[36;1m\u001b[1;3m166.748027626137\u001b[0m\u001b[32;1m\u001b[1;3mThe knee angle at the beginning is approximately 166.75 degrees.\u001b[0m\n",
+      "\n",
+      "\u001b[1m> Finished chain.\u001b[0m\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "{'input': 'Compute my knee angle at the beginning: [[705.0933227539062, 159.55224609375], [0.0, 0.0], [688.4795532226562, 135.9303436279297], [0.0, 0.0], [628.56689453125, 150.44094848632812], [603.4036254882812, 295.99420166015625], [619.6266479492188, 305.51202392578125], [0.0, 0.0], [629.2274780273438, 532.8370361328125], [0.0, 0.0], [665.978515625, 716.4405517578125], [634.9310302734375, 684.9545288085938], [642.503173828125, 691.6080932617188], [633.3930053710938, 1001.8157958984375], [649.4693603515625, 1014.472900390625], [601.3526611328125, 1321.026123046875], [580.6210327148438, 1337.936279296875]]',\n",
+       " 'output': 'The knee angle at the beginning is approximately 166.75 degrees.'}"
+      ]
+     },
+     "execution_count": 91,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "# Create an agent executor by passing in the agent and tools\n",
+    "agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True)\n",
+    "agent_executor.invoke({\"input\": f\"Compute my knee angle at the beginning: {sequence[0]}\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain import hub\n",
+    "from langchain.agents import AgentExecutor, create_json_chat_agent\n",
+    "from langchain_community.tools.tavily_search import TavilySearchResults\n",
+    "\n",
+    "\n",
+    "tools = [compute_right_knee_angle]\n",
+    "\n",
+    "# Get the prompt to use - you can modify this!\n",
+    "prompt = hub.pull(\"hwchase17/react-chat-json\")\n",
+    "\n",
+    "# Construct the JSON agent\n",
+    "agent = create_json_chat_agent(llm, tools, prompt)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Create an agent executor by passing in the agent and tools\n",
+    "agent_executor = AgentExecutor(\n",
+    "    agent=agent, tools=tools, verbose=True, handle_parsing_errors=False\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Parameter `stop` not yet supported (https://docs.mistral.ai/api)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n"
+     ]
+    },
+    {
+     "ename": "SSEError",
+     "evalue": "Expected response header Content-Type to contain 'text/event-stream', got 'application/json'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mSSEError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[51], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43magent_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minput\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mHi, is my squat correct ? \u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mkeypoints\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/chains/base.py:163\u001b[0m, in \u001b[0;36mChain.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    162\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_chain_error(e)\n\u001b[0;32m--> 163\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m    164\u001b[0m run_manager\u001b[38;5;241m.\u001b[39mon_chain_end(outputs)\n\u001b[1;32m    166\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m include_run_info:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/chains/base.py:153\u001b[0m, in \u001b[0;36mChain.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    150\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    151\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_inputs(inputs)\n\u001b[1;32m    152\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 153\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    154\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m new_arg_supported\n\u001b[1;32m    155\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call(inputs)\n\u001b[1;32m    156\u001b[0m     )\n\u001b[1;32m    158\u001b[0m     final_outputs: Dict[\u001b[38;5;28mstr\u001b[39m, Any] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprep_outputs(\n\u001b[1;32m    159\u001b[0m         inputs, outputs, return_only_outputs\n\u001b[1;32m    160\u001b[0m     )\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1432\u001b[0m, in \u001b[0;36mAgentExecutor._call\u001b[0;34m(self, inputs, run_manager)\u001b[0m\n\u001b[1;32m   1430\u001b[0m \u001b[38;5;66;03m# We now enter the agent loop (until it returns something).\u001b[39;00m\n\u001b[1;32m   1431\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_continue(iterations, time_elapsed):\n\u001b[0;32m-> 1432\u001b[0m     next_step_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_take_next_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1433\u001b[0m \u001b[43m        \u001b[49m\u001b[43mname_to_tool_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1434\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcolor_mapping\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1435\u001b[0m \u001b[43m        \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1436\u001b[0m \u001b[43m        \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1437\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1438\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1439\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(next_step_output, AgentFinish):\n\u001b[1;32m   1440\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_return(\n\u001b[1;32m   1441\u001b[0m             next_step_output, intermediate_steps, run_manager\u001b[38;5;241m=\u001b[39mrun_manager\n\u001b[1;32m   1442\u001b[0m         )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1138\u001b[0m, in \u001b[0;36mAgentExecutor._take_next_step\u001b[0;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[1;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[1;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[1;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[0;32m-> 1138\u001b[0m         [\n\u001b[1;32m   1139\u001b[0m             a\n\u001b[1;32m   1140\u001b[0m             \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iter_next_step(\n\u001b[1;32m   1141\u001b[0m                 name_to_tool_map,\n\u001b[1;32m   1142\u001b[0m                 color_mapping,\n\u001b[1;32m   1143\u001b[0m                 inputs,\n\u001b[1;32m   1144\u001b[0m                 intermediate_steps,\n\u001b[1;32m   1145\u001b[0m                 run_manager,\n\u001b[1;32m   1146\u001b[0m             )\n\u001b[1;32m   1147\u001b[0m         ]\n\u001b[1;32m   1148\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1138\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[1;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[1;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[0;32m-> 1138\u001b[0m         [\n\u001b[1;32m   1139\u001b[0m             a\n\u001b[1;32m   1140\u001b[0m             \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iter_next_step(\n\u001b[1;32m   1141\u001b[0m                 name_to_tool_map,\n\u001b[1;32m   1142\u001b[0m                 color_mapping,\n\u001b[1;32m   1143\u001b[0m                 inputs,\n\u001b[1;32m   1144\u001b[0m                 intermediate_steps,\n\u001b[1;32m   1145\u001b[0m                 run_manager,\n\u001b[1;32m   1146\u001b[0m             )\n\u001b[1;32m   1147\u001b[0m         ]\n\u001b[1;32m   1148\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1166\u001b[0m, in \u001b[0;36mAgentExecutor._iter_next_step\u001b[0;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[1;32m   1163\u001b[0m     intermediate_steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_intermediate_steps(intermediate_steps)\n\u001b[1;32m   1165\u001b[0m     \u001b[38;5;66;03m# Call the LLM to see what to do.\u001b[39;00m\n\u001b[0;32m-> 1166\u001b[0m     output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplan\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1167\u001b[0m \u001b[43m        \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1168\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1169\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1170\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1171\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m OutputParserException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m   1172\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_parsing_errors, \u001b[38;5;28mbool\u001b[39m):\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:397\u001b[0m, in \u001b[0;36mRunnableAgent.plan\u001b[0;34m(self, intermediate_steps, callbacks, **kwargs)\u001b[0m\n\u001b[1;32m    389\u001b[0m final_output: Any \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    390\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream_runnable:\n\u001b[1;32m    391\u001b[0m     \u001b[38;5;66;03m# Use streaming to make sure that the underlying LLM is invoked in a\u001b[39;00m\n\u001b[1;32m    392\u001b[0m     \u001b[38;5;66;03m# streaming\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    395\u001b[0m     \u001b[38;5;66;03m# Because the response from the plan is not a generator, we need to\u001b[39;00m\n\u001b[1;32m    396\u001b[0m     \u001b[38;5;66;03m# accumulate the output into final output and return that.\u001b[39;00m\n\u001b[0;32m--> 397\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[39mrunnable\u001b[38;5;241m.\u001b[39mstream(inputs, config\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcallbacks\u001b[39m\u001b[38;5;124m\"\u001b[39m: callbacks}):\n\u001b[1;32m    398\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m final_output \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    399\u001b[0m             final_output \u001b[38;5;241m=\u001b[39m chunk\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2875\u001b[0m, in \u001b[0;36mRunnableSequence.stream\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2869\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstream\u001b[39m(\n\u001b[1;32m   2870\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   2871\u001b[0m     \u001b[38;5;28minput\u001b[39m: Input,\n\u001b[1;32m   2872\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   2873\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[1;32m   2874\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 2875\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtransform(\u001b[38;5;28miter\u001b[39m([\u001b[38;5;28minput\u001b[39m]), config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2862\u001b[0m, in \u001b[0;36mRunnableSequence.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2856\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[1;32m   2857\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   2858\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[1;32m   2859\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   2860\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[1;32m   2861\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 2862\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_stream_with_config(\n\u001b[1;32m   2863\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m   2864\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform,\n\u001b[1;32m   2865\u001b[0m         patch_config(config, run_name\u001b[38;5;241m=\u001b[39m(config \u001b[38;5;129;01mor\u001b[39;00m {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_name\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname),\n\u001b[1;32m   2866\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m   2867\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1880\u001b[0m, in \u001b[0;36mRunnable._transform_stream_with_config\u001b[0;34m(self, input, transformer, config, run_type, **kwargs)\u001b[0m\n\u001b[1;32m   1878\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1879\u001b[0m     \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m-> 1880\u001b[0m         chunk: Output \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m   1881\u001b[0m         \u001b[38;5;28;01myield\u001b[39;00m chunk\n\u001b[1;32m   1882\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m final_output_supported:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2826\u001b[0m, in \u001b[0;36mRunnableSequence._transform\u001b[0;34m(self, input, run_manager, config)\u001b[0m\n\u001b[1;32m   2817\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step \u001b[38;5;129;01min\u001b[39;00m steps:\n\u001b[1;32m   2818\u001b[0m     final_pipeline \u001b[38;5;241m=\u001b[39m step\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[1;32m   2819\u001b[0m         final_pipeline,\n\u001b[1;32m   2820\u001b[0m         patch_config(\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2823\u001b[0m         ),\n\u001b[1;32m   2824\u001b[0m     )\n\u001b[0;32m-> 2826\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m output \u001b[38;5;129;01min\u001b[39;00m final_pipeline:\n\u001b[1;32m   2827\u001b[0m     \u001b[38;5;28;01myield\u001b[39;00m output\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1283\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   1280\u001b[0m final: Input\n\u001b[1;32m   1281\u001b[0m got_first_val \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m-> 1283\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28minput\u001b[39m:\n\u001b[1;32m   1284\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m got_first_val:\n\u001b[1;32m   1285\u001b[0m         final \u001b[38;5;241m=\u001b[39m adapt_first_streaming_chunk(chunk)  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:4728\u001b[0m, in \u001b[0;36mRunnableBindingBase.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   4722\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[1;32m   4723\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   4724\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[1;32m   4725\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   4726\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m   4727\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 4728\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbound\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[1;32m   4729\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m   4730\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_merge_configs(config),\n\u001b[1;32m   4731\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs},\n\u001b[1;32m   4732\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1300\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   1293\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m   1294\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed while trying to add together \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1295\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtype \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(final)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(chunk)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1296\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThese types should be addable for transform to work.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1297\u001b[0m             )\n\u001b[1;32m   1299\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m got_first_val:\n\u001b[0;32m-> 1300\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream(final, config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:249\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    243\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_error(\n\u001b[1;32m    244\u001b[0m         e,\n\u001b[1;32m    245\u001b[0m         response\u001b[38;5;241m=\u001b[39mLLMResult(\n\u001b[1;32m    246\u001b[0m             generations\u001b[38;5;241m=\u001b[39m[[generation]] \u001b[38;5;28;01mif\u001b[39;00m generation \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[1;32m    247\u001b[0m         ),\n\u001b[1;32m    248\u001b[0m     )\n\u001b[0;32m--> 249\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m    250\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    251\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_end(LLMResult(generations\u001b[38;5;241m=\u001b[39m[[generation]]))\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:229\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    227\u001b[0m generation: Optional[ChatGenerationChunk] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    228\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 229\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[39m_stream(messages, stop\u001b[38;5;241m=\u001b[39mstop, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    230\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m chunk\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mid \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    231\u001b[0m             chunk\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mid \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun-\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mrun_manager\u001b[38;5;241m.\u001b[39mrun_id\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_mistralai/chat_models.py:428\u001b[0m, in \u001b[0;36mChatMistralAI._stream\u001b[0;34m(self, messages, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m    425\u001b[0m params \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mTrue\u001b[39;00m}\n\u001b[1;32m    427\u001b[0m default_chunk_class: Type[BaseMessageChunk] \u001b[38;5;241m=\u001b[39m AIMessageChunk\n\u001b[0;32m--> 428\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[39mcompletion_with_retry(\n\u001b[1;32m    429\u001b[0m     messages\u001b[38;5;241m=\u001b[39mmessage_dicts, run_manager\u001b[38;5;241m=\u001b[39mrun_manager, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\n\u001b[1;32m    430\u001b[0m ):\n\u001b[1;32m    431\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(chunk[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchoices\u001b[39m\u001b[38;5;124m\"\u001b[39m]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    432\u001b[0m         \u001b[38;5;28;01mcontinue\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_mistralai/chat_models.py:301\u001b[0m, in \u001b[0;36mChatMistralAI.completion_with_retry.<locals>._completion_with_retry.<locals>.iter_sse\u001b[0;34m()\u001b[0m\n\u001b[1;32m    297\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21miter_sse\u001b[39m() \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Dict]:\n\u001b[1;32m    298\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m connect_sse(\n\u001b[1;32m    299\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclient, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPOST\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/chat/completions\u001b[39m\u001b[38;5;124m\"\u001b[39m, json\u001b[38;5;241m=\u001b[39mkwargs\n\u001b[1;32m    300\u001b[0m     ) \u001b[38;5;28;01mas\u001b[39;00m event_source:\n\u001b[0;32m--> 301\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m event \u001b[38;5;129;01min\u001b[39;00m event_source\u001b[38;5;241m.\u001b[39miter_sse():\n\u001b[1;32m    302\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m event\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[DONE]\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    303\u001b[0m                 \u001b[38;5;28;01mreturn\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/httpx_sse/_api.py:28\u001b[0m, in \u001b[0;36mEventSource.iter_sse\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21miter_sse\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[ServerSentEvent]:\n\u001b[0;32m---> 28\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_content_type\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     29\u001b[0m     decoder \u001b[38;5;241m=\u001b[39m SSEDecoder()\n\u001b[1;32m     30\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response\u001b[38;5;241m.\u001b[39miter_lines():\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/httpx_sse/_api.py:18\u001b[0m, in \u001b[0;36mEventSource._check_content_type\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     16\u001b[0m content_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response\u001b[38;5;241m.\u001b[39mheaders\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent-type\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mpartition(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m;\u001b[39m\u001b[38;5;124m\"\u001b[39m)[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext/event-stream\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m content_type:\n\u001b[0;32m---> 18\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m SSEError(\n\u001b[1;32m     19\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpected response header Content-Type to contain \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtext/event-stream\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     20\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgot \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcontent_type\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     21\u001b[0m     )\n",
+      "\u001b[0;31mSSEError\u001b[0m: Expected response header Content-Type to contain 'text/event-stream', got 'application/json'"
+     ]
+    }
+   ],
+   "source": [
+    "agent_executor.invoke({\"input\": f\"Hi, is my squat correct ? {keypoints}\"})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Parameter `stop` not yet supported (https://docs.mistral.ai/api)\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "\n",
+      "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n"
+     ]
+    },
+    {
+     "ename": "SSEError",
+     "evalue": "Expected response header Content-Type to contain 'text/event-stream', got 'application/json'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mSSEError\u001b[0m                                  Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[44], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m input_\u001b[38;5;241m=\u001b[39m\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mIs my squat correct? \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkeypoints\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 2\u001b[0m \u001b[43magent_executor\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43minvoke\u001b[49m\u001b[43m(\u001b[49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43minput\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43minput_\u001b[49m\u001b[43m}\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/chains/base.py:163\u001b[0m, in \u001b[0;36mChain.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    162\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_chain_error(e)\n\u001b[0;32m--> 163\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m    164\u001b[0m run_manager\u001b[38;5;241m.\u001b[39mon_chain_end(outputs)\n\u001b[1;32m    166\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m include_run_info:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/chains/base.py:153\u001b[0m, in \u001b[0;36mChain.invoke\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m    150\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m    151\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_validate_inputs(inputs)\n\u001b[1;32m    152\u001b[0m     outputs \u001b[38;5;241m=\u001b[39m (\n\u001b[0;32m--> 153\u001b[0m         \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    154\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m new_arg_supported\n\u001b[1;32m    155\u001b[0m         \u001b[38;5;28;01melse\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_call(inputs)\n\u001b[1;32m    156\u001b[0m     )\n\u001b[1;32m    158\u001b[0m     final_outputs: Dict[\u001b[38;5;28mstr\u001b[39m, Any] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mprep_outputs(\n\u001b[1;32m    159\u001b[0m         inputs, outputs, return_only_outputs\n\u001b[1;32m    160\u001b[0m     )\n\u001b[1;32m    161\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1432\u001b[0m, in \u001b[0;36mAgentExecutor._call\u001b[0;34m(self, inputs, run_manager)\u001b[0m\n\u001b[1;32m   1430\u001b[0m \u001b[38;5;66;03m# We now enter the agent loop (until it returns something).\u001b[39;00m\n\u001b[1;32m   1431\u001b[0m \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_should_continue(iterations, time_elapsed):\n\u001b[0;32m-> 1432\u001b[0m     next_step_output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_take_next_step\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1433\u001b[0m \u001b[43m        \u001b[49m\u001b[43mname_to_tool_map\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1434\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcolor_mapping\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1435\u001b[0m \u001b[43m        \u001b[49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1436\u001b[0m \u001b[43m        \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1437\u001b[0m \u001b[43m        \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1438\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1439\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(next_step_output, AgentFinish):\n\u001b[1;32m   1440\u001b[0m         \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_return(\n\u001b[1;32m   1441\u001b[0m             next_step_output, intermediate_steps, run_manager\u001b[38;5;241m=\u001b[39mrun_manager\n\u001b[1;32m   1442\u001b[0m         )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1138\u001b[0m, in \u001b[0;36mAgentExecutor._take_next_step\u001b[0;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[1;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[1;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[1;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[0;32m-> 1138\u001b[0m         [\n\u001b[1;32m   1139\u001b[0m             a\n\u001b[1;32m   1140\u001b[0m             \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iter_next_step(\n\u001b[1;32m   1141\u001b[0m                 name_to_tool_map,\n\u001b[1;32m   1142\u001b[0m                 color_mapping,\n\u001b[1;32m   1143\u001b[0m                 inputs,\n\u001b[1;32m   1144\u001b[0m                 intermediate_steps,\n\u001b[1;32m   1145\u001b[0m                 run_manager,\n\u001b[1;32m   1146\u001b[0m             )\n\u001b[1;32m   1147\u001b[0m         ]\n\u001b[1;32m   1148\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1138\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m   1129\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m_take_next_step\u001b[39m(\n\u001b[1;32m   1130\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   1131\u001b[0m     name_to_tool_map: Dict[\u001b[38;5;28mstr\u001b[39m, BaseTool],\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   1135\u001b[0m     run_manager: Optional[CallbackManagerForChainRun] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   1136\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Union[AgentFinish, List[Tuple[AgentAction, \u001b[38;5;28mstr\u001b[39m]]]:\n\u001b[1;32m   1137\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_consume_next_step(\n\u001b[0;32m-> 1138\u001b[0m         [\n\u001b[1;32m   1139\u001b[0m             a\n\u001b[1;32m   1140\u001b[0m             \u001b[38;5;28;01mfor\u001b[39;00m a \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_iter_next_step(\n\u001b[1;32m   1141\u001b[0m                 name_to_tool_map,\n\u001b[1;32m   1142\u001b[0m                 color_mapping,\n\u001b[1;32m   1143\u001b[0m                 inputs,\n\u001b[1;32m   1144\u001b[0m                 intermediate_steps,\n\u001b[1;32m   1145\u001b[0m                 run_manager,\n\u001b[1;32m   1146\u001b[0m             )\n\u001b[1;32m   1147\u001b[0m         ]\n\u001b[1;32m   1148\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:1166\u001b[0m, in \u001b[0;36mAgentExecutor._iter_next_step\u001b[0;34m(self, name_to_tool_map, color_mapping, inputs, intermediate_steps, run_manager)\u001b[0m\n\u001b[1;32m   1163\u001b[0m     intermediate_steps \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_prepare_intermediate_steps(intermediate_steps)\n\u001b[1;32m   1165\u001b[0m     \u001b[38;5;66;03m# Call the LLM to see what to do.\u001b[39;00m\n\u001b[0;32m-> 1166\u001b[0m     output \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43magent\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mplan\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m   1167\u001b[0m \u001b[43m        \u001b[49m\u001b[43mintermediate_steps\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1168\u001b[0m \u001b[43m        \u001b[49m\u001b[43mcallbacks\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrun_manager\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_child\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mif\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mrun_manager\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01melse\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mNone\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m   1169\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43minputs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1170\u001b[0m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   1171\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m OutputParserException \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m   1172\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhandle_parsing_errors, \u001b[38;5;28mbool\u001b[39m):\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain/agents/agent.py:397\u001b[0m, in \u001b[0;36mRunnableAgent.plan\u001b[0;34m(self, intermediate_steps, callbacks, **kwargs)\u001b[0m\n\u001b[1;32m    389\u001b[0m final_output: Any \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    390\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream_runnable:\n\u001b[1;32m    391\u001b[0m     \u001b[38;5;66;03m# Use streaming to make sure that the underlying LLM is invoked in a\u001b[39;00m\n\u001b[1;32m    392\u001b[0m     \u001b[38;5;66;03m# streaming\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    395\u001b[0m     \u001b[38;5;66;03m# Because the response from the plan is not a generator, we need to\u001b[39;00m\n\u001b[1;32m    396\u001b[0m     \u001b[38;5;66;03m# accumulate the output into final output and return that.\u001b[39;00m\n\u001b[0;32m--> 397\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[39mrunnable\u001b[38;5;241m.\u001b[39mstream(inputs, config\u001b[38;5;241m=\u001b[39m{\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcallbacks\u001b[39m\u001b[38;5;124m\"\u001b[39m: callbacks}):\n\u001b[1;32m    398\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m final_output \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    399\u001b[0m             final_output \u001b[38;5;241m=\u001b[39m chunk\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2875\u001b[0m, in \u001b[0;36mRunnableSequence.stream\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2869\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mstream\u001b[39m(\n\u001b[1;32m   2870\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   2871\u001b[0m     \u001b[38;5;28minput\u001b[39m: Input,\n\u001b[1;32m   2872\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   2873\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[1;32m   2874\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 2875\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mtransform(\u001b[38;5;28miter\u001b[39m([\u001b[38;5;28minput\u001b[39m]), config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2862\u001b[0m, in \u001b[0;36mRunnableSequence.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   2856\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[1;32m   2857\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   2858\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[1;32m   2859\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   2860\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Optional[Any],\n\u001b[1;32m   2861\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 2862\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform_stream_with_config(\n\u001b[1;32m   2863\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m   2864\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_transform,\n\u001b[1;32m   2865\u001b[0m         patch_config(config, run_name\u001b[38;5;241m=\u001b[39m(config \u001b[38;5;129;01mor\u001b[39;00m {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun_name\u001b[39m\u001b[38;5;124m\"\u001b[39m) \u001b[38;5;129;01mor\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mname),\n\u001b[1;32m   2866\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs,\n\u001b[1;32m   2867\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1880\u001b[0m, in \u001b[0;36mRunnable._transform_stream_with_config\u001b[0;34m(self, input, transformer, config, run_type, **kwargs)\u001b[0m\n\u001b[1;32m   1878\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[1;32m   1879\u001b[0m     \u001b[38;5;28;01mwhile\u001b[39;00m \u001b[38;5;28;01mTrue\u001b[39;00m:\n\u001b[0;32m-> 1880\u001b[0m         chunk: Output \u001b[38;5;241m=\u001b[39m \u001b[43mcontext\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mnext\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43miterator\u001b[49m\u001b[43m)\u001b[49m  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n\u001b[1;32m   1881\u001b[0m         \u001b[38;5;28;01myield\u001b[39;00m chunk\n\u001b[1;32m   1882\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m final_output_supported:\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:2826\u001b[0m, in \u001b[0;36mRunnableSequence._transform\u001b[0;34m(self, input, run_manager, config)\u001b[0m\n\u001b[1;32m   2817\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m step \u001b[38;5;129;01min\u001b[39;00m steps:\n\u001b[1;32m   2818\u001b[0m     final_pipeline \u001b[38;5;241m=\u001b[39m step\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[1;32m   2819\u001b[0m         final_pipeline,\n\u001b[1;32m   2820\u001b[0m         patch_config(\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m   2823\u001b[0m         ),\n\u001b[1;32m   2824\u001b[0m     )\n\u001b[0;32m-> 2826\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m output \u001b[38;5;129;01min\u001b[39;00m final_pipeline:\n\u001b[1;32m   2827\u001b[0m     \u001b[38;5;28;01myield\u001b[39;00m output\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1283\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   1280\u001b[0m final: Input\n\u001b[1;32m   1281\u001b[0m got_first_val \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m\n\u001b[0;32m-> 1283\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m chunk \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28minput\u001b[39m:\n\u001b[1;32m   1284\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m got_first_val:\n\u001b[1;32m   1285\u001b[0m         final \u001b[38;5;241m=\u001b[39m adapt_first_streaming_chunk(chunk)  \u001b[38;5;66;03m# type: ignore\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:4728\u001b[0m, in \u001b[0;36mRunnableBindingBase.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   4722\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mtransform\u001b[39m(\n\u001b[1;32m   4723\u001b[0m     \u001b[38;5;28mself\u001b[39m,\n\u001b[1;32m   4724\u001b[0m     \u001b[38;5;28minput\u001b[39m: Iterator[Input],\n\u001b[1;32m   4725\u001b[0m     config: Optional[RunnableConfig] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m,\n\u001b[1;32m   4726\u001b[0m     \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs: Any,\n\u001b[1;32m   4727\u001b[0m ) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Output]:\n\u001b[0;32m-> 4728\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbound\u001b[38;5;241m.\u001b[39mtransform(\n\u001b[1;32m   4729\u001b[0m         \u001b[38;5;28minput\u001b[39m,\n\u001b[1;32m   4730\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_merge_configs(config),\n\u001b[1;32m   4731\u001b[0m         \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m{\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mkwargs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs},\n\u001b[1;32m   4732\u001b[0m     )\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/runnables/base.py:1300\u001b[0m, in \u001b[0;36mRunnable.transform\u001b[0;34m(self, input, config, **kwargs)\u001b[0m\n\u001b[1;32m   1293\u001b[0m             \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m   1294\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mFailed while trying to add together \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1295\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtype \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(final)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m and \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;28mtype\u001b[39m(chunk)\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1296\u001b[0m                 \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThese types should be addable for transform to work.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m   1297\u001b[0m             )\n\u001b[1;32m   1299\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m got_first_val:\n\u001b[0;32m-> 1300\u001b[0m     \u001b[38;5;28;01myield from\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstream(final, config, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs)\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:249\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    242\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mBaseException\u001b[39;00m \u001b[38;5;28;01mas\u001b[39;00m e:\n\u001b[1;32m    243\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_error(\n\u001b[1;32m    244\u001b[0m         e,\n\u001b[1;32m    245\u001b[0m         response\u001b[38;5;241m=\u001b[39mLLMResult(\n\u001b[1;32m    246\u001b[0m             generations\u001b[38;5;241m=\u001b[39m[[generation]] \u001b[38;5;28;01mif\u001b[39;00m generation \u001b[38;5;28;01melse\u001b[39;00m []\n\u001b[1;32m    247\u001b[0m         ),\n\u001b[1;32m    248\u001b[0m     )\n\u001b[0;32m--> 249\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m e\n\u001b[1;32m    250\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    251\u001b[0m     run_manager\u001b[38;5;241m.\u001b[39mon_llm_end(LLMResult(generations\u001b[38;5;241m=\u001b[39m[[generation]]))\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_core/language_models/chat_models.py:229\u001b[0m, in \u001b[0;36mBaseChatModel.stream\u001b[0;34m(self, input, config, stop, **kwargs)\u001b[0m\n\u001b[1;32m    227\u001b[0m generation: Optional[ChatGenerationChunk] \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m    228\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 229\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[39m_stream(messages, stop\u001b[38;5;241m=\u001b[39mstop, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[1;32m    230\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m chunk\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mid \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m    231\u001b[0m             chunk\u001b[38;5;241m.\u001b[39mmessage\u001b[38;5;241m.\u001b[39mid \u001b[38;5;241m=\u001b[39m \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mrun-\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mrun_manager\u001b[38;5;241m.\u001b[39mrun_id\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_mistralai/chat_models.py:428\u001b[0m, in \u001b[0;36mChatMistralAI._stream\u001b[0;34m(self, messages, stop, run_manager, **kwargs)\u001b[0m\n\u001b[1;32m    425\u001b[0m params \u001b[38;5;241m=\u001b[39m {\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mstream\u001b[39m\u001b[38;5;124m\"\u001b[39m: \u001b[38;5;28;01mTrue\u001b[39;00m}\n\u001b[1;32m    427\u001b[0m default_chunk_class: Type[BaseMessageChunk] \u001b[38;5;241m=\u001b[39m AIMessageChunk\n\u001b[0;32m--> 428\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[39mcompletion_with_retry(\n\u001b[1;32m    429\u001b[0m     messages\u001b[38;5;241m=\u001b[39mmessage_dicts, run_manager\u001b[38;5;241m=\u001b[39mrun_manager, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mparams\n\u001b[1;32m    430\u001b[0m ):\n\u001b[1;32m    431\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(chunk[\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mchoices\u001b[39m\u001b[38;5;124m\"\u001b[39m]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m    432\u001b[0m         \u001b[38;5;28;01mcontinue\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/langchain_mistralai/chat_models.py:301\u001b[0m, in \u001b[0;36mChatMistralAI.completion_with_retry.<locals>._completion_with_retry.<locals>.iter_sse\u001b[0;34m()\u001b[0m\n\u001b[1;32m    297\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21miter_sse\u001b[39m() \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[Dict]:\n\u001b[1;32m    298\u001b[0m     \u001b[38;5;28;01mwith\u001b[39;00m connect_sse(\n\u001b[1;32m    299\u001b[0m         \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mclient, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mPOST\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m/chat/completions\u001b[39m\u001b[38;5;124m\"\u001b[39m, json\u001b[38;5;241m=\u001b[39mkwargs\n\u001b[1;32m    300\u001b[0m     ) \u001b[38;5;28;01mas\u001b[39;00m event_source:\n\u001b[0;32m--> 301\u001b[0m         \u001b[38;5;28;01mfor\u001b[39;00m event \u001b[38;5;129;01min\u001b[39;00m event_source\u001b[38;5;241m.\u001b[39miter_sse():\n\u001b[1;32m    302\u001b[0m             \u001b[38;5;28;01mif\u001b[39;00m event\u001b[38;5;241m.\u001b[39mdata \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m[DONE]\u001b[39m\u001b[38;5;124m\"\u001b[39m:\n\u001b[1;32m    303\u001b[0m                 \u001b[38;5;28;01mreturn\u001b[39;00m\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/httpx_sse/_api.py:28\u001b[0m, in \u001b[0;36mEventSource.iter_sse\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21miter_sse\u001b[39m(\u001b[38;5;28mself\u001b[39m) \u001b[38;5;241m-\u001b[39m\u001b[38;5;241m>\u001b[39m Iterator[ServerSentEvent]:\n\u001b[0;32m---> 28\u001b[0m     \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_check_content_type\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m     29\u001b[0m     decoder \u001b[38;5;241m=\u001b[39m SSEDecoder()\n\u001b[1;32m     30\u001b[0m     \u001b[38;5;28;01mfor\u001b[39;00m line \u001b[38;5;129;01min\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response\u001b[38;5;241m.\u001b[39miter_lines():\n",
+      "File \u001b[0;32m~/Documents/Hackathon/FitnessEquation/venv/lib/python3.9/site-packages/httpx_sse/_api.py:18\u001b[0m, in \u001b[0;36mEventSource._check_content_type\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m     16\u001b[0m content_type \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_response\u001b[38;5;241m.\u001b[39mheaders\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mcontent-type\u001b[39m\u001b[38;5;124m\"\u001b[39m, \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m\"\u001b[39m)\u001b[38;5;241m.\u001b[39mpartition(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m;\u001b[39m\u001b[38;5;124m\"\u001b[39m)[\u001b[38;5;241m0\u001b[39m]\n\u001b[1;32m     17\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mtext/event-stream\u001b[39m\u001b[38;5;124m\"\u001b[39m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m content_type:\n\u001b[0;32m---> 18\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m SSEError(\n\u001b[1;32m     19\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mExpected response header Content-Type to contain \u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtext/event-stream\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m, \u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     20\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mgot \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mcontent_type\u001b[38;5;132;01m!r}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m     21\u001b[0m     )\n",
+      "\u001b[0;31mSSEError\u001b[0m: Expected response header Content-Type to contain 'text/event-stream', got 'application/json'"
+     ]
+    }
+   ],
+   "source": [
+    "input_=f\"Is my squat correct? {keypoints}\"\n",
+    "agent_executor.invoke({\"input\": input_})"
+   ]
   }
  ],
  "metadata": {