19.langgraph-crypto-agents.ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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    "id": "0iwD_lZEmHHB",
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     "text": [
      "  Preparing metadata (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
      "  Building wheel for pandas_ta (setup.py) ... \u001b[?25l\u001b[?25hdone\n"
     ]
    }
   ],
   "source": [
    "!pip install -Uqqq pip --progress-bar off\n",
    "!pip install -qqq langchain-groq==0.1.9 --progress-bar off\n",
    "!pip install -qqq langgraph==0.2.14 --progress-bar off\n",
    "!pip install -qqq openbb==4.3.1 --progress-bar off\n",
    "!pip install -qqq duckduckgo-search==6.2.11 --progress-bar off\n",
    "!pip install -qqq pandas_ta==0.3.14b --progress-bar off"
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "import sqlite3\n",
    "import textwrap\n",
    "from enum import Enum, auto\n",
    "from typing import Annotated, List, Literal, TypedDict\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import pandas_ta as ta\n",
    "from duckduckgo_search import DDGS\n",
    "from google.colab import userdata\n",
    "from IPython.display import Image, display\n",
    "from langchain_core.messages import HumanMessage\n",
    "from langchain_core.pydantic_v1 import BaseModel, Field\n",
    "from langchain_groq import ChatGroq\n",
    "from langgraph.graph import END, StateGraph\n",
    "from openbb import obb\n",
    "\n",
    "np.random.seed(42)\n",
    "\n",
    "# MODEL = \"llama3-groq-70b-8192-tool-use-preview\"\n",
    "MODEL = \"llama-3.1-70b-versatile\"\n",
    "DB_NAME = \"crypto_gpt.db\"\n",
    "\n",
    "llm = ChatGroq(temperature=0, model_name=MODEL, api_key=userdata.get(\"GROQ_API_KEY\"))\n",
    "obb.account.login(pat=userdata.get(\"OPENBB_API_KEY\"))\n",
    "obb.user.preferences.output_type = \"dataframe\""
   ],
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    "id": "0ZmTfGxWm1qh",
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   },
   "execution_count": 2,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Extensions to add: yfinance@1.3.2\n",
      "Extensions to remove: yfinance@1.3.1\n",
      "\n",
      "Building...\n"
     ]
    }
   ]
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   "cell_type": "markdown",
   "source": [
    "## Save Data"
   ],
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    "id": "ZnnKpaqNlmtL"
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   "source": [
    "def get_connection():\n",
    "    return sqlite3.connect(DB_NAME)\n",
    "\n",
    "\n",
    "db_connection = get_connection()"
   ],
   "metadata": {
    "id": "0TX56q_5g3I-"
   },
   "execution_count": 3,
   "outputs": []
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  {
   "cell_type": "code",
   "source": [
    "money_df = obb.economy.money_measures(start_date=\"2010-01-01\")\n",
    "money_df.month = pd.to_datetime(money_df.month)\n",
    "money_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 241
    },
    "id": "dMu6uwnahFgB",
    "outputId": "b3ddcc23-8c7e-4259-882b-fb4bc38e2adc"
   },
   "execution_count": 4,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stderr",
     "text": [
      "/usr/local/lib/python3.10/dist-packages/openbb_federal_reserve/models/money_measures.py:92: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
      "  df = df.applymap(lambda x: float(x) if x != \"-\" and x is not None else x)\n"
     ]
    },
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     "data": {
      "text/plain": [
       "       month      M1      M2  currency  demand_deposits  \\\n",
       "0 2010-01-01  1674.2  8464.4     860.6            436.0   \n",
       "1 2010-02-01  1685.2  8508.4     869.8            438.4   \n",
       "2 2010-03-01  1729.5  8576.6     875.7            458.8   \n",
       "3 2010-04-01  1716.0  8601.8     879.4            453.4   \n",
       "4 2010-05-01  1708.2  8584.2     882.5            450.5   \n",
       "\n",
       "   retail_money_market_funds  small_denomination_time_deposits  \\\n",
       "0                      796.9                            1163.6   \n",
       "1                      787.3                            1142.3   \n",
       "2                      770.7                            1119.7   \n",
       "3                      747.3                            1097.8   \n",
       "4                      736.4                            1075.0   \n",
       "\n",
       "   other_liquid_deposits  \n",
       "0                    NaN  \n",
       "1                    NaN  \n",
       "2                    NaN  \n",
       "3                    NaN  \n",
       "4                    NaN  "
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      "application/vnd.google.colaboratory.intrinsic+json": {
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       "variable_name": "money_df",
       "summary": "{\n  \"name\": \"money_df\",\n  \"rows\": 175,\n  \"fields\": [\n    {\n      \"column\": \"month\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2010-01-01 00:00:00\",\n        \"max\": \"2024-07-01 00:00:00\",\n        \"num_unique_values\": 175,\n        \"samples\": [\n          \"2023-01-01 00:00:00\",\n          \"2022-02-01 00:00:00\",\n          \"2018-06-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"M1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7321.65905917186,\n        \"min\": 1674.2,\n        \"max\": 20827.0,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          19591.4,\n          20523.9,\n          3656.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"M2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4379.709474735624,\n        \"min\": 8464.4,\n        \"max\": 21860.5,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          21292.3,\n          21584.7,\n          14074.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"currency\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 451.9199279142015,\n        \"min\": 860.6,\n        \"max\": 2264.6,\n        \"num_unique_values\": 173,\n        \"samples\": [\n          2243.1,\n          1134.7,\n          1490.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"demand_deposits\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1617.994934886456,\n        \"min\": 436.0,\n        \"max\": 5242.1,\n        \"num_unique_values\": 172,\n        \"samples\": [\n          1390.2,\n          4602.9,\n          5138.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"retail_money_market_funds\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 292.2784757507677,\n        \"min\": 623.1,\n        \"max\": 1855.2,\n        \"num_unique_values\": 170,\n        \"samples\": [\n          1008.2,\n          650.2,\n          1091.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"small_denomination_time_deposits\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 276.478589185189,\n        \"min\": 38.1,\n        \"max\": 1163.6,\n        \"num_unique_values\": 173,\n        \"samples\": [\n          991.0,\n          586.2,\n          396.2\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"other_liquid_deposits\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1056.6671868422052,\n        \"min\": 10499.8,\n        \"max\": 13783.2,\n        \"num_unique_values\": 51,\n        \"samples\": [\n          10839.1,\n          10993.6,\n          10780.3\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
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     "metadata": {},
     "execution_count": 4
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   "source": [
    "money_df = money_df[[\"month\", \"M1\", \"M2\"]]\n",
    "money_df.columns = [\"date\", \"m1\", \"m2\"]\n",
    "money_df.head()"
   ],
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       "        date      m1      m2\n",
       "0 2010-01-01  1674.2  8464.4\n",
       "1 2010-02-01  1685.2  8508.4\n",
       "2 2010-03-01  1729.5  8576.6\n",
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      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "money_df",
       "summary": "{\n  \"name\": \"money_df\",\n  \"rows\": 175,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2010-01-01 00:00:00\",\n        \"max\": \"2024-07-01 00:00:00\",\n        \"num_unique_values\": 175,\n        \"samples\": [\n          \"2023-01-01 00:00:00\",\n          \"2022-02-01 00:00:00\",\n          \"2018-06-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"m1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7321.65905917186,\n        \"min\": 1674.2,\n        \"max\": 20827.0,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          19591.4,\n          20523.9,\n          3656.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"m2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4379.709474735624,\n        \"min\": 8464.4,\n        \"max\": 21860.5,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          21292.3,\n          21584.7,\n          14074.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 5
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "money_df.to_sql(\"money_supply\", db_connection)"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "r3RO_NX8l4-m",
    "outputId": "42d8285f-34ec-480d-f040-1c3b245b99d8"
   },
   "execution_count": 6,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "175"
      ]
     },
     "metadata": {},
     "execution_count": 6
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "btc_df = obb.crypto.price.historical(symbol=\"BTCUSD\", start_date=\"2010-01-01\")\n",
    "eth_df = obb.crypto.price.historical(symbol=\"ETHUSD\", start_date=\"2010-01-01\")\n",
    "sol_df = obb.crypto.price.historical(symbol=\"SOLUSD\", start_date=\"2010-01-01\")"
   ],
   "metadata": {
    "id": "YpAWj_KurJYx"
   },
   "execution_count": 7,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "btc_df.head()"
   ],
   "metadata": {
    "colab": {
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     "height": 238
    },
    "id": "sV9cTNRGra-I",
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   "execution_count": 8,
   "outputs": [
    {
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       "                  open        high         low       close      volume\n",
       "date                                                                  \n",
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       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
       "        const docLink = document.createElement('div');\n",
       "        docLink.innerHTML = docLinkHtml;\n",
       "        element.appendChild(docLink);\n",
       "      }\n",
       "    </script>\n",
       "  </div>\n",
       "\n",
       "\n",
       "<div id=\"df-5e599cfa-7f4a-42c4-97fa-599ea6d33cce\">\n",
       "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-5e599cfa-7f4a-42c4-97fa-599ea6d33cce')\"\n",
       "            title=\"Suggest charts\"\n",
       "            style=\"display:none;\">\n",
       "\n",
       "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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       "    </g>\n",
       "</svg>\n",
       "  </button>\n",
       "\n",
       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
       "      --fill-color: #1967D2;\n",
       "      --hover-bg-color: #E2EBFA;\n",
       "      --hover-fill-color: #174EA6;\n",
       "      --disabled-fill-color: #AAA;\n",
       "      --disabled-bg-color: #DDD;\n",
       "  }\n",
       "\n",
       "  [theme=dark] .colab-df-quickchart {\n",
       "      --bg-color: #3B4455;\n",
       "      --fill-color: #D2E3FC;\n",
       "      --hover-bg-color: #434B5C;\n",
       "      --hover-fill-color: #FFFFFF;\n",
       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
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       "\n",
       "  .colab-df-quickchart {\n",
       "    background-color: var(--bg-color);\n",
       "    border: none;\n",
       "    border-radius: 50%;\n",
       "    cursor: pointer;\n",
       "    display: none;\n",
       "    fill: var(--fill-color);\n",
       "    height: 32px;\n",
       "    padding: 0;\n",
       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
       "    background-color: var(--hover-bg-color);\n",
       "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
       "    fill: var(--button-hover-fill-color);\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
       "  .colab-df-quickchart-complete:disabled:hover {\n",
       "    background-color: var(--disabled-bg-color);\n",
       "    fill: var(--disabled-fill-color);\n",
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       "  }\n",
       "\n",
       "  .colab-df-spinner {\n",
       "    border: 2px solid var(--fill-color);\n",
       "    border-color: transparent;\n",
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       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
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       "    20% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    30% {\n",
       "      border-color: transparent;\n",
       "      border-left-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    40% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-top-color: var(--fill-color);\n",
       "    }\n",
       "    60% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "  }\n",
       "</style>\n",
       "\n",
       "  <script>\n",
       "    async function quickchart(key) {\n",
       "      const quickchartButtonEl =\n",
       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-5e599cfa-7f4a-42c4-97fa-599ea6d33cce button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "btc_df",
       "summary": "{\n  \"name\": \"btc_df\",\n  \"rows\": 3636,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2014-09-17\",\n        \"max\": \"2024-08-30\",\n        \"num_unique_values\": 3636,\n        \"samples\": [\n          \"2018-03-29\",\n          \"2015-01-15\",\n          \"2017-01-03\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19463.12307858871,\n        \"min\": 176.89700317382812,\n        \"max\": 73079.375,\n        \"num_unique_values\": 3632,\n        \"samples\": [\n          10960.7353515625,\n          30249.626953125,\n          6596.8798828125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19900.601188436125,\n        \"min\": 211.7310028076172,\n        \"max\": 73750.0703125,\n        \"num_unique_values\": 3633,\n        \"samples\": [\n          10353.927734375,\n          264.2439880371094,\n          264.8479919433594\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 18982.551492257797,\n        \"min\": 171.50999450683594,\n        \"max\": 71334.09375,\n        \"num_unique_values\": 3634,\n        \"samples\": [\n          6683.93017578125,\n          176.89700317382812,\n          1044.4000244140625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19471.149987018107,\n        \"min\": 178.10299682617188,\n        \"max\": 73083.5,\n        \"num_unique_values\": 3633,\n        \"samples\": [\n          10280.3515625,\n          260.9280090332031,\n          261.7489929199219\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 19196947748.587482,\n        \"min\": 5914570.0,\n        \"max\": 350967941479.0,\n        \"num_unique_values\": 3636,\n        \"samples\": [\n          6361229824.0,\n          81773504.0,\n          185168000.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 8
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "btc_df[\"date\"] = pd.to_datetime(btc_df.index)\n",
    "btc_df[\"ticker\"] = \"BTC\"\n",
    "\n",
    "eth_df[\"date\"] = pd.to_datetime(eth_df.index)\n",
    "eth_df[\"ticker\"] = \"ETH\"\n",
    "\n",
    "sol_df[\"date\"] = pd.to_datetime(sol_df.index)\n",
    "sol_df[\"ticker\"] = \"SOL\""
   ],
   "metadata": {
    "id": "cZq7yay4t1Sw"
   },
   "execution_count": 9,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "price_df = pd.concat([btc_df, eth_df, sol_df], axis=0).reset_index(drop=True)\n",
    "price_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "LbGu8tVA0KQR",
    "outputId": "ad2424aa-3fe7-4345-ab70-040faccceb6d"
   },
   "execution_count": 10,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "         open        high         low       close      volume       date  \\\n",
       "0  465.864014  468.174011  452.421997  457.334015  21056800.0 2014-09-17   \n",
       "1  456.859985  456.859985  413.104004  424.440002  34483200.0 2014-09-18   \n",
       "2  424.102997  427.834991  384.532013  394.795990  37919700.0 2014-09-19   \n",
       "3  394.673004  423.295990  389.882996  408.903992  36863600.0 2014-09-20   \n",
       "4  408.084991  412.425995  393.181000  398.821014  26580100.0 2014-09-21   \n",
       "\n",
       "  ticker  \n",
       "0    BTC  \n",
       "1    BTC  \n",
       "2    BTC  \n",
       "3    BTC  \n",
       "4    BTC  "
      ],
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
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       "      <th>0</th>\n",
       "      <td>465.864014</td>\n",
       "      <td>468.174011</td>\n",
       "      <td>452.421997</td>\n",
       "      <td>457.334015</td>\n",
       "      <td>21056800.0</td>\n",
       "      <td>2014-09-17</td>\n",
       "      <td>BTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>456.859985</td>\n",
       "      <td>456.859985</td>\n",
       "      <td>413.104004</td>\n",
       "      <td>424.440002</td>\n",
       "      <td>34483200.0</td>\n",
       "      <td>2014-09-18</td>\n",
       "      <td>BTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>424.102997</td>\n",
       "      <td>427.834991</td>\n",
       "      <td>384.532013</td>\n",
       "      <td>394.795990</td>\n",
       "      <td>37919700.0</td>\n",
       "      <td>2014-09-19</td>\n",
       "      <td>BTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>394.673004</td>\n",
       "      <td>423.295990</td>\n",
       "      <td>389.882996</td>\n",
       "      <td>408.903992</td>\n",
       "      <td>36863600.0</td>\n",
       "      <td>2014-09-20</td>\n",
       "      <td>BTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>408.084991</td>\n",
       "      <td>412.425995</td>\n",
       "      <td>393.181000</td>\n",
       "      <td>398.821014</td>\n",
       "      <td>26580100.0</td>\n",
       "      <td>2014-09-21</td>\n",
       "      <td>BTC</td>\n",
       "    </tr>\n",
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       "\n",
       "    [theme=dark] .colab-df-convert:hover {\n",
       "      background-color: #434B5C;\n",
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       "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
       "      fill: #FFFFFF;\n",
       "    }\n",
       "  </style>\n",
       "\n",
       "    <script>\n",
       "      const buttonEl =\n",
       "        document.querySelector('#df-bfe87b42-5bd8-4f46-94f0-4b0ec3030428 button.colab-df-convert');\n",
       "      buttonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "\n",
       "      async function convertToInteractive(key) {\n",
       "        const element = document.querySelector('#df-bfe87b42-5bd8-4f46-94f0-4b0ec3030428');\n",
       "        const dataTable =\n",
       "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
       "                                                    [key], {});\n",
       "        if (!dataTable) return;\n",
       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
       "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
       "          + ' to learn more about interactive tables.';\n",
       "        element.innerHTML = '';\n",
       "        dataTable['output_type'] = 'display_data';\n",
       "        await google.colab.output.renderOutput(dataTable, element);\n",
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       "<style>\n",
       "  .colab-df-quickchart {\n",
       "      --bg-color: #E8F0FE;\n",
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       "\n",
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       "      --disabled-bg-color: #3B4455;\n",
       "      --disabled-fill-color: #666;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart {\n",
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       "    width: 32px;\n",
       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "\n",
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       "\n",
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       "\n",
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       "    0% {\n",
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       "      border-bottom-color: var(--fill-color);\n",
       "      border-left-color: var(--fill-color);\n",
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       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
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       "      border-right-color: var(--fill-color);\n",
       "    }\n",
       "    80% {\n",
       "      border-color: transparent;\n",
       "      border-right-color: var(--fill-color);\n",
       "      border-bottom-color: var(--fill-color);\n",
       "    }\n",
       "    90% {\n",
       "      border-color: transparent;\n",
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       "type": "dataframe",
       "variable_name": "price_df",
       "summary": "{\n  \"name\": \"price_df\",\n  \"rows\": 7727,\n  \"fields\": [\n    {\n      \"column\": \"open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15767.149791757223,\n        \"min\": 0.5133910179138184,\n        \"max\": 73079.375,\n        \"num_unique_values\": 7722,\n        \"samples\": [\n          187.49549865722656,\n          47491.203125,\n          20208.76953125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 16121.896853675375,\n        \"min\": 0.5597590208053589,\n        \"max\": 73750.0703125,\n        \"num_unique_values\": 7723,\n        \"samples\": [\n          193.4421844482422,\n          48745.734375,\n          20382.095703125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15380.608747250611,\n        \"min\": 0.5051940083503723,\n        \"max\": 71334.09375,\n        \"num_unique_values\": 7723,\n        \"samples\": [\n          184.96475219726562,\n          43881.15234375,\n          20359.845703125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15775.63049791046,\n        \"min\": 0.5152729749679565,\n        \"max\": 73083.5,\n        \"num_unique_values\": 7723,\n        \"samples\": [\n          188.92938232421875,\n          47504.8515625,\n          20209.98828125\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15616638196.384483,\n        \"min\": 652020.0,\n        \"max\": 350967941479.0,\n        \"num_unique_values\": 7727,\n        \"samples\": [\n          16159781303.0,\n          24128292755.0,\n          9214950400.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2014-09-17 00:00:00\",\n        \"max\": \"2024-08-30 00:00:00\",\n        \"num_unique_values\": 3636,\n        \"samples\": [\n          \"2018-03-29 00:00:00\",\n          \"2015-01-15 00:00:00\",\n          \"2017-01-03 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ticker\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"BTC\",\n          \"ETH\",\n          \"SOL\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 10
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "price_df = price_df[[\"date\", \"ticker\", \"open\", \"high\", \"low\", \"close\", \"volume\"]]\n",
    "price_df = price_df.sort_values(by=\"date\").reset_index(drop=True)\n",
    "price_df.tail()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "5kkNPAj5yRFs",
    "outputId": "ee6acd29-b5fa-44e1-b7a5-fd0b53e5bc2a"
   },
   "execution_count": 11,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "           date ticker          open          high           low  \\\n",
       "7722 2024-08-29    BTC  59027.468750  61184.082031  58786.226562   \n",
       "7723 2024-08-29    SOL    143.891068    147.220581    138.266068   \n",
       "7724 2024-08-30    BTC  59374.441406  59781.671875  57925.195312   \n",
       "7725 2024-08-30    ETH   2528.342529   2538.271484   2441.317871   \n",
       "7726 2024-08-30    SOL    140.053619    140.997818    132.659454   \n",
       "\n",
       "             close        volume  \n",
       "7722  59388.179688  3.222499e+10  \n",
       "7723    140.054031  2.098252e+09  \n",
       "7724  58859.777344  3.366401e+10  \n",
       "7725   2509.927490  1.597369e+10  \n",
       "7726    136.345306  2.761629e+09  "
      ],
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       "      <th>date</th>\n",
       "      <th>ticker</th>\n",
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       "      <th>7722</th>\n",
       "      <td>2024-08-29</td>\n",
       "      <td>BTC</td>\n",
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       "      <td>61184.082031</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>7723</th>\n",
       "      <td>2024-08-29</td>\n",
       "      <td>SOL</td>\n",
       "      <td>143.891068</td>\n",
       "      <td>147.220581</td>\n",
       "      <td>138.266068</td>\n",
       "      <td>140.054031</td>\n",
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       "      <th>7724</th>\n",
       "      <td>2024-08-30</td>\n",
       "      <td>BTC</td>\n",
       "      <td>59374.441406</td>\n",
       "      <td>59781.671875</td>\n",
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       "    <tr>\n",
       "      <th>7725</th>\n",
       "      <td>2024-08-30</td>\n",
       "      <td>ETH</td>\n",
       "      <td>2528.342529</td>\n",
       "      <td>2538.271484</td>\n",
       "      <td>2441.317871</td>\n",
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       "      <th>7726</th>\n",
       "      <td>2024-08-30</td>\n",
       "      <td>SOL</td>\n",
       "      <td>140.053619</td>\n",
       "      <td>140.997818</td>\n",
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      ],
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "summary": "{\n  \"name\": \"price_df\",\n  \"rows\": 5,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-08-29 00:00:00\",\n        \"max\": \"2024-08-30 00:00:00\",\n        \"num_unique_values\": 2,\n        \"samples\": [\n          \"2024-08-30 00:00:00\",\n          \"2024-08-29 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ticker\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"BTC\",\n          \"SOL\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"open\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 31927.350602613045,\n        \"min\": 140.05361938476562,\n        \"max\": 59374.44140625,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          143.8910675048828,\n          140.05361938476562\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 32630.20317931338,\n        \"min\": 140.99781799316406,\n        \"max\": 61184.08203125,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          147.2205810546875,\n          140.99781799316406\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 31483.102885622717,\n        \"min\": 132.65945434570312,\n        \"max\": 58786.2265625,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          138.2660675048828,\n          132.65945434570312\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 31890.075426638163,\n        \"min\": 136.34530639648438,\n        \"max\": 59388.1796875,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          140.0540313720703,\n          136.34530639648438\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 15286782483.955088,\n        \"min\": 2098251665.0,\n        \"max\": 33664014336.0,\n        \"num_unique_values\": 5,\n        \"samples\": [\n          2098251665.0,\n          2761629440.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 11
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "price_df.to_sql(\"prices\", db_connection)"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "uq49G34-2kmT",
    "outputId": "6c93dfe6-2192-477b-c02f-0134acb5923c"
   },
   "execution_count": 12,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "7727"
      ]
     },
     "metadata": {},
     "execution_count": 12
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "def search(keyword: str, max_results=100) -> pd.DataFrame:\n",
    "    search_tool = DDGS()\n",
    "    results = search_tool.news(\n",
    "        keywords=keyword, safesearch=\"off\", timelimit=\"m\", max_results=max_results\n",
    "    )\n",
    "    df = pd.DataFrame.from_records(results)\n",
    "    df[\"date\"] = pd.to_datetime(df.date)\n",
    "    return df.sort_values(by=\"date\", ascending=False)"
   ],
   "metadata": {
    "id": "zt5R2oHDIGfs"
   },
   "execution_count": 13,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "crypto_news_df = search(keyword=\"Cryptocurrency\")\n",
    "btc_news_df = search(keyword=\"Bitcoin\")\n",
    "eth_news_df = search(keyword=\"Ethereum\")\n",
    "sol_news_df = search(keyword=\"Solana\")\n",
    "crypto_news_df.shape, btc_news_df.shape, eth_news_df.shape, sol_news_df.shape"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "1FsduiuUIf6t",
    "outputId": "c7a00035-bb0e-4a06-8971-58ea7c34c35d"
   },
   "execution_count": 14,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "((100, 6), (100, 6), (100, 6), (100, 6))"
      ]
     },
     "metadata": {},
     "execution_count": 14
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "crypto_news_df[\"ticker\"] = None\n",
    "btc_news_df[\"ticker\"] = \"BTC\"\n",
    "eth_news_df[\"ticker\"] = \"ETH\"\n",
    "sol_news_df[\"ticker\"] = \"SOL\""
   ],
   "metadata": {
    "id": "ldbfqMevL-E1"
   },
   "execution_count": 15,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "news_df = pd.concat([crypto_news_df, btc_news_df, eth_news_df, sol_news_df], axis=0)\n",
    "news_df = news_df.sort_values(by=\"date\").reset_index(drop=True)\n",
    "news_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 206
    },
    "id": "BRTQgqzFMQfj",
    "outputId": "b977ca7d-7d42-423b-9749-c767313a308d"
   },
   "execution_count": 16,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                       date  \\\n",
       "0 2024-08-01 00:00:00+00:00   \n",
       "1 2024-08-01 02:01:00+00:00   \n",
       "2 2024-08-01 15:19:00+00:00   \n",
       "3 2024-08-01 20:58:00+00:00   \n",
       "4 2024-08-02 09:00:00+00:00   \n",
       "\n",
       "                                               title  \\\n",
       "0                     Bitcoin Goes All In With Trump   \n",
       "1          No, Bitcoin Won't Solve Our National Debt   \n",
       "2                     Trump's big cryptocurrency bet   \n",
       "3  FBI Issues New Warning If You Buy Crypto From ...   \n",
       "4  Ethereum price today: ETH is trading at $3,153.45   \n",
       "\n",
       "                                                body  \\\n",
       "0  With 10 senators and Trump in attendance at th...   \n",
       "1  At a Bitcoin conference last weekend, Senator ...   \n",
       "2  Former President Donald Trump, who once called...   \n",
       "3  With the billions of dollars held by cryptocur...   \n",
       "4  The return comparisons are as of 8 a.m. ET. Al...   \n",
       "\n",
       "                                                 url image      source ticker  \n",
       "0  https://www.thenation.com/article/politics/bit...        The Nation    BTC  \n",
       "1  https://www.forbes.com/sites/benritz/2024/07/3...            Forbes    BTC  \n",
       "2  https://www.cbsnews.com/news/trump-cryptocurre...          CBS News   None  \n",
       "3  https://www.forbes.com/sites/zakdoffman/2024/0...            Forbes   None  \n",
       "4  https://www.usatoday.com/money/blueprint/inves...         USA Today    ETH  "
      ],
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>date</th>\n",
       "      <th>title</th>\n",
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       "      <th>url</th>\n",
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       "      <th>0</th>\n",
       "      <td>2024-08-01 00:00:00+00:00</td>\n",
       "      <td>Bitcoin Goes All In With Trump</td>\n",
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       "      <td>No, Bitcoin Won't Solve Our National Debt</td>\n",
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       "      <td>https://www.forbes.com/sites/benritz/2024/07/3...</td>\n",
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       "      <td>Forbes</td>\n",
       "      <td>BTC</td>\n",
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       "      <th>2</th>\n",
       "      <td>2024-08-01 15:19:00+00:00</td>\n",
       "      <td>Trump's big cryptocurrency bet</td>\n",
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       "      <td>2024-08-01 20:58:00+00:00</td>\n",
       "      <td>FBI Issues New Warning If You Buy Crypto From ...</td>\n",
       "      <td>With the billions of dollars held by cryptocur...</td>\n",
       "      <td>https://www.forbes.com/sites/zakdoffman/2024/0...</td>\n",
       "      <td></td>\n",
       "      <td>Forbes</td>\n",
       "      <td>None</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2024-08-02 09:00:00+00:00</td>\n",
       "      <td>Ethereum price today: ETH is trading at $3,153.45</td>\n",
       "      <td>The return comparisons are as of 8 a.m. ET. Al...</td>\n",
       "      <td>https://www.usatoday.com/money/blueprint/inves...</td>\n",
       "      <td></td>\n",
       "      <td>USA Today</td>\n",
       "      <td>ETH</td>\n",
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       "  }\n",
       "\n",
       "  .colab-df-quickchart:hover {\n",
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       "  }\n",
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       "  .colab-df-quickchart-complete:disabled,\n",
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       "      spin 1s steps(1) infinite;\n",
       "  }\n",
       "\n",
       "  @keyframes spin {\n",
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       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "news_df",
       "summary": "{\n  \"name\": \"news_df\",\n  \"rows\": 400,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-08-01 00:00:00+00:00\",\n        \"max\": \"2024-08-30 19:32:06+00:00\",\n        \"num_unique_values\": 365,\n        \"samples\": [\n          \"2024-08-28 04:59:00+00:00\",\n          \"2024-08-18 19:00:00+00:00\",\n          \"2024-08-07 00:00:00+00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 386,\n        \"samples\": [\n          \"Is Riot Platforms, Inc. (RIOT) The Best Bitcoin and Blockchain Stock To Buy According to Analysts?\",\n          \"CME Group to Offer Bitcoin (BTC) Friday Futures Starting on Sept 30\",\n          \"Breaking Down 1 of Wall Street's Biggest Bitcoin Buys: A Warning or a Signal to Join the Cryptocurrency Revolution?\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"body\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 388,\n        \"samples\": [\n          \"Bitcoin's long-term holders are becoming active, indicating potential market shifts. BTC's price faces key levels at $60,000 and $58,790.\",\n          \"Demand for Bitcoin has been in a downtrend since April, approaching negative levels over the past few weeks. According to an Aug. 20 report from data analytics firm CryptoQuant, the apparent ...\",\n          \"A recent judgment from the Dubai Court of First Instance determined that part of an employee's remuneration can be paid in cryptocurrency, but notably does not change the basic principle that cryptocurrencies cannot be the sole form of remuneration in an ...\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"url\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 390,\n        \"samples\": [\n          \"https://www.newyorker.com/news/the-financial-page/trumps-dangerous-embrace-of-bitcoin-and-the-crypto-bros\",\n          \"https://www.dmnews.com/solanas-market-trajectory-hinges-on-key-price-levels/\",\n          \"https://thecurrencyanalytics.com/altcoins/solana-etf-faces-setback-with-cboe-filing-removal-131248\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"image\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 278,\n        \"samples\": [\n          \"https://techbullion.com/wp-content/uploads/2024/08/WhatsApp-Image-2024-08-20-at-7.37.38-PM-1000x600.jpeg\",\n          \"https://dailyhodl.com/wp-content/uploads/2021/12/hoskinson-decentralized-exchanges.jpg\",\n          \"https://techbullion.com/wp-content/uploads/2024/08/WhatsApp-Image-2024-08-30-at-12.16.19-AM-2-1000x600.jpeg\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"source\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 100,\n        \"samples\": [\n          \"Finbold | Finance in Bold\",\n          \"Internet of People\",\n          \"Cryptopolitan on MSN.com\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"ticker\",\n      \"properties\": {\n        \"dtype\": \"category\",\n        \"num_unique_values\": 3,\n        \"samples\": [\n          \"BTC\",\n          \"ETH\",\n          \"SOL\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 16
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "news_df.to_sql(\"news\", db_connection)"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "9X4yzln0PqfK",
    "outputId": "b90c2638-3827-4c78-b4bb-0f462a0a249b"
   },
   "execution_count": 17,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "400"
      ]
     },
     "metadata": {},
     "execution_count": 17
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Historical Prices"
   ],
   "metadata": {
    "id": "_f_m6akPIIk3"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "class Ticker(Enum):\n",
    "    BTC = auto()\n",
    "    ETH = auto()\n",
    "    SOL = auto()\n",
    "\n",
    "\n",
    "class TimeFrame(Enum):\n",
    "    DAILY = auto()\n",
    "    WEEKLY = auto()\n",
    "    MONTHLY = auto()\n",
    "\n",
    "\n",
    "def get_price_data(\n",
    "    ticker: Ticker, time_frame: TimeFrame = TimeFrame.DAILY\n",
    ") -> pd.DataFrame:\n",
    "    query = \"\"\"\n",
    "    SELECT date, high, low, close, volume\n",
    "    FROM prices\n",
    "    WHERE ticker=?\n",
    "    ORDER BY date\"\"\"\n",
    "    with get_connection() as connection:\n",
    "        df = pd.read_sql(\n",
    "            query,\n",
    "            connection,\n",
    "            params=[ticker.name],\n",
    "            index_col=\"date\",\n",
    "            parse_dates=[\"date\"],\n",
    "        )\n",
    "        if time_frame == TimeFrame.DAILY:\n",
    "            return df\n",
    "        interval = \"W\" if time_frame == TimeFrame.WEEKLY else \"M\"\n",
    "        return df.resample(interval).agg(\n",
    "            {\"high\": \"max\", \"low\": \"min\", \"close\": \"last\", \"volume\": \"sum\"}\n",
    "        )\n",
    "\n",
    "\n",
    "def get_money_supply() -> pd.DataFrame:\n",
    "    query = \"\"\"\n",
    "    SELECT date, m1, m2\n",
    "    FROM money_supply\n",
    "    ORDER BY date\n",
    "    \"\"\"\n",
    "    with get_connection() as connection:\n",
    "        return pd.read_sql(query, connection, index_col=\"date\", parse_dates=[\"date\"])"
   ],
   "metadata": {
    "id": "KxLUtJi2oA4Z"
   },
   "execution_count": 18,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "money_supply_df = get_money_supply()\n",
    "money_supply_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "id": "pg78NmIPdj5a",
    "outputId": "06cb4342-bc36-4b18-fb37-fc7e917e146d"
   },
   "execution_count": 19,
   "outputs": [
    {
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       "                m1      m2\n",
       "date                      \n",
       "2010-01-01  1674.2  8464.4\n",
       "2010-02-01  1685.2  8508.4\n",
       "2010-03-01  1729.5  8576.6\n",
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      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "money_supply_df",
       "summary": "{\n  \"name\": \"money_supply_df\",\n  \"rows\": 175,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2010-01-01 00:00:00\",\n        \"max\": \"2024-07-01 00:00:00\",\n        \"num_unique_values\": 175,\n        \"samples\": [\n          \"2023-01-01 00:00:00\",\n          \"2022-02-01 00:00:00\",\n          \"2018-06-01 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"m1\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 7321.65905917186,\n        \"min\": 1674.2,\n        \"max\": 20827.0,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          19591.4,\n          20523.9,\n          3656.6\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"m2\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 4379.709474735624,\n        \"min\": 8464.4,\n        \"max\": 21860.5,\n        \"num_unique_values\": 175,\n        \"samples\": [\n          21292.3,\n          21584.7,\n          14074.7\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 19
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "eth_weekly_df = get_price_data(Ticker.ETH, time_frame=TimeFrame.WEEKLY)\n",
    "eth_weekly_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "id": "0WTaN54LpM4i",
    "outputId": "0f0b9f82-0f79-423d-db15-9d58db40e614"
   },
   "execution_count": 20,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                  high         low       close        volume\n",
       "date                                                        \n",
       "2017-11-12  329.451996  294.541992  307.907990  4.235017e+09\n",
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       "\n",
       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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       "          + ' to learn more about interactive tables.';\n",
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       "\n",
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       "            title=\"Suggest charts\"\n",
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       "    fill: var(--button-hover-fill-color);\n",
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       "\n",
       "  .colab-df-quickchart-complete:disabled,\n",
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       "\n",
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       "      const quickchartButtonEl =\n",
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       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
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       "        console.error('Error during call to suggestCharts:', error);\n",
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       "\n",
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      "application/vnd.google.colaboratory.intrinsic+json": {
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       "variable_name": "eth_weekly_df",
       "summary": "{\n  \"name\": \"eth_weekly_df\",\n  \"rows\": 356,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2017-11-12 00:00:00\",\n        \"max\": \"2024-09-01 00:00:00\",\n        \"num_unique_values\": 356,\n        \"samples\": [\n          \"2022-03-20 00:00:00\",\n          \"2018-09-02 00:00:00\",\n          \"2022-10-09 00:00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"high\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1291.8375995791266,\n        \"min\": 96.2573013305664,\n        \"max\": 4891.70458984375,\n        \"num_unique_values\": 356,\n        \"samples\": [\n          2979.987060546875,\n          301.1440124511719,\n          1380.4049072265625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"low\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1106.4174873309664,\n        \"min\": 82.82988739013672,\n        \"max\": 4485.09326171875,\n        \"num_unique_values\": 356,\n        \"samples\": [\n          2505.29931640625,\n          273.6499938964844,\n          1271.15087890625\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"close\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 1207.8318088582716,\n        \"min\": 85.26210021972656,\n        \"max\": 4626.35888671875,\n        \"num_unique_values\": 356,\n        \"samples\": [\n          2860.459228515625,\n          294.3710021972656,\n          1322.604248046875\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"volume\",\n      \"properties\": {\n        \"dtype\": \"number\",\n        \"std\": 65234198330.55223,\n        \"min\": 4235016896.0,\n        \"max\": 400749195286.0,\n        \"num_unique_values\": 356,\n        \"samples\": [\n          94797948955.0,\n          10187290000.0,\n          63453338237.0\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 20
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## News"
   ],
   "metadata": {
    "id": "88E2mSvwwsbI"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "def get_news_data(ticker: Ticker, max_articles_per_day: int = 5) -> pd.DataFrame:\n",
    "    query = \"\"\"\n",
    "    SELECT date, title, body\n",
    "    FROM news\n",
    "    WHERE ticker=? OR ticker IS NULL\n",
    "    ORDER BY date\n",
    "    \"\"\"\n",
    "    with get_connection() as connection:\n",
    "        df = pd.read_sql(\n",
    "            query,\n",
    "            connection,\n",
    "            params=[ticker.name],\n",
    "            index_col=\"date\",\n",
    "            parse_dates=[\"date\"],\n",
    "        )\n",
    "        groups = [\n",
    "            group.sample(min(len(group), max_articles_per_day))\n",
    "            for _, group in df.groupby(df.index.date)\n",
    "        ]\n",
    "        return pd.concat(groups)"
   ],
   "metadata": {
    "id": "hVWmqV9ItbFm"
   },
   "execution_count": 21,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "btc_news_df = get_news_data(Ticker.BTC)\n",
    "btc_news_df.shape"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "w0YXjV6sshFv",
    "outputId": "2b3fa0cf-a6aa-4fdd-9b2a-2c88f9e12287"
   },
   "execution_count": 22,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "(69, 2)"
      ]
     },
     "metadata": {},
     "execution_count": 22
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "btc_news_df.head()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "id": "OwCyW-ikUORX",
    "outputId": "70e9393a-e63c-49c3-b227-8922f14f7a0a"
   },
   "execution_count": 23,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                                                                       title  \\\n",
       "date                                                                           \n",
       "2024-08-01 02:01:00+00:00          No, Bitcoin Won't Solve Our National Debt   \n",
       "2024-08-01 20:58:00+00:00  FBI Issues New Warning If You Buy Crypto From ...   \n",
       "2024-08-01 00:00:00+00:00                     Bitcoin Goes All In With Trump   \n",
       "2024-08-01 15:19:00+00:00                     Trump's big cryptocurrency bet   \n",
       "2024-08-02 11:30:00+00:00                                     Pump and Trump   \n",
       "\n",
       "                                                                        body  \n",
       "date                                                                          \n",
       "2024-08-01 02:01:00+00:00  At a Bitcoin conference last weekend, Senator ...  \n",
       "2024-08-01 20:58:00+00:00  With the billions of dollars held by cryptocur...  \n",
       "2024-08-01 00:00:00+00:00  With 10 senators and Trump in attendance at th...  \n",
       "2024-08-01 15:19:00+00:00  Former President Donald Trump, who once called...  \n",
       "2024-08-02 11:30:00+00:00  There were rumors that Elon Musk would introdu...  "
      ],
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       "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
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       "        document.querySelector('#' + key + ' button');\n",
       "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
       "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
       "      try {\n",
       "        const charts = await google.colab.kernel.invokeFunction(\n",
       "            'suggestCharts', [key], {});\n",
       "      } catch (error) {\n",
       "        console.error('Error during call to suggestCharts:', error);\n",
       "      }\n",
       "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
       "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
       "    }\n",
       "    (() => {\n",
       "      let quickchartButtonEl =\n",
       "        document.querySelector('#df-e7d6419f-e302-4b92-9a3e-a7697d0935f7 button');\n",
       "      quickchartButtonEl.style.display =\n",
       "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
       "    })();\n",
       "  </script>\n",
       "</div>\n",
       "\n",
       "    </div>\n",
       "  </div>\n"
      ],
      "application/vnd.google.colaboratory.intrinsic+json": {
       "type": "dataframe",
       "variable_name": "btc_news_df",
       "summary": "{\n  \"name\": \"btc_news_df\",\n  \"rows\": 69,\n  \"fields\": [\n    {\n      \"column\": \"date\",\n      \"properties\": {\n        \"dtype\": \"date\",\n        \"min\": \"2024-08-01 00:00:00+00:00\",\n        \"max\": \"2024-08-30 15:03:00+00:00\",\n        \"num_unique_values\": 68,\n        \"samples\": [\n          \"2024-08-26 16:25:00+00:00\",\n          \"2024-08-12 00:00:00+00:00\",\n          \"2024-08-02 11:30:00+00:00\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"title\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 69,\n        \"samples\": [\n          \"What is cryptocurrency and how does it work?\",\n          \"No, Bitcoin Won't Solve Our National Debt\",\n          \"Next Cryptocurrency to Explode Monday, August 26 \\u2014 TRON, Xodex, Floki, Flux\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    },\n    {\n      \"column\": \"body\",\n      \"properties\": {\n        \"dtype\": \"string\",\n        \"num_unique_values\": 69,\n        \"samples\": [\n          \"Cryptocurrency is digital money, like euros or United States dollars, but operates independently from governments and banks, using a decentralized technology called blockchain. Transactions are ...\",\n          \"At a Bitcoin conference last weekend, Senator Cynthia Lummis (R-Wyo.) announced forthcoming legislation that would direct the Treasury to buy 1 million Bitcoin, or roughly 5% of the global stock ...\",\n          \"Discover cryptos with explosive potential for today, August 26. Using today's market data, find out what makes these tokens promising.\"\n        ],\n        \"semantic_type\": \"\",\n        \"description\": \"\"\n      }\n    }\n  ]\n}"
      }
     },
     "metadata": {},
     "execution_count": 23
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Indicators"
   ],
   "metadata": {
    "id": "w1MJmJlzwrNQ"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "dates = pd.date_range(start=\"2023-01-01\", periods=100, freq=\"D\")\n",
    "price = np.cumsum(np.random.randn(100)) + 100  # Random walk\n",
    "\n",
    "df = pd.DataFrame({\"Date\": dates, \"Price\": price})\n",
    "df.set_index(\"Date\", inplace=True)"
   ],
   "metadata": {
    "id": "zHVqog8IuXK6"
   },
   "execution_count": 24,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "### RSI"
   ],
   "metadata": {
    "id": "BaFfHQpQv2kH"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "def calculate_rsi(data, periods=14):\n",
    "    delta = data.diff()\n",
    "    gain = (delta.where(delta > 0, 0)).rolling(window=periods).mean()\n",
    "    loss = (-delta.where(delta < 0, 0)).rolling(window=periods).mean()\n",
    "\n",
    "    rs = gain / loss\n",
    "    return 100 - (100 / (1 + rs))\n",
    "\n",
    "\n",
    "df[\"RSI\"] = calculate_rsi(df[\"Price\"])"
   ],
   "metadata": {
    "id": "K-XYZ3LywG_r"
   },
   "execution_count": 25,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10), sharex=True)\n",
    "\n",
    "ax1.plot(df.index, df[\"Price\"], label=\"Price\")\n",
    "ax1.set_title(\"RSI Indicator\")\n",
    "ax1.set_ylabel(\"Price\")\n",
    "ax1.legend(loc=\"upper left\")\n",
    "ax1.grid(True)\n",
    "\n",
    "ax2.plot(df.index, df[\"RSI\"], label=\"RSI\", color=\"orange\")\n",
    "ax2.axhline(y=70, color=\"red\", linestyle=\"--\", alpha=0.5)\n",
    "ax2.axhline(y=30, color=\"green\", linestyle=\"--\", alpha=0.5)\n",
    "ax2.fill_between(\n",
    "    df.index, df[\"RSI\"], 70, where=(df[\"RSI\"] >= 70), color=\"red\", alpha=0.3\n",
    ")\n",
    "ax2.fill_between(\n",
    "    df.index, df[\"RSI\"], 30, where=(df[\"RSI\"] <= 30), color=\"green\", alpha=0.3\n",
    ")\n",
    "ax2.set_ylabel(\"RSI\")\n",
    "ax2.set_ylim(0, 100)\n",
    "ax2.legend(loc=\"upper left\")\n",
    "ax2.grid(True)\n",
    "\n",
    "plt.xlabel(\"Date\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 1000
    },
    "id": "P8Td0s6rwKdG",
    "outputId": "a164ed53-ee66-49f0-daab-96c540fc29e3"
   },
   "execution_count": 26,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1200x1000 with 2 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Bollinger Bands"
   ],
   "metadata": {
    "id": "N1Y95KwuugQo"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "window = 20\n",
    "df[\"SMA\"] = df[\"Price\"].rolling(window=window).mean()\n",
    "df[\"STD\"] = df[\"Price\"].rolling(window=window).std()\n",
    "df[\"Upper\"] = df[\"SMA\"] + (df[\"STD\"] * 2)\n",
    "df[\"Lower\"] = df[\"SMA\"] - (df[\"STD\"] * 2)"
   ],
   "metadata": {
    "id": "HMcbmPaxuif_"
   },
   "execution_count": 27,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(12, 6))\n",
    "plt.plot(df.index, df[\"Price\"], label=\"Price\", alpha=0.5)\n",
    "plt.plot(df.index, df[\"SMA\"], label=\"SMA\", alpha=0.5)\n",
    "plt.plot(df.index, df[\"Upper\"], label=\"Upper Band\", alpha=0.5)\n",
    "plt.plot(df.index, df[\"Lower\"], label=\"Lower Band\", alpha=0.5)\n",
    "plt.fill_between(df.index, df[\"Upper\"], df[\"Lower\"], alpha=0.1)\n",
    "plt.title(\"Bollinger Bands (20-day, 2 standard deviations)\")\n",
    "plt.legend(loc=\"upper left\")\n",
    "plt.xlabel(\"Date\")\n",
    "plt.ylabel(\"Price\")\n",
    "plt.grid(True)\n",
    "plt.show()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 564
    },
    "id": "XF6uRg3gumoD",
    "outputId": "748ed82d-5475-4cb0-f487-d1cbd1752c6a"
   },
   "execution_count": 28,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1200x600 with 1 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "### MACD"
   ],
   "metadata": {
    "id": "lHEUJVW-so5B"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "df[\"EMA12\"] = df[\"Price\"].ewm(span=12, adjust=False).mean()\n",
    "df[\"EMA26\"] = df[\"Price\"].ewm(span=26, adjust=False).mean()\n",
    "\n",
    "df[\"MACD\"] = df[\"EMA12\"] - df[\"EMA26\"]\n",
    "df[\"Signal Line\"] = df[\"MACD\"].ewm(span=9, adjust=False).mean()\n",
    "df[\"Histogram\"] = df[\"MACD\"] - df[\"Signal Line\"]"
   ],
   "metadata": {
    "id": "X5Sj1HS-stvd"
   },
   "execution_count": 29,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "plt.figure(figsize=(14, 7))\n",
    "\n",
    "plt.subplot(2, 1, 1)\n",
    "plt.plot(df.index, df[\"Price\"], label=\"Price\")\n",
    "plt.title(\"MACD Indicator\")\n",
    "plt.legend(loc=\"upper left\")\n",
    "\n",
    "plt.subplot(2, 1, 2)\n",
    "plt.plot(df.index, df[\"MACD\"], label=\"MACD\", color=\"blue\")\n",
    "plt.plot(df.index, df[\"Signal Line\"], label=\"Signal Line\", color=\"red\")\n",
    "plt.bar(df.index, df[\"Histogram\"], label=\"Histogram\", color=\"gray\", alpha=0.5)\n",
    "plt.title(\"MACD Indicator\")\n",
    "plt.legend(loc=\"upper left\")\n",
    "\n",
    "plt.tight_layout()\n",
    "plt.show();"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 707
    },
    "id": "9BuktdNcuqwZ",
    "outputId": "936137d0-ecfc-490f-f11e-5e9302bc2c5a"
   },
   "execution_count": 30,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": [
       "<Figure size 1400x700 with 2 Axes>"
      ],
      "image/png": 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\n"
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "def add_indicators(data: pd.DataFrame) -> pd.DataFrame:\n",
    "    data = data.copy()\n",
    "    macd_df = ta.macd(data[\"close\"])\n",
    "    bbands_df = ta.bbands(data[\"close\"])\n",
    "\n",
    "    data[\"ma_50\"] = data[\"close\"].rolling(50).mean()\n",
    "    data[\"ma_200\"] = data[\"close\"].rolling(200).mean()\n",
    "    data[\"rsi\"] = ta.rsi(data[\"close\"])\n",
    "    data[\"macd\"], data[\"macd_signal\"], data[\"macd_histogram\"] = (\n",
    "        macd_df.iloc[:, 0],\n",
    "        macd_df.iloc[:, 1],\n",
    "        macd_df.iloc[:, 2],\n",
    "    )\n",
    "    data[\"bb_lower\"], data[\"bb_middle\"], data[\"bb_upper\"] = (\n",
    "        bbands_df.iloc[:, 0],\n",
    "        bbands_df.iloc[:, 1],\n",
    "        bbands_df.iloc[:, 2],\n",
    "    )\n",
    "    return data"
   ],
   "metadata": {
    "id": "EPL_kAOw3Y-I"
   },
   "execution_count": 31,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "add_indicators(eth_weekly_df).tail()"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 238
    },
    "id": "wy3kiLVTr30v",
    "outputId": "e1f1c5c3-c109-4a32-b316-63c7cfdf6df5"
   },
   "execution_count": 32,
   "outputs": [
    {
     "output_type": "execute_result",
     "data": {
      "text/plain": [
       "                   high          low        close        volume        ma_50  \\\n",
       "date                                                                           \n",
       "2024-08-04  3396.625732  2639.566650  2686.398926  1.291176e+11  2674.547463   \n",
       "2024-08-11  2721.954590  2122.546143  2553.252197  1.823062e+11  2692.462246   \n",
       "2024-08-18  2775.281006  2513.394043  2613.357178  9.936671e+10  2712.007036   \n",
       "2024-08-25  2820.020508  2538.657715  2749.157715  8.670627e+10  2734.653613   \n",
       "2024-09-01  2763.004150  2401.175049  2509.927490  8.059070e+10  2752.394229   \n",
       "\n",
       "                 ma_200        rsi        macd  macd_signal  macd_histogram  \\\n",
       "date                                                                          \n",
       "2024-08-04  2236.663028  42.933270  106.353238  -104.377164      210.730402   \n",
       "2024-08-11  2247.553579  41.169057   43.290933  -133.951575      177.242508   \n",
       "2024-08-18  2258.729296  42.321282   -1.815501  -143.246407      141.430906   \n",
       "2024-08-25  2270.443996  44.944923  -26.301518  -134.185939      107.884421   \n",
       "2024-09-01  2281.011842  41.374491  -64.269880  -137.723441       73.453561   \n",
       "\n",
       "               bb_lower    bb_middle     bb_upper  \n",
       "date                                               \n",
       "2024-08-04  2543.456667  3133.587061  3723.717454  \n",
       "2024-08-11  2308.900084  3058.360059  3807.820033  \n",
       "2024-08-18  2139.202792  2932.215674  3725.228556  \n",
       "2024-08-25  2260.687068  2774.726123  3288.765178  \n",
       "2024-09-01  2448.806177  2622.418701  2796.031225  "
      ],
      "text/html": [
       "\n",
       "  <div id=\"df-dd57dd36-ccf6-4bf4-951b-7c6b13133b79\" class=\"colab-df-container\">\n",
       "    <div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>ma_50</th>\n",
       "      <th>ma_200</th>\n",
       "      <th>rsi</th>\n",
       "      <th>macd</th>\n",
       "      <th>macd_signal</th>\n",
       "      <th>macd_histogram</th>\n",
       "      <th>bb_lower</th>\n",
       "      <th>bb_middle</th>\n",
       "      <th>bb_upper</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2024-08-04</th>\n",
       "      <td>3396.625732</td>\n",
       "      <td>2639.566650</td>\n",
       "      <td>2686.398926</td>\n",
       "      <td>1.291176e+11</td>\n",
       "      <td>2674.547463</td>\n",
       "      <td>2236.663028</td>\n",
       "      <td>42.933270</td>\n",
       "      <td>106.353238</td>\n",
       "      <td>-104.377164</td>\n",
       "      <td>210.730402</td>\n",
       "      <td>2543.456667</td>\n",
       "      <td>3133.587061</td>\n",
       "      <td>3723.717454</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-11</th>\n",
       "      <td>2721.954590</td>\n",
       "      <td>2122.546143</td>\n",
       "      <td>2553.252197</td>\n",
       "      <td>1.823062e+11</td>\n",
       "      <td>2692.462246</td>\n",
       "      <td>2247.553579</td>\n",
       "      <td>41.169057</td>\n",
       "      <td>43.290933</td>\n",
       "      <td>-133.951575</td>\n",
       "      <td>177.242508</td>\n",
       "      <td>2308.900084</td>\n",
       "      <td>3058.360059</td>\n",
       "      <td>3807.820033</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-18</th>\n",
       "      <td>2775.281006</td>\n",
       "      <td>2513.394043</td>\n",
       "      <td>2613.357178</td>\n",
       "      <td>9.936671e+10</td>\n",
       "      <td>2712.007036</td>\n",
       "      <td>2258.729296</td>\n",
       "      <td>42.321282</td>\n",
       "      <td>-1.815501</td>\n",
       "      <td>-143.246407</td>\n",
       "      <td>141.430906</td>\n",
       "      <td>2139.202792</td>\n",
       "      <td>2932.215674</td>\n",
       "      <td>3725.228556</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-08-25</th>\n",
       "      <td>2820.020508</td>\n",
       "      <td>2538.657715</td>\n",
       "      <td>2749.157715</td>\n",
       "      <td>8.670627e+10</td>\n",
       "      <td>2734.653613</td>\n",
       "      <td>2270.443996</td>\n",
       "      <td>44.944923</td>\n",
       "      <td>-26.301518</td>\n",
       "      <td>-134.185939</td>\n",
       "      <td>107.884421</td>\n",
       "      <td>2260.687068</td>\n",
       "      <td>2774.726123</td>\n",
       "      <td>3288.765178</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2024-09-01</th>\n",
       "      <td>2763.004150</td>\n",
       "      <td>2401.175049</td>\n",
       "      <td>2509.927490</td>\n",
       "      <td>8.059070e+10</td>\n",
       "      <td>2752.394229</td>\n",
       "      <td>2281.011842</td>\n",
       "      <td>41.374491</td>\n",
       "      <td>-64.269880</td>\n",
       "      <td>-137.723441</td>\n",
       "      <td>73.453561</td>\n",
       "      <td>2448.806177</td>\n",
       "      <td>2622.418701</td>\n",
       "      <td>2796.031225</td>\n",
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      }
     },
     "metadata": {},
     "execution_count": 32
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "def calculate_50_percent(data: pd.DataFrame, n_weeks: int = 4):\n",
    "    last_n_weeks = data.tail(n=n_weeks)\n",
    "    low = last_n_weeks.low.min()\n",
    "    high = last_n_weeks.high.max()\n",
    "    return (low + high) / 2, low, high"
   ],
   "metadata": {
    "id": "7cWG8IIIZQX8"
   },
   "execution_count": 33,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Graph"
   ],
   "metadata": {
    "id": "ULYocLKU0MvN"
   }
  },
  {
   "cell_type": "markdown",
   "source": [
    "### State"
   ],
   "metadata": {
    "id": "CSQZy06D3922"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "class TickerQuery(BaseModel):\n",
    "    \"\"\"Ticker symbol requested by the user\"\"\"\n",
    "\n",
    "    ticker: Literal[\"BTC\", \"ETH\", \"SOL\"] = Field(\n",
    "        description=\"Ticker symbol for the chosen cryptocurrency\",\n",
    "    )\n",
    "\n",
    "\n",
    "class FinalReport(BaseModel):\n",
    "    \"\"\"Report created by the financial reporter\"\"\"\n",
    "\n",
    "    action: Literal[\"BUY\", \"HODL\", \"SELL\"] = Field(\n",
    "        description=\"Action to take with the chosen cryptocurrency\"\n",
    "    )\n",
    "    score: int = Field(\n",
    "        description=\"Bullishness market score between 0 (extremely bearish) and 100 (extremely bullish)\"\n",
    "    )\n",
    "    trend: Literal[\"UP\", \"NEUTRAL\", \"DOWN\"] = Field(\n",
    "        description=\"Price trend for the chosen cryptocurrency\",\n",
    "    )\n",
    "    sentiment: Literal[\"GREED\", \"NEUTRAL\", \"FEAR\"] = Field(\n",
    "        description=\"Sentiment from the news for the chosen cryptocurrency\"\n",
    "    )\n",
    "    price_predictions: List[float] = Field(\n",
    "        description=\"Price predictions for 1, 2, 3 and 4 weeks ahead\"\n",
    "    )\n",
    "    summary: str = Field(\n",
    "        description=\"Summary of the current market conditions (1-3 sentences)\"\n",
    "    )\n",
    "\n",
    "\n",
    "class AppState(TypedDict):\n",
    "    user_query: str\n",
    "    ticker: Ticker\n",
    "    news: pd.DataFrame\n",
    "    prices: pd.DataFrame\n",
    "    price_analyst_report: str\n",
    "    news_analyst_report: str\n",
    "    final_report: FinalReport"
   ],
   "metadata": {
    "id": "_tmu_snALfGD"
   },
   "execution_count": 34,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Nodes"
   ],
   "metadata": {
    "id": "yPFvJmCb3_eJ"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "def ticker_extractor(state: AppState):\n",
    "    ticker_extractor_llm = llm.with_structured_output(TickerQuery)\n",
    "    extraction = ticker_extractor_llm.invoke([HumanMessage(state[\"user_query\"])])\n",
    "    return {\"ticker\": Ticker[extraction.ticker]}"
   ],
   "metadata": {
    "id": "BbfWTPxSt9MT"
   },
   "execution_count": 35,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "def news_retriever(state: AppState):\n",
    "    ticker = state[\"ticker\"]\n",
    "    news_df = get_news_data(ticker)\n",
    "    return {\"news\": news_df}"
   ],
   "metadata": {
    "id": "vZWQe5iAB1LJ"
   },
   "execution_count": 36,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "def price_retriever(state: AppState):\n",
    "    ticker = state[\"ticker\"]\n",
    "    price_df = get_price_data(ticker, time_frame=TimeFrame.WEEKLY)\n",
    "    price_df = add_indicators(price_df)\n",
    "    price_df = price_df.tail(n=24)\n",
    "    return {\"prices\": price_df}"
   ],
   "metadata": {
    "id": "Bni7VpkkDcXR"
   },
   "execution_count": 37,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "def price_analyst(state: AppState):\n",
    "\n",
    "    price_df = state[\"prices\"]\n",
    "    weeks_4_50_percent, _, _ = calculate_50_percent(price_df, n_weeks=4)\n",
    "    weeks_12_50_percent, _, _ = calculate_50_percent(price_df, n_weeks=12)\n",
    "    weeks_26_50_percent, _, _ = calculate_50_percent(price_df, n_weeks=26)\n",
    "\n",
    "    money_supply_df = get_money_supply()\n",
    "    money_supply_text = str(money_supply_df[\"m2\"])\n",
    "\n",
    "    prompt = f\"\"\"You have extensive knowledge of the cryptocurrency market and historical data.\n",
    "Think step-by-step and focus on the technical indicators.\n",
    "Use the following weekly close price history and technical indicators for ETH:\n",
    "\n",
    "price history:\n",
    "```\n",
    "{str(price_df[price_df.columns[2:]])}\n",
    "```\n",
    "\n",
    "M2 money supply history:\n",
    "```\n",
    "{money_supply_text}\n",
    "```\n",
    "\n",
    "4 weeks 50% level: {weeks_4_50_percent}\n",
    "12 weeks 50% level: {weeks_12_50_percent}\n",
    "26 weeks 50% level: {weeks_26_50_percent}\n",
    "\n",
    "Predict the next 4 weekly prices based on the data. Put the predictions on separate line.\n",
    "How certain are you of your predictions? Use a number between 0 (not certain at all) to 10 (sure thing).\n",
    "What is the overall trend outlook? Explain your predictions in 1-3 sentences.\n",
    "\n",
    "When creating your answer, focus on answering the user query:\n",
    "{state[\"user_query\"]}\n",
    "\"\"\"\n",
    "    response = llm.invoke([HumanMessage(prompt)])\n",
    "    return {\"price_analyst_report\": response.content}"
   ],
   "metadata": {
    "id": "VVozcBXJbuiu"
   },
   "execution_count": 38,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "def news_analyst(state: AppState):\n",
    "    news_df = state[\"news\"]\n",
    "    news_text = \"\"\n",
    "    for date, row in list(news_df.iterrows())[:20]:\n",
    "        news_text += f\"{date}\\n{row.title}\\n{row.body}\\n---\\n\"\n",
    "\n",
    "    prompt = f\"\"\"Choose a combined sentiment that best represents these news articles:\n",
    "\n",
    "```\n",
    "{news_text}\n",
    "```\n",
    "\n",
    "Each article is separated by `---`.\n",
    "\n",
    "Pick a number for the sentiment between 0 and 100 where:\n",
    "\n",
    "- 0 is extremely bearish\n",
    "- 100 is extremely bullish\n",
    "\n",
    "Reply only with the sentiment and a short explanation (1-2 sentences) of why.\n",
    "\n",
    "When creating your answer, focus on answering the user query:\n",
    "{state[\"user_query\"]}\n",
    "\"\"\"\n",
    "    response = llm.invoke([HumanMessage(prompt)])\n",
    "    return {\"news_analyst_report\": response.content}"
   ],
   "metadata": {
    "id": "ksQh8rU-g1MN"
   },
   "execution_count": 39,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "def financial_reporter(state: AppState):\n",
    "    price_report = state[\"price_analyst_report\"]\n",
    "    news_report = state[\"news_analyst_report\"]\n",
    "    prompt = f\"\"\"You're a senior cryptocurrency expert that makes extremely accurate predictions\n",
    "about future prices and trend in the crypto market. You're well versed into technological advancements\n",
    "and tokenomics of various projects.\n",
    "\n",
    "You're working with two other agents that have created reports of the current state of the crypto market.\n",
    "\n",
    "Report of the news analyst:\n",
    "\n",
    "```\n",
    "{news_report}\n",
    "```\n",
    "\n",
    "Report of the price analyst:\n",
    "\n",
    "```\n",
    "{price_report}\n",
    "```\n",
    "\n",
    "Based on the provided information, create a final report for the user.\n",
    "\n",
    "When creating your answer, focus on answering the user query:\n",
    "{state[\"user_query\"]}\n",
    "\"\"\"\n",
    "    final_report_llm = llm.with_structured_output(FinalReport)\n",
    "    response = final_report_llm.invoke([HumanMessage(prompt)])\n",
    "    return {\"final_report\": response}"
   ],
   "metadata": {
    "id": "UWyoHdBYiGr5"
   },
   "execution_count": 40,
   "outputs": []
  },
  {
   "cell_type": "markdown",
   "source": [
    "### Building the Graph"
   ],
   "metadata": {
    "id": "WO9V44To4C29"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "graph = StateGraph(AppState)"
   ],
   "metadata": {
    "id": "jmWbU919twwa"
   },
   "execution_count": 41,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "graph.add_node(\"ticker_extractor\", ticker_extractor)\n",
    "graph.add_node(\"news_retriever\", news_retriever)\n",
    "graph.add_node(\"price_retriever\", price_retriever)\n",
    "graph.add_node(\"price_analyst\", price_analyst)\n",
    "graph.add_node(\"news_analyst\", news_analyst)\n",
    "graph.add_node(\"financial_reporter\", financial_reporter)"
   ],
   "metadata": {
    "id": "8Ng8d-IvYqEs"
   },
   "execution_count": 42,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "graph.add_edge(\"ticker_extractor\", \"price_retriever\")\n",
    "graph.add_edge(\"ticker_extractor\", \"news_retriever\")\n",
    "graph.add_edge(\"news_retriever\", \"news_analyst\")\n",
    "graph.add_edge(\"price_retriever\", \"price_analyst\")\n",
    "graph.add_edge(\"price_analyst\", \"financial_reporter\")\n",
    "graph.add_edge(\"news_analyst\", \"financial_reporter\")\n",
    "\n",
    "graph.set_entry_point(\"ticker_extractor\")\n",
    "graph.set_finish_point(\"financial_reporter\")"
   ],
   "metadata": {
    "id": "DjpXW8mjYsRw"
   },
   "execution_count": 43,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "app = graph.compile()"
   ],
   "metadata": {
    "id": "tt8DuVtRYupo"
   },
   "execution_count": 44,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "display(Image(app.get_graph().draw_mermaid_png()))"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/",
     "height": 488
    },
    "id": "2NatV_FBu5_s",
    "outputId": "102feccd-500d-4227-fe4b-9ab229a545ef"
   },
   "execution_count": 45,
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "image/jpeg": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {}
    }
   ]
  },
  {
   "cell_type": "markdown",
   "source": [
    "## Use the Graph"
   ],
   "metadata": {
    "id": "mzInKmVE4LAv"
   }
  },
  {
   "cell_type": "code",
   "source": [
    "config = {\"configurable\": {\"thread_id\": 42}}\n",
    "\n",
    "state = app.invoke(\n",
    "    {\"user_query\": \"Analyze the long-term potential of Ethereum\"},\n",
    "    config=config,\n",
    ")"
   ],
   "metadata": {
    "id": "mgO9HyZ2y-rg"
   },
   "execution_count": 46,
   "outputs": []
  },
  {
   "cell_type": "code",
   "source": [
    "print(state.keys())"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jwU0StrNDSiy",
    "outputId": "897b0b23-0c61-4ac2-e5ac-b788c3915f63"
   },
   "execution_count": 47,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "dict_keys(['user_query', 'ticker', 'news', 'prices', 'price_analyst_report', 'news_analyst_report', 'final_report'])\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "for line in state[\"price_analyst_report\"].split(\"\\n\"):\n",
    "    print(textwrap.fill(line, 80))"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "sRgWzo5lXH0m",
    "outputId": "6e749487-88eb-437b-c6ef-6e44d5caef9b"
   },
   "execution_count": 48,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "**Predictions:**\n",
      "\n",
      "1. 2024-09-08: 2400\n",
      "2. 2024-09-15: 2350\n",
      "3. 2024-09-22: 2300\n",
      "4. 2024-09-29: 2250\n",
      "\n",
      "**Certainty:** 6\n",
      "\n",
      "**Overall Trend Outlook:** The overall trend outlook for Ethereum is bearish in\n",
      "the short term, as indicated by the recent decline in price and the MACD\n",
      "histogram crossing below the signal line. However, considering the long-term\n",
      "potential of Ethereum, the 26-week 50% level of 3048.05126953125 and the M2\n",
      "money supply history, which has been increasing over time, suggest that Ethereum\n",
      "may experience a rebound in the long term.\n",
      "\n",
      "**Explanation:** The predictions are based on the analysis of the technical\n",
      "indicators, specifically the MACD histogram, which has been declining and is\n",
      "currently below the signal line, indicating a bearish trend. Additionally, the\n",
      "price is below the 50-period moving average, which also suggests a bearish\n",
      "trend. However, considering the long-term potential of Ethereum, the increasing\n",
      "M2 money supply history, and the 26-week 50% level, it is likely that Ethereum\n",
      "will experience a rebound in the long term.\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "for line in state[\"news_analyst_report\"].split(\"\\n\"):\n",
    "    print(textwrap.fill(line, 80))"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "TBcu4rc4W0Rp",
    "outputId": "e1b1e71b-c5d9-4a97-a115-0c35f73d605d"
   },
   "execution_count": 49,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Sentiment: 72\n",
      "\n",
      "The overall sentiment is slightly bullish due to the long-term growth potential\n",
      "of Ethereum, with some articles highlighting its significant growth capabilities\n",
      "and others discussing its current market fluctuations. However, some articles\n",
      "also mention market doubts and a stalled price recovery, which prevents the\n",
      "sentiment from being extremely bullish.\n"
     ]
    }
   ]
  },
  {
   "cell_type": "code",
   "source": [
    "report = state[\"final_report\"]\n",
    "\n",
    "print(\n",
    "    f\"\"\"\n",
    "Action:     {report.action}\n",
    "Score:      {report.score}\n",
    "Trend:      {report.trend}\n",
    "Sentiment:  {report.sentiment}\n",
    "\n",
    "Price predictions (4 weeks ahead):\n",
    "{report.price_predictions}\n",
    "\n",
    "Summary:\n",
    "{textwrap.fill(report.summary, 80)}\n",
    "\"\"\"\n",
    ")"
   ],
   "metadata": {
    "colab": {
     "base_uri": "https://localhost:8080/"
    },
    "id": "jCEeKLoFWeQy",
    "outputId": "ab47e382-eb76-4d08-8047-8bc479986a11"
   },
   "execution_count": 50,
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "\n",
      "Action:     HODL\n",
      "Score:      72\n",
      "Trend:      DOWN\n",
      "Sentiment:  NEUTRAL\n",
      "\n",
      "Price predictions (4 weeks ahead):\n",
      "[2400.0, 2350.0, 2300.0, 2250.0]\n",
      "\n",
      "Summary:\n",
      "Ethereum's long-term growth potential is slightly bullish, with a current\n",
      "bearish short-term trend. However, the increasing M2 money supply history and\n",
      "the 26-week 50% level suggest a potential rebound in the long term.\n",
      "\n"
     ]
    }
   ]
  }
 ]
}