credaave_final.ipynb

{"cells":[{"cell_type":"code","execution_count":4,"metadata":{"trusted":true},"outputs":[],"source":["from fastai.vision.all import *\n","from fastai.vision.widgets import *"]},{"cell_type":"code","execution_count":5,"metadata":{"trusted":true},"outputs":[],"source":["from PIL import Image \n","AmazingCredit = Image.open(r\"./AmazingCredit.png\")\n","GoodCredit = Image.open(r\"./GoodCredit.png\")\n","BadCredit = Image.open(r\"./BadCredit.png\")\n","\n","import ipywidgets as widget\n","\n","AmazingCredit =  widget.HTML('<div id=\"img\" style=\"float:left\">'\n","                    '<img style=\"vertical-align:middle\" src=\"./AmazingCredit.png\" alt=\"\">'                       \n","                    '</div>')\n","\n","GoodCredit =  widget.HTML('<div id=\"img\" style=\"float:left\">'\n","                    '<img style=\"vertical-align:middle\" src=\"./GoodCredit.png\" alt=\"\">'                       \n","                    '</div>')\n","\n","BadCredit =  widget.HTML('<div id=\"img\" style=\"float:left\">'\n","                    '<img style=\"vertical-align:middle\" src=\"./BadCredit.png\" alt=\"\">'                       \n","                    '</div>')"]},{"cell_type":"code","execution_count":6,"metadata":{"trusted":true},"outputs":[],"source":["data_loading_bay = {\"avg_borrowRate\" : [], \"avg_amount_borrowed\" : [], \"num_borrows\" : [], \"num_prev_defaults\" : [], \"default_this_time\" : []}"]},{"cell_type":"code","execution_count":7,"metadata":{"trusted":true},"outputs":[],"source":["def eth_to_dict(input_address):\n","    graph_call = open(\"thing.sh\", \"w\")\n","    address = input_address\n","    variable = '''curl 'https://api.thegraph.com/subgraphs/name/aave/protocol-v2' --data-binary '{\"query\":\"query MyQuery { users(where: {id: \\\\\"''' + address + '''\\\\\"}) { borrowHistory { borrowRate  borrowRateMode  amount  id  timestamp } liquidationCallHistory { collateralAmount  id  timestamp  } } } \",\"variables\":{}}' > call_data.txt -s'''\n","    graph_call.write(r\"{}\".format(variable))\n","    graph_call.close()\n","\n","    os.system(\"bash thing.sh\")\n","\n","    data_loading_bay = {\"avg_borrowRate\" : [], \"avg_amount_borrowed\" : [], \"num_borrows\" : [], \"num_prev_defaults\" : [], \"default_this_time\" : []}\n","\n","    with open(\"call_data.txt\") as json_file:\n","      all_data = json.load(json_file)\n","      data = all_data[\"data\"]\n","      for user in data[\"users\"]:\n","        if user[\"borrowHistory\"] != []:\n","          num_borrows = 0\n","          total_amount = 0\n","          total_borrowRate = 0\n","          num_prev_defaults = 0\n","          for borrow in user[\"borrowHistory\"]:\n","            num_borrows += 1\n","            total_amount += int(borrow[\"amount\"])\n","            total_borrowRate += int(borrow[\"borrowRate\"])\n","            last_borrow_id = borrow[\"id\"]\n","          if user[\"liquidationCallHistory\"] != []:\n","            for default in user[\"liquidationCallHistory\"]:\n","              num_prev_defaults = 0\n","              for _ in user[\"liquidationCallHistory\"]:\n","                num_prev_defaults += 1\n","              # if default[\"id\"] == last_borrow_id:\n","                default_this_time = 1\n","                # num_prev_defaults -= 1\n","              # else:\n","              #   default_this_time = 0\n","          else:\n","            prev_defaults = 0\n","            default_this_time = 0\n","\n","          data_loading_bay[\"avg_borrowRate\"].append(total_borrowRate / num_borrows)\n","          data_loading_bay[\"avg_amount_borrowed\"].append(total_amount / num_borrows)\n","          data_loading_bay[\"num_borrows\"].append(num_borrows)\n","          data_loading_bay[\"num_prev_defaults\"].append(num_prev_defaults)\n","          data_loading_bay[\"default_this_time\"].append(default_this_time)\n","    return data_loading_bay"]},{"cell_type":"markdown","metadata":{},"source":["# CredAAVE"]},{"cell_type":"markdown","metadata":{"tags":[]},"source":["A tool allowing you to check the credit score of accounts for AAVE!\n","\n","Built using GraphQL, AAVE, and PyTorch (Machine Learning)\n","\n","[Video Demo](https://loom.com/)  \n","[GitHub](https://github.com/DicksonWu654/credaave)  \n","\n","You can try out some examples here! I just randomly picked some:\n","- Great Score! 0x0000006daea1723962647b7e189d311d757fb793. They took out loans 24 times, never defaulted\n","- Good Score! 0x6375b32ac8c1ffd97b1eb105659872b2e308502a\n","- Bad Score! 0x0bf66bed1971055c5df68946d5ad094d0a9901b7. They took out >40 loans and defaulted on >30 of them!\n","- Bad Score! 0x57dc4a5d2786cb0fef99fa526b0ff5038e185460\n","\n","You can sample your own by following the instructions here: https://gist.github.com/DicksonWu654/7a7510cbadccca3ebe8bb9597f4376eb\n","\n","Improvements: Train on a much bigger dataset with many more features, label the data to be unsupervised learning, implement state of the art techniques, use explainable AI\n","\n","-------"]},{"cell_type":"code","execution_count":8,"metadata":{"trusted":true},"outputs":[],"source":["path = Path()\n","learn_inf = load_learner(path/'testing3.pkl', cpu=True)\n","txt_input = widgets.Text()\n","out_pl = widgets.Output()\n","lbl_pred = widgets.Label()"]},{"cell_type":"code","execution_count":82,"metadata":{"trusted":true},"outputs":[],"source":["def display_credit(cred):\n","    cred = 1 - cred\n","    cred -= 0.5\n","    cred *= 8\n","    cred = 1 / (1 + math.exp(-cred))\n","    if cred >= 0.9:\n","        print(\"Amazing credit score! This ETH Address only has a {:.2f}% chance of defaulting!\".format((1 - cred) * 100))\n","        display(AmazingCredit)\n","    elif cred >=0.7:\n","        print(\"Good credit score! This ETH Address has a {:.2f}% chance of defaulting!\".format((1 - cred) * 100))\n","        display(GoodCredit)\n","    else:\n","        print (\"Bad credit score! This ETH Address has a {:.2f}% chance of defaulting!\".format((1 - cred) * 100))\n","        display(BadCredit)"]},{"cell_type":"code","execution_count":83,"metadata":{"trusted":true},"outputs":[],"source":["def on_text_change(change):\n","    lbl_pred.value = ''\n","    out_pl.clear_output()\n","    data_loading_bay = eth_to_dict(change)\n","    pred_df = pd.DataFrame(data_loading_bay)\n","    pred_df_true = pred_df.squeeze()\n","    cred = float(learn_inf.predict(pred_df_true)[2])\n","    return display_credit(cred)"]},{"cell_type":"code","execution_count":87,"metadata":{"trusted":true},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"9cba7e17771a46afa56b7f9112893a3d","version_major":2,"version_minor":0},"text/plain":["VBox(children=(Label(value='Input a valid Ethereum address:'), Text(value='0x57dc4a5d2786cb0fef99fa526b0ff5038…"]},"metadata":{},"output_type":"display_data"}],"source":["display(VBox([widgets.Label('Input a valid Ethereum address:'), txt_input, out_pl, lbl_pred]))"]},{"cell_type":"code","execution_count":88,"metadata":{"trusted":true},"outputs":[],"source":["button = widgets.Button(description='Run It!')"]},{"cell_type":"code","execution_count":89,"metadata":{"trusted":true},"outputs":[{"data":{"application/vnd.jupyter.widget-view+json":{"model_id":"2c070e1f7a5740e2b7bc8719951a1d2c","version_major":2,"version_minor":0},"text/plain":["VBox(children=(Button(description='Run It!', style=ButtonStyle()), Output()))"]},"metadata":{},"output_type":"display_data"}],"source":["out = widgets.Output()\n","def on_button_clicked(_):\n","      with out:\n","        out.clear_output()\n","        on_text_change(str(txt_input)[12:-2])\n","button.on_click(on_button_clicked)\n","widgets.VBox([button, out])"]},{"cell_type":"code","execution_count":null,"metadata":{},"outputs":[],"source":[]}],"metadata":{"jupytext":{"split_at_heading":true},"kernelspec":{"display_name":"Python 3 (ipykernel)","language":"python","name":"python3"},"language_info":{"codemirror_mode":{"name":"ipython","version":3},"file_extension":".py","mimetype":"text/x-python","name":"python","nbconvert_exporter":"python","pygments_lexer":"ipython3","version":"3.7.10"},"orig_nbformat":4,"toc":{"base_numbering":1,"nav_menu":{},"number_sections":false,"sideBar":true,"skip_h1_title":true,"title_cell":"Table of Contents","title_sidebar":"Contents","toc_cell":false,"toc_position":{},"toc_section_display":true,"toc_window_display":false}},"nbformat":4,"nbformat_minor":4}