17 changed files with 198 additions and 1194 deletions
--- a/.env
+++ b/.env
@ -1,7 +0,0 @@
 TOKEN=###TOKEN###
 TRAINING_DAYS=###TRAINING_DAYS###
 TIMEFRAME=###TIMEFRAME###
 MODEL=###MODEL###
 REGION=EU
 DATA_PROVIDER=###DATA_PROVIDER###
 CG_API_KEY=###CG_API_KEY###
--- a/.gitignore
+++ b/.gitignore
@ -1,19 +0,0 @@
 .DS_Store
 __pycache__
 *.pyc
 logs/*
 .allorad
 .cache
 inference-data
 worker-data
 /data
 **/*.venv*
 **/.cache
 **/env_file
 **/.gitkeep*
 **/*.csv
 **/*.pkl
 **/*.zip
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@ -1,18 +0,0 @@
 Any contribution that you make to this repository will
 be under the Apache 2 License, as dictated by that
 [license](http://www.apache.org/licenses/LICENSE-2.0.html):
 ~~~
 5. Submission of Contributions. Unless You explicitly state otherwise,
   any Contribution intentionally submitted for inclusion in the Work
   by You to the Licensor shall be under the terms and conditions of
   this License, without any additional terms or conditions.
   Notwithstanding the above, nothing herein shall supersede or modify
   the terms of any separate license agreement you may have executed
   with Licensor regarding such Contributions.
 ~~~
 Contributors must sign-off each commit by adding a `Signed-off-by: ...`
 line to commit messages to certify that they have the right to submit
 the code they are contributing to the project according to the
 [Developer Certificate of Origin (DCO)](https://developercertificate.org/).
--- a/6
+++ b/6
@ -1,7 +1,5 @@
-FROM python:3.11-slim AS project_env
+# Use an official Python runtime as the base image
-
+FROM amd64/python:3.9-buster as project_env
 # Install curl
 RUN apt-get update && apt-get install -y curl
 # Set the working directory in the container
 WORKDIR /app
--- a/201
+++ b/201
@ -1,201 +0,0 @@
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--- a/README.md
+++ b/README.md
@ -1,112 +0,0 @@
 # Basic Price Prediction Node
 This repository provides an example [Allora network](https://docs.allora.network/) worker node, designed to offer price predictions. The primary objective is to demonstrate the use of a basic inference model running within a dedicated container, showcasing its integration with the Allora network infrastructure to contribute valuable inferences.
 ## Components
 - **Worker**: The node that publishes inferences to the Allora chain.
 - **Inference**: A container that conducts inferences, maintains the model state, and responds to internal inference requests via a Flask application. This node operates with a basic linear regression model for price predictions.
 - **Updater**: A cron-like container designed to update the inference node's data by daily fetching the latest market information from the data provider, ensuring the model stays current with new market trends.
 Check the `docker-compose.yml` file for the detailed setup of each component.
 ## Docker-Compose Setup
 A complete working example is provided in the `docker-compose.yml` file.
 ### Steps to Setup
 1. **Clone the Repository**
 2. **Copy and Populate Model Configuration environment file**
    Copy the example .env.example file and populate it with your variables:
    ```sh
    cp .env.example .env
    ```
    Here are the currently accepted configurations:
    - TOKEN
    Must be one in ('ETH','SOL','BTC','BNB','ARB'). 
    Note: if you are using `Binance` as the data provider, any token could be used.
    If you are using Coingecko, you should add its `coin_id` in the [token_map here](https://github.com/allora-network/basic-coin-prediction-node/blob/main/updater.py#L107). Find [more info here](https://docs.coingecko.com/reference/simple-price) and the [list here](https://docs.google.com/spreadsheets/d/1wTTuxXt8n9q7C4NDXqQpI3wpKu1_5bGVmP9Xz0XGSyU/edit?usp=sharing).
    - TRAINING_DAYS
    Must be an `int` >= 1. 
    Represents how many days of historical data to use. 
    - TIMEFRAME
    This should be in this form: `10min`, `1h`, `1d`, `1m`, etc.
    Note: For Coingecko, Data granularity (candle's body) is automatic - [see here](https://docs.coingecko.com/reference/coins-id-ohlc). To avoid downsampling, it is recommanded to use with Coingecko:
        - TIMEFRAME >= 30m if TRAINING_DAYS <= 2
        - TIMEFRAME >= 4h if TRAINING_DAYS <= 30
        - TIMEFRAME >= 4d if TRAINING_DAYS >= 31
    - MODEL
    Must be one in ('LinearRegression','SVR','KernelRidge','BayesianRidge'). 
    You can easily add support for any other models by [adding it here](https://github.com/allora-network/basic-coin-prediction-node/blob/main/model.py#L133).
    - REGION
    Used for the Binance API. This should be in this form: `US`, `EU`, etc.
    - DATA_PROVIDER
    Must be `binance` or `coingecko`. Feel free to add support for other data providers to personalize your model!
    - CG_API_KEY
    This is your `Coingecko` API key, if you've set `DATA_PROVIDER=coingecko`.
 3. **Copy and Populate Worker Configuration**
    Copy the example configuration file and populate it with your variables:
    ```sh
    cp config.example.json config.json
    ```
 4. **Initialize Worker**
    Run the following commands from the project's root directory to initialize the worker:
    ```sh
    chmod +x init.config
    ./init.config
    ```
    These commands will:
    - Automatically create Allora keys for your worker.
    - Export the needed variables from the created account to be used by the worker node, bundle them with your provided `config.json`, and pass them to the node as environment variables.
 5. **Faucet Your Worker Node**
    You can find the offchain worker node's address in `./worker-data/env_file` under `ALLORA_OFFCHAIN_ACCOUNT_ADDRESS`. [Add faucet funds](https://docs.allora.network/devs/get-started/setup-wallet#add-faucet-funds) to your worker's wallet before starting it.
 6. **Start the Services**
    Run the following command to start the worker node, inference, and updater nodes:
    ```sh
    docker compose up --build
    ```
    To confirm that the worker successfully sends the inferences to the chain, look for the following log:
    ```
    {"level":"debug","msg":"Send Worker Data to chain","txHash":<tx-hash>,"time":<timestamp>,"message":"Success"}
    ```
 ## Testing Inference Only
 This setup allows you to develop your model without the need to bring up the offchain worker or the updater. To test the inference model only:
 1. Run the following command to start the inference node:
    ```sh
    docker compose up --build inference
    ```
    Wait for the initial data load.
 2. Send requests to the inference model. For example, request ETH price inferences:
    ```sh
    curl http://127.0.0.1:8000/inference/ETH
    ```
    Expected response:
    ```json
    {"value":"2564.021586281073"}
    ```
 3. Update the node's internal state (download pricing data, train, and update the model):
    ```sh
    curl http://127.0.0.1:8000/update
    ```
    Expected response:
    ```sh
    0
    ```
--- a/app.py
+++ b/app.py
@ -1,28 +1,43 @@
 import json
-from flask import Flask, Response
+import pickle
-from model import download_data, format_data, train_model, get_inference
+import pandas as pd
-from config import model_file_path, TOKEN, TIMEFRAME, TRAINING_DAYS, REGION, DATA_PROVIDER
+import numpy as np
-
+from datetime import datetime
 from flask import Flask, jsonify, Response
 from model import download_data, format_data, train_model
 from config import model_file_path
 app = Flask(__name__)
 def update_data():
    """Download price data, format data and train model."""
-    files = download_data(TOKEN, TRAINING_DAYS, REGION, DATA_PROVIDER)
+    download_data()
-    format_data(files, DATA_PROVIDER)
+    format_data()
-    train_model(TIMEFRAME)
+    train_model()
 def get_eth_inference():
    """Load model and predict current price."""
    with open(model_file_path, "rb") as f:
        loaded_model = pickle.load(f)
    now_timestamp = pd.Timestamp(datetime.now()).timestamp()
    X_new = np.array([now_timestamp]).reshape(-1, 1)
    current_price_pred = loaded_model.predict(X_new)
    return current_price_pred[0]
@app.route("/inference/<string:token>")
 def generate_inference(token):
    """Generate inference for given token."""
-    if not token or token.upper() != TOKEN:
+    if not token or token != "ETH":
        error_msg = "Token is required" if not token else "Token not supported"
        return Response(json.dumps({"error": error_msg}), status=400, mimetype='application/json')
    try:
-        inference = get_inference(token.upper(), TIMEFRAME, REGION, DATA_PROVIDER)
+        inference = get_eth_inference()
        return Response(str(inference), status=200)
    except Exception as e:
        return Response(json.dumps({"error": str(e)}), status=500, mimetype='application/json')
--- a/config.json
+++ b/config.json
@ -3,21 +3,39 @@
        "addressKeyName": "###WALLET###",
        "addressRestoreMnemonic": "###MNEMONIC###",
        "alloraHomeDir": "",
-        "gas": "auto",
+        "gas": "1000000",
-        "gasAdjustment": 1.5,
+        "gasAdjustment": 1.0,
        "nodeRpc": "###RPC_URL###",
        "maxRetries": 10,
-        "delay": 20,
+        "delay": 30,
-        "submitTx": true
+        "submitTx": false
    },
    "worker": [
        {
-            "topicId": ###TOPIC###,
+            "topicId": 1,
            "inferenceEntrypointName": "api-worker-reputer",
            "loopSeconds": 5,
            "parameters": {
                "InferenceEndpoint": "http://inference:8000/inference/{Token}",
-                "Token": "###TOKEN###"
+                "Token": "ETH"
            }
        },
        {
            "topicId": 2,
            "inferenceEntrypointName": "api-worker-reputer",
            "loopSeconds": 5,
            "parameters": {
                "InferenceEndpoint": "http://inference:8000/inference/{Token}",
                "Token": "ETH"
            }
        },
        {
            "topicId": 7,
            "inferenceEntrypointName": "api-worker-reputer",
            "loopSeconds": 5,
            "parameters": {
                "InferenceEndpoint": "http://inference:8000/inference/{Token}",
                "Token": "ETH"
            }
        }
    ]
--- a/config.py
+++ b/config.py
@ -1,21 +1,5 @@
 import os
 from dotenv import load_dotenv
 # Load environment variables from .env file
 load_dotenv()
 app_base_path = os.getenv("APP_BASE_PATH", default=os.getcwd())
 data_base_path = os.path.join(app_base_path, "data")
 model_file_path = os.path.join(data_base_path, "model.pkl")
 TOKEN = os.getenv("TOKEN").upper()
 TRAINING_DAYS = os.getenv("TRAINING_DAYS")
 TIMEFRAME = os.getenv("TIMEFRAME")
 MODEL = os.getenv("MODEL")
 REGION = os.getenv("REGION").lower()
 if REGION in ["us", "com", "usa"]:
    REGION = "us"
 else:
    REGION = "com"
 DATA_PROVIDER = os.getenv("DATA_PROVIDER").lower()
 CG_API_KEY = os.getenv("CG_API_KEY", default=None)
--- a/docker-compose.yml
+++ b/docker-compose.yml
@ -1,22 +1,21 @@
 services:
  inference:
-    container_name: inference
+    container_name: inference-basic-eth-pred
    env_file:
      - .env
    build: .
    command: python -u /app/app.py
    ports:
      - "8000:8000"
    healthcheck:
-      test: ["CMD", "curl", "-f", "http://inference:8000/inference/${TOKEN}"]
+      test: ["CMD", "curl", "-f", "http://localhost:8000/inference/ETH"]
      interval: 10s
      timeout: 5s
      retries: 12
    volumes:
      - ./inference-data:/app/data
    restart: always
  updater:
-    container_name: updater
+    container_name: updater-basic-eth-pred
    build: .
    environment:
      - INFERENCE_API_ADDRESS=http://inference:8000
@ -30,10 +29,11 @@ services:
    depends_on:
      inference:
        condition: service_healthy
    restart: always
  worker:
    container_name: worker
-    image: alloranetwork/allora-offchain-node:v0.3.0
+    image: alloranetwork/allora-offchain-node:latest
    volumes:
      - ./worker-data:/data
    depends_on:
@ -41,6 +41,7 @@ services:
        condition: service_healthy
    env_file:
      - ./worker-data/env_file
    restart: always
 volumes:
  inference-data:
--- a/init.config
+++ b/init.config
@ -1,4 +1,4 @@
-#!/bin/bash
+#!/usr/bin/env bash
 set -e
@ -25,7 +25,7 @@ if [ -n "$mnemonic" ]; then
    echo "NAME=$nodeName" >> ./worker-data/env_file
    echo "ENV_LOADED=true" >> ./worker-data/env_file
    echo "wallet mnemonic already provided by you, loading config.json . Please proceed to run docker compose"
-    exit 1
+    exit 0
 fi
 if [ ! -f ./worker-data/env_file ]; then
@ -36,7 +36,7 @@ ENV_LOADED=$(grep '^ENV_LOADED=' ./worker-data/env_file | cut -d '=' -f 2)
 if [ "$ENV_LOADED" = "false" ]; then
    json_content=$(cat ./config.json)
    stringified_json=$(echo "$json_content" | jq -c .)
-    docker run -it --entrypoint=bash -v $(pwd)/worker-data:/data -v $(pwd)/scripts:/scripts -e NAME="${nodeName}" -e ALLORA_OFFCHAIN_NODE_CONFIG_JSON="${stringified_json}" alloranetwork/allora-chain:v0.4.0 -c "bash /scripts/init.sh"
+    docker run -it --entrypoint=bash -v $(pwd)/worker-data:/data -v $(pwd)/scripts:/scripts -e NAME="${nodeName}" -e ALLORA_OFFCHAIN_NODE_CONFIG_JSON="${stringified_json}" alloranetwork/allora-chain:latest -c "bash /scripts/init.sh"
    echo "config.json saved to ./worker-data/env_file"
 else
    echo "config.json is already loaded, skipping the operation. You can set ENV_LOADED variable to false in ./worker-data/env_file to reload the config.json"
--- a/logs_parser.py
+++ b/logs_parser.py
@ -47,9 +47,6 @@ def parse_logs(timeout):
                        if current_retry == max_retry:
                            print(f"Max Retry Reached: {data}", flush=True)
                            return False, "Max Retry Reached"
                    elif data.get("message") == "Error getting latest open worker nonce on topic":
                        print(f"Error: {data}", flush=True)
                        return False, "Error getting latest open worker nonce on topic"
        except Exception as e:
            print(f"Exception occurred: {e}", flush=True)
--- a/model.py
+++ b/model.py
@ -1,55 +1,47 @@
 import json
 import os
 import pickle
 from zipfile import ZipFile
 from datetime import datetime
 import pandas as pd
-from sklearn.kernel_ridge import KernelRidge
+import numpy as np
-from sklearn.linear_model import BayesianRidge, LinearRegression
+from sklearn.model_selection import train_test_split
-from sklearn.svm import SVR
+from sklearn import linear_model
-from updater import download_binance_daily_data, download_binance_current_day_data, download_coingecko_data, download_coingecko_current_day_data
+from updater import download_binance_monthly_data, download_binance_daily_data
-from config import data_base_path, model_file_path, TOKEN, MODEL, CG_API_KEY
+from config import data_base_path, model_file_path
-binance_data_path = os.path.join(data_base_path, "binance")
+binance_data_path = os.path.join(data_base_path, "binance/futures-klines")
-coingecko_data_path = os.path.join(data_base_path, "coingecko")
+training_price_data_path = os.path.join(data_base_path, "eth_price_data.csv")
 training_price_data_path = os.path.join(data_base_path, "price_data.csv")
-def download_data_binance(token, training_days, region):
+def download_data():
-    files = download_binance_daily_data(f"{token}USDT", training_days, region, binance_data_path)
+    cm_or_um = "um"
-    print(f"Downloaded {len(files)} new files")
+    symbols = ["ETHUSDT"]
-    return files
+    intervals = ["1d"]
-
+    years = ["2020", "2021", "2022", "2023", "2024"]
-def download_data_coingecko(token, training_days):
+    months = ["01", "02", "03", "04", "05", "06", "07", "08", "09", "10", "11", "12"]
-    files = download_coingecko_data(token, training_days, coingecko_data_path, CG_API_KEY)
+    download_path = binance_data_path
-    print(f"Downloaded {len(files)} new files")
+    download_binance_monthly_data(
-    return files
+        cm_or_um, symbols, intervals, years, months, download_path
    )
    print(f"Downloaded monthly data to {download_path}.")
    current_datetime = datetime.now()
    current_year = current_datetime.year
    current_month = current_datetime.month
    download_binance_daily_data(
        cm_or_um, symbols, intervals, current_year, current_month, download_path
    )
    print(f"Downloaded daily data to {download_path}.")
-def download_data(token, training_days, region, data_provider):
+def format_data():
-    if data_provider == "coingecko":
+    files = sorted([x for x in os.listdir(binance_data_path)])
        return download_data_coingecko(token, int(training_days))
    elif data_provider == "binance":
        return download_data_binance(token, training_days, region)
    else:
        raise ValueError("Unsupported data provider")
 def format_data(files, data_provider):
    if not files:
        print("Already up to date")
        return
    if data_provider == "binance":
        files = sorted([x for x in os.listdir(binance_data_path) if x.startswith(f"{TOKEN}USDT")])
    elif data_provider == "coingecko":
        files = sorted([x for x in os.listdir(coingecko_data_path) if x.endswith(".json")])
    # No files to process
    if len(files) == 0:
        return
    price_df = pd.DataFrame()
    if data_provider == "binance":
    for file in files:
        zip_file_path = os.path.join(binance_data_path, file)
@ -74,75 +66,36 @@ def format_data(files, data_provider):
            "taker_volume",
            "taker_volume_usd",
        ]
-            df.index = [pd.Timestamp(x + 1, unit="ms").to_datetime64() for x in df["end_time"]]
+        df.index = [pd.Timestamp(x + 1, unit="ms") for x in df["end_time"]]
        df.index.name = "date"
        price_df = pd.concat([price_df, df])
    price_df.sort_index().to_csv(training_price_data_path)
    elif data_provider == "coingecko":
        for file in files:
            with open(os.path.join(coingecko_data_path, file), "r") as f:
                data = json.load(f)
                df = pd.DataFrame(data)
                df.columns = [
                    "timestamp",
                    "open",
                    "high",
                    "low",
                    "close"
                ]
                df["date"] = pd.to_datetime(df["timestamp"], unit="ms")
                df.drop(columns=["timestamp"], inplace=True)
                df.set_index("date", inplace=True)
                price_df = pd.concat([price_df, df])
            price_df.sort_index().to_csv(training_price_data_path)
-def load_frame(frame, timeframe):
+def train_model():
-    print(f"Loading data...")
+    # Load the eth price data
    df = frame.loc[:,['open','high','low','close']].dropna()
    df[['open','high','low','close']] = df[['open','high','low','close']].apply(pd.to_numeric)
    df['date'] = frame['date'].apply(pd.to_datetime)
    df.set_index('date', inplace=True)
    df.sort_index(inplace=True)
    return df.resample(f'{timeframe}', label='right', closed='right', origin='end').mean()
 def train_model(timeframe):
    # Load the price data
    price_data = pd.read_csv(training_price_data_path)
-    df = load_frame(price_data, timeframe)
+    df = pd.DataFrame()
    # Convert 'date' to a numerical value (timestamp) we can use for regression
    df["date"] = pd.to_datetime(price_data["date"])
    df["date"] = df["date"].map(pd.Timestamp.timestamp)
-    if df.empty:
+    df["price"] = price_data[["open", "close", "high", "low"]].mean(axis=1)
        raise ValueError("No data available after loading and formatting. Check the data source or timeframe.")
-    print(df.tail())
+    # Reshape the data to the shape expected by sklearn
    x = df["date"].values.reshape(-1, 1)
    y = df["price"].values.reshape(-1, 1)
-    y_train = df['close'].shift(-1).dropna().values
+    # Split the data into training set and test set
-    X_train = df[:-1]
+    x_train, _, y_train, _ = train_test_split(x, y, test_size=0.2, random_state=0)
    if X_train.empty or len(y_train) == 0:
        raise ValueError("Training data is empty. Ensure there is enough data for training.")
    print(f"Training data shape: {X_train.shape}, {y_train.shape}")
    # Define the model
    if MODEL == "LinearRegression":
        model = LinearRegression()
    elif MODEL == "SVR":
        model = SVR()
    elif MODEL == "KernelRidge":
        model = KernelRidge()
    elif MODEL == "BayesianRidge":
        model = BayesianRidge()
    # Add more models here
    else:
        raise ValueError("Unsupported model")
    # Train the model
-    model.fit(X_train, y_train)
+    print("Training model...")
    model = linear_model.Lasso(alpha=0.1)
    model.fit(x_train, y_train)
    print("Model trained.")
    # create the model's parent directory if it doesn't exist
    os.makedirs(os.path.dirname(model_file_path), exist_ok=True)
@ -152,22 +105,3 @@ def train_model(timeframe):
        pickle.dump(model, f)
    print(f"Trained model saved to {model_file_path}")
 def get_inference(token, timeframe, region, data_provider):
    """Load model and predict current price."""
    with open(model_file_path, "rb") as f:
        loaded_model = pickle.load(f)
    # Get current price
    if data_provider == "coingecko":
        X_new = load_frame(download_coingecko_current_day_data(token, CG_API_KEY), timeframe)
    else:
        X_new = load_frame(download_binance_current_day_data(f"{TOKEN}USDT", region), timeframe)
    print(X_new.tail())
    print(X_new.shape)
    current_price_pred = loaded_model.predict(X_new)
    return current_price_pred[0]
--- a/playbook.yml
+++ b/playbook.yml
@ -1,470 +0,0 @@
 - name: Allora deployment playbook
  hosts: all
  become: true
  vars:
    ansible_python_interpreter: /usr/bin/python3.11
    ipfs_url: https://bafybeigpiwl3o73zvvl6dxdqu7zqcub5mhg65jiky2xqb4rdhfmikswzqm.ipfs.w3s.link/manifest.json
  tasks:
    - name: Append command to .bash_history
      ansible.builtin.blockinfile:
        path: "~/.bash_history"
        create: true
        block: |
          #1724983098
          cd basic-coin-prediction-node/ ; docker compose logs -f
          #1724983099
          docker logs worker -f
          cd basic-coin-prediction-node/ ; docker compose up 
        marker: ""
        mode: '0644'
    - name: Set locale to C.UTF-8
      ansible.builtin.command:
        cmd: localectl set-locale LANG=C.UTF-8
      changed_when: false
    - name: Create APT configuration file to assume yes
      ansible.builtin.copy:
        dest: /etc/apt/apt.conf.d/90forceyes
        content: |
          APT::Get::Assume-Yes "true";
        mode: '0644'
    - name: Update /etc/bash.bashrc
      ansible.builtin.blockinfile:
        path: /etc/bash.bashrc
        block: |
          export HISTTIMEFORMAT='%F, %T '
          export HISTSIZE=10000
          export HISTFILESIZE=10000
          shopt -s histappend
          export PROMPT_COMMAND='history -a'
          export HISTCONTROL=ignoredups
          export LANG=C.UTF-8
          export LC_ALL=C.UTF-8
          alias ls='ls --color=auto'
          shopt -s cmdhist
    - name: Ensure ~/.inputrc exists
      ansible.builtin.file:
        path: /root/.inputrc
        state: touch
        mode: '0644'
    - name: Update ~/.inputrc
      ansible.builtin.blockinfile:
        path: ~/.inputrc
        block: |
          "\e[A": history-search-backward
          "\e[B": history-search-forward
    - name: Ensure ~/.nanorc exists
      ansible.builtin.file:
        path: /root/.nanorc
        state: touch
        mode: '0644'
    - name: Update ~/.nanorc
      ansible.builtin.blockinfile:
        path: ~/.nanorc
        block: |
          set nohelp
          set tabsize 4
          set tabstospaces
          set autoindent
          set positionlog
          set backup
          set backupdir /tmp/
          set locking
          include /usr/share/nano/*.nanorc
    - name: Set hostname
      ansible.builtin.shell: |
        hostnamectl set-hostname {{ serverid }}
        echo "127.0.1.1 {{ serverid }}" >> /etc/hosts
      changed_when: false
    - name: Update apt cache
      ansible.builtin.apt:
        update_cache: true
      register: apt_update_result
      retries: 5
      delay: 50
      until: apt_update_result is succeeded
    - name: Upgrade packages
      ansible.builtin.apt:
        upgrade: dist
        force_apt_get: true
        autoremove: true
      register: apt_upgrade_result
      retries: 5
      delay: 50
      until: apt_upgrade_result is succeeded
 #    - name: Install packages
 #      ansible.builtin.apt:
 #        name:
 #          - ca-certificates
 #          - zlib1g-dev
 #          - libncurses5-dev
 #          - libgdbm-dev
 #          - libnss3-dev
 #          - curl
 #          - jq
 #          - git
 #          - zip
 #          - wget
 #          - make
 #          - python3
 #          - python3-pip
 #          - iftop
 #        state: present
 #        update_cache: true
 #      async: "{{ 60 * 20 }}"
 #      poll: 30
 #    - name: Check no-proxy ipfs access
 #      ansible.builtin.shell: |
 #        curl -s -w "%{http_code}" -o response.json {{ ipfs_url }}
 #      register: noproxy_check
 #      changed_when: false
 #      failed_when: noproxy_check.stdout != "200"
 #
 #    - name: Check proxy ipfs access
 #      ansible.builtin.shell: |
 #        curl -s -w "%{http_code}" -o response.json -x {{ proxy }} {{ ipfs_url }}
 #      register: proxy_check
 #      changed_when: false
 #      failed_when: proxy_check.stdout != "200"
 #    - name: Install Docker
 #      ansible.builtin.shell: curl -fsSL https://get.docker.com | bash
 #      changed_when: false
 #      async: "{{ 60 * 5 }}"
 #      poll: 30
 #    - name: Update Docker daemon journald logging
 #      ansible.builtin.copy:
 #        dest: /etc/docker/daemon.json
 #        content: |
 #          {
 #            "log-driver": "journald"
 #          }
 #        mode: '0644'
 #
 #    - name: Restart Docker
 #      ansible.builtin.service:
 #        name: docker
 #        state: restarted
 #
 #    - name: Update journald log SystemMaxUse=2G configuration
 #      ansible.builtin.lineinfile:
 #        path: /etc/systemd/journald.conf
 #        line: 'SystemMaxUse=2G'
 #        insertafter: EOF
 #        create: true
 #        mode: '0644'
 #
 #    - name: Restart journald
 #      ansible.builtin.service:
 #        name: systemd-journald
 #        state: restarted
    - name: Docker login
      ansible.builtin.shell: docker login -u "{{ docker_username }}" -p "{{ docker_password }}"
      register: docker_login_result
      changed_when: false
      failed_when: "'Login Succeeded' not in docker_login_result.stdout"
    - name: Clone repository
      ansible.builtin.git:
        repo: https://gitea.vvzvlad.xyz/vvzvlad/allora
        dest: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
        version: "{{ git_version }}"
        force: true
      async: "{{ 60 * 15 }}"
      poll: 30
    - name: Update environment variables
      ansible.builtin.shell: |
        ./update.sh WALLET "{{ wallet }}"
        ./update.sh MNEMONIC "{{ mnemonic }}"
        ./update.sh RPC_URL "{{ rpc_url }}"
        ./update.sh TOKEN "{{ token }}"
        ./update.sh TOPIC "{{ topic }}"
        ./update.sh TRAINING_DAYS "{{ training_days }}"
        ./update.sh TIMEFRAME "{{ timeframe }}"
        ./update.sh MODEL "{{ model }}"
        ./update.sh DATA_PROVIDER "{{ data_provider }}"
        ./update.sh CG_API_KEY "{{ cg_api_key }}"
      args:
        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
      changed_when: false
    - name: Init config
      ansible.builtin.shell: ./init.config ; true
      args:
        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
      changed_when: false
    - name: Build docker compose
      ansible.builtin.command: docker compose build -q
      args:
        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
      environment:
        COMPOSE_INTERACTIVE_NO_CLI: 'true'
      changed_when: false
      async: "{{ 60 * 45 }}"
      poll: "{{ 60 * 5 }}"
 #    - name: Docker pre-up
 #      ansible.builtin.command: docker compose up -d
 #      args:
 #        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
 #      environment:
 #        COMPOSE_INTERACTIVE_NO_CLI: 'true'
 #      changed_when: false
 #      async: "{{ 60 * 80 }}"
 #      poll: "{{ 60 * 5 }}"
 #    - name: Check Docker container status
 #      ansible.builtin.shell: >
 #        if [ $(docker ps -q | wc -l) -eq $(docker ps -a -q | wc -l) ]; then
 #          echo "all_running";
 #        else
 #          echo "not_all_running";
 #        fi
 #      register: container_status
 #      retries: 10
 #      delay: 30
 #      until: container_status.stdout.find("all_running") != -1
 #
 #    - name: Docker stop (pre-up)
 #      ansible.builtin.command: docker compose stop
 #      args:
 #        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
 #      environment:
 #        COMPOSE_INTERACTIVE_NO_CLI: 'true'
 #      changed_when: false
 #
 #    - name: Check external IP before
 #      ansible.builtin.command: curl https://ifconfig.me
 #      register: ip_before
 #      changed_when: false
 #
 #    - name: Validate IP address
 #      ansible.builtin.assert:
 #        that:
 #          - ip_before.stdout | ansible.utils.ipaddr
 #        fail_msg: "The returned value is not a valid IP address."
 #        success_msg: "The returned value is a valid IP address."
 #    - name: Download tun2socks
 #      ansible.builtin.get_url:
 #        url: https://github.com/xjasonlyu/tun2socks/releases/download/v2.5.2/tun2socks-linux-amd64.zip
 #        dest: /tmp/tun2socks-linux-amd64.zip
 #        mode: '0644'
 #      async: "{{ 60 * 5 }}"
 #      poll: 30
 #
 #    - name: Unzip tun2socks
 #      ansible.builtin.unarchive:
 #        src: /tmp/tun2socks-linux-amd64.zip
 #        dest: /usr/local/sbin/
 #        remote_src: true
 #        mode: '0755'
 #
 #    - name: Create proxy file
 #      ansible.builtin.copy:
 #        content: "{{ proxy }}"
 #        dest: /root/proxy
 #        mode: '0644'
 #
 #    - name: Create tun2socks systemd service
 #      ansible.builtin.copy:
 #        dest: /etc/systemd/system/tun2socks.service
 #        content: |
 #          [Unit]
 #          Description=Tun2Socks gateway
 #          After=network.target
 #          Wants=network.target
 #
 #          [Service]
 #          User=root
 #          Type=simple
 #          RemainAfterExit=true
 #          ExecStartPre=/bin/sh -c 'ip route add $(cat /root/proxy | grep -oP "(?<=@)[0-9.]+(?=:)" )/32 via $(ip route | grep -oP "(?<=default via )[0-9.]+")'
 #          ExecStart=/bin/sh -c '/usr/local/sbin/tun2socks-linux-amd64 --device tun0 --proxy $(cat /root/proxy)'
 #          ExecStopPost=/bin/sh -c 'ip route del $(cat /root/proxy | grep -oP "(?<=@)[0-9.]+(?=:)" )/32 via $(ip route | grep -oP "(?<=default via )[0-9.]+")'
 #          Restart=always
 #
 #          [Install]
 #          WantedBy=multi-user.target
 #        mode: '0644'
 #
 #    - name: Create network configuration for tun0
 #      ansible.builtin.copy:
 #        dest: /etc/systemd/network/10-proxy.network
 #        content: |
 #          [Match]
 #          Name=tun0
 #
 #          [Network]
 #          Address=10.20.30.1/24
 #
 #          [Route]
 #          Gateway=0.0.0.0
 #        mode: '0644'
 #
 #    - name: Enable and start tun2socks service
 #      ansible.builtin.systemd:
 #        name: tun2socks
 #        enabled: true
 #        state: started
 #
 #    - name: Reload network configuration
 #      ansible.builtin.command: networkctl reload
 #      changed_when: false
 #
 #    - name: Restart tun2socks service
 #      ansible.builtin.systemd:
 #        name: tun2socks
 #        state: restarted
    - name: Check RPC availability
      ansible.builtin.uri:
        url: "{{ rpc_url }}/health?"
        method: GET
        return_content: true
        timeout: 30
      register: rpc_url_response
      retries: 3
      delay: 120
      failed_when:
        - rpc_url_response.status != 200
        - rpc_url_response.json is not none and rpc_url_response.json is not defined
    - name: Check Binance URL availability
      ansible.builtin.uri:
        url: "https://api.binance.com/api/v3/klines?symbol=BTCUSDT&interval=1M&limit=1"
        method: GET
        return_content: true
      register: binance_url_response
      retries: 3
      delay: 60
      failed_when:
        - binance_url_response.status != 200
        - binance_url_response.json is not none and binance_url_response.json is not defined
 #    - name: Get balance for the wallet
 #      retries: 3
 #      delay: 30
 #      ansible.builtin.shell: |
 #        response=$(curl --silent --location --request GET "https://allora-api.testnet.allora.network/cosmos/bank/v1beta1/balances/{{ wallet }}") && \
 #        echo "$response" && \
 #        uallo_balance=$(echo "$response" | jq -r '.balances[] | select(.denom == "uallo") | .amount // 0') && \
 #        echo "uallo_balance: $uallo_balance" && \
 #        if [ "$uallo_balance" -gt 100000 ]; then
 #          echo "Balance {{ wallet }} > 100000"
 #        else
 #          echo "Balance {{ wallet }} <  100000"
 #          exit 1
 #        fi
 #      register: wallet_balance_check
 #      failed_when: wallet_balance_check.rc != 0
 #    - name: Check external IP after
 #      ansible.builtin.command: curl https://ifconfig.me
 #      register: ip_after
 #      changed_when: false
 #
 #    - name: Validate IP address
 #      ansible.builtin.assert:
 #        that:
 #          - ip_after.stdout | ansible.utils.ipaddr
 #        fail_msg: "The returned value is not a valid IP address."
 #        success_msg: "The returned value is a valid IP address."
 #
 #    - name: Show IPs
 #      ansible.builtin.debug:
 #        msg: "External IP before: {{ ip_before.stdout }}, External IP after: {{ ip_after.stdout }}"
 #
 #    - name: Compare external IPs
 #      ansible.builtin.fail:
 #        msg: "External IP before and after should not be the same"
 #      when: ip_before.stdout == ip_after.stdout
    - name: Docker up
      ansible.builtin.command: docker compose up -d
      args:
        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
      environment:
        COMPOSE_INTERACTIVE_NO_CLI: 'true'
      changed_when: false
      async: "{{ 60 * 80 }}"
      poll: "{{ 60 * 5 }}"
    - name: Check Docker containers status
      ansible.builtin.shell: >
        if [ $(docker ps -q | wc -l) -eq $(docker ps -a -q | wc -l) ]; then
          echo "all_running";
        else
          echo "not_all_running";
        fi
      register: container_status
      retries: 10
      delay: 30
      until: container_status.stdout.find("all_running") != -1
    - name: Check "not have enough balance"
      ansible.builtin.command: docker logs {{ item }} 2>&1
      register: docker_logs_check
      changed_when: false
      failed_when: '"not have enough balance" in docker_logs_check.stdout'
      with_items:
        - worker
        - worker-1
        - worker-2
    - name: Check updater endpoint
      ansible.builtin.shell: |
        response=$(curl --silent --location --request GET http://localhost:8000/update) && \
        if [ "$response" != "0" ]; then
          echo "Updater endpoint check failed: $response != 0"
          exit 1
        fi
      register: updater_shell_response
      retries: 2
      delay: 60
      until: updater_shell_response.rc == 0
      changed_when: false
    - name: Check inference endpoint
      ansible.builtin.shell: |
        response=$(curl --silent --location --request GET http://localhost:8000/inference/{{ token }}) && \
        status=$(curl -o /dev/null -s -w "%{http_code}\\n" http://localhost:8000/inference/{{ token }}) && \
        if [ "$status" -ne 200 ] || ! echo "$response" | grep -qE '^[0-9]+(\.[0-9]+)?$'; then
          echo "Inference endpoint check failed: status $status, response $response"
          exit 1
        fi
      register: inference_shell_response
      retries: 2
      delay: 60
      failed_when: inference_shell_response.rc != 0
      changed_when: false
 #    - name: Wait success send
 #      ansible.builtin.shell: |
 #        python3 logs_parser.py 80
 #      args:
 #        chdir: "{{ ansible_env.HOME }}/basic-coin-prediction-node"
 #      register: docker_logs_check
 #      changed_when: false
 #      failed_when: docker_logs_check.rc != 0
    - name: Remove docker login credentials
      ansible.builtin.file:
        path: /root/.docker/config.json
        state: absent
--- a/requirements.txt
+++ b/requirements.txt
@ -1,9 +1,7 @@
 flask[async]
 gunicorn[gthread]
-numpy
+numpy==1.26.2
-pandas
+pandas==2.1.3
-Requests
+Requests==2.32.0
-aiohttp
+scikit_learn==1.3.2
-multiprocess
+werkzeug>=3.0.3 # not directly required, pinned by Snyk to avoid a vulnerability
 scikit_learn
 python-dotenv
--- a/update.sh
+++ b/update.sh
@ -1,20 +1,22 @@
 #!/usr/bin/env bash
-if [ "$#" -ne 2 ]; then
+if [ "$#" -ne 3 ]; then
-    echo "Usage: $0 <PARAMETER> <NEW_VALUE>"
+    echo "Usage: $0 <mnemonic> <wallet> <rpc_url>"
    exit 1
 fi
-PARAMETER=$1
+MNEMONIC=$1
-NEW_VALUE=$2
+WALLET=$2
 RPC_URL=$3
-# Список файлов
+# List of files
 FILES=(
    "./config.json"
    ".env"
 )
 for FILE in "${FILES[@]}"; do
    EXPANDED_FILE=$(eval echo "$FILE")
-    sed -i "s|###$PARAMETER###|$NEW_VALUE|g" "$EXPANDED_FILE"
+    sed -i "s|###MNEMONIC###|$MNEMONIC|g" "$EXPANDED_FILE"
    sed -i "s|###WALLET###|$WALLET|g" "$EXPANDED_FILE"
    sed -i "s|###RPC_URL###|$RPC_URL|g" "$EXPANDED_FILE"
 done
--- a/updater.py
+++ b/updater.py
@ -1,175 +1,59 @@
 import os
 from datetime import date, timedelta
 import pathlib
 import time
 import requests
 from requests.adapters import HTTPAdapter
 from urllib3.util import Retry
 from concurrent.futures import ThreadPoolExecutor
 import pandas as pd
 import json
 # Define the retry strategy
 retry_strategy = Retry(
    total=4,  # Maximum number of retries
    backoff_factor=2, # Exponential backoff factor (e.g., 2 means 1, 2, 4, 8 seconds, ...)
    status_forcelist=[429, 500, 502, 503, 504],  # HTTP status codes to retry on
 )
 # Create an HTTP adapter with the retry strategy and mount it to session
 adapter = HTTPAdapter(max_retries=retry_strategy)
 # Create a new session object
 session = requests.Session()
 session.mount('http://', adapter)
 session.mount('https://', adapter)
 files = []
 # Function to download the URL, called asynchronously by several child processes
-def download_url(url, download_path, name=None):
+def download_url(url, download_path):
-    try:
+    target_file_path = os.path.join(download_path, os.path.basename(url)) 
-        global files
+    if os.path.exists(target_file_path):
-        if name:
+        # print(f"File already exists: {url}")
            file_name = os.path.join(download_path, name)
        else:
            file_name = os.path.join(download_path, os.path.basename(url))
        dir_path = os.path.dirname(file_name)
        pathlib.Path(dir_path).mkdir(parents=True, exist_ok=True) 
        if os.path.isfile(file_name):
            # print(f"{file_name} already exists")
        return
-        # Make a request using the session object
+    
-        response = session.get(url)
+    response = requests.get(url)
    if response.status_code == 404:
-            print(f"File does not exist: {url}")
+        # print(f"File not exist: {url}")
-        elif response.status_code == 200:
+        pass
            with open(file_name, 'wb') as f:
                f.write(response.content)
            # print(f"Downloaded: {url} to {file_name}")
            files.append(file_name)
            return
    else:
-            print(f"Failed to download {url}")
+
        # create the entire path if it doesn't exist
        os.makedirs(os.path.dirname(target_file_path), exist_ok=True)
        with open(target_file_path, "wb") as f:
            f.write(response.content)
        # print(f"Downloaded: {url} to {target_file_path}")
 def download_binance_monthly_data(
    cm_or_um, symbols, intervals, years, months, download_path
 ):
    # Verify if CM_OR_UM is correct, if not, exit
    if cm_or_um not in ["cm", "um"]:
        print("CM_OR_UM can be only cm or um")
        return
-    except Exception as e:
+    base_url = f"https://data.binance.vision/data/futures/{cm_or_um}/monthly/klines"
        print(str(e))
 # Function to generate a range of dates
 def daterange(start_date, end_date):
    for n in range(int((end_date - start_date).days)):
        yield start_date + timedelta(n)
 # Function to download daily data from Binance
 def download_binance_daily_data(pair, training_days, region, download_path):
    base_url = f"https://data.binance.vision/data/spot/daily/klines"
    end_date = date.today()
    start_date = end_date - timedelta(days=int(training_days))
    global files
    files = []
    # Main loop to iterate over all the arrays and launch child processes
    with ThreadPoolExecutor() as executor:
-        print(f"Downloading data for {pair}")
+        for symbol in symbols:
-        for single_date in daterange(start_date, end_date):
+            for interval in intervals:
-            url = f"{base_url}/{pair}/1m/{pair}-1m-{single_date}.zip"
+                for year in years:
                    for month in months:
                        url = f"{base_url}/{symbol}/{interval}/{symbol}-{interval}-{year}-{month}.zip"
                        executor.submit(download_url, url, download_path)
    return files
-
+def download_binance_daily_data(
-def download_binance_current_day_data(pair, region):
+    cm_or_um, symbols, intervals, year, month, download_path
-    limit = 1000
+):
-    base_url = f'https://api.binance.{region}/api/v3/klines?symbol={pair}&interval=1m&limit={limit}'
+    if cm_or_um not in ["cm", "um"]:
-
+        print("CM_OR_UM can be only cm or um")
-    # Make a request using the session object
+        return
-    response = session.get(base_url)
+    base_url = f"https://data.binance.vision/data/futures/{cm_or_um}/daily/klines"
    response.raise_for_status()
    resp = str(response.content, 'utf-8').rstrip()
    columns = ['start_time','open','high','low','close','volume','end_time','volume_usd','n_trades','taker_volume','taker_volume_usd','ignore']
    df = pd.DataFrame(json.loads(resp),columns=columns)
    df['date'] = [pd.to_datetime(x+1,unit='ms') for x in df['end_time']]
    df['date'] = df['date'].apply(pd.to_datetime)
    df[["volume", "taker_volume", "open", "high", "low", "close"]] = df[["volume", "taker_volume", "open", "high", "low", "close"]].apply(pd.to_numeric)
    return df.sort_index()
 def get_coingecko_coin_id(token):
    token_map = {
        'ETH': 'ethereum',
        'SOL': 'solana',
        'BTC': 'bitcoin',
        'BNB': 'binancecoin',
        'ARB': 'arbitrum',
        # Add more tokens here
    }
    token = token.upper()
    if token in token_map:
        return token_map[token]
    else:
        raise ValueError("Unsupported token")
 def download_coingecko_data(token, training_days, download_path, CG_API_KEY):
    if training_days <= 7:
        days = 7
    elif training_days <= 14:
        days = 14
    elif training_days <= 30:
        days = 30
    elif training_days <= 90:
        days = 90
    elif training_days <= 180:
        days = 180
    elif training_days <= 365:
        days = 365
    else:
        days = "max"
    print(f"Days: {days}")
    coin_id = get_coingecko_coin_id(token)
    print(f"Coin ID: {coin_id}")
    # Get OHLC data from Coingecko
    url = f'https://api.coingecko.com/api/v3/coins/{coin_id}/ohlc?vs_currency=usd&days={days}&api_key={CG_API_KEY}'
    global files
    files = []
    with ThreadPoolExecutor() as executor:
-        print(f"Downloading data for {coin_id}")
+        for symbol in symbols:
-        name = os.path.basename(url).split("?")[0].replace("/", "_") + ".json"
+            for interval in intervals:
-        executor.submit(download_url, url, download_path, name)
+                for day in range(1, 32):  # Assuming days range from 1 to 31
-    
+                    url = f"{base_url}/{symbol}/{interval}/{symbol}-{interval}-{year}-{month:02d}-{day:02d}.zip"
-    return files
+                    executor.submit(download_url, url, download_path)
 def download_coingecko_current_day_data(token, CG_API_KEY):
    coin_id = get_coingecko_coin_id(token)
    print(f"Coin ID: {coin_id}")
    url = f'https://api.coingecko.com/api/v3/coins/{coin_id}/ohlc?vs_currency=usd&days=1&api_key={CG_API_KEY}'
    # Make a request using the session object
    response = session.get(url)
    response.raise_for_status()
    resp = str(response.content, 'utf-8').rstrip()
    columns = ['timestamp','open','high','low','close']
    df = pd.DataFrame(json.loads(resp), columns=columns)
    df['date'] = [pd.to_datetime(x,unit='ms') for x in df['timestamp']]
    df['date'] = df['date'].apply(pd.to_datetime)
    df[["open", "high", "low", "close"]] = df[["open", "high", "low", "close"]].apply(pd.to_numeric)
    return df.sort_index()