made significant rework. Console version works unconstrained

AI-Adventure-2bb65e3a4e2f.json

@@ -1,12 +0,0 @@
-{
-  "type": "service_account",
-  "project_id": "ai-adventure",
-  "private_key_id": "2bb65e3a4e2f0c0ef073cb0f10c9c26e1bb1447b",
-  "private_key": "-----BEGIN PRIVATE KEY-----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\nnVir78ePOnyRJzLKm2iql1I=\n-----END PRIVATE KEY-----\n",
-  "client_email": "ai-adventure@appspot.gserviceaccount.com",
-  "client_id": "100390463556501175877",
-  "auth_uri": "https://accounts.google.com/o/oauth2/auth",
-  "token_uri": "https://oauth2.googleapis.com/token",
-  "auth_provider_x509_cert_url": "https://www.googleapis.com/oauth2/v1/certs",
-  "client_x509_cert_url": "https://www.googleapis.com/robot/v1/metadata/x509/ai-adventure%40appspot.gserviceaccount.com"
-}

console_play.py

@@ -3,22 +3,28 @@ from story.utils import *
 from google.cloud import storage
 import json
 from story.story_manager import *
-from generator.tf_local.generator_local import *
+from generator.web.web_generator import *
 import tensorflow as tf
+import textwrap
+
+
+# Set the key
+def console_print(str):
+    LINE_WIDTH=80
+    print((textwrap.fill(str, 80)))
+
 
 if __name__ == '__main__':
-
-    sess = tf.Session()
-    generator = LocalGenerator(sess)
+    generator = WebGenerator("./AI-Adventure-2bb65e3a4e2f.json")
     prompt = "You enter a dungeon with your trusty sword and shield. You are searching for the evil necromancer who killed your family. You've heard that he resides at the bottom of the dungeon, guarded by legions of the undead. You enter the first door and see"
     story_manager = UnconstrainedStoryManager(generator, prompt)
-    print(story_manager.story)
+
+    console_print(str(story_manager.story))
     while(True):
         action = input("> ")
         action = "You " + action
-        print(action)
         result = story_manager.act(action)
-        print(result)
+        console_print(action + result)
 
 
 

cortex/cortex.sh

@@ -1,468 +0,0 @@
-#!/bin/bash
-
-# Copyright 2019 Cortex Labs, Inc.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-
-set -e
-
-####################
-### FLAG PARSING ###
-####################
-
-flag_help=false
-positional_args=()
-
-while [[ $# -gt 0 ]]; do
-  key="$1"
-  case $key in
-    -c|--config)
-    export CORTEX_CONFIG="$2"
-    shift
-    shift
-    ;;
-    -h|--help)
-    flag_help="true"
-    shift
-    ;;
-    *)
-    positional_args+=("$1")
-    shift
-    ;;
-  esac
-done
-
-set -- "${positional_args[@]}"
-positional_args=()
-for i in "$@"; do
-  case $i in
-    -c=*|--config=*)
-    export CORTEX_CONFIG="${i#*=}"
-    shift
-    ;;
-    -h=*|--help=*)
-    flag_help="true"
-    ;;
-    *)
-    positional_args+=("$1")
-    shift
-    ;;
-  esac
-done
-
-set -- "${positional_args[@]}"
-if [ "$flag_help" == "true" ]; then
-  show_help
-  exit 0
-fi
-
-for arg in "$@"; do
-  if [[ "$arg" == -* ]]; then
-    echo "unknown flag: $arg"
-    show_help
-    exit 1
-  fi
-done
-
-#####################
-### CONFIGURATION ###
-#####################
-
-if [ "$CORTEX_CONFIG" != "" ]; then
-  if [ ! -f "$CORTEX_CONFIG" ]; then
-    echo "Cortex config file does not exist: $CORTEX_CONFIG"
-    exit 1
-  fi
-  source $CORTEX_CONFIG
-fi
-
-set -u
-
-export CORTEX_VERSION_STABLE=0.7.3
-
-# Defaults
-export AWS_ACCESS_KEY_ID="${AWS_ACCESS_KEY_ID:-""}"
-
-if [ "$AWS_ACCESS_KEY_ID" = "" ]; then
-  echo -e "\nPlease set AWS_ACCESS_KEY_ID"
-  exit 1
-fi
-
-export AWS_SECRET_ACCESS_KEY="${AWS_SECRET_ACCESS_KEY:-""}"
-
-if [ "$AWS_SECRET_ACCESS_KEY" = "" ]; then
-  echo -e "\nPlease set AWS_SECRET_ACCESS_KEY"
-  exit 1
-fi
-
-export CORTEX_LOG_GROUP="${CORTEX_LOG_GROUP:-cortex}"
-export CORTEX_BUCKET="${CORTEX_BUCKET:-""}"
-export CORTEX_REGION="${CORTEX_REGION:-us-west-2}"
-export CORTEX_ZONES="${CORTEX_ZONES:-""}"
-
-export CORTEX_CLUSTER="${CORTEX_CLUSTER:-cortex}"
-export CORTEX_NODE_TYPE="${CORTEX_NODE_TYPE:-t3.large}"
-export CORTEX_NODES_MIN="${CORTEX_NODES_MIN:-2}"
-export CORTEX_NODES_MAX="${CORTEX_NODES_MAX:-5}"
-export CORTEX_NAMESPACE="${CORTEX_NAMESPACE:-cortex}"
-
-export CORTEX_IMAGE_MANAGER="${CORTEX_IMAGE_MANAGER:-cortexlabs/manager:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_FLUENTD="${CORTEX_IMAGE_FLUENTD:-cortexlabs/fluentd:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_NGINX_BACKEND="${CORTEX_IMAGE_NGINX_BACKEND:-cortexlabs/nginx-backend:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_NGINX_CONTROLLER="${CORTEX_IMAGE_NGINX_CONTROLLER:-cortexlabs/nginx-controller:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_OPERATOR="${CORTEX_IMAGE_OPERATOR:-cortexlabs/operator:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_SPARK="${CORTEX_IMAGE_SPARK:-cortexlabs/spark:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_SPARK_OPERATOR="${CORTEX_IMAGE_SPARK_OPERATOR:-cortexlabs/spark-operator:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_TF_SERVE="${CORTEX_IMAGE_TF_SERVE:-cortexlabs/tf-serve:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_TF_TRAIN="${CORTEX_IMAGE_TF_TRAIN:-cortexlabs/tf-train:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_TF_API="${CORTEX_IMAGE_TF_API:-cortexlabs/tf-api:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_PYTHON_PACKAGER="${CORTEX_IMAGE_PYTHON_PACKAGER:-cortexlabs/python-packager:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_TF_SERVE_GPU="${CORTEX_IMAGE_TF_SERVE_GPU:-cortexlabs/tf-serve-gpu:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_TF_TRAIN_GPU="${CORTEX_IMAGE_TF_TRAIN_GPU:-cortexlabs/tf-train-gpu:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_ONNX_SERVE="${CORTEX_IMAGE_ONNX_SERVE:-cortexlabs/onnx-serve:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_ONNX_SERVE_GPU="${CORTEX_IMAGE_ONNX_SERVE_GPU:-cortexlabs/onnx-serve-gpu:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_CLUSTER_AUTOSCALER="${CORTEX_IMAGE_CLUSTER_AUTOSCALER:-cortexlabs/cluster-autoscaler:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_NVIDIA="${CORTEX_IMAGE_NVIDIA:-cortexlabs/nvidia:$CORTEX_VERSION_STABLE}"
-export CORTEX_IMAGE_METRICS_SERVER="${CORTEX_IMAGE_METRICS_SERVER:-cortexlabs/metrics-server:$CORTEX_VERSION_STABLE}"
-
-export CORTEX_ENABLE_TELEMETRY="${CORTEX_ENABLE_TELEMETRY:-""}"
-
-##########################
-### TOP-LEVEL COMMANDS ###
-##########################
-
-function install_eks() {
-  echo
-  docker run -it --entrypoint /root/install_eks.sh \
-    -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
-    -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
-    -e CORTEX_CLUSTER=$CORTEX_CLUSTER \
-    -e CORTEX_REGION=$CORTEX_REGION \
-    -e CORTEX_NODE_TYPE=$CORTEX_NODE_TYPE \
-    -e CORTEX_NODES_MIN=$CORTEX_NODES_MIN \
-    -e CORTEX_NODES_MAX=$CORTEX_NODES_MAX \
-    $CORTEX_IMAGE_MANAGER
-}
-
-function uninstall_eks() {
-  echo
-  docker run -it --entrypoint /root/uninstall_eks.sh \
-    -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
-    -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
-    -e CORTEX_CLUSTER=$CORTEX_CLUSTER \
-    -e CORTEX_REGION=$CORTEX_REGION \
-    $CORTEX_IMAGE_MANAGER
-}
-
-function install_cortex() {
-  echo
-  docker run -it --entrypoint /root/install_cortex.sh \
-    -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
-    -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
-    -e CORTEX_CLUSTER=$CORTEX_CLUSTER \
-    -e CORTEX_REGION=$CORTEX_REGION \
-    -e CORTEX_NAMESPACE=$CORTEX_NAMESPACE \
-    -e CORTEX_NODE_TYPE=$CORTEX_NODE_TYPE \
-    -e CORTEX_LOG_GROUP=$CORTEX_LOG_GROUP \
-    -e CORTEX_BUCKET=$CORTEX_BUCKET \
-    -e CORTEX_IMAGE_FLUENTD=$CORTEX_IMAGE_FLUENTD \
-    -e CORTEX_IMAGE_NGINX_BACKEND=$CORTEX_IMAGE_NGINX_BACKEND \
-    -e CORTEX_IMAGE_NGINX_CONTROLLER=$CORTEX_IMAGE_NGINX_CONTROLLER \
-    -e CORTEX_IMAGE_OPERATOR=$CORTEX_IMAGE_OPERATOR \
-    -e CORTEX_IMAGE_SPARK=$CORTEX_IMAGE_SPARK \
-    -e CORTEX_IMAGE_SPARK_OPERATOR=$CORTEX_IMAGE_SPARK_OPERATOR \
-    -e CORTEX_IMAGE_TF_SERVE=$CORTEX_IMAGE_TF_SERVE \
-    -e CORTEX_IMAGE_TF_TRAIN=$CORTEX_IMAGE_TF_TRAIN \
-    -e CORTEX_IMAGE_TF_API=$CORTEX_IMAGE_TF_API \
-    -e CORTEX_IMAGE_PYTHON_PACKAGER=$CORTEX_IMAGE_PYTHON_PACKAGER \
-    -e CORTEX_IMAGE_TF_SERVE_GPU=$CORTEX_IMAGE_TF_SERVE_GPU \
-    -e CORTEX_IMAGE_TF_TRAIN_GPU=$CORTEX_IMAGE_TF_TRAIN_GPU \
-    -e CORTEX_IMAGE_ONNX_SERVE=$CORTEX_IMAGE_ONNX_SERVE \
-    -e CORTEX_IMAGE_ONNX_SERVE_GPU=$CORTEX_IMAGE_ONNX_SERVE_GPU \
-    -e CORTEX_IMAGE_CLUSTER_AUTOSCALER=$CORTEX_IMAGE_CLUSTER_AUTOSCALER \
-    -e CORTEX_IMAGE_NVIDIA=$CORTEX_IMAGE_NVIDIA \
-    -e CORTEX_IMAGE_METRICS_SERVER=$CORTEX_IMAGE_METRICS_SERVER \
-    -e CORTEX_ENABLE_TELEMETRY=$CORTEX_ENABLE_TELEMETRY \
-    $CORTEX_IMAGE_MANAGER
-}
-
-function uninstall_operator() {
-  echo
-  docker run -it --entrypoint /root/uninstall_operator.sh \
-    -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
-    -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
-    -e CORTEX_CLUSTER=$CORTEX_CLUSTER \
-    -e CORTEX_REGION=$CORTEX_REGION \
-    -e CORTEX_NAMESPACE=$CORTEX_NAMESPACE \
-    $CORTEX_IMAGE_MANAGER
-}
-
-function info() {
-  echo
-  docker run -it --entrypoint /root/info.sh \
-    -e AWS_ACCESS_KEY_ID=$AWS_ACCESS_KEY_ID \
-    -e AWS_SECRET_ACCESS_KEY=$AWS_SECRET_ACCESS_KEY \
-    -e CORTEX_CLUSTER=$CORTEX_CLUSTER \
-    -e CORTEX_REGION=$CORTEX_REGION \
-    -e CORTEX_NAMESPACE=$CORTEX_NAMESPACE \
-    $CORTEX_IMAGE_MANAGER
-}
-
-################
-### CHECK OS ###
-################
-
-case "$OSTYPE" in
-  darwin*)  PARSED_OS="darwin" ;;
-  linux*)   PARSED_OS="linux" ;;
-  *)        echo -e "\nerror: only mac and linux are supported"; exit 1 ;;
-esac
-
-#############################
-### DEPENDENCY MANAGEMENT ###
-#############################
-
-function check_dep_curl() {
-  if ! command -v curl >/dev/null; then
-    echo -e "\nerror: please install \`curl\`"
-    exit 1
-  fi
-}
-
-function install_cli() {
-  set -e
-
-  check_dep_curl
-
-  echo -e "\nInstalling the Cortex CLI (/usr/local/bin/cortex) ..."
-
-  CORTEX_SH_TMP_DIR="$HOME/.cortex-sh-tmp"
-  rm -rf $CORTEX_SH_TMP_DIR && mkdir -p $CORTEX_SH_TMP_DIR
-  curl -s -o $CORTEX_SH_TMP_DIR/cortex https://s3-us-west-2.amazonaws.com/get-cortex/$CORTEX_VERSION_STABLE/cli/$PARSED_OS/cortex
-  chmod +x $CORTEX_SH_TMP_DIR/cortex
-
-  if [ $(id -u) = 0 ]; then
-    mv -f $CORTEX_SH_TMP_DIR/cortex /usr/local/bin/cortex
-  else
-    ask_sudo
-    sudo mv -f $CORTEX_SH_TMP_DIR/cortex /usr/local/bin/cortex
-  fi
-
-  rm -rf $CORTEX_SH_TMP_DIR
-  echo "✓ Installed the Cortex CLI"
-
-  bash_profile_path=$(get_bash_profile)
-  if [ ! "$bash_profile_path" = "" ]; then
-    if ! grep -Fxq "source <(cortex completion)" "$bash_profile_path"; then
-      echo
-      read -p "Would you like to modify your bash profile ($bash_profile_path) to enable cortex command completion and the cx alias? [Y/n] " -n 1 -r
-      echo
-      if [[ $REPLY =~ ^[Yy]$ ]]; then
-        echo -e "\nsource <(cortex completion)" >> $bash_profile_path
-        echo "✓ Your bash profile ($bash_profile_path) has been updated"
-        echo
-        echo "Note: \`bash_completion\` must be installed on your system for cortex command completion to function properly"
-        echo
-        echo "Command to update your current terminal session:"
-        echo "  source $bash_profile_path"
-      else
-        echo "Your bash profile has not been modified. If you would like to modify it manually, add this line to your bash profile:"
-        echo "  source <(cortex completion)"
-        echo "Note: \`bash_completion\` must be installed on your system for cortex command completion to function properly"
-      fi
-    fi
-  else
-    echo -e "\nIf your would like to enable cortex command completion and the cx alias, add this line to your bash profile:"
-    echo "  source <(cortex completion)"
-    echo "Note: \`bash_completion\` must be installed on your system for cortex command completion to function properly"
-  fi
-}
-
-function uninstall_cli() {
-  set -e
-
-  rm -rf $HOME/.cortex
-
-  if ! command -v cortex >/dev/null; then
-    echo -e "\nThe Cortex CLI is not installed"
-    return
-  fi
-
-  if [[ ! -f /usr/local/bin/cortex ]]; then
-    echo -e "\nThe Cortex CLI was not found at /usr/local/bin/cortex, please uninstall it manually"
-    return
-  fi
-
-  if [ $(id -u) = 0 ]; then
-    rm /usr/local/bin/cortex
-  else
-    ask_sudo
-    sudo rm /usr/local/bin/cortex
-  fi
-  echo -e "\n✓ Uninstalled the Cortex CLI"
-
-  bash_profile_path=$(get_bash_profile)
-  if [ ! "$bash_profile_path" = "" ]; then
-    if grep -Fxq "source <(cortex completion)" "$bash_profile_path"; then
-      echo
-      read -p "Would you like to remove \"source <(cortex completion)\" from your bash profile ($bash_profile_path)? [Y/n] " -n 1 -r
-      echo
-      if [[ $REPLY =~ ^[Yy]$ ]]; then
-        sed '/^source <(cortex completion)$/d' "$bash_profile_path" > "${bash_profile_path}_cortex_modified" && mv -f "${bash_profile_path}_cortex_modified" "$bash_profile_path"
-        echo "✓ Your bash profile ($bash_profile_path) has been updated"
-      fi
-    fi
-  fi
-}
-
-function get_bash_profile() {
-  if [ "$PARSED_OS" = "darwin" ]; then
-    if [ -f $HOME/.bash_profile ]; then
-      echo $HOME/.bash_profile
-      return
-    elif [ -f $HOME/.bashrc ]; then
-      echo $HOME/.bashrc
-      return
-    fi
-  else
-    if [ -f $HOME/.bashrc ]; then
-      echo $HOME/.bashrc
-      return
-    elif [ -f $HOME/.bash_profile ]; then
-      echo $HOME/.bash_profile
-      return
-    fi
-  fi
-
-  echo ""
-}
-
-function ask_sudo() {
-  if ! sudo -n true 2>/dev/null; then
-    echo -e "\nPlease enter your sudo password"
-  fi
-}
-
-function prompt_for_telemetry() {
-  if [ "$CORTEX_ENABLE_TELEMETRY" != "true" ] && [ "$CORTEX_ENABLE_TELEMETRY" != "false" ]; then
-    while true
-    do
-      echo
-      read -p "Would you like to help improve Cortex by anonymously sending error reports and usage stats to the dev team? [Y/n] " -n 1 -r
-      echo
-      if [[ $REPLY =~ ^[Yy]$ ]]; then
-        export CORTEX_ENABLE_TELEMETRY=true
-        break
-      elif [[ $REPLY =~ ^[Nn]$ ]]; then
-        export CORTEX_ENABLE_TELEMETRY=false
-        break
-      fi
-      echo "Unexpected value, please enter \"Y\" or \"n\""
-    done
-  fi
-}
-
-############
-### HELP ###
-############
-
-function show_help() {
-  echo "
-Usage:
-  ./cortex.sh command [sub-command] [flags]
-
-Available Commands:
-  install             install Cortex
-  uninstall           uninstall Cortex
-  update              update Cortex
-  info                information about Cortex
-
-  install cli         install the Cortex CLI
-  uninstall cli       uninstall the Cortex CLI
-
-Flags:
-  -c, --config  path to a Cortex config file
-  -h, --help
-"
-}
-
-######################
-### ARG PROCESSING ###
-######################
-
-arg1=${1:-""}
-arg2=${2:-""}
-arg3=${3:-""}
-
-if [ -z "$arg1" ]; then
-  show_help
-  exit 0
-fi
-
-if [ "$arg1" = "install" ]; then
-  if [ ! "$arg3" = "" ]; then
-    echo -e "\nerror: too many arguments for install command"
-    show_help
-    exit 1
-  elif [ "$arg2" = "" ]; then
-    prompt_for_telemetry && install_eks && install_cortex && info
-  elif [ "$arg2" = "cli" ]; then
-    install_cli
-  elif [ "$arg2" = "" ]; then
-    echo -e "\nerror: missing subcommand for install"
-    show_help
-    exit 1
-  else
-    echo -e "\nerror: invalid subcommand for install: $arg2"
-    show_help
-    exit 1
-  fi
-elif [ "$arg1" = "uninstall" ]; then
-  if [ ! "$arg3" = "" ]; then
-    echo -e "\nerror: too many arguments for uninstall command"
-    show_help
-    exit 1
-  elif [ "$arg2" = "" ]; then
-    uninstall_eks
-  elif [ "$arg2" = "cli" ]; then
-    uninstall_cli
-  elif [ "$arg2" = "" ]; then
-    echo -e "\nerror: missing subcommand for uninstall"
-    show_help
-    exit 1
-  else
-    echo -e "\nerror: invalid subcommand for uninstall: $arg2"
-    show_help
-    exit 1
-  fi
-elif [ "$arg1" = "update" ]; then
-  if [ ! "$arg2" = "" ]; then
-    echo -e "\nerror: too many arguments for get command"
-    show_help
-    exit 1
-  else
-    uninstall_operator && install_cortex
-  fi
-elif [ "$arg1" = "info" ]; then
-  if [ ! "$arg2" = "" ]; then
-    echo -e "\nerror: too many arguments for get command"
-    show_help
-    exit 1
-  else
-    info
-  fi
-else
-  echo -e "\nerror: unknown command: $arg1"
-  show_help
-  exit 1
-fi

cortex/cortex.yaml

@@ -1,11 +0,0 @@
-# cortex.yaml
-- kind: deployment
-  name: text
-- kind: api
-  name: generator
-  model: s3://cortex-examples/gpt-2/774M/1539234541.zip
-  request_handler: encoder.py
-  compute:
-    gpu: 1
-    min_replicas: 1
-    max_replicas: 1

cortex/encoder.py

@@ -1,129 +0,0 @@
-# This file includes code which was modified from https://github.com/openai/gpt-2
-
-import tensorflow as tf
-import os
-import json
-import regex as re
-from functools import lru_cache
-import requests
-import boto3
-
-
-@lru_cache()
-def bytes_to_unicode():
-    bs = (
-        list(range(ord("!"), ord("~") + 1))
-        + list(range(ord("¡"), ord("¬") + 1))
-        + list(range(ord("®"), ord("ÿ") + 1))
-    )
-    cs = bs[:]
-    n = 0
-    for b in range(2 ** 8):
-        if b not in bs:
-            bs.append(b)
-            cs.append(2 ** 8 + n)
-            n += 1
-    cs = [chr(n) for n in cs]
-    return dict(zip(bs, cs))
-
-
-def get_pairs(word):
-    pairs = set()
-    prev_char = word[0]
-    for char in word[1:]:
-        pairs.add((prev_char, char))
-        prev_char = char
-    return pairs
-
-
-class Encoder:
-    def __init__(self, encoder, bpe_merges, errors="replace"):
-        self.encoder = encoder
-        self.decoder = {v: k for k, v in self.encoder.items()}
-        self.errors = errors
-        self.byte_encoder = bytes_to_unicode()
-        self.byte_decoder = {v: k for k, v in self.byte_encoder.items()}
-        self.bpe_ranks = dict(zip(bpe_merges, range(len(bpe_merges))))
-        self.cache = {}
-        self.pat = re.compile(
-            r"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""
-        )
-
-    def bpe(self, token):
-        if token in self.cache:
-            return self.cache[token]
-        word = tuple(token)
-        pairs = get_pairs(word)
-
-        if not pairs:
-            return token
-
-        while True:
-            bigram = min(pairs, key=lambda pair: self.bpe_ranks.get(pair, float("inf")))
-            if bigram not in self.bpe_ranks:
-                break
-            first, second = bigram
-            new_word = []
-            i = 0
-            while i < len(word):
-                try:
-                    j = word.index(first, i)
-                    new_word.extend(word[i:j])
-                    i = j
-                except:
-                    new_word.extend(word[i:])
-                    break
-
-                if word[i] == first and i < len(word) - 1 and word[i + 1] == second:
-                    new_word.append(first + second)
-                    i += 2
-                else:
-                    new_word.append(word[i])
-                    i += 1
-            new_word = tuple(new_word)
-            word = new_word
-            if len(word) == 1:
-                break
-            else:
-                pairs = get_pairs(word)
-        word = " ".join(word)
-        self.cache[token] = word
-        return word
-
-    def encode(self, text):
-        bpe_tokens = []
-        for token in re.findall(self.pat, text):
-            token = "".join(self.byte_encoder[b] for b in token.encode("utf-8"))
-            bpe_tokens.extend(self.encoder[bpe_token] for bpe_token in self.bpe(token).split(" "))
-        return bpe_tokens
-
-    def decode(self, tokens):
-        text = "".join([self.decoder[token] for token in tokens])
-        text = bytearray([self.byte_decoder[c] for c in text]).decode("utf-8", errors=self.errors)
-        return text
-
-
-def get_encoder():
-    s3 = boto3.client("s3")
-    encoder = json.load(
-        s3.get_object(Bucket="cortex-examples", Key="gpt-2/774M/encoder.json")["Body"]
-    )
-    bpe_data = (
-        s3.get_object(Bucket="cortex-examples", Key="gpt-2/774M/vocab.bpe")["Body"]
-        .read()
-        .decode("utf-8")
-    )
-    bpe_merges = [tuple(merge_str.split()) for merge_str in bpe_data.split("\n")[1:-1]]
-    return Encoder(encoder=encoder, bpe_merges=bpe_merges)
-
-
-encoder = get_encoder()
-
-
-def pre_inference(sample, metadata):
-    context = encoder.encode(sample["text"])
-    return {"context": [context]}
-
-
-def post_inference(prediction, metadata):
-    return {encoder.decode(prediction["response"]["sample"])}

generator/tf/models/774M/.gitignore

@@ -0,0 +1,2 @@
+model.ckpt.data-00000-of-00001
+

generator/tf/models/774M/hparams.json

@@ -0,0 +1,7 @@
+{
+  "n_vocab": 50257,
+  "n_ctx": 1024,
+  "n_embd": 1280,
+  "n_head": 20,
+  "n_layer": 36
+}

generator/tf/src/sample.py

@@ -1,6 +1,6 @@
 import tensorflow as tf
 
-import gpt2.src.model as model
+from src.model import *
 
 def top_k_logits(logits, k):
     if k == 0:
@@ -30,11 +30,11 @@ def sample_sequence(*, hparams, length, start_token=None, batch_size=None, conte
         context = tf.fill([batch_size, 1], start_token)
 
     def step(hparams, tokens, past=None):
-        lm_output = model.model(hparams=hparams, X=tokens, past=past, reuse=tf.AUTO_REUSE)
+        lm_output = model(hparams=hparams, X=tokens, past=past, reuse=tf.AUTO_REUSE)
 
         logits = lm_output['logits'][:, :, :hparams.n_vocab]
         presents = lm_output['present']
-        presents.set_shape(model.past_shape(hparams=hparams, batch_size=batch_size))
+        presents.set_shape(past_shape(hparams=hparams, batch_size=batch_size))
         return {
             'logits': logits,
             'presents': presents,
@@ -69,7 +69,7 @@ def sample_sequence(*, hparams, length, start_token=None, batch_size=None, conte
                 context,
             ],
             shape_invariants=[
-                tf.TensorShape(model.past_shape(hparams=hparams, batch_size=batch_size)),
+                tf.TensorShape(past_shape(hparams=hparams, batch_size=batch_size)),
                 tf.TensorShape([batch_size]),
                 tf.TensorShape([batch_size, None]),
             ],

generator/tf_local/models/117M/.gitignore

@@ -1 +0,0 @@
-model*

generator/tf_local/models/117M/hparams.json

@@ -1,7 +0,0 @@
-{
-  "n_vocab": 50257,
-  "n_ctx": 1024,
-  "n_embd": 768,
-  "n_head": 12,
-  "n_layer": 12
-}

generator/web/web_generator.py

@@ -0,0 +1,44 @@
+from generator.tf.src.encoder import *
+import googleapiclient.discovery
+
+pos_action_starts = ["You attack", "You tell", "You use", "You go"]
+project = "ai-adventure"
+model = "generator_v1"
+version = "version2"
+
+class WebGenerator():
+
+    def __init__(self, credentials_file):
+        os.environ['GOOGLE_APPLICATION_CREDENTIALS'] = credentials_file
+        model_path = './generator/tf/models/117M'
+        self.enc = get_encoder(model_path)
+
+    def predict(self, context_tokens):
+        service = googleapiclient.discovery.build('ml', 'v1')
+        name = 'projects/{}/models/{}'.format(project, model)
+        instance = context_tokens
+
+        if version is not None:
+            name += '/versions/{}'.format(version)
+
+        response = service.projects().predict(
+            name=name,
+            body={'instances': [{'context': instance}]}
+        ).execute()
+
+        if 'error' in response:
+            raise RuntimeError(response['error'])
+
+        return response['predictions']
+
+    def generate(self, prompt):
+        while (True):
+            context_tokens = self.enc.encode(prompt)
+            try:
+                pred = self.predict(context_tokens)
+                pred = pred[0]["output"][len(context_tokens):]
+                output = self.enc.decode(pred)
+                return output
+            except:
+                print("generate request failed, trying again")
+                continue

main.py

@@ -134,37 +134,6 @@ def about():
     return render_template('about.html')
 
 
-def cache_file(seed, prompt_num, choices, response, tag):
-    return
-    # blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag
-    # for action in choices:
-    #     blob_file_name = blob_file_name + str(action)
-    # blob = bucket.blob(blob_file_name)
-    #
-    # blob.upload_from_string(response)
-    #
-    # print("File ", blob_file_name, " cached")
-
-
-def retrieve_from_cache(seed, prompt_num, choices, tag):
-    return None
-    # blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag
-    #
-    # for action in choices:
-    #     blob_file_name = blob_file_name + str(action)
-    #
-    # blob = bucket.blob(blob_file_name)
-    #
-    # if blob.exists(storage_client):
-    #     result = blob.download_as_string().decode("utf-8")
-    #     print(blob_file_name, " found in cache")
-    # else:
-    #     result = None
-    #     print(blob_file_name, " not found in cache")
-    #
-    # return result
-
-
 @app.route('/generate', methods=['POST'])
 def story_request():
     print("****Generating Story****")

other/caching.py

@@ -0,0 +1,44 @@
+from flask import g
+from flask import session
+import os
+import googleapiclient.discovery
+from story.utils import *
+from google.cloud import storage
+import json
+from flask import Flask, render_template, request, abort
+from generator import StoryGenerator
+import gpt2.src.encoder as encoder
+
+# Model/Cache Info
+storage_client = storage.Client()
+bucket = storage_client.get_bucket("dungeon-cache")
+
+
+def cache_file(seed, prompt_num, choices, response, tag):
+
+    blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag
+    for action in choices:
+        blob_file_name = blob_file_name + str(action)
+    blob = bucket.blob(blob_file_name)
+
+    blob.upload_from_string(response)
+
+    print("File ", blob_file_name, " cached")
+
+
+def retrieve_from_cache(seed, prompt_num, choices, tag):
+    blob_file_name = "prompt" + str(prompt_num) + "/seed" + str(seed) + "/" + tag
+
+    for action in choices:
+        blob_file_name = blob_file_name + str(action)
+
+    blob = bucket.blob(blob_file_name)
+
+    if blob.exists(storage_client):
+        result = blob.download_as_string().decode("utf-8")
+        print(blob_file_name, " found in cache")
+    else:
+        result = None
+        print(blob_file_name, " not found in cache")
+
+    return result

story/story_manager.py

@@ -1,5 +1,6 @@
 from story.utils import *
 
+
 class Story():
 
     def __init__(self, story_start):
@@ -28,19 +29,20 @@ class Story():
             story_list.append(self.actions[i])
             story_list.append(self.results[i])
 
-        return sum(story_list)
+        return "".join(story_list)
 
 
 class UnconstrainedStoryManager():
 
     def __init__(self, generator, story_prompt):
+        self.generator = generator
+
         block = self.generator.generate(story_prompt)
         block = cut_trailing_sentence(block)
         block = story_replace(block)
         story_start = story_prompt + block
 
         self.story = Story(story_start)
-        self.generator = generator
 
     def act(self, action_choice):