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222 lines
8.6 KiB
ReStructuredText
222 lines
8.6 KiB
ReStructuredText
Integrating OpenAI with Dry's Sample Chat Game
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################################################################
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:author: Russell Ballestrini
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:slug: integrating-openai-with-dry-sample-chat-game
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:date: 2024-02-17 14:11
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:tags: Code, Machine Learning, Game Development
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:status: published
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This tutorial demonstrates enhancing `Dry's Sample Chat Game <https://gitlab.com/luckeyproductions/dry/-/blob/master/Source/Samples/16_Chat/Chat.cpp>`_ by integrating OpenAI's language models, enabling the game to provide intelligent, Machine Learning-driven responses to user queries. Dry, the successor to Urho3D, offers a comprehensive framework for developing 2D and 3D games. Leveraging LLMs within the Dry engine opens up new possibilities.
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Background
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----------
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The Sample Chat game in Dry provides basic messaging functionality where multiple copies of the game client can connect to a server to communicate via text messages. Our aim is to extend this functionality to include responses from OpenAI's language models when messages contain specific triggers, such as "gpt-3".
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Prerequisites
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-------------
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Ensure you have the following before starting:
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- An OpenAI API key.
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- A `configured Dry build environment <https://russell.ballestrini.net/building-dry-and-park-from-source-on-fedora-linux/>`_.
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- Some familiarity with build tooling or at least the ability to copy and paste commands into the terminal.
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Step-by-Step Integration
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------------------------
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Follow these steps to integrate OpenAI with the Sample Chat game:
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1. **Obtain the OpenAI C++ Client**
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Before modifying the chat game, you need to download the necessary files from the OpenAI C++ client repository. Use the following commands to create a directory for these files and download them:
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.. code-block:: bash
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cd ~/git/dry
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mkdir -p Source/ThirdParty/openai
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mkdir -p Source/ThirdParty/openai/nlohmann
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cd Source/ThirdParty/openai
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wget https://raw.githubusercontent.com/olrea/openai-cpp/main/include/openai/openai.hpp
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cd nlohmann
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wget https://raw.githubusercontent.com/olrea/openai-cpp/main/include/openai/nlohmann/json.hpp
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I also found the need to modify the client to code slightly for the JSON import, pardon me if this is ignorant:
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.. code-block:: cpp
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// #include <nlohmann/json.hpp> // nlohmann/json
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#include <Dry/ThirdParty/openai/nlohmann/json.hpp>
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The client requires cURL development files, on Fedora:
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.. code-block:: bash
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sudo dnf install libcurl-devel
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2. **Update the CMake Configuration**
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Note: update ``PROJECT_SOURCE_DIR`` with your file path.
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Apply the following diff to `CMakeLists.txt` to include the OpenAI C++ client as well as cURL in your dry project:
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.. code-block:: diff
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diff --git a/CMakeLists.txt b/CMakeLists.txt
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index a1eff04..0f32bc7 100644
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--- a/CMakeLists.txt
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+++ b/CMakeLists.txt
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@@ -188,6 +188,20 @@ else ()
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endif ()
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file (MAKE_DIRECTORY ${THIRD_PARTY_INCLUDE_DIR})
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+# Find the cURL library
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+find_package(CURL REQUIRED)
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+
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+# Globally link cURL to all targets
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+link_libraries(${CURL_LIBRARIES})
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+
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+# Assuming this is set to your project's root directory
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+set(PROJECT_SOURCE_DIR /home/fox/git/dry)
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+
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+# Create a symbolic link for openai
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+execute_process(COMMAND ${CMAKE_COMMAND} -E create_symlink
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+ ${PROJECT_SOURCE_DIR}/Source/ThirdParty/openai
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+ ${CMAKE_BINARY_DIR}/include/Dry/ThirdParty/openai)
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+
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3. **Modify Sample/16_Chat/chat.cpp file**
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Implement the changes outlined in the diffs below for ``chat.cpp``:
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.. code-block:: diff
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diff --git a/Source/Samples/16_Chat/Chat.cpp b/Source/Samples/16_Chat/Chat.cpp
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index ee7c2b7..9d0e454 100644
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--- a/Source/Samples/16_Chat/Chat.cpp
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+++ b/Source/Samples/16_Chat/Chat.cpp
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@@ -41,6 +41,7 @@
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#include <Dry/UI/Text.h>
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#include <Dry/UI/UI.h>
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#include <Dry/UI/UIEvents.h>
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+#include <Dry/ThirdParty/openai/openai.hpp>
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#include "Chat.h"
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@@ -201,16 +202,58 @@ void Chat::HandleSend(StringHash /*eventType*/, VariantMap& eventData)
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if (serverConnection)
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{
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- // A VectorBuffer object is convenient for constructing a message to send
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- VectorBuffer msg;
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- msg.WriteString(text);
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- // Send the chat message as in-order and reliable
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- serverConnection->SendMessage(MSG_CHAT, true, true, msg);
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+ // Check if the message contains "gpt-3"
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+ if (text.Contains("gpt-3"))
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+ {
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+ // Initialize OpenAI
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+ openai::start();
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+
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+ // Correctly construct the JSON payload as a std::string
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+ std::string payload = std::string(R"({"model": "gpt-3.5-turbo", "messages":[{"role":"user", "content":")") + text.CString() + std::string(R"("}], "max_tokens": 600, "temperature": 0.5})");
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+ nlohmann::json gptResponse;
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+ try {
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+ // Parse the payload to JSON and make the API call
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+ gptResponse = openai::chat().create(nlohmann::json::parse(payload));
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+ } catch (const std::exception& e) {
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+ // Handle JSON parsing errors or API call failures
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+ std::cerr << "Error making API call or parsing response: " << e.what() << '\n';
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+ return;
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+ }
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+
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+ std::string responseText;
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+ try {
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+ // Extract the response text from the JSON response
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+ responseText = gptResponse["choices"][0]["message"]["content"].get<std::string>();
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+ } catch (const std::exception& e) {
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+ // Handle errors in accessing the response content
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+ std::cerr << "Error extracting response text: " << e.what() << '\n';
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+ return;
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+ }
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+
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+ // send the user's message to gpt-3 to the server.
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+ VectorBuffer msg1;
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+ msg1.WriteString(text);
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+ serverConnection->SendMessage(MSG_CHAT, true, true, msg1);
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+
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+ // send the gpt-3 completion to the server.
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+ VectorBuffer msg2;
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+ msg2.WriteString(String(responseText.c_str()));
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+ serverConnection->SendMessage(MSG_CHAT, true, true, msg2);
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+ }
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+ else
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+ {
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+ // Normal chat message handling
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+ VectorBuffer msg;
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+ msg.WriteString(text);
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+ serverConnection->SendMessage(MSG_CHAT, true, true, msg);
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+ }
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+
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// Empty the text edit after sending
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textEdit_->SetText(String::EMPTY);
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}
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}
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4. **Prepare the Build Environment**
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Before running CMake, ensure that any previous build configurations are cleared to avoid conflicts. This might involve deleting the CMake cache file:
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.. code-block:: bash
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rm CMakeCache.txt # If exists
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Then, generate the build configuration:
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.. code-block:: bash
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cmake .. -DCMAKE_BUILD_TYPE=Debug -DRY_64BIT=1
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5. **Build the Chat Game**
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Compile the Sample Chat game with the newly integrated OpenAI C++ client:
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.. code-block:: bash
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make 16_Chat/fast
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Testing the Integration
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-----------------------
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After applying the changes and compiling the game, ensure your OpenAI API key is available to the game:
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.. code-block:: bash
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export OPENAI_API_KEY='your_openai_api_key_here'
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Run the Sample Chat game and try sending a message containing "gpt-3". You should see an intelligent response generated by OpenAI's language model.
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.. code-block:: bash
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./bin/16_Chat
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Remember you'll need at least one instance of the game running as server mode before a client can interact with the LLM.
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That means you need to run ``./bin/16_Chat`` at least twice in two different windows to see the experience.
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What's Next?
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------------
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You've now integrated OpenAI into Dry's Sample Chat game, enhancing it with Machine Learning-driven conversational capabilities. Explore further by customizing triggers, integrating other models using the same OpenAI client, or expanding the game's features.
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I think personally I will try to get the client communicating with vllm likely running openchat.
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Happy coding, and enjoy bringing LLM capabilities to your Dry games!
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.. contents::
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