前言
現在Chat GPT功能越來越強了,幾乎你想問實際問題它都能給你回答。
正好,小組結課的 Android專案 有一個解夢的功能。正好呼叫chatGpt的Api來實現。
下面就來簡單實現在Andorid專案中打造一個簡易的聊天機器人。
先貼個效果, 還沒進行美化:
1.建立一個Andorid專案
這裡就不在詳細地介紹如何建立一個Andorid專案了。谷歌上很多文章,比如官網示例:
https://developer.android.com/training/basics/firstapp/creati...
2.在 build.gradle 中新增依賴
這是用到的依賴
implementation 'com.google.android.material:material:1.7.0'
implementation 'com.android.volley:volley:1.2.0'
implementation 'com.fasterxml.jackson.datatype:jackson-datatype-jdk8:2.9.3'
compileOnly 'org.projectlombok:lombok:1.18.4'
annotationProcessor 'org.projectlombok:lombok:1.18.4'
implementation 'org.apache.commons:commons-lang3:3.6'
3.在 AndroidManifest.xml 中新增聯網許可權
<uses-permission android:name="android.permission.INTERNET"/>
4. 註冊OpenAI api
來到 OpenAI api 註冊賬號,並生成 SECRET KEY
記得儲存好,之後會用到。
5.編寫xml介面檔案
在res/layout下新建activity_chat.xml檔案
<?xml version="1.0" encoding="utf-8"?>
<RelativeLayout xmlns:android="http://schemas.android.com/apk/res/android"
xmlns:app="http://schemas.android.com/apk/res-auto"
xmlns:tools="http://schemas.android.com/tools"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:background="@color/grey">
<ScrollView
android:layout_width="match_parent"
android:layout_height="match_parent"
android:layout_above="@id/idTILQuery"
android:layout_alignParentTop="true"
android:padding="5dp"
android:layout_marginTop="5dp"
android:layout_marginStart="5dp"
android:layout_marginEnd="5dp"
android:layout_marginBottom="5dp">
<LinearLayout
android:layout_width="match_parent"
android:layout_height="match_parent"
android:orientation="vertical">
<!-- text view for displaying question-->
<TextView
android:id="@+id/idTVQuestion"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:layout_marginTop="30dp"
android:padding="4dp"
android:text="Question"
android:textColor="@color/purple_700"
android:textSize="17sp"/>
<!-- text view for displaying response-->
<TextView
android:id="@+id/idTVResponse"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:layout_marginTop="5dp"
android:padding="4dp"
android:text="Response"
android:textColor="@color/purple_700"
android:textSize="15sp"/>
</LinearLayout>
</ScrollView>
<!-- text field for asking question-->
<com.google.android.material.textfield.TextInputLayout
android:id="@+id/idTILQuery"
android:layout_width="match_parent"
android:layout_height="wrap_content"
android:layout_alignParentBottom="true"
android:layout_margin="5dp"
app:endIconMode="custom"
app:endIconDrawable="@drawable/send"
android:hint="Enter your query"
android:padding="5dp"
android:textColorHint="@color/black"
app:hintTextColor="@color/black">
<com.google.android.material.textfield.TextInputEditText
android:id="@+id/idEdtQuery"
android:layout_width="match_parent"
android:layout_height="match_parent"
android:background="@color/grey"
android:ems="10"
android:imeOptions="actionSend"
android:importantForAutofill="no"
android:inputType="textEmailAddress"
android:textColor="@color/black"
android:textColorHint="@color/black"
android:textSize="14sp" />
</com.google.android.material.textfield.TextInputLayout>
</RelativeLayout>
一個簡單的頁面如下
5.編寫Activity檔案
繫結控制元件
首先,我們先建立了三個控制元件顯示內容:問題、響應、使用者輸入。
用 setContentView 繫結xml檔案,並使用 findViewById 給三個控制元件初始化
public class ChatActivity extends AppCompatActivity {
TextView responseTV;
TextView questionTV;
TextInputLayout queryEdt;
@Override
protected void onCreate(Bundle savedInstanceState) {
DynamicColors.applyToActivityIfAvailable(this);
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_chat);
// initializing
responseTV = findViewById(R.id.idTVResponse);
questionTV = findViewById(R.id.idTVQuestion);
queryEdt = findViewById(R.id.idTILQuery);
}
}
監聽傳送按鈕
其次,我們需要監聽傳送按鈕
,當使用者點選後傳送後,請求chatGpt。並顯示 Please wait..
,讓使用者等待請求結果
@Override
protected void onCreate(Bundle savedInstanceState) {
DynamicColors.applyToActivityIfAvailable(this);
super.onCreate(savedInstanceState);
setContentView(R.layout.activity_chat);
// initializing variables on below line.
responseTV = findViewById(R.id.idTVResponse);
questionTV = findViewById(R.id.idTVQuestion);
queryEdt = findViewById(R.id.idTILQuery);
queryEdt.setEndIconOnClickListener(new View.OnClickListener() {
@Override
public void onClick(View view) {
responseTV.setText("Please wait..");
if (queryEdt.getEditText().getText().toString().length() > 0) {
getResponse(queryEdt.getEditText().getText().toString());
} else {
Toast.makeText(ChatActivity.this, "Please enter your query..", Toast.LENGTH_SHORT).show();
}
}
});
}
對 HttpURLConnection 設定代理
之後。我們應該對api進行請求了。由於眾所周知的原因,我們需要對 HttpURLConnection 設定代理:
假設當前的代理在192.168.2.197,7890埠
新建ProxiedHurlStack類, 填上代理伺服器的地址和埠。
public class ProxiedHurlStack extends HurlStack {
@Override
protected HttpURLConnection createConnection(URL url) throws IOException {
// Start the connection by specifying a proxy server
Proxy proxy = new Proxy(Type.HTTP,
InetSocketAddress.createUnresolved("192.168.2.197", 7890));//the proxy server(Can be your laptop ip or company proxy)
HttpURLConnection returnThis = (HttpURLConnection) url
.openConnection(proxy);
return returnThis;
}
}
新建響應實體
根據OpenAI API Reference, 響應如下:
{
"id": "chatcmpl-123",
"object": "chat.completion",
"created": 1677652288,
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": "\n\nHello there, how may I assist you today?",
},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 9,
"completion_tokens": 12,
"total_tokens": 21
}
}
所以,我們只需要獲取到 content
欄位, 就能我們和收到ChatGPT聊天的結果了。
對ChatGpt返回的響應,建立實體跟其對應
@Data
@AllArgsConstructor
@NoArgsConstructor
@JsonIgnoreProperties(ignoreUnknown = true)
public class ChatGptResponse {
private String id;
private String object;
private Long created;
private List<Choice> choices;
}
@Data
@AllArgsConstructor
@NoArgsConstructor
@JsonIgnoreProperties(ignoreUnknown = true)
public class Choice implements Serializable {
private String index;
private String finish_reason;
private Message message;
}
@Data
@AllArgsConstructor
@NoArgsConstructor
@JsonIgnoreProperties(ignoreUnknown = true)
public class Message implements Serializable {
private String role;
private String content;
}
發起請求
之後,檢視OpenAI API Reference, 根據文件對api進行請求。這裡請求的模型是ChatGpt3.5。
記得在下面的程式碼中填寫你的SecretKey
private void getResponse(String query) {
try {
questionTV.setText(query);
RequestQueue requestQueue = Volley.newRequestQueue(this, new ProxiedHurlStack());
String URL = "https://api.openai.com/v1/chat/completions";
JSONObject jsonBody = new JSONObject();
jsonBody.put("model", "gpt-3.5-turbo");
JSONArray array = new JSONArray();
JSONObject jsonObject = new JSONObject();
jsonObject.put("role", "user");
jsonObject.put("content", query);
array.put(jsonObject);
jsonBody.put("messages", array);
final String requestBody = jsonBody.toString();
StringRequest stringRequest = new StringRequest(Request.Method.POST, URL, new Response.Listener<String>() {
@Override
public void onResponse(String response) {
Log.i("VOLLEY", response);
}
}, new Response.ErrorListener() {
@Override
public void onErrorResponse(VolleyError error) {
Log.i("VOLLEY", String.valueOf(error));
}
}) {
@Override
public String getBodyContentType() {
return "application/json; charset=utf-8";
}
@Override
public Map<String, String> getHeaders() throws AuthFailureError {
Map<String, String> params = new HashMap<String, String>();
params.put("Content-Type", "application/json");
params.put("Authorization", "Bearer yourSecretKey");
return params;
}
@Override
public byte[] getBody() throws AuthFailureError {
try {
return requestBody == null ? null : requestBody.getBytes("utf-8");
} catch (UnsupportedEncodingException uee) {
VolleyLog.wtf("Unsupported Encoding while trying to get the bytes of %s using %s", requestBody, "utf-8");
return null;
}
}
@Override
protected Response<String> parseNetworkResponse(NetworkResponse response) {
String responseString = new String(response.data, StandardCharsets.UTF_8);
// 建立ObjectMapper物件。
ObjectMapper mapper = new ObjectMapper();
// Json格式字串轉Java物件。
try {
ChatGptResponse javaEntity = mapper.readValue(responseString, ChatGptResponse.class);
String responseMsg = javaEntity.getChoices().get(0).getMessage().getContent();
runOnUiThread(new Runnable() {
@Override
public void run() {
responseTV.setText(responseMsg);
}
});
} catch (JsonProcessingException e) {
throw new RuntimeException(e);
} catch (IOException e) {
throw new RuntimeException(e);
}
return Response.success(responseString, HttpHeaderParser.parseCacheHeaders(response));
}
};
stringRequest.setRetryPolicy(new RetryPolicy() {
@Override
public int getCurrentTimeout() {
return 50000;
}
@Override
public int getCurrentRetryCount() {
return 50000;
}
@Override
public void retry(VolleyError error) throws VolleyError {
Log.i("VOLLEY", String.valueOf(error));
}
});
requestQueue.add(stringRequest);
} catch (JSONException e) {
e.printStackTrace();
}
}
我們在請求頭上填上我們的 SecretKey
作為認證資訊。
等待 ChatGpt 響應後,把響應的 byte[]
轉換為Java物件。
之後將資訊顯示在螢幕上。
目前我只取了響應的 content 資訊, 所以對話不是連續的,對接不了上文。
之後可以再參考 文件 將聊天做成連續的。
每個賬戶有 18美元 的免費額度,測試的時候 發了25個請求, 也才花了0.01美元。自己用著玩的話足夠使用了。