Google Java Format

arakoodev · Sep 30, 2023 · 4cdea9c · 4cdea9c
1 parent e8162ff
commit 4cdea9c
Show file tree

Hide file tree

Showing 41 changed files with 1,684 additions and 1,681 deletions.
diff --git a/Examples/airtable/AirtableExample.java b/Examples/airtable/AirtableExample.java
@@ -17,11 +17,12 @@
 import java.util.Properties;
 
 /**
- * For the purpose, of this example, create a simple table using AirTable i.e, "Speakers"
- * Following are some basic fields: "speaker_name", "designation", "organization", "biography", "speaker_photo", "rating
- * To get, your BASE_ID of specific database; use the following API https://api.airtable.com/v0/meta/bases
- * --header 'Authorization: Bearer YOUR_PERSONAL_ACCESS_TOKEN'
- * You can create, complex tables using Airtable; also define relationships b/w tables via lookups.
+ * For the purpose, of this example, create a simple table using AirTable i.e, "Speakers" Following
+ * are some basic fields: "speaker_name", "designation", "organization", "biography",
+ * "speaker_photo", "rating To get, your BASE_ID of specific database; use the following API
+ * https://api.airtable.com/v0/meta/bases --header 'Authorization: Bearer
+ * YOUR_PERSONAL_ACCESS_TOKEN' You can create, complex tables using Airtable; also define
+ * relationships b/w tables via lookups.
  */
 @SpringBootApplication
 public class AirtableExample {
@@ -123,11 +124,11 @@ public ArkResponse update(ArkRequest arkRequest) {
       return new EdgeChain<>(airtableEndpoint.update("Speakers", record)).getArkResponse();
     }
 
-      @DeleteMapping("/delete")
-      public ArkResponse delete(ArkRequest arkRequest) {
-          JSONObject body = arkRequest.getBody();
-          String id = body.getString("id");
-          return new EdgeChain<>(airtableEndpoint.delete("Speakers", id)).getArkResponse();
-      }
+    @DeleteMapping("/delete")
+    public ArkResponse delete(ArkRequest arkRequest) {
+      JSONObject body = arkRequest.getBody();
+      String id = body.getString("id");
+      return new EdgeChain<>(airtableEndpoint.delete("Speakers", id)).getArkResponse();
+    }
   }
 }
diff --git a/Examples/pinecone/PineconeExample.java b/Examples/pinecone/PineconeExample.java
@@ -61,7 +61,7 @@ public static void main(String[] args) {
 
     // Redis Configuration
     properties.setProperty("redis.url", "");
-    properties.setProperty("redis.port","");
+    properties.setProperty("redis.port", "");
     properties.setProperty("redis.username", "default");
     properties.setProperty("redis.password", "");
     properties.setProperty("redis.ttl", "3600");
@@ -72,12 +72,11 @@ public static void main(String[] args) {
     properties.setProperty("postgres.db.username", "postgres");
     properties.setProperty("postgres.db.password", "");
 
-
     new SpringApplicationBuilder(PineconeExample.class).properties(properties).run(args);
 
     gpt3Endpoint =
         new OpenAiChatEndpoint(
-             OPENAI_CHAT_COMPLETION_API,
+            OPENAI_CHAT_COMPLETION_API,
             OPENAI_AUTH_KEY,
             OPENAI_ORG_ID,
             "gpt-3.5-turbo",
@@ -96,7 +95,8 @@ public static void main(String[] args) {
             true,
             new ExponentialDelay(3, 5, 2, TimeUnit.SECONDS));
 
-    OpenAiEmbeddingEndpoint ada002 = new OpenAiEmbeddingEndpoint(
+    OpenAiEmbeddingEndpoint ada002 =
+        new OpenAiEmbeddingEndpoint(
             OPENAI_EMBEDDINGS_API,
             OPENAI_AUTH_KEY,
             OPENAI_ORG_ID,

diff --git a/Examples/postgresql/PostgreSQLExample.java b/Examples/postgresql/PostgreSQLExample.java
@@ -90,7 +90,8 @@ public static void main(String[] args) {
             true,
             new ExponentialDelay(3, 5, 2, TimeUnit.SECONDS));
 
-    OpenAiEmbeddingEndpoint adaEmbedding = new OpenAiEmbeddingEndpoint(
+    OpenAiEmbeddingEndpoint adaEmbedding =
+        new OpenAiEmbeddingEndpoint(
             OPENAI_EMBEDDINGS_API,
             OPENAI_AUTH_KEY,
             OPENAI_ORG_ID,
@@ -100,7 +101,10 @@ public static void main(String[] args) {
     // Defining tablename and namespace...
     postgresEndpoint =
         new PostgresEndpoint(
-            "pg_vectors", "machine-learning", adaEmbedding, new ExponentialDelay(5, 5, 2, TimeUnit.SECONDS));
+            "pg_vectors",
+            "machine-learning",
+            adaEmbedding,
+            new ExponentialDelay(5, 5, 2, TimeUnit.SECONDS));
 
     contextEndpoint = new PostgreSQLHistoryContextEndpoint(new FixedDelay(2, 3, TimeUnit.SECONDS));
   }
@@ -159,12 +163,7 @@ public void upsert(ArkRequest arkRequest) throws IOException {
 
       PostgresRetrieval retrieval =
           new PostgresRetrieval(
-              arr,
-              postgresEndpoint,
-              1536,
-              filename,
-              PostgresLanguage.ENGLISH,
-              arkRequest);
+              arr, postgresEndpoint, 1536, filename, PostgresLanguage.ENGLISH, arkRequest);
 
       //   retrieval.setBatchSize(50); // Modifying batchSize....(Default is 30)
 
@@ -186,12 +185,7 @@ public ArkResponse query(ArkRequest arkRequest) {
       EdgeChain<List<PostgresWordEmbeddings>> queryChain =
           new EdgeChain<>(
               postgresEndpoint.query(
-                  List.of(query),
-                  PostgresDistanceMetric.COSINE,
-                  topK,
-                  topK,
-                  10,
-                  arkRequest));
+                  List.of(query), PostgresDistanceMetric.COSINE, topK, topK, 10, arkRequest));
 
       //  Chain 3 ===> Our queryFn passes takes list and passes each response with base prompt to
       // OpenAI
@@ -227,15 +221,17 @@ public ArkResponse chat(ArkRequest arkRequest) {
 
       EdgeChain<List<PostgresWordEmbeddings>> postgresChain =
           new EdgeChain<>(
-              postgresEndpoint.query(List.of(query), PostgresDistanceMetric.COSINE, topK, topK, arkRequest));
+              postgresEndpoint.query(
+                  List.of(query), PostgresDistanceMetric.COSINE, topK, topK, arkRequest));
 
       // Chain 3 ===> Transform String of Queries into List<Queries>
       // let's say topK=5; then we concatenate List into a string using String.join method
       EdgeChain<String> queryChain =
           new EdgeChain<>(postgresChain)
               .transform(
                   postgresResponse -> {
-                    List<PostgresWordEmbeddings> postgresWordEmbeddingsList = postgresResponse.get();
+                    List<PostgresWordEmbeddings> postgresWordEmbeddingsList =
+                        postgresResponse.get();
                     List<String> queryList = new ArrayList<>();
                     postgresWordEmbeddingsList.forEach(q -> queryList.add(q.getRawText()));
                     return String.join("\n", queryList);

diff --git a/Examples/react-chain/ReactChainApplication.java b/Examples/react-chain/ReactChainApplication.java
@@ -1,6 +1,5 @@
 package com.edgechain;
 
-
 import com.edgechain.lib.endpoint.impl.llm.OpenAiChatEndpoint;
 import com.edgechain.lib.jsonnet.JsonnetArgs;
 import com.edgechain.lib.jsonnet.JsonnetLoader;

diff --git a/Examples/redis/RedisExample.java b/Examples/redis/RedisExample.java
@@ -61,15 +61,13 @@ public static void main(String[] args) {
 
     // If you want to use PostgreSQL only; then just provide dbHost, dbUsername & dbPassword.
     // If you haven't specified PostgreSQL, then logs won't be stored.
-    properties.setProperty(
-            "postgres.db.host", "");
+    properties.setProperty("postgres.db.host", "");
     properties.setProperty("postgres.db.username", "postgres");
     properties.setProperty("postgres.db.password", "");
 
-
     // Redis Configuration
     properties.setProperty("redis.url", "");
-    properties.setProperty("redis.port","12285");
+    properties.setProperty("redis.port", "12285");
     properties.setProperty("redis.username", "default");
     properties.setProperty("redis.password", "");
     properties.setProperty("redis.ttl", "3600");
@@ -98,16 +96,19 @@ public static void main(String[] args) {
             new ExponentialDelay(3, 5, 2, TimeUnit.SECONDS));
 
     OpenAiEmbeddingEndpoint ada002Endpoint =
-            new OpenAiEmbeddingEndpoint(
-                    OPENAI_EMBEDDINGS_API,
-                    OPENAI_AUTH_KEY,
-                    OPENAI_ORG_ID,
-                    "text-embedding-ada-002",
-                    new ExponentialDelay(3, 3, 2, TimeUnit.SECONDS));
+        new OpenAiEmbeddingEndpoint(
+            OPENAI_EMBEDDINGS_API,
+            OPENAI_AUTH_KEY,
+            OPENAI_ORG_ID,
+            "text-embedding-ada-002",
+            new ExponentialDelay(3, 3, 2, TimeUnit.SECONDS));
 
     redisEndpoint =
         new RedisEndpoint(
-            "vector_index", "machine-learning", ada002Endpoint, new ExponentialDelay(3, 3, 2, TimeUnit.SECONDS));
+            "vector_index",
+            "machine-learning",
+            ada002Endpoint,
+            new ExponentialDelay(3, 3, 2, TimeUnit.SECONDS));
 
     contextEndpoint =
         new RedisHistoryContextEndpoint(new ExponentialDelay(2, 2, 2, TimeUnit.SECONDS));
@@ -166,8 +167,7 @@ public void upsert(ArkRequest arkRequest) throws IOException {
        * asynchronously...;
        */
       RedisRetrieval retrieval =
-          new RedisRetrieval(
-              arr, redisEndpoint, 1536, RedisDistanceMetric.COSINE, arkRequest);
+          new RedisRetrieval(arr, redisEndpoint, 1536, RedisDistanceMetric.COSINE, arkRequest);
       retrieval.upsert();
     }
 
@@ -184,7 +184,8 @@ public ArkResponse similaritySearch(ArkRequest arkRequest) {
       int topK = arkRequest.getIntQueryParam("topK");
 
       // Chain 1 ==> Pass those embeddings to Redis & Return Score/values (Similarity search)
-      EdgeChain<List<WordEmbeddings>> redisQueries = new EdgeChain<>(redisEndpoint.query(query, topK, arkRequest));
+      EdgeChain<List<WordEmbeddings>> redisQueries =
+          new EdgeChain<>(redisEndpoint.query(query, topK, arkRequest));
 
       return redisQueries.getArkResponse();
     }
@@ -196,7 +197,8 @@ public ArkResponse queryRedis(ArkRequest arkRequest) {
       int topK = arkRequest.getIntQueryParam("topK");
 
       //  Chain 1 ==> Query Embeddings from Redis
-      EdgeChain<List<WordEmbeddings>> queryChain = new EdgeChain<>(redisEndpoint.query(query, topK, arkRequest));
+      EdgeChain<List<WordEmbeddings>> queryChain =
+          new EdgeChain<>(redisEndpoint.query(query, topK, arkRequest));
 
       //  Chain 3 ===> Our queryFn passes takes list and passes each response with base prompt to
       // OpenAI
@@ -227,7 +229,6 @@ public ArkResponse chatWithRedis(ArkRequest arkRequest) {
       // Extract topK value from JsonnetLoader;
       int topK = chatLoader.getInt("topK");
 
-
       // Chain 1==> Query Embeddings from Redis & Then concatenate it (preparing for prompt)
 
       EdgeChain<List<WordEmbeddings>> redisChain =

diff --git a/Examples/supabase-miniLM/SupabaseMiniLMExample.java b/Examples/supabase-miniLM/SupabaseMiniLMExample.java
@@ -49,9 +49,9 @@ public class SupabaseMiniLMExample {
   private static PostgreSQLHistoryContextEndpoint contextEndpoint;
 
   private JsonnetLoader queryLoader =
-          new FileJsonnetLoader("./supabase-miniLM/postgres-query.jsonnet");
+      new FileJsonnetLoader("./supabase-miniLM/postgres-query.jsonnet");
   private JsonnetLoader chatLoader =
-          new FileJsonnetLoader("./supabase-miniLM/postgres-chat.jsonnet");
+      new FileJsonnetLoader("./supabase-miniLM/postgres-chat.jsonnet");
 
   public static void main(String[] args) {
 
@@ -77,7 +77,6 @@ public static void main(String[] args) {
     properties.setProperty("postgres.db.username", "postgres");
     properties.setProperty("postgres.db.password", "");
 
-
     new SpringApplicationBuilder(SupabaseMiniLMExample.class).properties(properties).run(args);
 
     gpt3Endpoint =
@@ -112,7 +111,10 @@ public static void main(String[] args) {
     // vectors;
     postgresEndpoint =
         new PostgresEndpoint(
-            "minilm_vectors", "minilm-ns", miniLMEndpoint, new ExponentialDelay(2, 3, 2, TimeUnit.SECONDS));
+            "minilm_vectors",
+            "minilm-ns",
+            miniLMEndpoint,
+            new ExponentialDelay(2, 3, 2, TimeUnit.SECONDS));
 
     contextEndpoint = new PostgreSQLHistoryContextEndpoint(new FixedDelay(2, 3, TimeUnit.SECONDS));
   }
@@ -172,12 +174,7 @@ public void upsert(ArkRequest arkRequest) throws IOException {
 
       PostgresRetrieval retrieval =
           new PostgresRetrieval(
-              arr,
-              postgresEndpoint,
-              384,
-              filename,
-              PostgresLanguage.ENGLISH,
-              arkRequest);
+              arr, postgresEndpoint, 384, filename, PostgresLanguage.ENGLISH, arkRequest);
 
       //   retrieval.setBatchSize(50); // Modifying batchSize....
 
@@ -199,7 +196,8 @@ public ArkResponse queryPostgres(ArkRequest arkRequest) {
       //  Chain 2 ==> Query Embeddings from PostgreSQL
       EdgeChain<List<PostgresWordEmbeddings>> queryChain =
           new EdgeChain<>(
-              postgresEndpoint.query(List.of(query), PostgresDistanceMetric.L2, topK, topK,arkRequest));
+              postgresEndpoint.query(
+                  List.of(query), PostgresDistanceMetric.L2, topK, topK, arkRequest));
 
       //  Chain 3 ===> Our queryFn passes takes list and passes each response with base prompt to
       // OpenAI
@@ -237,14 +235,16 @@ public ArkResponse chatWithPostgres(ArkRequest arkRequest) {
       // let's say topK=5; then we concatenate List into a string using String.join method
       EdgeChain<List<PostgresWordEmbeddings>> postgresChain =
           new EdgeChain<>(
-              postgresEndpoint.query(List.of(query), PostgresDistanceMetric.L2, topK, topK, arkRequest));
+              postgresEndpoint.query(
+                  List.of(query), PostgresDistanceMetric.L2, topK, topK, arkRequest));
 
       // Chain 3 ===> Transform String of Queries into List<Queries>
       EdgeChain<String> queryChain =
           new EdgeChain<>(postgresChain)
               .transform(
                   postgresResponse -> {
-                    List<PostgresWordEmbeddings> postgresWordEmbeddingsList = postgresResponse.get();
+                    List<PostgresWordEmbeddings> postgresWordEmbeddingsList =
+                        postgresResponse.get();
                     List<String> queryList = new ArrayList<>();
                     postgresWordEmbeddingsList.forEach(q -> queryList.add(q.getRawText()));
                     return String.join("\n", queryList);