fix a few things, comment out facts

Author: lalalune

.env.example

@@ -37,10 +37,6 @@ SMALL_OLLAMA_MODEL=         #default llama3.2
 MEDIUM_OLLAMA_MODEL=        #default herems3
 LARGE_OLLAMA_MODEL=         #default hermes3:70b
 
-#to still use the original LOCALLLAMA provider but with ollama
-LOCAL_LLAMA_PROVIDER= #"OLLAMA" #Leave blank for LLAMA-CPP or add OLLAMA
-
-
 # For asking Claude stuff
 ANTHROPIC_API_KEY=
 

packages/adapter-sqlite/src/index.ts

@@ -350,6 +350,8 @@ export class SqliteDatabaseAdapter extends DatabaseAdapter {
       ORDER BY vec_distance_L2(${opts.query_field_name}, ?) ASC
       LIMIT ?
     `;
+    console.log("sql", sql)
+    console.log("opts.query_input", opts.query_input)
         const memories = this.db.prepare(sql).all(
             opts.query_table_name,
             new Float32Array(opts.query_input.split(",").map(Number)), // Convert string to Float32Array

packages/client-discord/src/providers/channelState.ts

@@ -16,7 +16,6 @@ const channelStateProvider: Provider = {
             (state?.discordMessage as DiscordMessage) ||
             (state?.discordChannel as DiscordMessage);
         if (!discordMessage) {
-            console.log("discordMessage is null");
             return "";
         }
 

packages/core/src/embedding.ts

@@ -13,25 +13,28 @@ import {
  */
 export async function embed(runtime: IAgentRuntime, input: string) {
     // get the charcter, and handle by model type
-    const model = models[runtime.character.settings.model];
+    const modelProvider = models[runtime.character.modelProvider];
+    const embeddingModel = modelProvider.model.embedding;
 
     if (
-        model !== ModelProviderName.OPENAI &&
-        model !== ModelProviderName.OLLAMA
+        runtime.character.modelProvider !== ModelProviderName.OPENAI &&
+        runtime.character.modelProvider !== ModelProviderName.OLLAMA
     ) {
         const service = runtime.getService<ITextGenerationService>(
             ServiceType.TEXT_GENERATION
         );
-        return await service.getInstance().getEmbeddingResponse(input);
-    }
-
-    const embeddingModel = models[runtime.modelProvider].model.embedding;
+        
+        const instance = service?.getInstance();
 
-    // Check if we already have the embedding in the lore
-    const cachedEmbedding = await retrieveCachedEmbedding(runtime, input);
-    if (cachedEmbedding) {
-        return cachedEmbedding;
+        if (instance) {
+            return await instance.getEmbeddingResponse(input);
+        }
     }
+    // Check if we already have the embedding in the lore
+    // const cachedEmbedding = await retrieveCachedEmbedding(runtime, input);
+    // if (cachedEmbedding) {
+    //     return cachedEmbedding;
+    // }
 
     const requestOptions = {
         method: "POST",
@@ -51,7 +54,7 @@ export async function embed(runtime: IAgentRuntime, input: string) {
     try {
         const response = await fetch(
             // TODO: make this not hardcoded
-            `${runtime.serverUrl}${runtime.modelProvider === ModelProviderName.OLLAMA ? "/v1" : ""}/embeddings`,
+            `${runtime.character.modelEndpointOverride || modelProvider.endpoint}${runtime.character.modelProvider === ModelProviderName.OLLAMA ? "/v1" : ""}/embeddings`,
             requestOptions
         );
 
@@ -81,6 +84,11 @@ export async function retrieveCachedEmbedding(
     runtime: IAgentRuntime,
     input: string
 ) {
+    if(!input) {
+        console.log("No input to retrieve cached embedding for");
+        return null;
+    }
+
     const similaritySearchResult =
         await runtime.messageManager.getCachedEmbeddings(input);
     if (similaritySearchResult.length > 0) {

packages/plugin-bootstrap/src/providers/facts.ts

@@ -20,19 +20,23 @@ const factsProvider: Provider = {
 
         const embedding = await embed(runtime, recentMessages);
 
+        console.log("embedding", embedding);
+
         const memoryManager = new MemoryManager({
             runtime,
             tableName: "facts",
         });
 
-        const relevantFacts = await memoryManager.searchMemoriesByEmbedding(
-            embedding,
-            {
-                roomId: message.roomId,
-                count: 10,
-                agentId: runtime.agentId,
-            }
-        );
+        const relevantFacts = []
+        
+        // await memoryManager.searchMemoriesByEmbedding(
+        //     embedding,
+        //     {
+        //         roomId: message.roomId,
+        //         count: 10,
+        //         agentId: runtime.agentId,
+        //     }
+        // );
 
         const recentFactsData = await memoryManager.getMemories({
             roomId: message.roomId,