Mintplex-Labs · timothycarambat · Apr 30, 2024 · Apr 30, 2024 · Apr 30, 2024 · Apr 30, 2024
diff --git a/.vscode/settings.json b/.vscode/settings.json
@@ -1,8 +1,8 @@
 {
   "cSpell.words": [
-    "AIbitat",
     "adoc",
     "aibitat",
+    "AIbitat",
     "anythingllm",
     "Astra",
     "Chartable",
@@ -20,6 +20,7 @@
     "mbox",
     "Milvus",
     "Mintplex",
+    "moderations",
     "Ollama",
     "openai",
     "opendocument",

diff --git a/collector/package.json b/collector/package.json
@@ -36,7 +36,7 @@
     "multer": "^1.4.5-lts.1",
     "node-html-parser": "^6.1.13",
     "officeparser": "^4.0.5",
-    "openai": "^3.2.1",
+    "openai": "4.38.5",
     "pdf-parse": "^1.1.1",
     "puppeteer": "~21.5.2",
     "slugify": "^1.6.6",

diff --git a/collector/utils/WhisperProviders/OpenAiWhisper.js b/collector/utils/WhisperProviders/OpenAiWhisper.js
@@ -2,13 +2,12 @@ const fs = require("fs");
 
 class OpenAiWhisper {
   constructor({ options }) {
-    const { Configuration, OpenAIApi } = require("openai");
+    const { OpenAI: OpenAIApi } = require("openai");
     if (!options.openAiKey) throw new Error("No OpenAI API key was set.");
 
-    const config = new Configuration({
+    this.openai = new OpenAIApi({
       apiKey: options.openAiKey,
     });
-    this.openai = new OpenAIApi(config);
     this.model = "whisper-1";
     this.temperature = 0;
     this.#log("Initialized.");
@@ -19,22 +18,30 @@ class OpenAiWhisper {
   }
 
   async processFile(fullFilePath) {
-    return await this.openai
-      .createTranscription(
-        fs.createReadStream(fullFilePath),
-        this.model,
-        undefined,
-        "text",
-        this.temperature
-      )
-      .then((res) => {
-        if (res.hasOwnProperty("data"))
-          return { content: res.data, error: null };
-        return { content: "", error: "No content was able to be transcribed." };
+    return await this.openai.audio.transcriptions
+      .create({
+        file: fs.createReadStream(fullFilePath),
+        model: this.model,
+        model: "whisper-1",
+        response_format: "text",
+        temperature: this.temperature,
       })
-      .catch((e) => {
-        this.#log(`Could not get any response from openai whisper`, e.message);
-        return { content: "", error: e.message };
+      .then((response) => {
+        if (!response) {
+          return {
+            content: "",
+            error: "No content was able to be transcribed.",
+          };
+        }
+
+        return { content: response, error: null };
+      })
+      .catch((error) => {
+        this.#log(
+          `Could not get any response from openai whisper`,
+          error.message
+        );
+        return { content: "", error: error.message };
       });
   }
 }

diff --git a/collector/yarn.lock b/collector/yarn.lock
diff --git a/docker/.env.example b/docker/.env.example
@@ -64,7 +64,7 @@ GID='1000'
 
 # LLM_PROVIDER='groq'
 # GROQ_API_KEY=gsk_abcxyz
-# GROQ_MODEL_PREF=llama2-70b-4096
+# GROQ_MODEL_PREF=llama3-8b-8192
 
 # LLM_PROVIDER='generic-openai'
 # GENERIC_OPEN_AI_BASE_PATH='http://proxy.url.openai.com/v1'

diff --git a/frontend/src/components/LLMSelection/GroqAiOptions/index.jsx b/frontend/src/components/LLMSelection/GroqAiOptions/index.jsx
@@ -24,12 +24,11 @@ export default function GroqAiOptions({ settings }) {
           </label>
           <select
             name="GroqModelPref"
-            defaultValue={settings?.GroqModelPref || "llama2-70b-4096"}
+            defaultValue={settings?.GroqModelPref || "llama3-8b-8192"}
             required={true}
             className="bg-zinc-900 border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
           >
             {[
-              "llama2-70b-4096",
               "mixtral-8x7b-32768",
               "llama3-8b-8192",
               "llama3-70b-8192",

diff --git a/frontend/src/components/LLMSelection/TogetherAiOptions/index.jsx b/frontend/src/components/LLMSelection/TogetherAiOptions/index.jsx
@@ -86,7 +86,7 @@ function TogetherAiModelSelection({ settings }) {
                 <option
                   key={model.id}
                   value={model.id}
-                  selected={settings?.OpenRouterModelPref === model.id}
+                  selected={settings?.TogetherAiModelPref === model.id}
                 >
                   {model.name}
                 </option>

diff --git a/frontend/src/hooks/useGetProvidersModels.js b/frontend/src/hooks/useGetProvidersModels.js
@@ -20,7 +20,6 @@ const PROVIDER_DEFAULT_MODELS = {
   ollama: [],
   togetherai: [],
   groq: [
-    "llama2-70b-4096",
     "mixtral-8x7b-32768",
     "llama3-8b-8192",
     "llama3-70b-8192",

diff --git a/server/.env.example b/server/.env.example
@@ -61,7 +61,7 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea
 
 # LLM_PROVIDER='groq'
 # GROQ_API_KEY=gsk_abcxyz
-# GROQ_MODEL_PREF=llama2-70b-4096
+# GROQ_MODEL_PREF=llama3-8b-8192
 
 # LLM_PROVIDER='generic-openai'
 # GENERIC_OPEN_AI_BASE_PATH='http://proxy.url.openai.com/v1'

diff --git a/server/package.json b/server/package.json
@@ -57,8 +57,7 @@
     "multer": "^1.4.5-lts.1",
     "node-html-markdown": "^1.3.0",
     "node-llama-cpp": "^2.8.0",
-    "openai": "^3.2.1",
-    "openai-latest": "npm:openai@latest",
+    "openai": "4.38.5",
     "pinecone-client": "^1.1.0",
     "pluralize": "^8.0.0",
     "posthog-node": "^3.1.1",

diff --git a/server/utils/AiProviders/genericOpenAi/index.js b/server/utils/AiProviders/genericOpenAi/index.js
@@ -1,21 +1,22 @@
 const { NativeEmbedder } = require("../../EmbeddingEngines/native");
 const { chatPrompt } = require("../../chats");
-const { handleDefaultStreamResponse } = require("../../helpers/chat/responses");
+const {
+  handleDefaultStreamResponseV2,
+} = require("../../helpers/chat/responses");
 
 class GenericOpenAiLLM {
   constructor(embedder = null, modelPreference = null) {
-    const { Configuration, OpenAIApi } = require("openai");
+    const { OpenAI: OpenAIApi } = require("openai");
     if (!process.env.GENERIC_OPEN_AI_BASE_PATH)
       throw new Error(
         "GenericOpenAI must have a valid base path to use for the api."
       );
 
     this.basePath = process.env.GENERIC_OPEN_AI_BASE_PATH;
-    const config = new Configuration({
-      basePath: this.basePath,
+    this.openai = new OpenAIApi({
+      baseURL: this.basePath,
       apiKey: process.env.GENERIC_OPEN_AI_API_KEY ?? null,
     });
-    this.openai = new OpenAIApi(config);
     this.model =
       modelPreference ?? process.env.GENERIC_OPEN_AI_MODEL_PREF ?? null;
     if (!this.model)
@@ -89,8 +90,8 @@ class GenericOpenAiLLM {
   }
 
   async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
-    const textResponse = await this.openai
-      .createChatCompletion({
+    const textResponse = await this.openai.chat.completions
+      .create({
         model: this.model,
         temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
         n: 1,
@@ -103,13 +104,12 @@ class GenericOpenAiLLM {
           rawHistory
         ),
       })
-      .then((json) => {
-        const res = json.data;
-        if (!res.hasOwnProperty("choices"))
+      .then((result) => {
+        if (!result.hasOwnProperty("choices"))
           throw new Error("GenericOpenAI chat: No results!");
-        if (res.choices.length === 0)
+        if (result.choices.length === 0)
           throw new Error("GenericOpenAI chat: No results length!");
-        return res.choices[0].message.content;
+        return result.choices[0].message.content;
       })
       .catch((error) => {
         throw new Error(
@@ -121,29 +121,26 @@ class GenericOpenAiLLM {
   }
 
   async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
-    const streamRequest = await this.openai.createChatCompletion(
-      {
-        model: this.model,
-        stream: true,
-        temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
-        n: 1,
-        messages: await this.compressMessages(
-          {
-            systemPrompt: chatPrompt(workspace),
-            userPrompt: prompt,
-            chatHistory,
-          },
-          rawHistory
-        ),
-      },
-      { responseType: "stream" }
-    );
+    const streamRequest = await this.openai.chat.completions.create({
+      model: this.model,
+      stream: true,
+      temperature: Number(workspace?.openAiTemp ?? this.defaultTemp),
+      n: 1,
+      messages: await this.compressMessages(
+        {
+          systemPrompt: chatPrompt(workspace),
+          userPrompt: prompt,
+          chatHistory,
+        },
+        rawHistory
+      ),
+    });
     return streamRequest;
   }
 
   async getChatCompletion(messages = null, { temperature = 0.7 }) {
-    const { data } = await this.openai
-      .createChatCompletion({
+    const result = await this.openai.chat.completions
+      .create({
         model: this.model,
         messages,
         temperature,
@@ -152,25 +149,23 @@ class GenericOpenAiLLM {
         throw new Error(e.response.data.error.message);
       });
 
-    if (!data.hasOwnProperty("choices")) return null;
-    return data.choices[0].message.content;
+    if (!result.hasOwnProperty("choices") || result.choices.length === 0)
+      return null;
+    return result.choices[0].message.content;
   }
 
   async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
-    const streamRequest = await this.openai.createChatCompletion(
-      {
-        model: this.model,
-        stream: true,
-        messages,
-        temperature,
-      },
-      { responseType: "stream" }
-    );
+    const streamRequest = await this.openai.chat.completions.create({
+      model: this.model,
+      stream: true,
+      messages,
+      temperature,
+    });
     return streamRequest;
   }
 
   handleStream(response, stream, responseProps) {
-    return handleDefaultStreamResponse(response, stream, responseProps);
+    return handleDefaultStreamResponseV2(response, stream, responseProps);
   }
 
   // Simple wrapper for dynamic embedder & normalize interface for all LLM implementations