Add support for multiple OpenAI compatible endpoints

src/endpoints/togetherai.js

@@ -0,0 +1,4 @@
+/**
+ * sends a request to the together AI api
+ * 
+ */

src/endpoints/vectors.js

@@ -12,8 +12,9 @@ const { jsonParser } = require('../express-common');
  */
 async function getVector(source, text) {
     switch (source) {
+        case 'togetherai':
         case 'openai':
-            return require('../openai-vectors').getOpenAIVector(text);
+            return require('../openai-vectors').getOpenAIVector(text, source);
         case 'transformers':
             return require('../embedding').getTransformersVector(text);
         case 'palm':

src/openai-vectors.js

@@ -2,19 +2,40 @@ const fetch = require('node-fetch').default;
 const { SECRET_KEYS, readSecret } = require('./endpoints/secrets');
 
 /**
- * Gets the vector for the given text from OpenAI ada model
+ * Gets the vector for the given text from an OpenAI compatible endpoint.
  * @param {string} text - The text to get the vector for
+ * @param {string} source - The source of the vector
  * @returns {Promise<number[]>} - The vector for the text
  */
-async function getOpenAIVector(text) {
+async function getOpenAIVector(text, source) {
-    const key = readSecret(SECRET_KEYS.OPENAI);
+
+    // dictionary of sources to endpoints with source as key and endpoint, model and secret key as value
+    const endpoints = {
+        'togetherai': {
+            endpoint: 'https://api.togetherai.xyz/v1/embeddings',  // is this correct?
+            model: 'togethercomputer/GPT-NeoXT-Chat-Base-20B', 
+            secret: SECRET_KEYS.TOGETHERAI,
+        },
+        'openai': {
+            endpoint: 'https://api.openai.com/v1/embeddings',
+            model: 'text-embedding-ada-002',
+            secret: SECRET_KEYS.OPENAI,
+        },
+        'mistral': {
+            endpoint: 'https://api.mistral.ai/v1/embeddings',
+            model: 'mistral-embed',
+            secret: SECRET_KEYS.MISTRAL,
+        },
+    };
+
+    const key = readSecret(endpoints[source].secret);
 
     if (!key) {
-        console.log('No OpenAI key found');
+        console.log('No %s key found.', source);
-        throw new Error('No OpenAI key found');
+        throw new Error('No ${source} key found.');
     }
 
-    const response = await fetch('https://api.openai.com/v1/embeddings', {
+    const response = await fetch(endpoints[source].endpoint, {
         method: 'POST',
         headers: {
             'Content-Type': 'application/json',
@@ -22,22 +43,22 @@ async function getOpenAIVector(text) {
         },
         body: JSON.stringify({
             input: text,
-            model: 'text-embedding-ada-002',
+            model: endpoints[source].model,
         }),
     });
 
     if (!response.ok) {
         const text = await response.text();
-        console.log('OpenAI request failed', response.statusText, text);
+        console.log('${source} request failed', response.statusText, text);
-        throw new Error('OpenAI request failed');
+        throw new Error('${source} request failed');
     }
 
     const data = await response.json();
     const vector = data?.data[0]?.embedding;
 
     if (!Array.isArray(vector)) {
-        console.log('OpenAI response was not an array');
+        console.log('${source} response was not an array');
-        throw new Error('OpenAI response was not an array');
+        throw new Error('${source} response was not an array');
     }
 
     return vector;