improved error msg

ollama-config.json

@@ -0,0 +1,4 @@
+{
+    "url": "http://localhost:11434",
+    "embedding_model": "nomic-embed-text"
+}

src/models/ollama.js

@@ -0,0 +1,107 @@
+import OpenAIApi from 'openai';
+import axios from 'axios';
+import { readFileSync } from 'fs';
+
+
+let ollamaSettings = JSON.parse(readFileSync('./ollama-config.json', 'utf8'));
+
+function getContentInBrackets(str) {
+    const startIndex = str.indexOf("[");
+    const endIndex = str.indexOf("]");
+  
+    if (startIndex !== -1 && endIndex !== -1 && endIndex > startIndex) {
+      return str.substring(startIndex + 1, endIndex);
+    } else {
+      return "";
+    }
+  }
+
+export class Ollama {
+
+    constructor(model_name) {
+        this.model_name = getContentInBrackets(model_name);
+
+        if (this.model_name = "") {
+            throw new Error('Model is not specified! Please ensure you input the model in the following format: ollama[model]. For example, for Mistral, use: ollama[mistral]');
+        }
+
+        let ollamaConfig = null;
+        
+        ollamaConfig = {
+            baseURL: ollamaSettings["url"] + '/v1',
+            apiKey: 'ollama', // required but unused
+        };
+
+
+        this.openai = new OpenAIApi(ollamaConfig);
+
+    }
+
+
+    async sendRequest(turns, systemMessage, stop_seq='***') {
+
+        let messages = [{'role': 'system', 'content': systemMessage}].concat(turns);
+
+        let res = null;
+        try {
+            console.log('Awaiting ollama response...')
+            console.log('Messages:', messages);
+            let completion = await this.openai.chat.completions.create({
+                //model: this.model_name,
+                model: "mistral",
+                messages: messages,
+                stop: stop_seq,
+            });
+            if (completion.choices[0].finish_reason == 'length')
+                throw new Error('Context length exceeded'); 
+            console.log('Received.')
+            res = completion.choices[0].message.content;
+        }
+        catch (err) {
+            if ((err.message == 'Context length exceeded' || err.code == 'context_length_exceeded') && turns.length > 1) {
+                console.log('Context length exceeded, trying again with shorter context.');
+                return await sendRequest(turns.slice(1), systemMessage, stop_seq);
+            } else {
+                console.log(err);
+                res = 'My brain disconnected, try again.';
+            }
+        }
+        return res;
+    }
+
+    async embed(text) {
+        
+        
+        // Will implement this when Ollama will support embeddings in OpenAI format
+        /*
+        const embedding = await this.openai.embeddings.create({
+            model: "nomic-embed-text",
+            input: text,
+            encoding_format: "float",
+        });
+
+        return embedding.data[0].embedding;
+        */
+
+        // For now, I'll do http request using axios:
+
+        try {
+            const response = await axios.post(ollamaSettings["url"] + '/api/embeddings', {
+              model: ollamaSettings["embedding_model"],
+              prompt: text
+            });
+            return response.data.embedding;
+          } catch (error) {
+            console.error('Error embedding text:', error.response ? error.response.data : error.message);
+            throw error;
+          }
+        }
+
+
+
+
+
+}
+
+
+