Ollama agents (#1270)

* add LMStudio agent support (generic) support
"work" with non-tool callable LLMs, highly dependent on system specs

* add comments

* enable few-shot prompting per function for OSS models

* Add Agent support for Ollama models

* improve json parsing for ollama text responses

frontend/src/pages/WorkspaceSettings/AgentConfig/AgentLLMSelection/index.jsx

@@ -5,8 +5,8 @@ import { AVAILABLE_LLM_PROVIDERS } from "@/pages/GeneralSettings/LLMPreference";
 import { CaretUpDown, Gauge, MagnifyingGlass, X } from "@phosphor-icons/react";
 import AgentModelSelection from "../AgentModelSelection";
 
-const ENABLED_PROVIDERS = ["openai", "anthropic", "lmstudio"];
-const WARN_PERFORMANCE = ["lmstudio"];
+const ENABLED_PROVIDERS = ["openai", "anthropic", "lmstudio", "ollama"];
+const WARN_PERFORMANCE = ["lmstudio", "ollama"];
 
 const LLM_DEFAULT = {
   name: "Please make a selection",

server/package.json

@@ -46,6 +46,7 @@
     "dotenv": "^16.0.3",
     "express": "^4.18.2",
     "express-ws": "^5.0.2",
+    "extract-json-from-string": "^1.0.1",
     "extract-zip": "^2.0.1",
     "graphql": "^16.7.1",
     "joi": "^17.11.0",
@@ -59,6 +60,7 @@
     "multer": "^1.4.5-lts.1",
     "node-html-markdown": "^1.3.0",
     "node-llama-cpp": "^2.8.0",
+    "ollama": "^0.5.0",
     "openai": "4.38.5",
     "pinecone-client": "^1.1.0",
     "pluralize": "^8.0.0",

server/utils/agents/aibitat/index.js

@@ -741,6 +741,8 @@ ${this.getHistory({ to: route.to })
         return new Providers.AnthropicProvider({ model: config.model });
       case "lmstudio":
         return new Providers.LMStudioProvider({});
+      case "ollama":
+        return new Providers.OllamaProvider({ model: config.model });
 
       default:
         throw new Error(

server/utils/agents/aibitat/providers/helpers/untooled.js

@@ -102,48 +102,34 @@ ${JSON.stringify(def.parameters.properties, null, 4)}\n`;
     return { valid: true, reason: null };
   }
 
-  async functionCall(messages, functions) {
+  async functionCall(messages, functions, chatCb = null) {
     const history = [...messages].filter((msg) =>
       ["user", "assistant"].includes(msg.role)
     );
     if (history[history.length - 1].role !== "user") return null;
+    const response = await chatCb({
+      messages: [
+        {
+          content: `You are a program which picks the most optimal function and parameters to call. 
+      DO NOT HAVE TO PICK A FUNCTION IF IT WILL NOT HELP ANSWER OR FULFILL THE USER'S QUERY.
+      When a function is selection, respond in JSON with no additional text.
+      When there is no relevant function to call - return with a regular chat text response.
+      Your task is to pick a **single** function that we will use to call, if any seem useful or relevant for the user query.
 
-    const response = await this.client.chat.completions
-      .create({
-        model: this.model,
-        temperature: 0,
-        messages: [
-          {
-            content: `You are a program which picks the most optimal function and parameters to call. 
-DO NOT HAVE TO PICK A FUNCTION IF IT WILL NOT HELP ANSWER OR FULFILL THE USER'S QUERY.
-When a function is selection, respond in JSON with no additional text.
-When there is no relevant function to call - return with a regular chat text response.
-Your task is to pick a **single** function that we will use to call, if any seem useful or relevant for the user query.
+      All JSON responses should have two keys.
+      'name': this is the name of the function name to call. eg: 'web-scraper', 'rag-memory', etc..
+      'arguments': this is an object with the function properties to invoke the function.
+      DO NOT INCLUDE ANY OTHER KEYS IN JSON RESPONSES.
 
-All JSON responses should have two keys.
-'name': this is the name of the function name to call. eg: 'web-scraper', 'rag-memory', etc..
-'arguments': this is an object with the function properties to invoke the function.
-DO NOT INCLUDE ANY OTHER KEYS IN JSON RESPONSES.
+      Here are the available tools you can use an examples of a query and response so you can understand how each one works.
+      ${this.showcaseFunctions(functions)}
 
-Here are the available tools you can use an examples of a query and response so you can understand how each one works.
-${this.showcaseFunctions(functions)}
-
-Now pick a function if there is an appropriate one to use given the last user message and the given conversation so far.`,
-            role: "system",
-          },
-          ...history,
-        ],
-      })
-      .then((result) => {
-        if (!result.hasOwnProperty("choices"))
-          throw new Error("LMStudio chat: No results!");
-        if (result.choices.length === 0)
-          throw new Error("LMStudio chat: No results length!");
-        return result.choices[0].message.content;
-      })
-      .catch((_) => {
-        return null;
-      });
+      Now pick a function if there is an appropriate one to use given the last user message and the given conversation so far.`,
+          role: "system",
+        },
+        ...history,
+      ],
+    });
 
     const call = safeJsonParse(response, null);
     if (call === null) return { toolCall: null, text: response }; // failed to parse, so must be text.

server/utils/agents/aibitat/providers/index.js

@@ -1,9 +1,11 @@
 const OpenAIProvider = require("./openai.js");
 const AnthropicProvider = require("./anthropic.js");
 const LMStudioProvider = require("./lmstudio.js");
+const OllamaProvider = require("./ollama.js");
 
 module.exports = {
   OpenAIProvider,
   AnthropicProvider,
   LMStudioProvider,
+  OllamaProvider,
 };

server/utils/agents/aibitat/providers/lmstudio.js

@@ -27,6 +27,25 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
     return this._client;
   }
 
+  async #handleFunctionCallChat({ messages = [] }) {
+    return await this.client.chat.completions
+      .create({
+        model: this.model,
+        temperature: 0,
+        messages,
+      })
+      .then((result) => {
+        if (!result.hasOwnProperty("choices"))
+          throw new Error("LMStudio chat: No results!");
+        if (result.choices.length === 0)
+          throw new Error("LMStudio chat: No results length!");
+        return result.choices[0].message.content;
+      })
+      .catch((_) => {
+        return null;
+      });
+  }
+
   /**
    * Create a completion based on the received messages.
    *
@@ -38,7 +57,11 @@ class LMStudioProvider extends InheritMultiple([Provider, UnTooled]) {
     try {
       let completion;
       if (functions.length > 0) {
-        const { toolCall, text } = await this.functionCall(messages, functions);
+        const { toolCall, text } = await this.functionCall(
+          messages,
+          functions,
+          this.#handleFunctionCallChat.bind(this)
+        );
 
         if (toolCall !== null) {
           this.providerLog(`Valid tool call found - running ${toolCall.name}.`);

server/utils/agents/aibitat/providers/ollama.js

@@ -0,0 +1,107 @@
+const Provider = require("./ai-provider.js");
+const InheritMultiple = require("./helpers/classes.js");
+const UnTooled = require("./helpers/untooled.js");
+const { Ollama } = require("ollama");
+
+/**
+ * The provider for the Ollama provider.
+ */
+class OllamaProvider extends InheritMultiple([Provider, UnTooled]) {
+  model;
+
+  constructor(config = {}) {
+    const {
+      // options = {},
+      model = null,
+    } = config;
+
+    super();
+    this._client = new Ollama({ host: process.env.OLLAMA_BASE_PATH });
+    this.model = model;
+    this.verbose = true;
+  }
+
+  get client() {
+    return this._client;
+  }
+
+  async #handleFunctionCallChat({ messages = [] }) {
+    const response = await this.client.chat({
+      model: this.model,
+      messages,
+      options: {
+        temperature: 0,
+      },
+    });
+    return response?.message?.content || null;
+  }
+
+  /**
+   * Create a completion based on the received messages.
+   *
+   * @param messages A list of messages to send to the API.
+   * @param functions
+   * @returns The completion.
+   */
+  async complete(messages, functions = null) {
+    try {
+      let completion;
+      if (functions.length > 0) {
+        const { toolCall, text } = await this.functionCall(
+          messages,
+          functions,
+          this.#handleFunctionCallChat.bind(this)
+        );
+
+        if (toolCall !== null) {
+          this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
+          this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
+          return {
+            result: null,
+            functionCall: {
+              name: toolCall.name,
+              arguments: toolCall.arguments,
+            },
+            cost: 0,
+          };
+        }
+        completion = { content: text };
+      }
+
+      if (!completion?.content) {
+        this.providerLog(
+          "Will assume chat completion without tool call inputs."
+        );
+        const response = await this.client.chat({
+          model: this.model,
+          messages: this.cleanMsgs(messages),
+          options: {
+            use_mlock: true,
+            temperature: 0.5,
+          },
+        });
+        completion = response.message;
+      }
+
+      return {
+        result: completion.content,
+        cost: 0,
+      };
+    } catch (error) {
+      throw error;
+    }
+  }
+
+  /**
+   * Get the cost of the completion.
+   *
+   * @param _usage The completion to get the cost for.
+   * @returns The cost of the completion.
+   * Stubbed since LMStudio has no cost basis.
+   */
+  getCost(_usage) {
+    return 0;
+  }
+}
+
+module.exports = OllamaProvider;

server/utils/agents/index.js

@@ -79,7 +79,11 @@ class AgentHandler {
         break;
       case "lmstudio":
         if (!process.env.LMSTUDIO_BASE_PATH)
-          throw new Error("LMStudio bash path must be provided to use agents.");
+          throw new Error("LMStudio base path must be provided to use agents.");
+        break;
+      case "ollama":
+        if (!process.env.OLLAMA_BASE_PATH)
+          throw new Error("Ollama base path must be provided to use agents.");
         break;
       default:
         throw new Error("No provider found to power agent cluster.");
@@ -94,6 +98,8 @@ class AgentHandler {
         return "claude-3-sonnet-20240229";
       case "lmstudio":
         return "server-default";
+      case "ollama":
+        return "llama3:latest";
       default:
         return "unknown";
     }

server/utils/http/index.js

@@ -4,6 +4,7 @@ process.env.NODE_ENV === "development"
 const JWT = require("jsonwebtoken");
 const { User } = require("../../models/user");
 const { jsonrepair } = require("jsonrepair");
+const extract = require("extract-json-from-string");
 
 function reqBody(request) {
   return typeof request.body === "string"
@@ -67,8 +68,6 @@ function safeJsonParse(jsonString, fallback = null) {
     return JSON.parse(jsonString);
   } catch {}
 
-  // If the jsonString does not look like an Obj or Array, dont attempt
-  // to repair it.
   if (jsonString?.startsWith("[") || jsonString?.startsWith("{")) {
     try {
       const repairedJson = jsonrepair(jsonString);
@@ -76,6 +75,10 @@ function safeJsonParse(jsonString, fallback = null) {
     } catch {}
   }
 
+  try {
+    return extract(jsonString)[0];
+  } catch {}
+
   return fallback;
 }
 

server/yarn.lock

@@ -2678,6 +2678,11 @@ extract-files@^9.0.0:
   resolved "https://registry.yarnpkg.com/extract-files/-/extract-files-9.0.0.tgz#8a7744f2437f81f5ed3250ed9f1550de902fe54a"
   integrity sha512-CvdFfHkC95B4bBBk36hcEmvdR2awOdhhVUYH6S/zrVj3477zven/fJMYg7121h4T1xHZC+tetUpubpAhxwI7hQ==
 
+extract-json-from-string@^1.0.1:
+  version "1.0.1"
+  resolved "https://registry.yarnpkg.com/extract-json-from-string/-/extract-json-from-string-1.0.1.tgz#5001f17e6c905826dcd5989564e130959de60c96"
+  integrity sha512-xfQOSFYbELVs9QVkKsV9FZAjlAmXQ2SLR6FpfFX1kpn4QAvaGBJlrnVOblMLwrLPYc26H+q9qxo6JTd4E7AwgQ==
+
 extract-zip@^2.0.1:
   version "2.0.1"
   resolved "https://registry.yarnpkg.com/extract-zip/-/extract-zip-2.0.1.tgz#663dca56fe46df890d5f131ef4a06d22bb8ba13a"
@@ -4560,6 +4565,13 @@ octokit@^3.1.0:
     "@octokit/request-error" "^5.0.0"
     "@octokit/types" "^12.0.0"
 
+ollama@^0.5.0:
+  version "0.5.0"
+  resolved "https://registry.yarnpkg.com/ollama/-/ollama-0.5.0.tgz#cb9bc709d4d3278c9f484f751b0d9b98b06f4859"
+  integrity sha512-CRtRzsho210EGdK52GrUMohA2pU+7NbgEaBG3DcYeRmvQthDO7E2LHOkLlUUeaYUlNmEd8icbjC02ug9meSYnw==
+  dependencies:
+    whatwg-fetch "^3.6.20"
+
 on-finished@2.4.1:
   version "2.4.1"
   resolved "https://registry.yarnpkg.com/on-finished/-/on-finished-2.4.1.tgz#58c8c44116e54845ad57f14ab10b03533184ac3f"
@@ -5980,7 +5992,7 @@ webidl-conversions@^3.0.0:
   resolved "https://registry.yarnpkg.com/webidl-conversions/-/webidl-conversions-3.0.1.tgz#24534275e2a7bc6be7bc86611cc16ae0a5654871"
   integrity sha512-2JAn3z8AR6rjK8Sm8orRC0h/bcl/DqL7tRPdGZ4I1CjdF+EaMLmYxBHyXuKL849eucPFhvBoxMsflfOb8kxaeQ==
 
-whatwg-fetch@^3.4.1:
+whatwg-fetch@^3.4.1, whatwg-fetch@^3.6.20:
   version "3.6.20"
   resolved "https://registry.yarnpkg.com/whatwg-fetch/-/whatwg-fetch-3.6.20.tgz#580ce6d791facec91d37c72890995a0b48d31c70"
   integrity sha512-EqhiFU6daOA8kpjOWTL0olhVOF3i7OrFzSYiGsEMB8GcXS+RrzauAERX65xMeNWVqxA6HXH2m69Z9LaKKdisfg==