Anthropic (Claude) provider (#22)

* Add Anthropic (Claude) chat provider

* Bump  package

* Add code completer based on Anthropic Chat

* Update system message

* Workaround to build settings for Anthropic

* lint

* Update README

Author: brichet

README.md

@@ -53,8 +53,8 @@ The process is different for each provider, so you may refer to their documentat
 
 ![Screenshot showing how to create an API key](./img/1-api-key.png)
 
-2. Open the JupyterLab settings and go to the **Ai providers** section to select the provider
-   (`mistral` is only supported one currently) and the API key (required).
+2. Open the JupyterLab settings and go to the **Ai providers** section to select the `MistralAI`
+   provider and the API key (required).
 
 ![Screenshot showing how to add the API key to the settings](./img/2-jupyterlab-settings.png)
 

package.json

@@ -61,6 +61,7 @@
         "@jupyterlab/notebook": "^4.4.0-alpha.0",
         "@jupyterlab/rendermime": "^4.4.0-alpha.0",
         "@jupyterlab/settingregistry": "^4.4.0-alpha.0",
+        "@langchain/anthropic": "^0.3.9",
         "@langchain/core": "^0.3.13",
         "@langchain/mistralai": "^0.1.1",
         "@lumino/coreutils": "^2.1.2",

schema/ai-provider.json

@@ -8,7 +8,7 @@
       "title": "The AI provider",
       "description": "The AI provider to use for chat and completion",
       "default": "None",
-      "enum": ["None", "MistralAI"]
+      "enum": ["None", "Anthropic", "MistralAI"]
     }
   },
   "additionalProperties": true

scripts/settings-generator.js

@@ -20,23 +20,57 @@ const schemaBase = tsj
   .createGenerator(configBase)
   .createSchema(configBase.type);
 
+/**
+ *  The providers are the list of providers for which we'd like to build settings from their interface.
+ *  The keys will be the names of the json files that will be linked to the selected provider.
+ *  The values are:
+ *   - path: path of the module containing the provider input description, in @langchain package.
+ *   - type: the type or interface to format to json settings.
+ *   - excludedProps: (optional) the properties to not include in the settings.
+ *     "ts-json-schema-generator" seems to not handle some imported types, so the workaround is
+ *     to exclude them at the moment, to be able to build other settings.
+ */
 const providers = {
   mistralAI: {
     path: 'node_modules/@langchain/mistralai/dist/chat_models.d.ts',
     type: 'ChatMistralAIInput'
+  },
+  anthropic: {
+    path: 'node_modules/@langchain/anthropic/dist/chat_models.d.ts',
+    type: 'AnthropicInput',
+    excludedProps: ['clientOptions']
   }
 };
 
 Object.entries(providers).forEach(([name, desc], index) => {
+  // The configuration doesn't include functions, which may probably not be filled
+  // from the settings panel.
   const config = {
     path: desc.path,
     tsconfig: './tsconfig.json',
-    type: desc.type
+    type: desc.type,
+    functions: 'hide'
   };
 
   const outputPath = path.join(outputDir, `${name}.json`);
 
-  const schema = tsj.createGenerator(config).createSchema(config.type);
+  const generator = tsj.createGenerator(config);
+  let schema;
+
+  // Workaround to exclude some properties from a type or interface.
+  if (desc.excludedProps) {
+    const nodes = generator.getRootNodes(config.type);
+    const finalMembers = [];
+    nodes[0].members.forEach(member => {
+      if (!desc.excludedProps.includes(member.symbol.escapedName)) {
+        finalMembers.push(member);
+      }
+    });
+    nodes[0].members = finalMembers;
+    schema = generator.createSchemaFromNodes(nodes);
+  } else {
+    schema = generator.createSchema(config.type);
+  }
 
   if (!schema.definitions) {
     return;

src/completion-provider.ts

@@ -3,10 +3,10 @@ import {
   IInlineCompletionContext,
   IInlineCompletionProvider
 } from '@jupyterlab/completer';
-import { LLM } from '@langchain/core/language_models/llms';
+import { BaseLanguageModel } from '@langchain/core/language_models/base';
+import { ReadonlyPartialJSONObject } from '@lumino/coreutils';
 
 import { getCompleter, IBaseCompleter, BaseCompleter } from './llm-models';
-import { ReadonlyPartialJSONObject } from '@lumino/coreutils';
 
 /**
  * The generic completion provider to register to the completion provider manager.
@@ -57,7 +57,7 @@ export class CompletionProvider implements IInlineCompletionProvider {
   /**
    * Get the LLM completer.
    */
-  get llmCompleter(): LLM | null {
+  get llmCompleter(): BaseLanguageModel | null {
     return this._completer?.provider || null;
   }
 

src/llm-models/anthropic-completer.ts

@@ -0,0 +1,65 @@
+import {
+  CompletionHandler,
+  IInlineCompletionContext
+} from '@jupyterlab/completer';
+import { ChatAnthropic } from '@langchain/anthropic';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { AIMessage, SystemMessage } from '@langchain/core/messages';
+
+import { BaseCompleter, IBaseCompleter } from './base-completer';
+
+export class AnthropicCompleter implements IBaseCompleter {
+  constructor(options: BaseCompleter.IOptions) {
+    this._anthropicProvider = new ChatAnthropic({ ...options.settings });
+  }
+
+  get provider(): BaseChatModel {
+    return this._anthropicProvider;
+  }
+
+  async fetch(
+    request: CompletionHandler.IRequest,
+    context: IInlineCompletionContext
+  ) {
+    const { text, offset: cursorOffset } = request;
+    const prompt = text.slice(0, cursorOffset);
+
+    // Anthropic does not allow whitespace at the end of the AIMessage
+    const trimmedPrompt = prompt.trim();
+
+    const messages = [
+      new SystemMessage(
+        'You are a code-completion AI completing the following code from a Jupyter Notebook cell.'
+      ),
+      new AIMessage(trimmedPrompt)
+    ];
+
+    try {
+      const response = await this._anthropicProvider.invoke(messages);
+      const items = [];
+
+      // Anthropic can return string or complex content, a list of string/images/other.
+      if (typeof response.content === 'string') {
+        items.push({
+          insertText: response.content
+        });
+      } else {
+        response.content.forEach(content => {
+          if (content.type !== 'text') {
+            return;
+          }
+          items.push({
+            insertText: content.text,
+            filterText: prompt.substring(trimmedPrompt.length)
+          });
+        });
+      }
+      return { items };
+    } catch (error) {
+      console.error('Error fetching completions', error);
+      return { items: [] };
+    }
+  }
+
+  private _anthropicProvider: ChatAnthropic;
+}

src/llm-models/base-completer.ts

@@ -2,14 +2,14 @@ import {
   CompletionHandler,
   IInlineCompletionContext
 } from '@jupyterlab/completer';
-import { LLM } from '@langchain/core/language_models/llms';
+import { BaseLanguageModel } from '@langchain/core/language_models/base';
 import { ReadonlyPartialJSONObject } from '@lumino/coreutils';
 
 export interface IBaseCompleter {
   /**
    * The LLM completer.
    */
-  provider: LLM;
+  provider: BaseLanguageModel;
 
   /**
    * The function to fetch a new completion.

src/llm-models/utils.ts

@@ -1,12 +1,15 @@
+import { ChatAnthropic } from '@langchain/anthropic';
 import { BaseChatModel } from '@langchain/core/language_models/chat_models';
 import { ChatMistralAI } from '@langchain/mistralai';
 import { JSONObject } from '@lumino/coreutils';
 
 import { IBaseCompleter } from './base-completer';
+import { AnthropicCompleter } from './anthropic-completer';
 import { CodestralCompleter } from './codestral-completer';
 import { ReadonlyPartialJSONObject } from '@lumino/coreutils';
 
 import mistralAI from '../_provider-settings/mistralAI.json';
+import anthropic from '../_provider-settings/anthropic.json';
 
 /**
  * Get an LLM completer from the name.
@@ -17,6 +20,8 @@ export function getCompleter(
 ): IBaseCompleter | null {
   if (name === 'MistralAI') {
     return new CodestralCompleter({ settings });
+  } else if (name === 'Anthropic') {
+    return new AnthropicCompleter({ settings });
   }
   return null;
 }
@@ -30,6 +35,8 @@ export function getChatModel(
 ): BaseChatModel | null {
   if (name === 'MistralAI') {
     return new ChatMistralAI({ ...settings });
+  } else if (name === 'Anthropic') {
+    return new ChatAnthropic({ ...settings });
   }
   return null;
 }
@@ -40,6 +47,8 @@ export function getChatModel(
 export function getErrorMessage(name: string, error: any): string {
   if (name === 'MistralAI') {
     return error.message;
+  } else if (name === 'Anthropic') {
+    return error.error.error.message;
   }
   return 'Unknown provider';
 }
@@ -50,6 +59,8 @@ export function getErrorMessage(name: string, error: any): string {
 export function getSettings(name: string): JSONObject | null {
   if (name === 'MistralAI') {
     return mistralAI.definitions.ChatMistralAIInput.properties;
+  } else if (name === 'Anthropic') {
+    return anthropic.definitions.AnthropicInput.properties;
   }
   return null;
 }