さらに小型のモデルに変更、環境変数に切り出し

.env.example

@@ -1,2 +1,6 @@
 OPENAI_API_KEY=
-CLOUDFLARE_AI_GATEWAY=
+CLOUDFLARE_AI_GATEWAY=
+OLLAMA_BASE_URL=http://localhost:11434
+OLLAMA_CHAT_MODEL=smollm:135m
+OLLAMA_EMBED_MODEL=all-minilm:l6-v2
+OLLAMA_ENABLED=true

.env.test

@@ -0,0 +1,6 @@
+OPENAI_API_KEY=
+CLOUDFLARE_AI_GATEWAY=
+OLLAMA_BASE_URL=http://localhost:11434
+OLLAMA_CHAT_MODEL=smollm:135m
+OLLAMA_EMBED_MODEL=all-minilm:l6-v2
+OLLAMA_ENABLED=true

.github/workflows/test-with-ollama.yml

@@ -15,12 +15,12 @@ jobs:
       - uses: actions/checkout@v4
         with:
           fetch-depth: 1
-      - name: Run Ollama Docker image and pull models
+      - name: Launch Ollama Docker image and pull models
         run: |
           mkdir -p ~/.ollama/models
           docker run -d -v ollama:/home/runner/.ollama -p 11434:11434 --name ollama ollama/ollama
           sleep 20
-          docker exec ollama ollama pull gemma2:2b
+          docker exec ollama ollama pull smollm:135m
           docker exec ollama ollama pull all-minilm:l6-v2
           sleep 20
           time curl -i http://localhost:11434

scripts/agent.ts

@@ -69,7 +69,7 @@ let llm;
 if (process.env.OLLAMA_BASE_URL && process.env.OLLAMA_ENABLED === "true") {
   llm = new ChatOllama({
     baseUrl: process.env.OLLAMA_BASE_URL,
-    model: process.env.OLLAMA_MODEL,
+    model: process.env.OLLAMA_CHAT_MODEL,
     temperature: 0.0,
   });
 } else {

scripts/instruct.ts

@@ -143,7 +143,7 @@ const setupCharitesAiDynamicPrompt = async (
   if (process.env.OLLAMA_BASE_URL && process.env.OLLAMA_ENABLED === "true") {
     embeddings = new OllamaEmbeddings({
       baseUrl: process.env.OLLAMA_BASE_URL,
-      model: "all-minilm:l6-v2",
+      model: process.env.OLLAMA_EMBED_MODEL,
     });
   } else {
     if (!process.env.OPENAI_API_KEY) {
@@ -341,7 +341,7 @@ export const initializeCharitesAiChain = async (): Promise<
   if (process.env.OLLAMA_BASE_URL && process.env.OLLAMA_ENABLED === "true") {
     llm = new ChatOllama({
       baseUrl: process.env.OLLAMA_BASE_URL,
-      model: process.env.OLLAMA_MODEL,
+      model: process.env.OLLAMA_CHAT_MODEL,
       temperature: 0.0,
     });
   } else {

test/ollamaEmbeddings.test.ts

@@ -3,10 +3,15 @@ import { MemoryVectorStore } from "langchain/vectorstores/memory";
 import type { Document } from "@langchain/core/documents";
 import { expect, test } from "vitest";
 
+// process.env を .env.test から読み込む
+import process from "node:process";
+import { config } from "dotenv";
+config({ path: ".env.test" });
+
 test("ollama embedding", async () => {
   const embeddings = new OllamaEmbeddings({
-    baseUrl: "http://localhost:11434",
-    model: "all-minilm:l6-v2",
+    baseUrl: process.env.OLLAMA_BASE_URL,
+    model: process.env.OLLAMA_EMBED_MODEL,
   });
 
   const vectorStore = new MemoryVectorStore(embeddings);

test/ollamaInvoke.test.ts

@@ -1,10 +1,15 @@
 import { Ollama } from "@langchain/ollama";
 import { expect, test } from "vitest";
 
+// process.env を .env.test から読み込む
+import process from "node:process";
+import { config } from "dotenv";
+config({ path: ".env.test" });
+
 test("ollama invoke", async () => {
   const llm = new Ollama({
-    baseUrl: "http://localhost:11434",
-    model: "gemma2:2b",
+    baseUrl: process.env.OLLAMA_BASE_URL,
+    model: process.env.OLLAMA_CHAT_MODEL,
     temperature: 0.0,
   });