Added rag examples for Ollama and a small readme

Author: damijanc

examples/ollama/Ollama.md

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+# Symfony Ollama Examples
+
+This directory contains various examples of how to use the Symfony AI with [Ollama](https://ollama.com/).
+
+## Getting started
+
+To get started with Ollama please check their [Quickstart guide](https://github.com/ollama/ollama/blob/main/README.md#quickstart).
+
+## Running the examples
+
+To run the examples you will need to download [Llama 3.2](https://ollama.com/library/llama3.2)
+and [nomic-embed-text](https://ollama.com/library/nomic-embed-text) models.
+
+Once models are downloaded you can run them with
+```bash
+ollama run <model-name>
+```
+for example
+
+```bash
+ollama run llama3.2
+```
+
+#### Configuration
+To run Ollama examples you will need to provide a OLLAMA_HOST_URL key in your env.local file.
+
+For example
+```bash
+OLLAMA_HOST_URL=http://localhost:11434
+```

examples/ollama/indexer.php

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+<?php
+
+/*
+ * This file is part of the Symfony package.
+ *
+ * (c) Fabien Potencier <fabien@symfony.com>
+ *
+ * For the full copyright and license information, please view the LICENSE
+ * file that was distributed with this source code.
+ */
+
+use Symfony\AI\Platform\Bridge\Ollama\Ollama;
+use Symfony\AI\Platform\Bridge\Ollama\PlatformFactory;
+use Symfony\AI\Store\Bridge\Local\InMemoryStore;
+use Symfony\AI\Store\Document\Loader\TextFileLoader;
+use Symfony\AI\Store\Document\Transformer\TextReplaceTransformer;
+use Symfony\AI\Store\Document\Transformer\TextSplitTransformer;
+use Symfony\AI\Store\Document\Vectorizer;
+use Symfony\AI\Store\Indexer;
+
+require_once dirname(__DIR__).'/bootstrap.php';
+
+$platform = PlatformFactory::create(env('OLLAMA_HOST_URL'), http_client());
+$store = new InMemoryStore();
+$vectorizer = new Vectorizer($platform, $embeddings = new Ollama(Ollama::NOMIC_EMBED_TEXT), logger());;
+$indexer = new Indexer(
+    loader: new TextFileLoader(),
+    vectorizer: $vectorizer,
+    store: $store,
+    source: [
+        dirname(__DIR__, 2).'/fixtures/movies/gladiator.md',
+        dirname(__DIR__, 2).'/fixtures/movies/inception.md',
+        dirname(__DIR__, 2).'/fixtures/movies/jurassic-park.md',
+    ],
+    transformers: [
+        new TextReplaceTransformer(search: '## Plot', replace: '## Synopsis'),
+        new TextSplitTransformer(chunkSize: 500, overlap: 100),
+    ],
+);
+
+$indexer->index();
+
+$vector = $vectorizer->vectorize('Roman gladiator revenge');
+$results = $store->query($vector);
+foreach ($results as $i => $document) {
+    echo sprintf("%d. %s\n", $i + 1, substr($document->id, 0, 40).'...');
+}

examples/ollama/rag.php

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+<?php
+
+/*
+ * This file is part of the Symfony package.
+ *
+ * (c) Fabien Potencier <fabien@symfony.com>
+ *
+ * For the full copyright and license information, please view the LICENSE
+ * file that was distributed with this source code.
+ */
+
+use Symfony\AI\Agent\Agent;
+use Symfony\AI\Agent\Toolbox\AgentProcessor;
+use Symfony\AI\Agent\Toolbox\Tool\SimilaritySearch;
+use Symfony\AI\Agent\Toolbox\Toolbox;
+use Symfony\AI\Fixtures\Movies;
+use Symfony\AI\Platform\Bridge\Ollama\PlatformFactory;
+use Symfony\AI\Platform\Message\Message;
+use Symfony\AI\Platform\Message\MessageBag;
+use Symfony\AI\Store\Bridge\Local\InMemoryStore;
+use Symfony\AI\Store\Document\Loader\InMemoryLoader;
+use Symfony\AI\Store\Document\Metadata;
+use Symfony\AI\Store\Document\TextDocument;
+use Symfony\AI\Store\Document\Vectorizer;
+use Symfony\AI\Store\Indexer;
+use Symfony\Component\Uid\Uuid;
+use Symfony\AI\Platform\Bridge\Ollama\Ollama;
+
+require_once dirname(__DIR__).'/bootstrap.php';
+
+// initialize the store
+$store = new InMemoryStore();
+$documents = [];
+
+// create embeddings and documents
+foreach (Movies::all() as $i => $movie) {
+    $documents[] = new TextDocument(
+        id: Uuid::v4(),
+        content: 'Title: '.$movie['title'].\PHP_EOL.'Director: '.$movie['director'].\PHP_EOL.'Description: '.$movie['description'],
+        metadata: new Metadata($movie),
+    );
+}
+
+// create embeddings for documents
+$platform = PlatformFactory::create(env('OLLAMA_HOST_URL'), http_client());
+$vectorizer = new Vectorizer($platform, $embeddings = new Ollama(Ollama::NOMIC_EMBED_TEXT), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
+$indexer->index($documents);
+
+$model = new Ollama();
+
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
+$toolbox = new Toolbox([$similaritySearch], logger: logger());
+$processor = new AgentProcessor($toolbox);
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
+
+$messages = new MessageBag(
+    Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),
+    Message::ofUser('Which movie fits the theme of the mafia?')
+);
+$result = $agent->call($messages);
+
+echo $result->getContent().\PHP_EOL;