[Examples] Fix Indexer & Agent usage in examples

examples/anthropic/toolcall.php

@@ -26,7 +26,7 @@
 $wikipedia = new Wikipedia(http_client());
 $toolbox = new Toolbox([$wikipedia], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('Who is the current chancellor of Germany?'));
 $result = $agent->call($messages);

examples/bedrock/toolcall-claude.php

@@ -32,7 +32,7 @@
 $wikipedia = new Wikipedia(http_client());
 $toolbox = new Toolbox([$wikipedia]);
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('Who is the current chancellor of Germany?'));
 $result = $agent->call($messages);

examples/bedrock/toolcall-nova.php

@@ -32,7 +32,7 @@
 $wikipedia = new Wikipedia(http_client());
 $toolbox = new Toolbox([$wikipedia]);
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::ofUser('Who is the current chancellor of Germany? Use Wikipedia to find the answer.')

examples/gemini/server-tools.php

@@ -27,7 +27,7 @@
 
 $toolbox = new Toolbox([new Clock()], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $llm, [$processor], [$processor], logger());
+$agent = new Agent($platform, $llm, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::ofUser(

examples/gemini/structured-output-clock.php

@@ -29,7 +29,7 @@
 $toolbox = new Toolbox([$clock]);
 $toolProcessor = new ToolProcessor($toolbox);
 $structuredOutputProcessor = new StructuredOutputProcessor();
-$agent = new Agent($platform, $model, [$toolProcessor, $structuredOutputProcessor], [$toolProcessor, $structuredOutputProcessor], logger());
+$agent = new Agent($platform, $model, [$toolProcessor, $structuredOutputProcessor], [$toolProcessor, $structuredOutputProcessor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('What date and time is it?'));
 $result = $agent->call($messages, ['response_format' => [

examples/gemini/structured-output-math.php

@@ -23,7 +23,7 @@
 $model = new Gemini(Gemini::GEMINI_1_5_FLASH);
 
 $processor = new AgentProcessor();
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 $messages = new MessageBag(
     Message::forSystem('You are a helpful math tutor. Guide the user through the solution step by step.'),
     Message::ofUser('how can I solve 8x + 7 = -23'),

examples/gemini/toolcall.php

@@ -25,7 +25,7 @@
 
 $toolbox = new Toolbox([new Clock()], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $llm, [$processor], [$processor], logger());
+$agent = new Agent($platform, $llm, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('What time is it?'));
 $result = $agent->call($messages);

examples/memory/mariadb.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\MariaDb\Store;
+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;
@@ -59,7 +60,7 @@
 // create embeddings for documents as preparation of the chain memory
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
 $vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 // Execute a chat call that is utilizing the memory

examples/mistral/structured-output-math.php

@@ -28,7 +28,7 @@
 $serializer = new Serializer([new ObjectNormalizer()], [new JsonEncoder()]);
 
 $processor = new AgentProcessor(new ResponseFormatFactory(), $serializer);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 $messages = new MessageBag(
     Message::forSystem('You are a helpful math tutor. Guide the user through the solution step by step.'),
     Message::ofUser('how can I solve 8x + 7 = -23'),

examples/mistral/toolcall-stream.php

@@ -26,7 +26,7 @@
 $transcriber = new YouTubeTranscriber(http_client());
 $toolbox = new Toolbox([$transcriber], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('Please summarize this video for me: https://www.youtube.com/watch?v=6uXW-ulpj0s'));
 $result = $agent->call($messages, [

examples/mistral/toolcall.php

@@ -25,7 +25,7 @@
 
 $toolbox = new Toolbox([new Clock()], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('What time is it?'));
 $result = $agent->call($messages);

examples/ollama/structured-output-math.php

@@ -23,7 +23,7 @@
 $model = new Ollama();
 
 $processor = new AgentProcessor();
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 $messages = new MessageBag(
     Message::forSystem('You are a helpful math tutor. Guide the user through the solution step by step.'),
     Message::ofUser('how can I solve 8x + 7 = -23'),

examples/ollama/toolcall.php

@@ -25,7 +25,7 @@
 
 $toolbox = new Toolbox([new Clock()], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('What time is it?'));
 $result = $agent->call($messages);

examples/openai/structured-output-math.php

@@ -23,7 +23,7 @@
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
 $processor = new AgentProcessor();
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 $messages = new MessageBag(
     Message::forSystem('You are a helpful math tutor. Guide the user through the solution step by step.'),
     Message::ofUser('how can I solve 8x + 7 = -23'),

examples/openai/toolcall-stream.php

@@ -26,7 +26,7 @@
 $wikipedia = new Wikipedia(http_client());
 $toolbox = new Toolbox([$wikipedia], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 $messages = new MessageBag(Message::ofUser(<<<TXT
         First, define unicorn in 30 words.
         Then lookup at Wikipedia what the irish history looks like in 2 sentences.

examples/openai/toolcall.php

@@ -26,7 +26,7 @@
 $transcriber = new YouTubeTranscriber(http_client());
 $toolbox = new Toolbox([$transcriber], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(Message::ofUser('Please summarize this video for me: https://www.youtube.com/watch?v=6uXW-ulpj0s'));
 $result = $agent->call($messages);

examples/rag/cache.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\Local\CacheStore;
+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;
@@ -43,16 +44,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/chromadb.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\ChromaDb\Store;
+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;
@@ -50,16 +51,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/clickhouse.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\ClickHouse\Store;
+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;
@@ -51,16 +52,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/cloudflare.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\Cloudflare\Store;
+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;
@@ -51,16 +52,16 @@
 
 // create embeddings for documents (keep in mind that upserting vectors is asynchronous)
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/in-memory.php

@@ -20,6 +20,7 @@
 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;
@@ -42,16 +43,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/mariadb-gemini.php

@@ -23,6 +23,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\MariaDb\Store;
+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;
@@ -53,16 +54,16 @@
 // create embeddings for documents
 $platform = PlatformFactory::create(env('GEMINI_API_KEY'), http_client());
 $embeddings = new Embeddings(options: ['dimensions' => 768, 'task_type' => TaskType::SemanticSimilarity]);
-$vectorizer = new Vectorizer($platform, $embeddings);
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gemini(Gemini::GEMINI_2_FLASH_LITE);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/mariadb-openai.php

@@ -22,6 +22,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\MariaDb\Store;
+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;
@@ -51,16 +52,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),

examples/rag/meilisearch.php

@@ -20,6 +20,7 @@
 use Symfony\AI\Platform\Message\Message;
 use Symfony\AI\Platform\Message\MessageBag;
 use Symfony\AI\Store\Bridge\Meilisearch\Store;
+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;
@@ -51,16 +52,16 @@
 
 // create embeddings for documents
 $platform = PlatformFactory::create(env('OPENAI_API_KEY'), http_client());
-$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings());
-$indexer = new Indexer($vectorizer, $store, logger());
+$vectorizer = new Vectorizer($platform, $embeddings = new Embeddings(), logger());
+$indexer = new Indexer(new InMemoryLoader($documents), $vectorizer, $store, logger: logger());
 $indexer->index($documents);
 
 $model = new Gpt(Gpt::GPT_4O_MINI);
 
-$similaritySearch = new SimilaritySearch($platform, $embeddings, $store);
+$similaritySearch = new SimilaritySearch($vectorizer, $store);
 $toolbox = new Toolbox([$similaritySearch], logger: logger());
 $processor = new AgentProcessor($toolbox);
-$agent = new Agent($platform, $model, [$processor], [$processor], logger());
+$agent = new Agent($platform, $model, [$processor], [$processor], logger: logger());
 
 $messages = new MessageBag(
     Message::forSystem('Please answer all user questions only using SimilaritySearch function.'),