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fix: update example notebook imports to match v3 module structure (fixes #2356) #2387

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fix: update example notebook imports to match v3 module structure (fixes #2356) #2387

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68 changes: 32 additions & 36 deletions docs/examples_notebooks/local_search.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -189,42 +189,38 @@
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from graphrag.config.enums import ModelType\n",
"from graphrag.config.models.language_model_config import LanguageModelConfig\n",
"from graphrag.language_model.manager import ModelManager\n",
"from graphrag.tokenizer.get_tokenizer import get_tokenizer\n",
"\n",
"api_key = os.environ[\"GRAPHRAG_API_KEY\"]\n",
"\n",
"chat_config = LanguageModelConfig(\n",
" api_key=api_key,\n",
" type=ModelType.Chat,\n",
" model_provider=\"openai\",\n",
" model=\"gpt-4.1\",\n",
" max_retries=20,\n",
")\n",
"chat_model = ModelManager().get_or_create_chat_model(\n",
" name=\"local_search\",\n",
" model_type=ModelType.Chat,\n",
" config=chat_config,\n",
")\n",
"\n",
"embedding_config = LanguageModelConfig(\n",
" api_key=api_key,\n",
" type=ModelType.Embedding,\n",
" model_provider=\"openai\",\n",
" model=\"text-embedding-3-small\",\n",
" max_retries=20,\n",
")\n",
"\n",
"text_embedder = ModelManager().get_or_create_embedding_model(\n",
" name=\"local_search_embedding\",\n",
" model_type=ModelType.Embedding,\n",
" config=embedding_config,\n",
")\n",
"\n",
"tokenizer = get_tokenizer(chat_config)"
"source": [
"from graphrag_llm.config import ModelConfig\n",
"from graphrag_llm.completion.completion_factory import completion_factory\n",
"from graphrag_llm.embedding.embedding_factory import embedding_factory\n",
"from graphrag.tokenizer.get_tokenizer import get_tokenizer\n",
"\n",
"api_key = os.environ[\"GRAPHRAG_API_KEY\"]\n",
"\n",
"chat_config = ModelConfig(\n",
" api_key=api_key,\n",
" model_provider=\"openai\",\n",
" model=\"gpt-4.1\",\n",
" max_retries=20,\n",
")\n",
"chat_model = completion_factory.create(\n",
" name=\"local_search\",\n",
" config=chat_config,\n",
")\n",
"\n",
"embedding_config = ModelConfig(\n",
" api_key=api_key,\n",
" model_provider=\"openai\",\n",
" model=\"text-embedding-3-small\",\n",
" max_retries=20,\n",
")\n",
"\n",
"text_embedder = embedding_factory.create(\n",
" name=\"local_search_embedding\",\n",
" config=embedding_config,\n",
")\n",
"\n",
"tokenizer = get_tokenizer(chat_config)"
]
},
{
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