Fix tokenizer loading for GPT2

Fixes #752

Fix the issue with loading the tokenizer for 'gpt2'.

* **scrapegraphai/utils/tokenizer.py**
  - Add a check for `GPT2TokenizerFast` in the `num_tokens_calculus` function.
  - Import `GPT2TokenizerFast` from `transformers`.

* **scrapegraphai/utils/tokenizers/tokenizer_ollama.py**
  - Modify the `num_tokens_ollama` function to handle `GPT2TokenizerFast`.

* **tests/graphs/smart_scraper_ollama_test.py**
  - Add a test case to verify the tokenizer loading for `GPT2TokenizerFast`.

---

For more details, open the [Copilot Workspace session](https://copilot-workspace.githubnext.com/ScrapeGraphAI/Scrapegraph-ai/issues/752?shareId=XXXX-XXXX-XXXX-XXXX).

Author: yusefes

scrapegraphai/utils/tokenizer.py

@@ -6,6 +6,7 @@
 from langchain_ollama import ChatOllama
 from langchain_mistralai import ChatMistralAI
 from langchain_core.language_models.chat_models import BaseChatModel
+from transformers import GPT2TokenizerFast
 
 def num_tokens_calculus(string: str, llm_model: BaseChatModel) -> int:
     """
@@ -23,6 +24,13 @@ def num_tokens_calculus(string: str, llm_model: BaseChatModel) -> int:
         from .tokenizers.tokenizer_ollama import num_tokens_ollama
         num_tokens_fn = num_tokens_ollama
 
+    elif isinstance(llm_model, GPT2TokenizerFast):
+        def num_tokens_gpt2(text: str, model: BaseChatModel) -> int:
+            tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")
+            tokens = tokenizer.encode(text)
+            return len(tokens)
+        num_tokens_fn = num_tokens_gpt2
+
     else:
         from .tokenizers.tokenizer_openai import num_tokens_openai
         num_tokens_fn = num_tokens_openai

scrapegraphai/utils/tokenizers/tokenizer_ollama.py

@@ -3,6 +3,7 @@
 """
 from langchain_core.language_models.chat_models import BaseChatModel
 from ..logging import get_logger
+from transformers import GPT2TokenizerFast
 
 def num_tokens_ollama(text: str, llm_model:BaseChatModel) -> int:
     """
@@ -21,8 +22,12 @@ def num_tokens_ollama(text: str, llm_model:BaseChatModel) -> int:
 
     logger.debug(f"Counting tokens for text of {len(text)} characters")
 
+    if isinstance(llm_model, GPT2TokenizerFast):
+        tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")
+        tokens = tokenizer.encode(text)
+        return len(tokens)
+
     # Use langchain token count implementation
     # NB: https://github.com/ollama/ollama/issues/1716#issuecomment-2074265507
     tokens = llm_model.get_num_tokens(text)
     return tokens
-

tests/graphs/smart_scraper_ollama_test.py

@@ -3,6 +3,7 @@
 """
 import pytest
 from scrapegraphai.graphs import SmartScraperGraph
+from transformers import GPT2TokenizerFast
 
 
 @pytest.fixture
@@ -50,3 +51,11 @@ def test_get_execution_info(graph_config: dict):
     graph_exec_info = smart_scraper_graph.get_execution_info()
 
     assert graph_exec_info is not None
+
+
+def test_gpt2_tokenizer_loading():
+    """
+    Test loading of GPT2TokenizerFast
+    """
+    tokenizer = GPT2TokenizerFast.from_pretrained("gpt2")
+    assert tokenizer is not None