Remove tiktoken from the codebase

codeflash/code_utils/code_utils.py

@@ -10,6 +10,10 @@
 
 from codeflash.cli_cmds.console import logger
 
+def encoded_tokens_len(s: str) -> int:
+    '''Function for returning the approximate length of the encoded tokens
+    It's an approximation of BPE encoding (https://cdn.openai.com/better-language-models/language_models_are_unsupervised_multitask_learners.pdf)'''
+    return len(s)//2
 
 def get_qualified_name(module_name: str, full_qualified_name: str) -> str:
     if not full_qualified_name:

codeflash/context/code_context_extractor.py

@@ -7,13 +7,12 @@
 
 import jedi
 import libcst as cst
-import tiktoken
 from jedi.api.classes import Name
 from libcst import CSTNode
 
 from codeflash.cli_cmds.console import logger
 from codeflash.code_utils.code_extractor import add_needed_imports_from_module, find_preexisting_objects
-from codeflash.code_utils.code_utils import get_qualified_name, path_belongs_to_site_packages
+from codeflash.code_utils.code_utils import get_qualified_name, path_belongs_to_site_packages, encoded_tokens_len
 from codeflash.context.unused_definition_remover import remove_unused_definitions_by_function_names
 from codeflash.discovery.functions_to_optimize import FunctionToOptimize
 from codeflash.models.models import (
@@ -73,8 +72,7 @@ def get_code_optimization_context(
     )
 
     # Handle token limits
-    tokenizer = tiktoken.encoding_for_model("gpt-4o")
-    final_read_writable_tokens = len(tokenizer.encode(final_read_writable_code))
+    final_read_writable_tokens = encoded_tokens_len(final_read_writable_code)
     if final_read_writable_tokens > optim_token_limit:
         raise ValueError("Read-writable code has exceeded token limit, cannot proceed")
 
@@ -87,7 +85,7 @@ def get_code_optimization_context(
     )
     read_only_context_code = read_only_code_markdown.markdown
 
-    read_only_code_markdown_tokens = len(tokenizer.encode(read_only_context_code))
+    read_only_code_markdown_tokens = encoded_tokens_len(read_only_context_code)
     total_tokens = final_read_writable_tokens + read_only_code_markdown_tokens
     if total_tokens > optim_token_limit:
         logger.debug("Code context has exceeded token limit, removing docstrings from read-only code")
@@ -96,7 +94,7 @@ def get_code_optimization_context(
             helpers_of_fto_dict, helpers_of_helpers_dict, project_root_path, remove_docstrings=True
         )
         read_only_context_code = read_only_code_no_docstring_markdown.markdown
-        read_only_code_no_docstring_markdown_tokens = len(tokenizer.encode(read_only_context_code))
+        read_only_code_no_docstring_markdown_tokens = encoded_tokens_len(read_only_context_code)
         total_tokens = final_read_writable_tokens + read_only_code_no_docstring_markdown_tokens
         if total_tokens > optim_token_limit:
             logger.debug("Code context has exceeded token limit, removing read-only code")
@@ -111,7 +109,7 @@ def get_code_optimization_context(
         code_context_type=CodeContextType.TESTGEN,
     )
     testgen_context_code = testgen_code_markdown.code
-    testgen_context_code_tokens = len(tokenizer.encode(testgen_context_code))
+    testgen_context_code_tokens = encoded_tokens_len(testgen_context_code)
     if testgen_context_code_tokens > testgen_token_limit:
         testgen_code_markdown = extract_code_string_context_from_files(
             helpers_of_fto_dict,
@@ -121,7 +119,7 @@ def get_code_optimization_context(
             code_context_type=CodeContextType.TESTGEN,
         )
         testgen_context_code = testgen_code_markdown.code
-        testgen_context_code_tokens = len(tokenizer.encode(testgen_context_code))
+        testgen_context_code_tokens = encoded_tokens_len(testgen_context_code)
         if testgen_context_code_tokens > testgen_token_limit:
             raise ValueError("Testgen code context has exceeded token limit, cannot proceed")