remove chromadb dependent code

Author: CTY-git

patchwork/common/utils/dependency.py

@@ -2,7 +2,6 @@
 from functools import lru_cache
 
 __DEPENDENCY_GROUPS = {
-    "rag": ["chromadb"],
     "security": ["semgrep", "depscan"],
     "notification": ["slack_sdk"],
 }
@@ -22,9 +21,5 @@ def import_with_dependency_group(name):
         raise ImportError(error_msg)
 
 
-def chromadb():
-    return import_with_dependency_group("chromadb")
-
-
 def slack_sdk():
     return import_with_dependency_group("slack_sdk")

patchwork/common/utils/utils.py

@@ -15,7 +15,6 @@
 from git import Head, Repo
 from typing_extensions import Any, Callable, Counter
 
-from patchwork.common.utils.dependency import chromadb
 from patchwork.logger import logger
 from patchwork.managed_files import HOME_FOLDER
 
@@ -129,68 +128,6 @@ def count_openai_tokens(code: str):
     return len(_ENCODING.encode(code))
 
 
-def get_vector_db_path() -> str:
-    CHROMA_DB_PATH = HOME_FOLDER / "chroma.db"
-    if CHROMA_DB_PATH:
-        return str(CHROMA_DB_PATH)
-    else:
-        return ".chroma.db"
-
-
-def openai_embedding_model(
-    inputs: dict,
-) -> "chromadb.api.types.EmbeddingFunction"["chromadb.api.types.Documents"] | None:
-    model = inputs.get(openai_embedding_model.__name__)
-    if model is None:
-        return None
-
-    api_key = inputs.get("openai_api_key")
-    if api_key is None:
-        raise ValueError("Missing required input data: 'openai_api_key'")
-
-    return chromadb().utils.embedding_functions.OpenAIEmbeddingFunction(
-        api_key=api_key,
-        model_name=model,
-    )
-
-
-def huggingface_embedding_model(
-    inputs: dict,
-) -> "chromadb.api.types.EmbeddingFunction"["chromadb.api.types.Documents"] | None:
-    model = inputs.get(huggingface_embedding_model.__name__)
-    if model is None:
-        return None
-
-    api_key = inputs.get("openai_api_key") or inputs.get("huggingface_api_key")
-    if api_key is None:
-        raise ValueError("Missing required input data: 'openai_api_key' or 'huggingface_api_key'")
-
-    return chromadb().utils.embedding_functions.HuggingFaceEmbeddingFunction(
-        api_key=api_key,
-        model_name=model,
-    )
-
-
-_EMBEDDING_FUNCS = [openai_embedding_model, huggingface_embedding_model]
-
-_EMBEDDING_TO_API_KEY_NAME: dict[
-    str, Callable[[dict], "chromadb.api.type.EmbeddingFunction"["chromadb.api.types.Documents"] | None]
-] = {func.__name__: func for func in _EMBEDDING_FUNCS}
-
-
-def get_embedding_function(inputs: dict) -> "chromadb.api.types.EmbeddingFunction"["chromadb.api.types.Documents"]:
-    embedding_function = next(
-        (func(inputs) for input_key, func in _EMBEDDING_TO_API_KEY_NAME.items() if input_key in inputs.keys()),
-        None,
-    )
-    if embedding_function is None:
-        raise ValueError(
-            f"Must specify an embedding model. Available options: {list(_EMBEDDING_TO_API_KEY_NAME.keys())}"
-        )
-
-    return embedding_function
-
-
 def get_current_branch(repo: Repo) -> Head:
     remote = repo.remote("origin")
     if repo.head.is_detached: