OpenAIv1: Don't instantiate openai.completions.create if key isn't present in environ

Author: irgolic

guardrails/applications/text2sql.py

@@ -7,7 +7,7 @@
 from guardrails.document_store import DocumentStoreBase, EphemeralDocumentStore
 from guardrails.embedding import EmbeddingBase, OpenAIEmbedding
 from guardrails.guard import Guard
-from guardrails.utils.openai_utils import static_openai_create_func
+from guardrails.utils.openai_utils import get_static_openai_create_func
 from guardrails.utils.sql_utils import create_sql_driver
 from guardrails.vectordb import Faiss, VectorDBBase
 
@@ -70,7 +70,7 @@ def __init__(
         rail_params: Optional[Dict] = None,
         example_formatter: Callable = example_formatter,
         reask_prompt: str = REASK_PROMPT,
-        llm_api: Callable = static_openai_create_func,
+        llm_api: Optional[Callable] = None,
         llm_api_kwargs: Optional[Dict] = None,
         num_relevant_examples: int = 2,
     ):
@@ -87,6 +87,8 @@ def __init__(
             example_formatter: Fn to format examples. Defaults to example_formatter.
             reask_prompt: Prompt to use for reasking. Defaults to REASK_PROMPT.
         """
+        if llm_api is None:
+            llm_api = get_static_openai_create_func()
 
         self.example_formatter = example_formatter
         self.llm_api = llm_api
@@ -184,9 +186,10 @@ def __call__(self, text: str) -> Optional[str]:
                 "Async API is not supported in Text2SQL application. "
                 "Please use a synchronous API."
             )
-
+        if self.llm_api is None:
+            return None
         try:
-            output = self.guard(
+            return self.guard(
                 self.llm_api,
                 prompt_params={
                     "nl_instruction": text,
@@ -200,6 +203,4 @@ def __call__(self, text: str) -> Optional[str]:
                 "generated_sql"
             ]
         except TypeError:
-            output = None
-
-        return output
+            return None

guardrails/llm_providers.py

@@ -6,10 +6,10 @@
 from guardrails.utils.openai_utils import (
     AsyncOpenAIClient,
     OpenAIClient,
-    static_openai_acreate_func,
-    static_openai_chat_acreate_func,
-    static_openai_chat_create_func,
-    static_openai_create_func,
+    get_static_openai_chat_acreate_func,
+    get_static_openai_chat_create_func,
+    get_static_openai_create_func,
+    get_static_openai_acreate_func,
 )
 from guardrails.utils.pydantic_utils import convert_pydantic_model_to_openai_fn
 
@@ -260,9 +260,9 @@ def _invoke_llm(self, *args, **kwargs) -> LLMResponse:
 def get_llm_ask(llm_api: Callable, *args, **kwargs) -> PromptCallableBase:
     if "temperature" not in kwargs:
         kwargs.update({"temperature": 0})
-    if llm_api == static_openai_create_func:
+    if llm_api == get_static_openai_create_func():
         return OpenAICallable(*args, **kwargs)
-    if llm_api == static_openai_chat_create_func:
+    if llm_api == get_static_openai_chat_create_func():
         return OpenAIChatCallable(*args, **kwargs)
 
     try:
@@ -475,9 +475,9 @@ def get_async_llm_ask(
 ) -> AsyncPromptCallableBase:
 
     # these only work with openai v0 (None otherwise)
-    if llm_api == static_openai_acreate_func:
+    if llm_api == get_static_openai_acreate_func():
         return AsyncOpenAICallable(*args, **kwargs)
-    if llm_api == static_openai_chat_acreate_func:
+    if llm_api == get_static_openai_chat_acreate_func():
         return AsyncOpenAIChatCallable(*args, **kwargs)
 
     try:

guardrails/utils/openai_utils/__init__.py

@@ -7,30 +7,30 @@
     from .v0 import OpenAIClientV0 as OpenAIClient
     from .v0 import (
         OpenAIServiceUnavailableError,
-        static_openai_acreate_func,
-        static_openai_chat_acreate_func,
-        static_openai_chat_create_func,
-        static_openai_create_func,
+        get_static_openai_chat_acreate_func,
+        get_static_openai_chat_create_func,
+        get_static_openai_create_func,
+        get_static_openai_acreate_func,
     )
 else:
     from .v1 import AsyncOpenAIClientV1 as AsyncOpenAIClient
     from .v1 import OpenAIClientV1 as OpenAIClient
     from .v1 import (
         OpenAIServiceUnavailableError,
-        static_openai_acreate_func,
-        static_openai_chat_acreate_func,
-        static_openai_chat_create_func,
-        static_openai_create_func,
+        get_static_openai_chat_acreate_func,
+        get_static_openai_chat_create_func,
+        get_static_openai_create_func,
+        get_static_openai_acreate_func,
     )
 
 
 __all__ = [
     "OPENAI_VERSION",
     "AsyncOpenAIClient",
     "OpenAIClient",
-    "static_openai_create_func",
-    "static_openai_chat_create_func",
-    "static_openai_acreate_func",
-    "static_openai_chat_acreate_func",
+    "get_static_openai_create_func",
+    "get_static_openai_chat_create_func",
+    "get_static_openai_acreate_func",
+    "get_static_openai_chat_acreate_func",
     "OpenAIServiceUnavailableError",
 ]

guardrails/utils/openai_utils/v0.py

@@ -10,10 +10,23 @@
     BaseSyncOpenAIClient,
 )
 
-static_openai_create_func = openai.Completion.create
-static_openai_chat_create_func = openai.ChatCompletion.create
-static_openai_acreate_func = openai.Completion.acreate
-static_openai_chat_acreate_func = openai.ChatCompletion.acreate
+
+def get_static_openai_create_func():
+    return openai.Completion.create
+
+
+def get_static_openai_chat_create_func():
+    return openai.ChatCompletion.create
+
+
+def get_static_openai_acreate_func():
+    return openai.Completion.acreate
+
+
+def get_static_openai_chat_acreate_func():
+    return openai.ChatCompletion.acreate
+
+
 OpenAIServiceUnavailableError = openai.error.ServiceUnavailableError
 
 OPENAI_RETRYABLE_ERRORS = [

guardrails/utils/openai_utils/v1.py

@@ -1,14 +1,32 @@
+import os
 from typing import Any, List
 
 import openai
 
 from guardrails.utils.llm_response import LLMResponse
 from guardrails.utils.openai_utils.base import BaseOpenAIClient
 
-static_openai_create_func = openai.completions.create
-static_openai_chat_create_func = openai.chat.completions.create
-static_openai_acreate_func = None
-static_openai_chat_acreate_func = None
+
+def get_static_openai_create_func():
+    if "OPENAI_API_KEY" not in os.environ:
+        return None
+    return openai.completions.create
+
+
+def get_static_openai_chat_create_func():
+    if "OPENAI_API_KEY" not in os.environ:
+        return None
+    return openai.chat.completions.create
+
+
+def get_static_openai_acreate_func():
+    return None
+
+
+def get_static_openai_chat_acreate_func():
+    return None
+
+
 OpenAIServiceUnavailableError = openai.APIError
 
 

guardrails/validators.py

@@ -20,7 +20,10 @@
 
 from guardrails.utils.casting_utils import to_int
 from guardrails.utils.docs_utils import get_chunks_from_text, sentence_split
-from guardrails.utils.openai_utils import OpenAIClient, static_openai_chat_create_func
+from guardrails.utils.openai_utils import (
+    OpenAIClient,
+    get_static_openai_chat_create_func,
+)
 from guardrails.utils.sql_utils import SQLDriver, create_sql_driver
 from guardrails.utils.validator_utils import PROVENANCE_V1_PROMPT
 from guardrails.validator_base import (
@@ -1285,7 +1288,7 @@ def __init__(
             )
 
         self.llm_callable = (
-            llm_callable if llm_callable else static_openai_chat_create_func
+            llm_callable if llm_callable else get_static_openai_chat_create_func()
         )
 
         self._threshold = threshold
@@ -1397,7 +1400,7 @@ def __init__(
             )
 
         self.llm_callable = (
-            llm_callable if llm_callable else static_openai_chat_create_func
+            llm_callable if llm_callable else get_static_openai_chat_create_func()
         )
 
     def _selfeval(self, question: str, answer: str):

tests/integration_tests/test_guard.py

@@ -8,8 +8,8 @@
 import guardrails as gd
 from guardrails.guard import Guard
 from guardrails.utils.openai_utils import (
-    static_openai_chat_create_func,
-    static_openai_create_func,
+    get_static_openai_chat_create_func,
+    get_static_openai_create_func,
 )
 from guardrails.utils.reask_utils import FieldReAsk
 from guardrails.validators import FailResult, OneLine
@@ -140,7 +140,7 @@ def test_entity_extraction_with_reask(
     guard = guard_initializer(rail, prompt)
 
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
         max_tokens=2000,
@@ -219,7 +219,7 @@ def test_entity_extraction_with_noop(mocker, rail, prompt):
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = guard_initializer(rail, prompt)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
     )
@@ -255,7 +255,7 @@ def test_entity_extraction_with_filter(mocker, rail, prompt):
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = guard_initializer(rail, prompt)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
     )
@@ -290,7 +290,7 @@ def test_entity_extraction_with_fix(mocker, rail, prompt):
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = guard_initializer(rail, prompt)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
     )
@@ -326,7 +326,7 @@ def test_entity_extraction_with_refrain(mocker, rail, prompt):
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = guard_initializer(rail, prompt)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
     )
@@ -369,7 +369,7 @@ def test_entity_extraction_with_fix_chat_models(mocker, rail, prompt, instructio
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = guard_initializer(rail, prompt, instructions)
     _, final_output = guard(
-        llm_api=static_openai_chat_create_func,
+        llm_api=get_static_openai_chat_create_func(),
         prompt_params={"document": content[:6000]},
         num_reasks=1,
     )
@@ -399,7 +399,7 @@ def test_string_output(mocker):
 
     guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_STRING)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"ingredients": "tomato, cheese, sour cream"},
         num_reasks=1,
     )
@@ -421,7 +421,7 @@ def test_string_reask(mocker):
 
     guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_STRING_REASK)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"ingredients": "tomato, cheese, sour cream"},
         num_reasks=1,
         max_tokens=100,
@@ -454,7 +454,7 @@ def test_skeleton_reask(mocker):
     content = gd.docs_utils.read_pdf("docs/examples/data/chase_card_agreement.pdf")
     guard = gd.Guard.from_rail_string(entity_extraction.RAIL_SPEC_WITH_SKELETON_REASK)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         prompt_params={"document": content[:6000]},
         max_tokens=1000,
         num_reasks=1,
@@ -497,7 +497,7 @@ def test_skeleton_reask(mocker):
 
     guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_LIST)
     _, final_output = guard(
-        llm_api=static_openai_create_func,
+        llm_api=get_static_openai_create_func(),
         num_reasks=1,
     )
     assert final_output == string.LIST_LLM_OUTPUT
@@ -523,7 +523,7 @@ def test_skeleton_reask(mocker):
             entity_extraction.OPTIONAL_PROMPT_COMPLETION_MODEL,
             None,
             None,
-            static_openai_create_func,
+            get_static_openai_create_func(),
             entity_extraction.COMPILED_PROMPT,
             None,
             entity_extraction.COMPILED_PROMPT_REASK,
@@ -534,7 +534,7 @@ def test_skeleton_reask(mocker):
             entity_extraction.OPTIONAL_PROMPT_CHAT_MODEL,
             entity_extraction.OPTIONAL_INSTRUCTIONS_CHAT_MODEL,
             None,
-            static_openai_chat_create_func,
+            get_static_openai_chat_create_func(),
             entity_extraction.COMPILED_PROMPT_WITHOUT_INSTRUCTIONS,
             entity_extraction.COMPILED_INSTRUCTIONS,
             entity_extraction.COMPILED_PROMPT_REASK_WITHOUT_INSTRUCTIONS,
@@ -545,7 +545,7 @@ def test_skeleton_reask(mocker):
             None,
             None,
             entity_extraction.OPTIONAL_MSG_HISTORY,
-            static_openai_chat_create_func,
+            get_static_openai_chat_create_func(),
             None,
             None,
             entity_extraction.COMPILED_PROMPT_REASK_WITHOUT_INSTRUCTIONS,
@@ -566,7 +566,7 @@ def test_entity_extraction_with_reask_with_optional_prompts(
     expected_reask_instructions,
 ):
     """Test that the entity extraction works with re-asking."""
-    if llm_api == static_openai_create_func:
+    if llm_api == get_static_openai_create_func():
         mocker.patch("guardrails.llm_providers.OpenAICallable", new=MockOpenAICallable)
     else:
         mocker.patch(
@@ -653,7 +653,7 @@ def test_string_with_message_history_reask(mocker):
 
     guard = gd.Guard.from_rail_string(string.RAIL_SPEC_FOR_MSG_HISTORY)
     _, final_output = guard(
-        llm_api=static_openai_chat_create_func,
+        llm_api=get_static_openai_chat_create_func(),
         msg_history=string.MOVIE_MSG_HISTORY,
         temperature=0.0,
         model="gpt-3.5-turbo",
@@ -689,7 +689,7 @@ def test_pydantic_with_message_history_reask(mocker):
 
     guard = gd.Guard.from_pydantic(output_class=pydantic.WITH_MSG_HISTORY)
     raw_output, guarded_output = guard(
-        llm_api=static_openai_chat_create_func,
+        llm_api=get_static_openai_chat_create_func(),
         msg_history=string.MOVIE_MSG_HISTORY,
         temperature=0.0,
         model="gpt-3.5-turbo",
@@ -731,7 +731,7 @@ def test_sequential_validator_log_is_not_duplicated(mocker):
         )
 
         _, final_output = guard(
-            llm_api=static_openai_create_func,
+            llm_api=get_static_openai_create_func(),
             prompt_params={"document": content[:6000]},
             num_reasks=1,
         )
@@ -765,7 +765,7 @@ def test_in_memory_validator_log_is_not_duplicated(mocker):
         )
 
         _, final_output = guard(
-            llm_api=static_openai_create_func,
+            llm_api=get_static_openai_create_func(),
             prompt_params={"document": content[:6000]},
             num_reasks=1,
         )