services(google): make api_key argument mandatory

CHANGELOG.md

@@ -7,6 +7,10 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 
 ## [Unreleased]
 
+### Changed
+
+- GoogleLLMService `api_key` argument is now mandatory.
+
 ### Fixed
 
 - Fixed AzureLLMService.

examples/foundational/12a-describe-video-gemini-flash.py

@@ -62,19 +62,15 @@ async def main(room_url: str, token):
             )
         )
 
-        tts = ElevenLabsTTSService(
-            aiohttp_session=session,
-            api_key=os.getenv("ELEVENLABS_API_KEY"),
-            voice_id=os.getenv("ELEVENLABS_VOICE_ID"),
-        )
-
         user_response = UserResponseAggregator()
 
         image_requester = UserImageRequester()
 
         vision_aggregator = VisionImageFrameAggregator()
 
-        google = GoogleLLMService(model="gemini-1.5-flash-latest")
+        google = GoogleLLMService(
+            model="gemini-1.5-flash-latest",
+            api_key=os.getenv("GOOGLE_API_KEY"))
 
         tts = ElevenLabsTTSService(
             aiohttp_session=session,

src/pipecat/services/anthropic.py

@@ -44,9 +44,9 @@ class AnthropicLLMService(LLMService):
 
     def __init__(
             self,
-            api_key,
-            model="claude-3-opus-20240229",
-            max_tokens=1024):
+            api_key: str,
+            model: str = "claude-3-opus-20240229",
+            max_tokens: int = 1024):
         super().__init__()
         self._client = AsyncAnthropic(api_key=api_key)
         self._model = model

src/pipecat/services/azure.py

@@ -11,6 +11,7 @@ import io
 from PIL import Image
 from typing import AsyncGenerator
 
+from numpy import str_
 from openai import AsyncAzureOpenAI
 
 from pipecat.frames.frames import AudioRawFrame, ErrorFrame, Frame, URLImageRawFrame
@@ -73,10 +74,10 @@ class AzureLLMService(BaseOpenAILLMService):
     def __init__(
             self,
             *,
-            api_key,
-            endpoint,
-            api_version="2023-12-01-preview",
-            model):
+            api_key: str,
+            endpoint: str,
+            model: str,
+            api_version: str = "2023-12-01-preview"):
         # Initialize variables before calling parent __init__() because that
         # will call create_client() and we need those values there.
         self._endpoint = endpoint
@@ -96,12 +97,12 @@ class AzureImageGenServiceREST(ImageGenService):
     def __init__(
         self,
         *,
-        api_version="2023-06-01-preview",
-        image_size: str,
         aiohttp_session: aiohttp.ClientSession,
-        api_key,
-        endpoint,
-        model,
+        image_size: str,
+        api_key: str,
+        endpoint: str,
+        model: str,
+        api_version="2023-06-01-preview",
     ):
         super().__init__()
 

src/pipecat/services/fireworks.py

@@ -19,6 +19,6 @@ except ModuleNotFoundError as e:
 
 class FireworksLLMService(BaseOpenAILLMService):
     def __init__(self,
-                 model="accounts/fireworks/models/firefunction-v1",
-                 base_url="https://api.fireworks.ai/inference/v1"):
+                 model: str = "accounts/fireworks/models/firefunction-v1",
+                 base_url: str = "https://api.fireworks.ai/inference/v1"):
         super().__init__(model, base_url)

src/pipecat/services/google.py

@@ -40,9 +40,9 @@ class GoogleLLMService(LLMService):
     franca for all LLM services, so that it is easy to switch between different LLMs.
     """
 
-    def __init__(self, model="gemini-1.5-flash-latest", api_key=None, **kwargs):
+    def __init__(self, api_key: str, model: str = "gemini-1.5-flash-latest", **kwargs):
         super().__init__(**kwargs)
-        gai.configure(api_key=api_key or os.environ["GOOGLE_API_KEY"])
+        gai.configure(api_key=api_key)
         self._client = gai.GenerativeModel(model)
 
     def _get_messages_from_openai_context(

src/pipecat/services/ollama.py

@@ -9,5 +9,5 @@ from pipecat.services.openai import BaseOpenAILLMService
 
 class OLLamaLLMService(BaseOpenAILLMService):
 
-    def __init__(self, model="llama2", base_url="http://localhost:11434/v1"):
+    def __init__(self, model: str = "llama2", base_url: str = "http://localhost:11434/v1"):
         super().__init__(model=model, base_url=base_url, api_key="ollama")