Add LLMService stubs for Grok and Groq, add examples

src/pipecat/services/grok.py

@@ -0,0 +1,103 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+from loguru import logger
+
+from pipecat.metrics.metrics import LLMTokenUsage
+from pipecat.processors.aggregators.openai_llm_context import OpenAILLMContext
+from pipecat.services.openai import OpenAILLMService
+
+
+class GrokLLMService(OpenAILLMService):
+    """A service for interacting with Grok's API using the OpenAI-compatible interface.
+
+    This service extends OpenAILLMService to connect to Grok's API endpoint while
+    maintaining full compatibility with OpenAI's interface and functionality.
+
+    Args:
+        api_key (str): The API key for accessing Grok's API
+        base_url (str, optional): The base URL for Grok API. Defaults to "https://api.x.ai/v1"
+        model (str, optional): The model identifier to use. Defaults to "grok-beta"
+        **kwargs: Additional keyword arguments passed to OpenAILLMService
+    """
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        base_url: str = "https://api.x.ai/v1",
+        model: str = "grok-beta",
+        **kwargs,
+    ):
+        super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs)
+        # Initialize counters for token usage metrics
+        self._prompt_tokens = 0
+        self._completion_tokens = 0
+        self._total_tokens = 0
+        self._has_reported_prompt_tokens = False
+        self._is_processing = False
+
+    def create_client(self, api_key=None, base_url=None, **kwargs):
+        """Create OpenAI-compatible client for Grok API endpoint."""
+        logger.debug(f"Creating Grok client with api {base_url}")
+        return super().create_client(api_key, base_url, **kwargs)
+
+    async def _process_context(self, context: OpenAILLMContext):
+        """Process a context through the LLM and accumulate token usage metrics.
+
+        This method overrides the parent class implementation to handle Grok's
+        incremental token reporting style, accumulating the counts and reporting
+        them once at the end of processing.
+
+        Args:
+            context (OpenAILLMContext): The context to process, containing messages
+                and other information needed for the LLM interaction.
+        """
+        # Reset all counters and flags at the start of processing
+        self._prompt_tokens = 0
+        self._completion_tokens = 0
+        self._total_tokens = 0
+        self._has_reported_prompt_tokens = False
+        self._is_processing = True
+
+        try:
+            await super()._process_context(context)
+        finally:
+            self._is_processing = False
+            # Report final accumulated token usage at the end of processing
+            if self._prompt_tokens > 0 or self._completion_tokens > 0:
+                self._total_tokens = self._prompt_tokens + self._completion_tokens
+                tokens = LLMTokenUsage(
+                    prompt_tokens=self._prompt_tokens,
+                    completion_tokens=self._completion_tokens,
+                    total_tokens=self._total_tokens,
+                )
+                await super().start_llm_usage_metrics(tokens)
+
+    async def start_llm_usage_metrics(self, tokens: LLMTokenUsage):
+        """Accumulate token usage metrics during processing.
+
+        This method intercepts the incremental token updates from Grok's API
+        and accumulates them instead of passing each update to the metrics system.
+        The final accumulated totals are reported at the end of processing.
+
+        Args:
+            tokens (LLMTokenUsage): The token usage metrics for the current chunk
+                of processing, containing prompt_tokens and completion_tokens counts.
+        """
+        # Only accumulate metrics during active processing
+        if not self._is_processing:
+            return
+
+        # Record prompt tokens the first time we see them
+        if not self._has_reported_prompt_tokens and tokens.prompt_tokens > 0:
+            self._prompt_tokens = tokens.prompt_tokens
+            self._has_reported_prompt_tokens = True
+
+        # Update completion tokens count if it has increased
+        if tokens.completion_tokens > self._completion_tokens:
+            self._completion_tokens = tokens.completion_tokens

src/pipecat/services/groq.py

@@ -0,0 +1,39 @@
+#
+# Copyright (c) 2024, Daily
+#
+# SPDX-License-Identifier: BSD 2-Clause License
+#
+
+
+from loguru import logger
+
+from pipecat.services.openai import OpenAILLMService
+
+
+class GroqLLMService(OpenAILLMService):
+    """A service for interacting with Groq's API using the OpenAI-compatible interface.
+
+    This service extends OpenAILLMService to connect to Groq's API endpoint while
+    maintaining full compatibility with OpenAI's interface and functionality.
+
+    Args:
+        api_key (str): The API key for accessing Groq's API
+        base_url (str, optional): The base URL for Groq API. Defaults to "https://api.groq.com/openai/v1"
+        model (str, optional): The model identifier to use. Defaults to "llama-3.1-70b-versatile"
+        **kwargs: Additional keyword arguments passed to OpenAILLMService
+    """
+
+    def __init__(
+        self,
+        *,
+        api_key: str,
+        base_url: str = "https://api.groq.com/openai/v1",
+        model: str = "llama-3.1-70b-versatile",
+        **kwargs,
+    ):
+        super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs)
+
+    def create_client(self, api_key=None, base_url=None, **kwargs):
+        """Create OpenAI-compatible client for Groq API endpoint."""
+        logger.debug(f"Creating Groq client with api {base_url}")
+        return super().create_client(api_key, base_url, **kwargs)

src/pipecat/services/together.py

@@ -9,20 +9,19 @@ from loguru import logger
 
 from pipecat.services.openai import OpenAILLMService
 
-try:
-    # Together.ai is recommending OpenAI-compatible function calling, so we've switched over
-    # to using the OpenAI client library here rather than the Together Python client library.
-    from openai import AsyncOpenAI, DefaultAsyncHttpxClient
-except ModuleNotFoundError as e:
-    logger.error(f"Exception: {e}")
-    logger.error(
-        "In order to use Together.ai, you need to `pip install pipecat-ai[together]`. Also, set `TOGETHER_API_KEY` environment variable."
-    )
-    raise Exception(f"Missing module: {e}")
-
 
 class TogetherLLMService(OpenAILLMService):
-    """This class implements inference with Together's Llama 3.1 models"""
+    """A service for interacting with Together.ai's API using the OpenAI-compatible interface.
+
+    This service extends OpenAILLMService to connect to Together.ai's API endpoint while
+    maintaining full compatibility with OpenAI's interface and functionality.
+
+    Args:
+        api_key (str): The API key for accessing Together.ai's API
+        base_url (str, optional): The base URL for Together.ai API. Defaults to "https://api.together.xyz/v1"
+        model (str, optional): The model identifier to use. Defaults to "meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo"
+        **kwargs: Additional keyword arguments passed to OpenAILLMService
+    """
 
     def __init__(
         self,
@@ -35,5 +34,6 @@ class TogetherLLMService(OpenAILLMService):
         super().__init__(api_key=api_key, base_url=base_url, model=model, **kwargs)
 
     def create_client(self, api_key=None, base_url=None, **kwargs):
+        """Create OpenAI-compatible client for Together.ai API endpoint."""
         logger.debug(f"Creating Together.ai client with api {base_url}")
         return super().create_client(api_key, base_url, **kwargs)