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name = "vonage" -version = "3.15.0" +version = "3.16.0" description = "Vonage Server SDK for Python" optional = true python-versions = ">=3.8" files = [ - {file = "vonage-3.15.0-py2.py3-none-any.whl", hash = "sha256:2843345a744444ab5a7ba24ffed8ea2b5493edbc2e47292b1a3e924b2df55cac"}, - {file = "vonage-3.15.0.tar.gz", hash = "sha256:4ce60ad0d52c43fb05e860050598576b97a4397aa426f19c3326c76978b4ffc8"}, + {file = "vonage-3.16.0-py2.py3-none-any.whl", hash = "sha256:ce14eb29f0942c55899c48254d39cb6624cdc1ff5e9b1ca6d520afea85abc352"}, + {file = "vonage-3.16.0.tar.gz", hash = "sha256:63ea60a70b358ddfc7b5491b1b39d3699d25fa41a6e9246ac4c8f3c5aeeff830"}, ] [package.dependencies] @@ -4496,13 +4869,14 @@ doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linke test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"] [extras] -all = ["cartesia", "google-cloud-speech", "google-cloud-texttospeech", "langchain", "langchain-community", "miniaudio", "nltk", "pvkoala", "pydub", "twilio", "vonage"] -misc = ["langchain", "langchain-community"] -synthesizers = ["cartesia", "google-cloud-texttospeech", "miniaudio", "nltk", "pvkoala", "pydub"] +all = ["cartesia", "google-cloud-speech", "google-cloud-texttospeech", "langchain", "langchain-anthropic", "langchain-community", "langchain-google-vertexai", "langchain-openai", "miniaudio", "nltk", "pvkoala", "pydub", "twilio", "vonage"] +langchain = ["langchain", "langchain-community"] +langchain-extras = ["langchain-anthropic", "langchain-google-vertexai", "langchain-openai"] +synthesizers = ["cartesia", "google-cloud-texttospeech", "miniaudio", "pvkoala", "pydub"] telephony = ["twilio", "vonage"] transcribers = ["google-cloud-speech"] [metadata] lock-version = "2.0" python-versions = ">=3.10,<4.0" -content-hash = "0153515588beee9a13a33a4fb32d26dad863de37b6c55f903148f9c88904dc82" +content-hash = "59b6b342ffc54a65f689eefb365412d8ad21d2e47dd4cf104bc7ac779b723e34" diff --git a/pyproject.toml b/pyproject.toml index 32785b226..8e2cb3b53 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -49,9 +49,12 @@ google-cloud-speech = { version = "^2.26.0", optional = true } twilio = { version = "^9.1.0", optional = true } vonage = { version = "^3.14.0", optional = true } -# Misc -langchain = { version = "^0.2.1", optional = true } -langchain-community = { version = "^0.2.1", optional = true } +# Langchain +langchain = { version = "^0.2.3", optional = true } +langchain-community = { version = "^0.2.4", optional = true } +langchain-openai = { version = "^0.1.8", optional = true } +langchain-anthropic = { version = "^0.1.15", optional = true } +langchain-google-vertexai = { version = "^1.0.5", optional = true } [tool.poetry.group.lint.dependencies] @@ -86,7 +89,8 @@ synthesizers = [ ] transcribers = ["google-cloud-speech"] telephony = ["twilio", "vonage"] -misc = ["langchain", "langchain-community"] +langchain = ["langchain", "langchain-community"] +langchain-extras = ["langchain-openai", "langchain-anthropic", "langchain-google-vertexai"] all = [ "google-cloud-texttospeech", "miniaudio", @@ -98,6 +102,9 @@ all = [ "vonage", "langchain", "langchain-community", + "langchain-openai", + "langchain-anthropic", + "langchain-google-vertexai", "cartesia" ] diff --git a/vocode/streaming/agent/anthropic_utils.py b/vocode/streaming/agent/anthropic_utils.py index 2a2e131d2..54cefa972 100644 --- a/vocode/streaming/agent/anthropic_utils.py +++ b/vocode/streaming/agent/anthropic_utils.py @@ -27,3 +27,12 @@ def format_anthropic_chat_messages_from_transcript( {"role": "assistant", "content": "BOT:"}, ] # TODO: reliably count tokens of Anthropic messages so that we don't exceed the context window + +def merge_bot_messages_for_langchain(messages: list[tuple]) -> list[tuple]: + merged_messages: list[tuple] = [] + for role, message in messages: + if role == "ai" and merged_messages and merged_messages[-1][0] == "ai": + merged_messages[-1] = ("ai", merged_messages[-1][1] + message) + else: + merged_messages.append((role, message)) + return merged_messages \ No newline at end of file diff --git a/vocode/streaming/agent/langchain_agent.py b/vocode/streaming/agent/langchain_agent.py new file mode 100644 index 000000000..9daa426ca --- /dev/null +++ b/vocode/streaming/agent/langchain_agent.py @@ -0,0 +1,133 @@ +from typing import AsyncGenerator, AsyncIterator, Optional + +import sentry_sdk +from loguru import logger + +from langchain_core.messages.base import BaseMessage as LangchainBaseMessage +from langchain_core.prompts import ChatPromptTemplate +from langchain_core.runnables.base import Runnable +from langchain.chat_models import init_chat_model + +from vocode.streaming.action.abstract_factory import AbstractActionFactory +from vocode.streaming.action.default_factory import DefaultActionFactory +from vocode.streaming.agent.anthropic_utils import merge_bot_messages_for_langchain +from vocode.streaming.agent.base_agent import GeneratedResponse, RespondAgent, StreamedResponse +from vocode.streaming.agent.streaming_utils import collate_response_async, stream_response_async +from vocode.streaming.models.agent import LangchainAgentConfig +from vocode.streaming.models.events import Sender +from vocode.streaming.models.message import BaseMessage, LLMToken +from vocode.streaming.models.transcript import Message +from vocode.utils.sentry_utils import CustomSentrySpans, sentry_create_span + + +class LangchainAgent(RespondAgent[LangchainAgentConfig]): + + def __init__( + self, + agent_config: LangchainAgentConfig, + action_factory: AbstractActionFactory = DefaultActionFactory(), + chain: Optional[Runnable] = None, + **kwargs, + ): + super().__init__( + agent_config=agent_config, + action_factory=action_factory, + **kwargs, + ) + self.chain = chain if chain else self.create_chain() + + def create_chain(self): + model = init_chat_model(model = self.agent_config.model_name, model_provider=self.agent_config.provider, temperature=self.agent_config.temperature, max_tokens=self.agent_config.max_tokens) + messages_for_prompt_template = [ + ("placeholder", "{chat_history}") + ] + if self.agent_config.prompt_preamble: + messages_for_prompt_template.insert(0, ("system", self.agent_config.prompt_preamble)) + prompt_template = ChatPromptTemplate.from_messages(messages_for_prompt_template) + chain = prompt_template | model + return chain + + async def token_generator( + self, + gen: AsyncIterator[LangchainBaseMessage], + ) -> AsyncGenerator[str, None]: + async for chunk in gen: + if isinstance(chunk.content, str): + yield chunk.content + else: + raise ValueError(f"Received unexpected message type {type(chunk)} from Langchain. Expected str.") + + def format_langchain_messages_from_transcript(self) -> list[tuple]: + if not self.transcript: + raise ValueError("A transcript is not attached to the agent") + messages = [] + for event_log in self.transcript.event_logs: + if isinstance(event_log, Message): + messages.append( + ("ai" if event_log.sender == Sender.BOT else "human", event_log.to_string(include_sender=False)) + ) + else: + raise ValueError(f"Invalid event log type {type(event_log)}. Langchain currently only supports human and bot messages") + + if self.agent_config.provider == "anthropic": + messages = merge_bot_messages_for_langchain(messages) + + return messages + + async def generate_response( + self, + human_input, + conversation_id: str, + is_interrupt: bool = False, + bot_was_in_medias_res: bool = False, + ) -> AsyncGenerator[GeneratedResponse, None]: + if not self.transcript: + raise ValueError("A transcript is not attached to the agent") + try: + first_sentence_total_span = sentry_create_span( + sentry_callable=sentry_sdk.start_span, op=CustomSentrySpans.LLM_FIRST_SENTENCE_TOTAL + ) + + ttft_span = sentry_create_span( + sentry_callable=sentry_sdk.start_span, op=CustomSentrySpans.TIME_TO_FIRST_TOKEN + ) + stream = self.chain.astream({"chat_history": self.format_langchain_messages_from_transcript()}) + except Exception as e: + logger.error( + f"Error while hitting Langchain", + exc_info=True, + ) + raise e + + response_generator = collate_response_async + + using_input_streaming_synthesizer = ( + self.conversation_state_manager.using_input_streaming_synthesizer() + ) + if using_input_streaming_synthesizer: + response_generator = stream_response_async + async for message in response_generator( + conversation_id=conversation_id, + gen=self.token_generator( + stream, + ), + sentry_span=ttft_span, + ): + if first_sentence_total_span: + first_sentence_total_span.finish() + + ResponseClass = ( + StreamedResponse if using_input_streaming_synthesizer else GeneratedResponse + ) + MessageType = LLMToken if using_input_streaming_synthesizer else BaseMessage + + if isinstance(message, str): + yield ResponseClass( + message=MessageType(text=message), + is_interruptible=True, + ) + else: + yield ResponseClass( + message=message, + is_interruptible=True, + ) diff --git a/vocode/streaming/models/agent.py b/vocode/streaming/models/agent.py index 7e5a3e6ba..26e5165f1 100644 --- a/vocode/streaming/models/agent.py +++ b/vocode/streaming/models/agent.py @@ -48,6 +48,7 @@ class AgentType(str, Enum): RESTFUL_USER_IMPLEMENTED = "agent_restful_user_implemented" WEBSOCKET_USER_IMPLEMENTED = "agent_websocket_user_implemented" ACTION = "agent_action" + LANGCHAIN = "agent_langchain" class FillerAudioConfig(BaseModel): @@ -130,6 +131,13 @@ class AnthropicAgentConfig(AgentConfig, type=AgentType.ANTHROPIC.value): # type model_name: str = CHAT_ANTHROPIC_DEFAULT_MODEL_NAME max_tokens: int = LLM_AGENT_DEFAULT_MAX_TOKENS temperature: float = LLM_AGENT_DEFAULT_TEMPERATURE + +class LangchainAgentConfig(AgentConfig, type=AgentType.LANGCHAIN.value): # type: ignore + prompt_preamble: str + model_name: str + provider: str + temperature: float = LLM_AGENT_DEFAULT_TEMPERATURE + max_tokens: int = LLM_AGENT_DEFAULT_MAX_TOKENS class ChatVertexAIAgentConfig(AgentConfig, type=AgentType.CHAT_VERTEX_AI.value): # type: ignore