AnthropicChatGenerator
This component enables chat completions using Anthropic large language models (LLMs).
Name | AnthropicChatGenerator |
Source | https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/anthropic |
Most common position in a pipeline | After a ChatPromptBuilder |
Mandatory input variables | “messages” A list of ChatMessage objects |
Output variables | "replies": A list of ChatMessage objects”meta”: A list of dictionaries with the metadata associated with each reply, such as token count, finish reason, and so on |
Overview
This integration supports Anthropic chat
models such as claude-3-5-sonnet-20240620
,claude-3-opus-20240229
, claude-3-haiku-20240307
, and similar. Check out the most recent full list in Anthropic documentation.
Parameters
AnthropicChatGenerator
needs an Anthropic API key to work. You can provide this key in:
- The
ANTHROPIC_API_KEY
environment variable (recommended) - The
api_key
init parameter and Haystack Secret API:Secret.from_token("your-api-key-here")
AnthropicChatGenerator
requires a prompt to generate text, but you can pass any text generation parameters available in the Anthropic Messaging API method directly to this component using the generation_kwargs
parameter, both at initialization and when running the component. For more details on the parameters supported by the Anthropic API, see the Anthropic documentation.
Finally, the component needs a list of ChatMessage
objects to operate. ChatMessage
is a data class that contains a message, a role (who generated the message, such as user
, assistant
, system
, function
), and optional metadata.
Only text input modality is supported at this time.
Streaming
AnthropicChatGenerator
supports streaming the tokens from the LLM directly in output. To do so, pass a function to the streaming_callback
init parameter.
Usage
Install theanthropic-haystack
package to use the AnthropicChatGenerator
:
pip install anthropic-haystack
On its own
from haystack_integrations.components.generators.anthropic import AnthropicChatGenerator
from haystack.dataclasses import ChatMessage
generator = AnthropicChatGenerator()
message = ChatMessage.from_user("What's Natural Language Processing? Be brief.")
print(generator.run([message]))
In a pipeline
You can also use AnthropicChatGenerator
with the Anthropic chat models in your pipeline.
from haystack import Pipeline
from haystack.components.builders import ChatPromptBuilder
from haystack.dataclasses import ChatMessage
from haystack_integrations.components.generators.anthropic import AnthropicChatGenerator
from haystack.utils import Secret
pipe = Pipeline()
pipe.add_component("prompt_builder", ChatPromptBuilder())
pipe.add_component("llm", AnthropicChatGenerator(Secret.from_env_var("ANTHROPIC_API_KEY")))
pipe.connect("prompt_builder", "llm")
country = "Germany"
system_message = ChatMessage.from_system("You are an assistant giving out valuable information to language learners.")
messages = [system_message, ChatMessage.from_user("What's the official language of {{ country }}?")]
res = pipe.run(data={"prompt_builder": {"template_variables": {"country": country}, "template": messages}})
print(res)
Updated 5 months ago