Files
t6_mem0/mem0/llms/anthropic.py
2025-03-14 17:42:48 +05:30

68 lines
2.0 KiB
Python

import os
from typing import Dict, List, Optional
try:
import anthropic
except ImportError:
raise ImportError(
"The 'anthropic' library is required. Please install it using 'pip install anthropic'."
)
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.base import LLMBase
class AnthropicLLM(LLMBase):
"""
A class for interacting with Anthropic's Claude models using the specified configuration.
"""
def __init__(self, config: Optional[BaseLlmConfig] = None):
"""
Initializes the AnthropicLLM instance with the given configuration.
Args:
config (Optional[BaseLlmConfig]): Configuration settings for the language model.
"""
super().__init__(config)
if not self.config.model:
self.config.model = "claude-3-5-sonnet-20240620"
api_key = self.config.api_key or os.getenv("ANTHROPIC_API_KEY")
self.client = anthropic.Anthropic(api_key=api_key)
def generate_response(
self,
messages: List[Dict[str, str]],
) -> str:
"""
Generates a response using Anthropic's Claude model based on the provided messages.
Args:
messages (List[Dict[str, str]]): A list of dictionaries, each containing a 'role' and 'content' key.
Returns:
str: The generated response from the model.
"""
# Extract system message separately
system_message = ""
filtered_messages = []
for message in messages:
if message["role"] == "system":
system_message = message["content"]
else:
filtered_messages.append(message)
params = {
"model": self.config.model,
"messages": filtered_messages,
"system": system_message,
"temperature": self.config.temperature,
"max_tokens": self.config.max_tokens,
"top_p": self.config.top_p,
}
response = self.client.messages.create(**params)
return response.content[0].text