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chore: import upstream snapshot with attribution
2026-07-13 13:03:45 +08:00

93 lines
3.2 KiB
Python

import json
import os
from typing import Dict, List, Optional
try:
from together import Together
except ImportError:
raise ImportError("The 'together' library is required. Please install it using 'pip install together'.")
from mem0.configs.llms.base import BaseLlmConfig
from mem0.llms.base import LLMBase
from mem0.memory.utils import extract_json
class TogetherLLM(LLMBase):
def __init__(self, config: Optional[BaseLlmConfig] = None):
super().__init__(config)
if not self.config.model:
self.config.model = "MiniMaxAI/MiniMax-M3"
api_key = self.config.api_key or os.getenv("TOGETHER_API_KEY")
self.client = Together(api_key=api_key)
def _parse_response(self, response, tools):
"""
Process the response based on whether tools are used or not.
Args:
response: The raw response from API.
tools: The list of tools provided in the request.
Returns:
str or dict: The processed response.
"""
if tools:
processed_response = {
"content": response.choices[0].message.content,
"tool_calls": [],
}
if response.choices[0].message.tool_calls:
for tool_call in response.choices[0].message.tool_calls:
processed_response["tool_calls"].append(
{
"name": tool_call.function.name,
"arguments": json.loads(extract_json(tool_call.function.arguments)),
}
)
return processed_response
else:
return response.choices[0].message.content
def generate_response(
self,
messages: List[Dict[str, str]],
response_format=None,
tools: Optional[List[Dict]] = None,
tool_choice: str = "auto",
**kwargs,
):
"""
Generate a response based on the given messages using TogetherAI.
Args:
messages (list): List of message dicts containing 'role' and 'content'.
response_format (str or object, optional): Format of the response. Defaults to "text".
tools (list, optional): List of tools that the model can call. Defaults to None.
tool_choice (str, optional): Tool choice method. Defaults to "auto".
**kwargs: Additional provider-specific parameters forwarded to the Together
client (matches the ``LLMBase.generate_response`` contract).
Returns:
str: The generated response.
"""
params = {
"model": self.config.model,
"messages": messages,
"temperature": self.config.temperature,
"max_tokens": self.config.max_tokens,
"top_p": self.config.top_p,
}
params.update(kwargs)
if response_format:
params["response_format"] = response_format
if tools: # TODO: Remove tools if no issues found with new memory addition logic
params["tools"] = tools
params["tool_choice"] = tool_choice
response = self.client.chat.completions.create(**params)
return self._parse_response(response, tools)