Files
t6_mem0/mem0/llms/together.py
2024-07-19 22:19:15 -07:00

82 lines
2.8 KiB
Python

import json
from typing import Dict, List, Optional
try:
from together import Together
except ImportError:
raise ImportError("Together requires extra dependencies. Install with `pip install together`") from None
from mem0.llms.base import LLMBase
from mem0.configs.llms.base import BaseLlmConfig
class TogetherLLM(LLMBase):
def __init__(self, config: Optional[BaseLlmConfig] = None):
super().__init__(config)
if not self.config.model:
self.config.model="mistralai/Mixtral-8x7B-Instruct-v0.1"
self.client = Together()
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(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",
):
"""
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".
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
}
if response_format:
params["response_format"] = response_format
if tools:
params["tools"] = tools
params["tool_choice"] = tool_choice
response = self.client.chat.completions.create(**params)
return self._parse_response(response, tools)