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# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. ========= | |
# Licensed under the Apache License, Version 2.0 (the "License"); | |
# you may not use this file except in compliance with the License. | |
# You may obtain a copy of the License at | |
# | |
# http://www.apache.org/licenses/LICENSE-2.0 | |
# | |
# Unless required by applicable law or agreed to in writing, software | |
# distributed under the License is distributed on an "AS IS" BASIS, | |
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
# See the License for the specific language governing permissions and | |
# limitations under the License. | |
# ========= Copyright 2023-2024 @ CAMEL-AI.org. All Rights Reserved. ========= | |
from typing import Optional | |
from camel.agents.chat_agent import ChatAgent | |
from camel.messages import BaseMessage | |
from camel.models import BaseModelBackend | |
from camel.prompts import TextPrompt | |
from camel.types import RoleType | |
from camel.utils import create_chunks | |
# AgentOps decorator setting | |
try: | |
import os | |
if os.getenv("AGENTOPS_API_KEY") is not None: | |
from agentops import track_agent | |
else: | |
raise ImportError | |
except (ImportError, AttributeError): | |
from camel.utils import track_agent | |
class SearchAgent(ChatAgent): | |
r"""An agent that summarizes text based on a query and evaluates the | |
relevance of an answer. | |
Args: | |
model (BaseModelBackend, optional): The model backend to use for | |
generating responses. (default: :obj:`OpenAIModel` with | |
`GPT_4O_MINI`) | |
""" | |
def __init__( | |
self, | |
model: Optional[BaseModelBackend] = None, | |
) -> None: | |
system_message = BaseMessage( | |
role_name="Assistant", | |
role_type=RoleType.ASSISTANT, | |
meta_dict=None, | |
content="You are a helpful assistant.", | |
) | |
super().__init__(system_message, model=model) | |
def summarize_text(self, text: str, query: str) -> str: | |
r"""Summarize the information from the text, base on the query. | |
Args: | |
text (str): Text to summarize. | |
query (str): What information you want. | |
Returns: | |
str: Strings with information. | |
""" | |
self.reset() | |
summary_prompt = TextPrompt( | |
'''Gather information from this text that relative to the | |
question, but do not directly answer the question.\nquestion: | |
{query}\ntext ''' | |
) | |
summary_prompt = summary_prompt.format(query=query) | |
# Max length of each chunk | |
max_len = 3000 | |
results = "" | |
chunks = create_chunks(text, max_len) | |
# Summarize | |
for i, chunk in enumerate(chunks, start=1): | |
prompt = summary_prompt + str(i) + ": " + chunk | |
user_msg = BaseMessage.make_user_message( | |
role_name="User", | |
content=prompt, | |
) | |
result = self.step(user_msg).msg.content | |
results += result + "\n" | |
# Final summarization | |
final_prompt = TextPrompt( | |
'''Here are some summarized texts which split from one text. Using | |
the information to answer the question. If can't find the answer, | |
you must answer "I can not find the answer to the query" and | |
explain why.\n Query:\n{query}.\n\nText:\n''' | |
) | |
final_prompt = final_prompt.format(query=query) | |
prompt = final_prompt + results | |
user_msg = BaseMessage.make_user_message( | |
role_name="User", | |
content=prompt, | |
) | |
response = self.step(user_msg).msg.content | |
return response | |
def continue_search(self, query: str, answer: str) -> bool: | |
r"""Ask whether to continue search or not based on the provided answer. | |
Args: | |
query (str): The question. | |
answer (str): The answer to the question. | |
Returns: | |
bool: `True` if the user want to continue search, `False` | |
otherwise. | |
""" | |
prompt = TextPrompt( | |
"Do you think the ANSWER can answer the QUERY? " | |
"Use only 'yes' or 'no' to answer.\n" | |
"===== QUERY =====\n{query}\n\n" | |
"===== ANSWER =====\n{answer}" | |
) | |
prompt = prompt.format(query=query, answer=answer) | |
user_msg = BaseMessage.make_user_message( | |
role_name="User", | |
content=prompt, | |
) | |
response = self.step(user_msg).msg.content | |
if "yes" in str(response).lower(): | |
return False | |
return True | |