74 lines
2.2 KiB
Python
74 lines
2.2 KiB
Python
import pandas as pd
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from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
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from langchain_openai.chat_models import ChatOpenAI
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from langchain_community.chat_message_histories import ChatMessageHistory
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from langchain_core.chat_history import BaseChatMessageHistory
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from langchain_core.runnables.history import RunnableWithMessageHistory
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def get_session_history(session_id: str) -> BaseChatMessageHistory:
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if session_id not in store:
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store[session_id] = ChatMessageHistory()
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return store[session_id]
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def read_txt_file(file_path: str) -> str:
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with open(file_path, "r", encoding='ISO-8859-1') as file:
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content = file.read()
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return content
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def read_csv_file(file_path: str) -> pd.DataFrame:
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return pd.read_csv(file_path)
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def format_csv_data(df: pd.DataFrame, start: int, end: int) -> str:
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formatted_data = []
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for index, row in df.iloc[start:end].iterrows():
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formatted_data.append(
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f"时刻{index + 1}: Sp={row['price']}, Sl={row['load']},"
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f"St={row['temperature']}, Si={row['irradiance']}, Sw={row['wind_speed']}"
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)
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return "\n".join(formatted_data)
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system_content = read_txt_file('./llm.txt')
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df = read_csv_file('./data.csv')
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llm = ChatOpenAI(
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streaming=True,
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verbose=True,
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openai_api_key="none",
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# openai_api_base="http://0.0.0.0:5049/v1/models",
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openai_api_base="http://localhost:8000/v1",
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model_name="Qwen1.5-32b-int4"
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)
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prompt = ChatPromptTemplate.from_messages(
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[
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("system", system_content,),
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MessagesPlaceholder(variable_name="history"),
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("human", "{input}"),
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]
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)
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runnable = prompt | llm
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store = {}
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with_message_history = RunnableWithMessageHistory(
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runnable,
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get_session_history,
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input_messages_key="input",
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history_messages_key="history",
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)
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num_hours = len(df)
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for i in range(num_hours):
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start = i
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end = start + 1
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csv_data_chunk = format_csv_data(df, start, end)
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result = with_message_history.invoke(
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{"input": f"数据如下：\n{csv_data_chunk}\n只返回json格式的五个决策数据：{{[x1 x2 x3 x4 x5]}}"},
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config={
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"configurable": {"session_id": "cxd"}
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},
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)
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print(f"Hour {i + 1}:\n{result.content}\n")
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