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加入图片ai功能

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renee
2026-02-02 12:39:01 -08:00
parent 04c44b4775
commit d23c27a177
1 changed files with 15 additions and 19 deletions
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34
app/ai/ai.py
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@@ -1,11 +1,3 @@
# -*- coding: utf-8 -*-
"""gemini-hackathon ai.ipynb
Automatically generated by Colab.
Original file is located at
https://colab.research.google.com/drive/1FyV9Lq9Sxh_dFiaNIqeu1brOl8DAoKUO
"""
!pip install -q langgraph-checkpoint-sqlite langchain_google_genai !pip install -q langgraph-checkpoint-sqlite langchain_google_genai
@@ -18,6 +10,8 @@ from langgraph.graph import StateGraph, START, END
from langgraph.checkpoint.sqlite import SqliteSaver from langgraph.checkpoint.sqlite import SqliteSaver
from langgraph.graph.message import add_messages from langgraph.graph.message import add_messages
from langchain_core.runnables import RunnableConfig from langchain_core.runnables import RunnableConfig
from typing import Union, List, Dict
# --- 1. 状态定义 --- # --- 1. 状态定义 ---
class State(TypedDict): class State(TypedDict):
@@ -57,6 +51,7 @@ def summarize_conversation(state: State):
"你是一个记忆管理专家。请更新摘要，合并新旧信息。" "你是一个记忆管理专家。请更新摘要，合并新旧信息。"
"1. 保持简练，仅保留事实（姓名、偏好、核心议题）。" "1. 保持简练，仅保留事实（姓名、偏好、核心议题）。"
"2. 如果新消息包含对旧信息的修正，请更新它。" "2. 如果新消息包含对旧信息的修正，请更新它。"
"3. 如果对话中包含图片描述，请将图片的关键视觉信息也记录在摘要中"
) )
summary_input = f"现有摘要: {summary}\n\n待加入的新信息: {messages_to_summarize}" summary_input = f"现有摘要: {summary}\n\n待加入的新信息: {messages_to_summarize}"
@@ -96,7 +91,7 @@ workflow.add_edge("summarize", END)
app = workflow.compile(checkpointer=memory) app = workflow.compile(checkpointer=memory)
def chat(thread_id: str, system_prompt: str, user_message: str): def chat(thread_id: str, system_prompt: str, user_content: Union[str, List[Dict]]):
""" """
Processes a single user message and returns the AI response, Processes a single user message and returns the AI response,
persisting memory via the thread_id. persisting memory via the thread_id.
@@ -109,7 +104,7 @@ def chat(thread_id: str, system_prompt: str, user_message: str):
} }
# Prepare the input for this specific turn # Prepare the input for this specific turn
input_data = {"messages": [HumanMessage(content=user_message)]} input_data = {"messages": [HumanMessage(content=user_content)]}
ai_response = "" ai_response = ""
@@ -122,14 +117,15 @@ def chat(thread_id: str, system_prompt: str, user_message: str):
return ai_response return ai_response
if __name__ == "__main__": # 使用范例
tid = "py_expert_001" # if __name__ == "__main__":
sys_p = "你是个善解人意的机器人。" # tid = "py_expert_001"
# sys_p = "你是个善解人意的机器人。"
# Call 1: Establish context # # Call 1: Establish context
resp1 = chat(tid, sys_p, "你好，我叫小明。") # resp1 = chat(tid, sys_p, "你好，我叫小明。")
print(f"Bot: {resp1}") # print(f"Bot: {resp1}")
# Call 2: Test memory (The model should remember the name '小明') # # Call 2: Test memory (The model should remember the name '小明')
resp2 = chat(tid, sys_p, "我今天很开心") # resp2 = chat(tid, sys_p, "我今天很开心")
print(f"Bot: {resp2}") # print(f"Bot: {resp2}")