#！python==3.10.5
huggingface_hub==0.34.4
scikit-learn>=1.2.2
scipy==1.15.3
#torch==2.7.1
#torchvision>=0.15
#5090显卡安装torch命令 pip install torch==2.7.1 torchvision==0.22.1 torchaudio==2.7.1 --index-url https://download.pytorch.org/whl/cu128
tqdm==4.67.1

# 核心LangChain框架
langchain>=0.3.0,<0.4.0
langchain-core>=0.3.0,<0.4.0

# LangGraph - ReAct Agent支持
langgraph>=0.5.0,<0.6.0

# MCP集成适配器
langchain-mcp-adapters>=0.1.0,<0.2.0

# Ollama集成（替代DeepSeek）
# langchain-ollama>=0.3.0,<0.4.0

# OpenAI集成
langchain-openai>=0.3.0,<0.4.0

langchain_chroma==0.2.5

# FastMCP框架
fastmcp>=2.0.0,<3.0.0

# MCP协议核心
mcp>=1.9.0,<2.0.0

# 基础依赖
pydantic>=2.0.0,<3.0.0
httpx>=0.25.0,<1.0.0
anyio>=4.0.0,<5.0.0

langchain-community==0.3.29
openai==1.105.0
chromadb==1.0.20
# 安装llama-cpp-python的命令：
# # 确保已安装系统级 CUDA 驱动和 Toolkit（如 CUDA 12.2）
# 执行以下命令开启 GPU 编译
#CMAKE_ARGS="\
#-DGGML_BLAS=on \
#-DGGML_BLAS_VENDOR=OpenBLAS \
#-DBLAS_LIBRARIES=/usr/lib/x86_64-linux-gnu/libopenblas.so \
#-DBLAS_INCLUDE_DIRS=/usr/include/openblas \
#-DOpenMP_C_FLAGS=-fopenmp \
#-DOpenMP_CXX_FLAGS=-fopenmp \
#-DOpenMP_C_LIBRARY=/usr/lib/x86_64-linux-gnu/libgomp.so \
#-DOpenMP_CXX_LIBRARY=/usr/lib/x86_64-linux-gnu/libgomp.so \
#-DGGML_CUDA=on \  # 新参数：启用 CUDA 加速（替换原 LLAMA_CUBLAS=on）
#-DCUDAToolkit_ROOT=/usr/local/cuda" \  # 保持 CUDA 路径不变
#pip install --upgrade --force-reinstall llama-cpp-python \
#-i https://pypi.tuna.tsinghua.edu.cn/simple

fastapi==0.115.14
fastapi-utils==0.6.0

opencv-python==4.12.0.88
opencv-contrib-python==4.12.0.88

rospkg==1.6.0
catkin-tools==0.9.5
empy==4.2

sentence-transformers==5.0.0

