Upload 17 files

.env

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+OPENAI_API_KEY=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
+DEEPSEEK_API_KEY=sk-0dc2502319774252ae68e208c82dc419

.gitattributes

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-*.7z filter=lfs diff=lfs merge=lfs -text
-*.arrow filter=lfs diff=lfs merge=lfs -text
-*.bin filter=lfs diff=lfs merge=lfs -text
-*.bz2 filter=lfs diff=lfs merge=lfs -text
-*.ckpt filter=lfs diff=lfs merge=lfs -text
-*.ftz filter=lfs diff=lfs merge=lfs -text
-*.gz filter=lfs diff=lfs merge=lfs -text
-*.h5 filter=lfs diff=lfs merge=lfs -text
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-*.lfs.* filter=lfs diff=lfs merge=lfs -text
-*.mlmodel filter=lfs diff=lfs merge=lfs -text
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-*.msgpack filter=lfs diff=lfs merge=lfs -text
-*.npy filter=lfs diff=lfs merge=lfs -text
-*.npz filter=lfs diff=lfs merge=lfs -text
-*.onnx filter=lfs diff=lfs merge=lfs -text
-*.ot filter=lfs diff=lfs merge=lfs -text
-*.parquet filter=lfs diff=lfs merge=lfs -text
-*.pb filter=lfs diff=lfs merge=lfs -text
-*.pickle filter=lfs diff=lfs merge=lfs -text
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-*.pt filter=lfs diff=lfs merge=lfs -text
-*.pth filter=lfs diff=lfs merge=lfs -text
-*.rar filter=lfs diff=lfs merge=lfs -text
-*.safetensors filter=lfs diff=lfs merge=lfs -text
-saved_model/**/* filter=lfs diff=lfs merge=lfs -text
-*.tar.* filter=lfs diff=lfs merge=lfs -text
-*.tar filter=lfs diff=lfs merge=lfs -text
-*.tflite filter=lfs diff=lfs merge=lfs -text
-*.tgz filter=lfs diff=lfs merge=lfs -text
-*.wasm filter=lfs diff=lfs merge=lfs -text
-*.xz filter=lfs diff=lfs merge=lfs -text
-*.zip filter=lfs diff=lfs merge=lfs -text
-*.zst filter=lfs diff=lfs merge=lfs -text
-*tfevents* filter=lfs diff=lfs merge=lfs -text
+# Auto detect text files and perform LF normalization
+* text=auto

.gitignore

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+.env
+venv/

LICENSE

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+MIT License
+
+Copyright (c) 2025 range-h
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,13 +1,3 @@
----
-title: '2233'
-emoji: 🏃
-colorFrom: purple
-colorTo: purple
-sdk: gradio
-sdk_version: 5.35.0
-app_file: app.py
-pinned: false
-license: apache-2.0
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# sample-python
+
+### I am king

a.txt

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+这是a.txt的内容

b.txt

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+its a new file named as b.txt
+x = 1
+y = 1

basic_chains.py

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+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain_community.chat_models import ChatOpenAI
+from langchain_deepseek import ChatDeepSeek
+from langchain_core.runnables import RunnableLambda, RunnableMap
+
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+def get_summary_prompt():
+    return PromptTemplate.from_template("Summarize the following:\n\n{text}")
+
+
+def get_title_prompt():
+    return PromptTemplate.from_template("Create a 5-word title for this:\n\n{summary}")
+
+def translate_prompt():
+    return PromptTemplate.from_template("Translate the following text to Chinese:\n\n{text}")
+
+def build_hyper_chain():
+    llm = ChatDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat", temperature=0.7)
+    summarize_chain = get_summary_prompt() | llm
+    title_chain = get_title_prompt() | llm
+    translate_chain = translate_prompt() | llm
+
+    def chain_fn(inputs):
+        summary = summarize_chain.invoke({"text": inputs["text"]})
+        title = title_chain.invoke({"summary": summary})
+        chinese_summary = translate_chain.invoke({"text": summary.content})
+        return {"summary": summary, "title": title, "chinese_summary": chinese_summary}
+    return RunnableLambda(chain_fn)
+
+if __name__ == "__main__":
+    full_text = input("Paste your paragraph:\n\n")
+
+    chain = build_hyper_chain()
+    outputs = chain.invoke({"text": full_text})
+    
+    # Display outputs
+    print(f"\n[Summary]: {outputs['summary'].content}")
+    print(f"\n[Title]: {outputs['title'].content}")
+    print(f"\n[Chinese Summary]: {outputs['chinese_summary'].content}")

basic_knowledgebase.py

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+from langchain.agents import initialize_agent, AgentType, Tool
+from langchain.memory import ConversationBufferMemory
+from langchain_deepseek import ChatDeepSeek
+from langchain_openai import ChatOpenAI
+from langchain.document_loaders import TextLoader
+from langchain_community.document_loaders import PyPDFLoader  # Updated import for PDF loading
+
+from langchain.text_splitter import CharacterTextSplitter
+from langchain.chains.question_answering import load_qa_chain
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+llm = ChatDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
+
+
+memory = ConversationBufferMemory(
+    memory_key="chat_history", 
+    return_messages=True
+)
+
+def doc_tool(query: str) -> str:
+    """Search the knowledge base for an answer to the question in Chinese."""
+    docs = TextLoader("brainrent_part1.txt", encoding="utf-8").load()
+    splitter = CharacterTextSplitter(chunk_size=1000, chunk_overlap=100)
+    chunks = splitter.split_documents(docs)
+    qa_chain = load_qa_chain(llm=llm, chain_type="stuff")
+    return qa_chain.run(input_documents=chunks, question=query)
+
+
+tools = [
+    Tool(
+        name="KnowledgeBase",
+        func=doc_tool,
+        description="Useful for answering questions about Brainrent."
+    ),
+]
+
+
+# 4. Initialize the agent with tools and memory
+agent = initialize_agent(
+    tools=tools,
+    llm=llm,
+    agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION,
+    memory=memory,
+    verbose=True
+)
+
+if __name__ == "__main__":
+    while True:
+        query = input("\nEnter your question (or 'exit' to quit): ")
+        if query.lower() == 'exit':
+            break
+        result = agent.invoke(query)
+        print(f"Result: {result['output']}")
+

basic_llm.py

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+from langchain.prompts import PromptTemplate
+from langchain.chains import LLMChain
+from langchain_community.chat_models import ChatOpenAI
+from langchain_deepseek import ChatDeepSeek
+
+from dotenv import load_dotenv
+import os
+
+load_dotenv()
+
+def get_openai_chain():
+    """Builds an LLMChain using OpenAI's model"""
+    prompt = PromptTemplate.from_template("Answer this: {question}")
+    llm = ChatOpenAI(openai_api_key=os.getenv("OPENAI_API_KEY"), model="gpt-4o-mini")
+    return LLMChain(llm=llm, prompt=prompt)
+
+def get_deepseek_chain():
+    """Builds an LLMChain using DeepSeek's model"""
+    prompt = PromptTemplate.from_template("Answer this: {question}")
+    llm = ChatDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
+    return prompt | llm
+    # return LLMChain(llm=llm, prompt=prompt)
+
+def get_chain_by_model(model_name: str) -> LLMChain:
+    """Chooses the chain based on model selection"""
+    if model_name == "openai":
+        return get_openai_chain()
+    elif model_name == "deepseek":
+        return get_deepseek_chain()
+    else:
+        raise ValueError("Unsupported model. Choose 'openai' or 'deepseek'.")
+
+
+if __name__ == "__main__":
+    question = input("Enter your question: ").strip()
+
+    model = input("Choose model (openai / deepseek): ").strip().lower()
+
+    chain = get_chain_by_model(model)
+    response = chain.invoke({"question": question})
+    print(f"\n[Response]:\n{response.content}")
+    #print(f"\n[Response]:\n{response['text']}")

basic_memory.py

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+import math
+from typing import Optional
+from langchain.agents import initialize_agent,Tool, AgentType
+from langchain.memory import ConversationBufferMemory
+from langchain_deepseek import ChatDeepSeek
+from dotenv import load_dotenv
+import os
+from datetime import datetime
+
+load_dotenv()
+# 1. Initialize DeepSeek LLM
+#    You may need to pass your DeepSeek API key or client config here.
+llm = ChatDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
+
+def get_weather(location: str) -> str:
+    # stub implementation—replace with real weather API call
+    return f"Weather forecast for {location}: Sunny with a high of 25°C and low of 15°C. 10% chance of precipitation."
+
+def calculator(operation_input: str) -> str:
+    """Perform basic arithmetic operations from a text description."""
+    try:
+        # Parse the operation input
+        parts = operation_input.split()
+        
+        # Try to identify the operation and numbers
+        if "add" in operation_input.lower() or "+" in operation_input:
+            # Look for two numbers in the string
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if len(numbers) >= 2:
+                return f"{numbers[0]} + {numbers[1]} = {numbers[0] + numbers[1]}"
+            else:
+                return "Error: Could not identify two numbers for addition"
+            
+        elif "subtract" in operation_input.lower() or "-" in operation_input:
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if len(numbers) >= 2:
+                return f"{numbers[0]} - {numbers[1]} = {numbers[0] - numbers[1]}"
+            else:
+                return "Error: Could not identify two numbers for subtraction"
+            
+        elif "multiply" in operation_input.lower() or "*" in operation_input:
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if len(numbers) >= 2:
+                return f"{numbers[0]} * {numbers[1]} = {numbers[0] * numbers[1]}"
+            else:
+                return "Error: Could not identify two numbers for multiplication"
+            
+        elif "divide" in operation_input.lower() or "/" in operation_input:
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if len(numbers) >= 2:
+                if numbers[1] == 0:
+                    return "Error: Division by zero"
+                return f"{numbers[0]} / {numbers[1]} = {numbers[0] / numbers[1]}"
+            else:
+                return "Error: Could not identify two numbers for division"
+            
+        elif "power" in operation_input.lower() or "^" in operation_input:
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if len(numbers) >= 2:
+                return f"{numbers[0]}^{numbers[1]} = {numbers[0] ** numbers[1]}"
+            else:
+                return "Error: Could not identify two numbers for power operation"
+            
+        elif "sqrt" in operation_input.lower():
+            numbers = [float(s) for s in parts if s.replace('.', '', 1).isdigit()]
+            if numbers:
+                if numbers[0] < 0:
+                    return "Error: Cannot take square root of negative number"
+                return f"sqrt({numbers[0]}) = {math.sqrt(numbers[0])}"
+            else:
+                return "Error: Could not identify a number for square root"
+        else:
+            return f"Unknown operation. Please specify one of: add, subtract, multiply, divide, power, sqrt"
+    except Exception as e:
+        return f"Error performing calculation: {str(e)}"
+    
+tools = [
+    Tool(
+        name="Weather",
+        func=get_weather,
+        description="Get the current weather for a specified location."
+    ),
+    Tool(
+        name="Calculator",
+        func=calculator,
+        description="Perform mathematical calculations. Available operations: add, subtract, multiply, divide, power, sqrt. For example: operation='add', a=2, b=3 will return '2 + 3 = 5'."
+    ),
+]
+
+memory = ConversationBufferMemory(
+    memory_key="chat_history",
+    return_messages=True
+)
+
+agent_executor = initialize_agent(
+    tools=tools,
+    llm=llm,
+    memory=memory,
+    agent=AgentType.CHAT_CONVERSATIONAL_REACT_DESCRIPTION,
+    verbose=True,
+)
+
+if __name__ == "__main__":
+    while True:
+        query = input("\nEnter your question (or 'exit' to quit): ")
+        if query.lower() == 'exit':
+            break
+        result = agent_executor.invoke(query)
+        print(f"Result: {result['output']}")

basic_tools.py

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+import os
+from langchain.agents import AgentType, initialize_agent
+from langchain.tools import StructuredTool
+from langchain_deepseek import ChatDeepSeek
+from pydantic import BaseModel, Field
+from typing import Optional
+import math
+import requests
+
+class CalculatorInput(BaseModel):
+    operation: str = Field(description="Mathematical operation: add, subtract, multiply, divide, power, sqrt")
+    a: float = Field(description="First number")
+    b: Optional[float] = Field(default=None, description="Second number (not required for sqrt)")
+
+def calculator(operation: str, a: float, b: Optional[float] = None) -> str:
+    """Perform basic arithmetic operations."""
+    op = operation.lower()
+    
+    if op == "add":
+        return f"{a} + {b} = {a + b}"
+    elif op == "subtract":
+        return f"{a} - {b} = {a - b}"
+    elif op == "multiply":
+        return f"{a} * {b} = {a * b}"
+    elif op == "divide":
+        if b == 0:
+            return "Error: Division by zero"
+        return f"{a} / {b} = {a / b}"
+    elif op == "power":
+        return f"{a}^{b} = {a ** b}"
+    elif op == "sqrt":
+        if a < 0:
+            return "Error: Cannot take square root of negative number"
+        return f"sqrt({a}) = {math.sqrt(a)}"
+    else:
+        return f"Unknown operation: {op}"
+
+calculator_tool = StructuredTool.from_function(
+    func=calculator,
+    name="Calculator",
+    description="Useful for performing mathematical calculations. Input should include operation (add, subtract, multiply, divide, power, sqrt) and numbers.",
+    args_schema=CalculatorInput
+)
+
+class WeatherInput(BaseModel):
+    city: str = Field(description="Name of the city to get the weather for")
+
+def get_weather(city: str) -> str:
+    """模拟天气信息（不访问真实 API）"""
+    mock_data = {
+        "北京": {"description": "晴天", "temp": 26},
+        "上海": {"description": "小雨", "temp": 22},
+        "广州": {"description": "多云", "temp": 30},
+        "杭州": {"description": "雷阵雨", "temp": 24}
+    }
+
+    weather = mock_data.get(city, {"description": "未知", "temp": "N/A"})
+    return f"{city} 当前天气：{weather['description']}，温度：{weather['temp']}°C"
+
+weather_tool = StructuredTool.from_function(
+    func=get_weather,
+    name="WeatherTool",
+    description="查询指定城市的天气信息（模拟数据）",
+    args_schema=WeatherInput
+)
+
+
+llm = ChatDeepSeek(api_key=os.getenv("DEEPSEEK_API_KEY"), model="deepseek-chat")
+
+
+tools = [calculator_tool, weather_tool]
+
+agent = initialize_agent(
+    tools, 
+    llm, 
+    agent=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION, 
+    verbose=True
+)
+
+if __name__ == "__main__":
+    while True:
+        query = input("\nEnter your question (or 'exit' to quit): ")
+        if query.lower() == 'exit':
+            break
+        result = agent.invoke(query)
+        print(f"Result: {result['output']}")

brainrent_part1.txt

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+脑租科技有限公司（BrainRent Tech Co., Ltd.）是一家前沿科技企业，专注于“思维即服务（TaaS，Thinking as a Service）”模式，为全球用户提供按需租用智能大脑资源的服务。公司总部位于多伦多，研发中心设在硅谷和青岛，致力于打造世界一流的云端智能思维平台。
+
+BrainRent 提供的服务覆盖多个领域：学术研究支持、企业决策咨询、创新创意生成、复杂问题建模与推理等。用户可以通过移动应用或网页平台提交问题，系统会根据问题类型匹配最适合的“思维单元”（即高性能的AI大脑或真人思维专家），在约定时间内返回详尽的思考成果。
+
+核心产品“云脑池（BrainCloud）”是一个整合了数千名训练有素的专家与数百个高智能AI Agent的分布式思维网络。用户可选择使用“AI智能思维”、“人类专家思维”或“混合思维模式”，满足不同的预算和精准度要求。

fibonacci_list.py

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+# fibonacci_list.py
+
+def print_fibonacci_list(n):
+    """
+    Print the first `n` numbers in the Fibonacci sequence as a list.
+    """
+    if n <= 0:
+        print([])
+        return
+
+    fib_list = [0] if n == 1 else [0, 1]
+    while len(fib_list) < n:
+        fib_list.append(fib_list[-1] + fib_list[-2])
+    
+    print(fib_list)
+
+
+# Example usage
+if __name__ == "__main__":
+    print_fibonacci_list(10)

range_h.md

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+### 注意
+
+
+* 下面是 range_h 的帅照
+  
+  ---
+  ![](https://i.imgur.com/j8FfyH1.png)

requirements.txt

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+aiohappyeyeballs==2.6.1
+aiohttp==3.11.18
+aiosignal==1.3.2
+annotated-types==0.7.0
+anyio==4.9.0
+attrs==25.3.0
+beautifulsoup4==4.12.3
+Brotli==1.1.0
+cachetools==5.5.2
+certifi==2025.4.26
+charset-normalizer==3.4.2
+click==8.1.8
+dataclasses-json==0.6.7
+distro==1.9.0
+fastapi==0.110.1
+frozenlist==1.6.0
+google-api-core==2.25.0rc1
+google-api-python-client==2.125.0
+google-auth==2.40.1
+google-auth-httplib2==0.2.0
+googleapis-common-protos==1.70.0
+greenlet==3.2.2
+h11==0.16.0
+httpcore==1.0.9
+httplib2==0.22.0
+httpx==0.28.1
+httpx-sse==0.4.0
+idna==3.10
+jiter==0.9.0
+jsonpatch==1.33
+jsonpointer==3.0.0
+langchain==0.3.25
+langchain-community==0.3.24
+langchain-core==0.3.60
+langchain-deepseek==0.1.3
+langchain-openai==0.3.17
+langchain-text-splitters==0.3.8
+langgraph==0.4.5
+langgraph-checkpoint==2.0.26
+langgraph-prebuilt==0.1.8
+langgraph-sdk==0.1.69
+langsmith==0.1.147
+marshmallow==3.26.1
+multidict==6.4.3
+mutagen==1.47.0
+mypy_extensions==1.1.0
+numpy==2.2.5
+openai==1.79.0
+orjson==3.10.18
+ormsgpack==1.9.1
+packaging==23.2
+propcache==0.3.1
+proto-plus==1.26.1
+protobuf==6.30.2
+pyasn1==0.6.1
+pyasn1_modules==0.4.2
+pycryptodomex==3.22.0
+pydantic==2.11.4
+pydantic-settings==2.9.1
+pydantic_core==2.33.2
+pyparsing==3.2.3
+pypdf==4.2.0
+python-dotenv==1.0.1
+PyYAML==6.0.2
+regex==2024.11.6
+requests==2.32.3
+requests-toolbelt==1.0.0
+rsa==4.9.1
+setuptools==80.4.0
+sniffio==1.3.1
+soupsieve==2.7
+SQLAlchemy==2.0.40
+starlette==0.37.2
+tenacity==8.5.0
+tiktoken==0.9.0
+tqdm==4.67.1
+typing-inspect==0.9.0
+typing-inspection==0.4.0
+typing_extensions==4.13.2
+uritemplate==4.1.1
+urllib3==2.4.0
+uvicorn==0.29.0
+websockets==15.0.1
+wheel==0.45.1
+xxhash==3.5.0
+yarl==1.20.0
+yt-dlp==2024.4.9