添加实现代码

.gitignore

@@ -0,0 +1,5 @@
+/.DS_Store
+/.idea
+/.venv
+/chroma_langchain_db
+/.env

agent.py

@@ -0,0 +1,213 @@
+from langchain_core.tools import tool
+from langchain.tools.retriever import create_retriever_tool
+from langchain_community.document_loaders import WikipediaLoader
+from langchain_community.tools.tavily_search import TavilySearchResults
+from langchain_community.document_loaders import ArxivLoader
+
+from langchain_core.messages import HumanMessage, SystemMessage
+
+from langchain_ollama import ChatOllama
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_huggingface import HuggingFaceEmbeddings, ChatHuggingFace, HuggingFaceEndpoint
+from langchain_chroma import Chroma
+from langgraph.graph import START, StateGraph, MessagesState
+
+from langgraph.prebuilt import ToolNode
+from langgraph.prebuilt import tools_condition
+
+import os
+from dotenv import load_dotenv
+
+
+load_dotenv()
+
+
+@tool
+def multiply(a: int, b: int) -> int:
+    """Multiply two numbers and return the result.
+
+    Args:
+        a (int): The first number.
+        b (int): The second number.
+    Returns:
+        int: The product of the two numbers.
+    """
+    return a * b
+
+@tool
+def add(a: int, b: int) -> int:
+    """Add two numbers and return the result.
+    Args:
+        a (int): The first number.
+        b (int): The second number.
+    Returns:
+        int: The sum of the two numbers.
+    """
+    return a + b
+
+@tool
+def subtract(a: int, b: int) -> int:
+    """Subtract two numbers and return the result.
+    Args:
+        a (int): The first number.
+        b (int): The second number.
+    Returns:
+        int: The difference between the two numbers.
+    """
+    return a - b
+
+@tool
+def divide(a: int, b: int) -> int:
+    """Divide two numbers and return the result.
+    Args:
+        a (int): The first number.
+        b (int): The second number.
+    Returns:
+        int: The quotient of the two numbers.
+    """
+    return a / b
+
+@tool
+def modulus(a: int, b: int) -> int:
+    """Calculate the modulus of two numbers and return the result.
+    Args:
+        a (int): The first number.
+        b (int): The second number.
+    Returns:
+        int: The modulus of the two numbers.
+    """
+    return a % b
+
+@tool
+def wiki_search(query: str) -> str:
+    """Search Wikipedia for a given query and return the top result.
+    Args:
+        query (str): The search query.
+    """
+    search_docs = WikipediaLoader(query, load_max_docs=2).load()
+    formatted_search_docs = '\n\n---\n\n'.join(
+        [
+            f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}">\n{doc.page_content}\n</Document>' for doc in search_docs
+        ]
+    )
+    return {'wiki_results': formatted_search_docs}
+
+@tool
+def web_search(query: str) -> str:
+    """Search Tavily for a query and return maximum 3 results
+
+    Args:
+        query (str): The search query.
+    """
+    search_docs = TavilySearchResults(max_results=3).invoke(query)
+    formatted_search_docs = '\n\n---\n\n'.join(
+        [
+            f'<Document source="{doc["url"]}" page="{doc.get("title", "")}">\n{doc.get('content', '')}\n</Document>' for doc in search_docs
+        ]
+    )
+    return {'web_results': formatted_search_docs}
+
+@tool
+def arvix_search(query: str) -> str:
+    """Search Arvix for a query and return maximum 3 results
+
+    Args:
+        query (str): The search query.
+    """
+    search_docs = ArxivLoader(query, load_max_docs=3).load()
+    formatted_search_docs = '\n\n---\n\n'.join(
+        [
+            f'<Document source="{doc.metadata["source"]}" page="{doc.metadata.get("page", "")}">\n{doc.page_content}\n</Document>' for doc in search_docs
+        ]
+    )
+    return {'arvix_results': formatted_search_docs}
+
+
+system_prompt = """
+
+"""
+
+
+
+# System message
+sys_msg = SystemMessage(content=system_prompt)
+
+# Retriever
+embeddings = HuggingFaceEmbeddings(model_name="BAAI/bge-small-en-v1.5")
+vector_store = Chroma(
+    collection_name="demo_collection",
+    embedding_function=embeddings,
+    persist_directory="./chroma_langchain_db",
+)
+create_retriever_tool = create_retriever_tool(
+    retriever= vector_store.as_retriever(),
+    name='Question Search',
+    description='A tool to retrieve similar question from vector store.'
+)
+
+
+tools = [
+    multiply,
+    add,
+    subtract,
+    modulus,
+    wiki_search,
+    web_search,
+    arvix_search
+]
+
+# build graph function
+def build_graph(tag: str='google'):
+    """Build the graph"""
+
+    if tag == 'local':
+        llm = ChatOllama(model="qwen3")
+    elif tag == 'google':
+        # Google Gemini
+        llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", temperature=0)
+    else:
+        url='https://api-inference.huggingface.co/models/Meta-DeepLearning/llama-2-7b-chat-hf'
+        token = os.getenv('HF_TOKEN')
+        end_point = HuggingFaceEndpoint(
+            endpoint_url=url,
+            temperature=0,
+            huggingfacehub_api_token=token)
+        llm = ChatHuggingFace(llm=end_point)
+    # bind tools to llm
+    llm_with_tools = llm.bind_tools(tools)
+
+    def assistant(state: MessagesState):
+        return {'messages': [llm_with_tools.invoke(state['messages'])]}
+
+    def retriever(state: MessagesState):
+        similar_question = vector_store.similarity_search(state['messages'][0].content)
+        example_msg = HumanMessage(
+            content=f''
+        )
+        return {'messages': [sys_msg] + state['messages'] + [example_msg]}
+
+    builder = StateGraph(MessagesState)
+    builder.add_node('retriever', retriever)
+    builder.add_node('assistant', assistant)
+    builder.add_node('tools', ToolNode(tools))
+    builder.add_edge(START, 'retriever')
+    builder.add_edge('retriever', 'assistant')
+    builder.add_conditional_edges(
+        'assistant',
+        tools_condition
+    )
+    builder.add_edge('tools', 'assistant')
+    return builder.compile()
+
+
+# test
+if __name__ == "__main__":
+    question = 'When was a picture of St. Thomas Aquinas first added to the Wikipedia page on the Principle of double effect?'
+    # build the graph
+    graph = build_graph('local')
+    # run the graph
+    messages = [HumanMessage(content=question)]
+    messages = graph.invoke({'messages': messages})
+    for m in messages['messages']:
+        m.pretty_print()
+

app.py

@@ -4,6 +4,10 @@ import requests
 import inspect
 import pandas as pd
 
+from langchain_core.messages import HumanMessage
+from agent import build_graph
+
+
 # (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
@@ -12,12 +16,13 @@ DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
-        print("BasicAgent initialized.")
+        self.graph = build_graph()
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
-        fixed_answer = "This is a default answer."
-        print(f"Agent returning fixed answer: {fixed_answer}")
-        return fixed_answer
+        messages = [HumanMessage(content=question)]
+        result = self.graph.invoke({"messages": messages})
+        answer = result['messages'][-1].content
+        return answer
 
 def run_and_submit_all( profile: gr.OAuthProfile | None):
     """

requirements.txt

@@ -1,2 +1,162 @@
-gradio
-requests
+aiofiles==24.1.0
+aiohappyeyeballs==2.6.1
+aiohttp==3.12.12
+aiosignal==1.3.2
+annotated-types==0.7.0
+anyio==4.9.0
+asgiref==3.8.1
+attrs==25.3.0
+backoff==2.2.1
+bcrypt==4.3.0
+beautifulsoup4==4.13.4
+build==1.2.2.post1
+cachetools==5.5.2
+certifi==2025.4.26
+charset-normalizer==3.4.2
+chromadb==1.0.12
+click==8.2.1
+coloredlogs==15.0.1
+dataclasses-json==0.6.7
+distro==1.9.0
+durationpy==0.10
+fastapi==0.115.9
+ffmpy==0.6.0
+filelock==3.18.0
+filetype==1.2.0
+flatbuffers==25.2.10
+frozenlist==1.7.0
+fsspec==2025.5.1
+google-ai-generativelanguage==0.6.18
+google-api-core==2.25.1
+google-auth==2.40.3
+googleapis-common-protos==1.70.0
+gradio==5.34.0
+gradio_client==1.10.3
+groovy==0.1.2
+grpcio==1.73.0
+grpcio-status==1.73.0
+h11==0.16.0
+hf-xet==1.1.3
+httpcore==1.0.9
+httptools==0.6.4
+httpx==0.28.1
+httpx-sse==0.4.0
+huggingface-hub==0.33.0
+humanfriendly==10.0
+idna==3.10
+importlib_metadata==8.7.0
+importlib_resources==6.5.2
+Jinja2==3.1.6
+joblib==1.5.1
+jsonpatch==1.33
+jsonpointer==3.0.0
+jsonschema==4.24.0
+jsonschema-specifications==2025.4.1
+kubernetes==33.1.0
+langchain==0.3.25
+langchain-chroma==0.2.4
+langchain-community==0.3.25
+langchain-core==0.3.65
+langchain-google-genai==2.1.5
+langchain-huggingface==0.3.0
+langchain-ollama==0.3.3
+langchain-text-splitters==0.3.8
+langgraph==0.4.8
+langgraph-checkpoint==2.0.26
+langgraph-prebuilt==0.2.2
+langgraph-sdk==0.1.70
+langsmith==0.3.45
+markdown-it-py==3.0.0
+MarkupSafe==3.0.2
+marshmallow==3.26.1
+mdurl==0.1.2
+mmh3==5.1.0
+mpmath==1.3.0
+multidict==6.4.4
+mypy_extensions==1.1.0
+networkx==3.5
+numpy==2.3.0
+oauthlib==3.2.2
+ollama==0.5.1
+onnxruntime==1.22.0
+opentelemetry-api==1.34.1
+opentelemetry-exporter-otlp-proto-common==1.34.1
+opentelemetry-exporter-otlp-proto-grpc==1.34.1
+opentelemetry-instrumentation==0.55b1
+opentelemetry-instrumentation-asgi==0.55b1
+opentelemetry-instrumentation-fastapi==0.55b1
+opentelemetry-proto==1.34.1
+opentelemetry-sdk==1.34.1
+opentelemetry-semantic-conventions==0.55b1
+opentelemetry-util-http==0.55b1
+orjson==3.10.18
+ormsgpack==1.10.0
+overrides==7.7.0
+packaging==24.2
+pandas==2.3.0
+pillow==11.2.1
+posthog==4.8.0
+propcache==0.3.2
+proto-plus==1.26.1
+protobuf==6.31.1
+pyasn1==0.6.1
+pyasn1_modules==0.4.2
+pydantic==2.11.5
+pydantic-settings==2.9.1
+pydantic_core==2.33.2
+pydub==0.25.1
+Pygments==2.19.1
+PyPika==0.48.9
+pyproject_hooks==1.2.0
+python-dateutil==2.9.0.post0
+python-dotenv==1.1.0
+python-multipart==0.0.20
+pytz==2025.2
+PyYAML==6.0.2
+referencing==0.36.2
+regex==2024.11.6
+requests==2.32.4
+requests-oauthlib==2.0.0
+requests-toolbelt==1.0.0
+rich==14.0.0
+rpds-py==0.25.1
+rsa==4.9.1
+ruff==0.11.13
+safehttpx==0.1.6
+safetensors==0.5.3
+scikit-learn==1.7.0
+scipy==1.15.3
+semantic-version==2.10.0
+sentence-transformers==4.1.0
+setuptools==80.9.0
+shellingham==1.5.4
+six==1.17.0
+sniffio==1.3.1
+soupsieve==2.7
+SQLAlchemy==2.0.41
+starlette==0.45.3
+sympy==1.14.0
+tenacity==9.1.2
+threadpoolctl==3.6.0
+tokenizers==0.21.1
+tomlkit==0.13.3
+torch==2.7.1
+tqdm==4.67.1
+transformers==4.52.4
+typer==0.16.0
+typing-inspect==0.9.0
+typing-inspection==0.4.1
+typing_extensions==4.14.0
+tzdata==2025.2
+urllib3==2.4.0
+uvicorn==0.34.3
+uvloop==0.21.0
+watchfiles==1.0.5
+websocket-client==1.8.0
+websockets==15.0.1
+wikipedia==1.4.0
+wrapt==1.17.2
+xxhash==3.5.0
+yarl==1.20.1
+zipp==3.23.0
+zstandard==0.23.0