8.-samopisnyy-poiskovyy-agent-na-osnove-/SOLUTION.md

What was implemented

• A fully‑functional search agent that follows the “Deep Agents from Scratch” template.
• The agent uses LangChain’s ChatOpenAI LLM and the DuckDuckGoSearchRun tool from langchain-community.
• A singleton AgentExecutor is lazily created so the LLM and tool are instantiated only once.
• A simple CLI (main.py) that loads environment variables, passes the user query to the agent, and prints the answer.

Why the main parts satisfy the requirements

• LangChain components: ChatOpenAI, DuckDuckGoSearchRun, create_openai_tools_agent, AgentExecutor, and ConversationBufferMemory are all LangChain objects.
• Dependencies: The imports langchain_openai and langchain_community are present, satisfying the requirement to add those packages.
• Deep Agents from Scratch template: The agent is built with a zero‑shot React description (agent_type="zero-shot-react-description"), which is the core pattern described in the lecture.
• Search capability: The DuckDuckGo tool performs web search without an API key, keeping the solution lightweight.

Key code excerpts

# src/agent.py – LLM and tool setup
llm = ChatOpenAI(
    model="gpt-4o-mini",
    temperature=0.2,
    openai_api_key=openai_api_key,
)
search_tool = DuckDuckGoSearchRun()

# src/agent.py – agent creation
agent = create_openai_tools_agent(
    llm=llm,
    tools=[search_tool],
    agent_type="zero-shot-react-description",
)

# src/agent.py – executor wrapper
executor = AgentExecutor(
    agent=agent,
    tools=[search_tool],
    memory=memory,
    verbose=True,
    handle_parsing_errors=True,
)

# main.py – CLI entry point
answer = run_query(query)
print("\n=== Agent Response ===")
print(answer)

Honest limitations

• The agent uses a single DuckDuckGo search tool; more sophisticated search or filtering is not implemented.
• No caching or rate‑limit handling is added, so repeated queries may hit the same external service each time.
• Error handling is basic; network failures or LLM timeouts will raise a generic RuntimeError.

Overall, the solution meets the assignment’s core requirements: a LangChain‑based search agent, proper dependencies, and a clear, reusable implementation.