Add agent.py

agent.py

@@ -0,0 +1,150 @@
+"""
+Deep agent that can search the web, create virtual files and finally dump them to disk.
+
+The agent is built on top of LangChain 0.2+ and uses the "deep agents from scratch"
+approach described in the course.  It is intentionally minimal but fully functional.
+"""
+
+from __future__ import annotations
+
+import os
+from pathlib import Path
+from typing import Any, Dict
+
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.runnables import Runnable
+from langchain_ollama import ChatOllama
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_chroma import Chroma
+
+# Local modules
+from virtual_fs import virtual_fs
+
+# ---------------------------------------------------------------------------
+# 1. Tools
+# ---------------------------------------------------------------------------
+
+# 1.1 Web search tool – simple HTTP GET + title extraction
+import requests
+from bs4 import BeautifulSoup
+
+
+def web_search(query: str) -> str:
+    """Return the title and first paragraph of the first search result.
+
+    This is a very small wrapper around a Google search.  For a production
+    system you would use a real search API.
+    """
+    # Simple Bing search URL – works without API key for a few requests
+    url = f"https://www.bing.com/search?q={requests.utils.quote(query)}"
+    resp = requests.get(url, timeout=10)
+    resp.raise_for_status()
+    soup = BeautifulSoup(resp.text, "html.parser")
+    results = soup.select("li.b_algo")
+    if not results:
+        return "No results found."
+    first = results[0]
+    title = first.select_one("h2").get_text(strip=True)
+    snippet = first.select_one("p").get_text(strip=True)
+    return f"Title: {title}\nSnippet: {snippet}"
+
+# 1.2 Write file tool
+
+def write_file_tool(path: str, content: str) -> str:
+    virtual_fs.write(path, content)
+    return f"File written to {path}."
+
+# 1.3 Read file tool
+
+def read_file_tool(path: str) -> str:
+    try:
+        return virtual_fs.read(path)
+    except KeyError:
+        return f"File {path} does not exist in virtual FS."
+
+# 1.4 Dump virtual FS to disk
+
+def dump_virtual_fs_tool(output_dir: str = "output") -> str:
+    root = Path(output_dir)
+    virtual_fs.dump_to_disk(root)
+    return f"Virtual FS dumped to {root.resolve()}"
+
+# ---------------------------------------------------------------------------
+# 2. Agent definition – deep agent style
+# ---------------------------------------------------------------------------
+
+# 2.1 LLM
+llm = ChatOllama(model="llama3.1", temperature=0.7)
+
+# 2.2 Prompt template – instruct the agent how to use tools
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "You are a helpful assistant that can search the web, write files, read files and dump virtual files to disk.")
+])
+
+# 2.3 Tool mapping
+from langchain.tools import tool
+
+# Wrap tools with langchain Tool objects
+from langchain.tools import Tool
+
+search_tool = Tool(
+    name="WebSearch",
+    func=web_search,
+    description="Use this to search the web for information. Input should be a natural language query.",
+)
+write_tool = Tool(
+    name="WriteFile",
+    func=write_file_tool,
+    description="Write content to a file in the virtual file system. Input: path and content.",
+)
+read_tool = Tool(
+    name="ReadFile",
+    func=read_file_tool,
+    description="Read a file from the virtual file system. Input: path.",
+)
+dump_tool = Tool(
+    name="DumpVirtualFS",
+    func=dump_virtual_fs_tool,
+    description="Dump all virtual files to the real file system. Input: output directory (optional).",
+)
+
+# 2.4 Agent chain – simple chain that lets the LLM decide which tool to call
+from langchain.agents import AgentExecutor, ZeroShotAgent
+
+# Define the tool names and descriptions for the prompt
+tool_names = [search_tool.name, write_tool.name, read_tool.name, dump_tool.name]
+tool_descriptions = [t.description for t in [search_tool, write_tool, read_tool, dump_tool]]
+
+# Build the agent
+agent = ZeroShotAgent.from_llm_and_tools(
+    llm=llm,
+    tools=[search_tool, write_tool, read_tool, dump_tool],
+    prefix="You are a helpful assistant. Use the following tools when needed.",
+    suffix="When you are finished, output the final answer.",
+    tool_prompt="You can use the following tools: {tool_names}. {tool_descriptions}"
+)
+
+# Executor
+executor = AgentExecutor.from_agent_and_tools(
+    agent=agent,
+    tools=[search_tool, write_tool, read_tool, dump_tool],
+    verbose=True,
+)
+
+# ---------------------------------------------------------------------------
+# 3. Demo / entry point
+# ---------------------------------------------------------------------------
+
+if __name__ == "__main__":
+    print("Deep Agent Demo – type your question. Type 'exit' to quit.")
+    while True:
+        user_input = input("> ")
+        if user_input.lower() in {"exit", "quit"}:
+            print("Exiting…")
+            break
+        try:
+            result = executor.invoke({"input": user_input})
+            print("\nResult:\n", result)
+        except Exception as e:
+            print("Error:", e)