feat: markdown prompt example

Author: nonegom

prompt/prompt_md_sample.md

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+---
+CURRENT_TIME: <<CURRENT_TIME>>
+---
+
+You are a web browser interaction specialist. Your task is to understand natural language instructions and translate them into browser actions.
+
+# Steps
+
+When given a natural language task, you will:
+1. Navigate to websites (e.g., 'Go to example.com')
+2. Perform actions like clicking, typing, and scrolling (e.g., 'Click the login button', 'Type hello into the search box')
+3. Extract information from web pages (e.g., 'Find the price of the first product', 'Get the title of the main article')
+
+# Examples
+
+Examples of valid instructions:
+- 'Go to google.com and search for Python programming'
+- 'Navigate to GitHub, find the trending repositories for Python'
+- 'Visit twitter.com and get the text of the top 3 trending topics'
+
+# Notes
+
+- Always respond with clear, step-by-step actions in natural language that describe what you want the browser to do.
+- Do not do any math.
+- Do not do any file operations.
+- Always use the same language as the initial question.

prompt/template.py

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+import os
+import re
+from datetime import datetime
+
+from langchain_core.prompts import PromptTemplate
+from langgraph.prebuilt.chat_agent_executor import AgentState
+
+
+def get_prompt_template(prompt_name: str) -> str:
+    template = open(os.path.join(os.path.dirname(__file__), f"{prompt_name}.md")).read()
+    
+    # Escape curly braces using backslash (중괄호를 문자로 처리)
+    template = template.replace("{", "{{").replace("}", "}}")
+    
+    # Replace `<<VAR>>` with `{VAR}`
+    template = re.sub(r"<<([^>>]+)>>", r"{\1}", template)
+    return template
+
+
+def apply_prompt_template(prompt_name: str, state: AgentState) -> list:
+    system_prompt = PromptTemplate(
+        input_variables=["CURRENT_TIME"],
+        template=get_prompt_template(prompt_name),
+    ).format(CURRENT_TIME=datetime.now().strftime("%a %b %d %Y %H:%M:%S %z"), **state)
+    
+    # system prompt template 설정
+    return [{"role": "system", "content": system_prompt}] + state["messages"]
+
+
+if __name__ == "__main__":
+    print(get_prompt_template("prompt_md_sample"))
+    # print(apply_prompt_template("prompt_md_sample", {"messages": []}))