commit

agent.py

@@ -1,46 +1,143 @@
 # agent.py
-# =========================================================
-# GAIA Level 1 목표용 최소 Agent
-# - 목표: 30% 이상
-# - 전략: GPT-4o-mini 단독 직답
-# - 안정성 최우선 (절대 터지지 않게)
-# =========================================================
+# =====================================================
+# GAIA Level 1 ~ 50% Target Agent
+# LangGraph minimal + hard postprocess
+# =====================================================
+
+import re
+from typing import TypedDict
 
 from langchain_openai import ChatOpenAI
 from langchain_core.messages import SystemMessage, HumanMessage
+from langchain_community.tools import DuckDuckGoSearchRun
 
+from langgraph.graph import StateGraph, START, END
 
-SYSTEM_PROMPT = """
-You are answering GAIA benchmark questions.
 
-Rules:
-- Answer as concisely as possible.
-- Output ONLY the final answer.
-- No explanation.
-- If the answer is a list, separate items with commas.
-- If unsure, make your best factual guess.
-""".strip()
+# -----------------------------
+# State
+# -----------------------------
+class State(TypedDict):
+    question: str
+    search_result: str
+    answer: str
+    searched: bool
 
 
-class BasicAgent:
-    def __init__(self):
-        # OpenAI API Key는 HF Space Secret에 OPENAI_API_KEY로 있어야 함
-        self.llm = ChatOpenAI(
-            model="gpt-4o-mini",
-            temperature=0,
-            max_tokens=64,
-        )
+# -----------------------------
+# System Prompt (VERY IMPORTANT)
+# -----------------------------
+SYS = SystemMessage(
+    content=(
+        "You answer GAIA benchmark questions.\n"
+        "Rules:\n"
+        "- If factual info is needed, search ONCE.\n"
+        "- NEVER say you cannot access files, images, or audio.\n"
+        "- Output ONLY the final answer.\n"
+        "- No explanation.\n"
+        "- No quotes.\n"
+        "- No punctuation unless part of the answer."
+    )
+)
 
-        self.system_msg = SystemMessage(content=SYSTEM_PROMPT)
-        print("✅ BasicAgent initialized (GAIA Level 1 minimal)")
 
-    def __call__(self, question: str) -> str:
-        messages = [
-            self.system_msg,
-            HumanMessage(content=question),
-        ]
+# -----------------------------
+# Tools
+# -----------------------------
+search = DuckDuckGoSearchRun()
+
+
+# -----------------------------
+# Postprocess (CORE)
+# -----------------------------
+def postprocess(text: str) -> str:
+    t = text.strip()
+
+    # kill refusal patterns
+    if re.search(r"(cannot|unable|sorry|please provide)", t.lower()):
+        return ""
+
+    # remove quotes
+    t = t.strip("\"'")
+
+    # remove trailing punctuation
+    t = re.sub(r"[.。]$", "", t)
+
+    # first line only
+    if "\n" in t:
+        t = t.split("\n")[0].strip()
+
+    # numeric extraction if number-like
+    nums = re.findall(r"\d+", t)
+    if nums and len(t) > 6:
+        return nums[0]
+
+    return t
+
+
+# -----------------------------
+# Nodes
+# -----------------------------
+llm = ChatOpenAI(model="gpt-4o-mini", temperature=0, max_tokens=64)
+
+def decide_and_search(state: State):
+    if state["searched"]:
+        return state
 
-        response = self.llm.invoke(messages)
+    q = state["question"]
+    result = search.run(q)
 
-        # 안전장치: 무조건 str 반환
-        return response.content.strip()
+    return {
+        "question": q,
+        "search_result": result,
+        "searched": True,
+    }
+
+def answer(state: State):
+    prompt = (
+        f"Question:\n{state['question']}\n\n"
+        f"Search result:\n{state.get('search_result','')}\n\n"
+        "Final answer:"
+    )
+
+    msg = llm.invoke([SYS, HumanMessage(content=prompt)])
+    clean = postprocess(msg.content)
+
+    return {
+        **state,
+        "answer": clean,
+    }
+
+
+# -----------------------------
+# Graph
+# -----------------------------
+def build():
+    g = StateGraph(State)
+
+    g.add_node("search", decide_and_search)
+    g.add_node("answer", answer)
+
+    g.add_edge(START, "search")
+    g.add_edge("search", "answer")
+    g.add_edge("answer", END)
+
+    return g.compile()
+
+
+# -----------------------------
+# Public API
+# -----------------------------
+class BasicAgent:
+    def __init__(self):
+        self.graph = build()
+        print("GAIA 50% Agent ready")
+
+    def __call__(self, question: str) -> str:
+        out = self.graph.invoke(
+            {
+                "question": question,
+                "searched": False,
+            }
+        )
+        return out.get("answer", "")

requirements.txt

@@ -1,4 +1,8 @@
 gradio
 requests
+langgraph
+langchain
+langchain-community
 langchain_openai
-langchain_core
+duckduckgo-search
+ddgs