chore: adapt to hf studio

app.py

@@ -0,0 +1,247 @@
+import streamlit as st
+import json
+import os
+import time
+from io import BytesIO
+from PIL import Image
+from typing import Dict, List, Any
+
+# 导入项目的核心逻辑和配置
+from geo_bot import (
+    GeoBot,
+    AGENT_PROMPT_TEMPLATE,
+    BENCHMARK_PROMPT,
+)  # 导入Prompt模板以供复用
+from benchmark import MapGuesserBenchmark
+from config import MODELS_CONFIG, DATA_PATHS, SUCCESS_THRESHOLD_KM
+from langchain_openai import ChatOpenAI
+from langchain_anthropic import ChatAnthropic
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+# --- 页面UI设置 ---
+st.set_page_config(page_title="MapCrunch AI Agent", layout="wide")
+st.title("🗺️ MapCrunch AI Agent")
+st.caption("一个通过多步交互探索和识别地理位置的AI智能体")
+
+# --- Sidebar用于配置 ---
+with st.sidebar:
+    st.header("⚙️ 运行配置")
+
+    # 从HF Secrets获取API密钥 (部署到HF Spaces时，需要在Settings->Secrets中设置)
+    os.environ["OPENAI_API_KEY"] = st.secrets.get("OPENAI_API_KEY", "")
+    os.environ["ANTHROPIC_API_KEY"] = st.secrets.get("ANTHROPIC_API_KEY", "")
+    # 添加其他你可能需要的API密钥
+    # os.environ['GOOGLE_API_KEY'] = st.secrets.get("GOOGLE_API_KEY", "")
+
+    model_choice = st.selectbox("选择AI模型", list(MODELS_CONFIG.keys()))
+    steps_per_sample = st.slider(
+        "每轮最大探索步数", min_value=3, max_value=20, value=10
+    )
+
+    # 加载golden labels以供选择
+    try:
+        with open(DATA_PATHS["golden_labels"], "r", encoding="utf-8") as f:
+            golden_labels = json.load(f).get("samples", [])
+        total_samples = len(golden_labels)
+        num_samples_to_run = st.slider(
+            "选择测试样本数量", min_value=1, max_value=total_samples, value=3
+        )
+    except FileNotFoundError:
+        st.error(f"数据文件 '{DATA_PATHS['golden_labels']}' 未找到。请先准备数据。")
+        golden_labels = []
+        num_samples_to_run = 0
+
+    start_button = st.button(
+        "🚀 启动Agent Benchmark", disabled=(num_samples_to_run == 0), type="primary"
+    )
+
+# --- Agent运行逻辑 ---
+if start_button:
+    # 准备运行环境
+    test_samples = golden_labels[:num_samples_to_run]
+
+    config = MODELS_CONFIG.get(model_choice)
+    model_class = globals()[config["class"]]
+    model_instance_name = config["model_name"]
+
+    # 初始化用于统计结果的辅助类和列表
+    benchmark_helper = MapGuesserBenchmark()
+    all_results = []
+
+    st.info(
+        f"即将开始Agent Benchmark... 模型: {model_choice}, 步数: {steps_per_sample}, 样本数: {num_samples_to_run}"
+    )
+
+    # 创建一个总进度条
+    overall_progress_bar = st.progress(0, text="总进度")
+
+    # 初始化Bot (注意：在HF Spaces上，必须以headless模式运行)
+    # 将Bot的初始化放在循环外，可以复用同一个浏览器实例，提高效率
+    with st.spinner("正在初始化浏览器和AI模型..."):
+        bot = GeoBot(model=model_class, model_name=model_instance_name, headless=True)
+
+    # 主循环，遍历所有选择的测试样本
+    for i, sample in enumerate(test_samples):
+        sample_id = sample.get("id", "N/A")
+        st.divider()
+        st.header(f"▶️ 运行中:样本 {i + 1}/{num_samples_to_run} (ID: {sample_id})")
+
+        # 加载地图位置
+        if not bot.controller.load_location_from_data(sample):
+            st.error(f"加载样本 {sample_id} 失败，已跳过。")
+            continue
+
+        bot.controller.setup_clean_environment()
+
+        # 为当前样本创建可视化布局
+        col1, col2 = st.columns([2, 3])
+        with col1:
+            image_placeholder = st.empty()
+        with col2:
+            reasoning_placeholder = st.empty()
+            action_placeholder = st.empty()
+
+        # --- 内部的Agent探索循环 ---
+        history = []
+        final_guess = None
+
+        for step in range(steps_per_sample):
+            step_num = step + 1
+            reasoning_placeholder.info(
+                f"思考中... (第 {step_num}/{steps_per_sample} 步)"
+            )
+            action_placeholder.empty()
+
+            # 观察并标记箭头
+            bot.controller.label_arrows_on_screen()
+            screenshot_bytes = bot.controller.take_street_view_screenshot()
+            image_placeholder.image(
+                screenshot_bytes, caption=f"Step {step_num} View", use_column_width=True
+            )
+
+            # 更新历史
+            history.append(
+                {
+                    "image_b64": bot.pil_to_base64(
+                        Image.open(BytesIO(screenshot_bytes))
+                    ),
+                    "action": "N/A",
+                }
+            )
+
+            # 思考
+            prompt = AGENT_PROMPT_TEMPLATE.format(
+                remaining_steps=steps_per_sample - step,
+                history_text="\n".join(
+                    [f"Step {j + 1}: {h['action']}" for j, h in enumerate(history)]
+                ),
+                available_actions=json.dumps(bot.controller.get_available_actions()),
+            )
+            message = bot._create_message_with_history(
+                prompt, [h["image_b64"] for h in history]
+            )
+            response = bot.model.invoke(message)
+            decision = bot._parse_agent_response(response)
+
+            if not decision:  # Fallback
+                decision = {
+                    "action_details": {"action": "PAN_RIGHT"},
+                    "reasoning": "Default recovery.",
+                }
+
+            action = decision.get("action_details", {}).get("action")
+            history[-1]["action"] = action
+
+            reasoning_placeholder.info(
+                f"**AI Reasoning:**\n\n{decision.get('reasoning', 'N/A')}"
+            )
+            action_placeholder.success(f"**AI Action:** `{action}`")
+
+            # 强制在最后一步进行GUESS
+            if step_num == steps_per_sample and action != "GUESS":
+                st.warning("已达最大步数，强制执行GUESS。")
+                action = "GUESS"
+
+            # 行动
+            if action == "GUESS":
+                lat, lon = (
+                    decision.get("action_details", {}).get("lat"),
+                    decision.get("action_details", {}).get("lon"),
+                )
+                if lat is not None and lon is not None:
+                    final_guess = (lat, lon)
+                else:
+                    # 如果AI没在GUESS时提供坐标，再问一次
+                    # (这里的简化处理是直接结束，但在更复杂的版本可以再调用一次AI)
+                    st.error("GUESS动作中缺少坐标，本次猜测失败。")
+                break  # 结束当前样本的探索
+
+            elif action == "MOVE_FORWARD":
+                bot.controller.move("forward")
+            elif action == "MOVE_BACKWARD":
+                bot.controller.move("backward")
+            elif action == "PAN_LEFT":
+                bot.controller.pan_view("left")
+            elif action == "PAN_RIGHT":
+                bot.controller.pan_view("right")
+
+            time.sleep(1)  # 在步骤之间稍作停顿，改善视觉效果
+
+        # --- 单个样本运行结束，计算并展示结果 ---
+        true_coords = {"lat": sample.get("lat"), "lng": sample.get("lng")}
+        distance_km = None
+        is_success = False
+
+        if final_guess:
+            distance_km = benchmark_helper.calculate_distance(true_coords, final_guess)
+            if distance_km is not None:
+                is_success = distance_km <= SUCCESS_THRESHOLD_KM
+
+            st.subheader("🎯 本轮结果")
+            res_col1, res_col2, res_col3 = st.columns(3)
+            res_col1.metric(
+                "最终猜测 (Lat, Lon)", f"{final_guess[0]:.3f}, {final_guess[1]:.3f}"
+            )
+            res_col2.metric(
+                "真实位置 (Lat, Lon)",
+                f"{true_coords['lat']:.3f}, {true_coords['lng']:.3f}",
+            )
+            res_col3.metric(
+                "距离误差",
+                f"{distance_km:.1f} km" if distance_km is not None else "N/A",
+                delta=f"{'成功' if is_success else '失败'}",
+                delta_color=("inverse" if is_success else "off"),
+            )
+        else:
+            st.error("Agent 未能做出最终猜测。")
+
+        all_results.append(
+            {
+                "sample_id": sample_id,
+                "model": model_choice,
+                "true_coordinates": true_coords,
+                "predicted_coordinates": final_guess,
+                "distance_km": distance_km,
+                "success": is_success,
+            }
+        )
+
+        # 更新总进度条
+        overall_progress_bar.progress(
+            (i + 1) / num_samples_to_run, text=f"总进度: {i + 1}/{num_samples_to_run}"
+        )
+
+    # --- 所有样本运行完毕，显示最终摘要 ---
+    bot.close()  # 关闭浏览器
+    st.divider()
+    st.header("🏁 Benchmark 最终摘要")
+
+    summary = benchmark_helper.generate_summary(all_results)
+    if summary and model_choice in summary:
+        stats = summary[model_choice]
+        sum_col1, sum_col2 = st.columns(2)
+        sum_col1.metric("总成功率", f"{stats.get('success_rate', 0) * 100:.1f} %")
+        sum_col2.metric("平均距离误差", f"{stats.get('average_distance_km', 0):.1f} km")
+        st.dataframe(all_results)  # 显示详细结果表格
+    else:
+        st.warning("没有足够的结果来生成摘要。")

geo_bot.py

@@ -6,6 +6,7 @@ from typing import Tuple, List, Optional, Dict, Any, Type
 
 from PIL import Image
 from langchain_core.messages import HumanMessage, BaseMessage
+from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_openai import ChatOpenAI
 from langchain_anthropic import ChatAnthropic
 from langchain_google_genai import ChatGoogleGenerativeAI
@@ -64,15 +65,13 @@ class GeoBot:
         use_selenium: bool = True,
         headless: bool = False,
     ):
-        self.model = model(model=model_name)
+        self.model: BaseChatModel = model(model=model_name)
         self.model_name = model_name
         self.use_selenium = use_selenium
-        self.controller = (
-            MapCrunchController(headless=headless) if use_selenium else None
-        )
+        self.controller = MapCrunchController(headless=headless)
 
     @staticmethod
-    def pil_to_base64(image: Image) -> str:
+    def pil_to_base64(image: Image.Image) -> str:
         buffered = BytesIO()
         image.thumbnail((1024, 1024))
         image.save(buffered, format="PNG")
@@ -119,6 +118,7 @@ class GeoBot:
         Robustly parses JSON from the LLM response, handling markdown code blocks.
         """
         try:
+            assert isinstance(response.content, str), "Response content is not a string"
             content = response.content.strip()
             match = re.search(r"```json\s*(\{.*?\})\s*```", content, re.DOTALL)
             if match:
@@ -146,13 +146,13 @@ class GeoBot:
                 return None
 
             current_screenshot_b64 = self.pil_to_base64(
-                Image.open(BytesIO(screenshot_bytes))
+                image=Image.open(BytesIO(screenshot_bytes))
             )
             available_actions = self.controller.get_available_actions()
             print(f"Available actions: {available_actions}")
 
-            history_text = ""
-            image_b64_for_prompt = []
+            history_text: str = ""
+            image_b64_for_prompt: List[str] = []
             if not history:
                 history_text = "No history yet. This is the first step."
             else:
@@ -208,7 +208,7 @@ class GeoBot:
         print("Max steps reached. Agent did not make a final guess.")
         return None
 
-    def analyze_image(self, image: Image) -> Optional[Tuple[float, float]]:
+    def analyze_image(self, image: Image.Image) -> Optional[Tuple[float, float]]:
         image_b64 = self.pil_to_base64(image)
         message = self._create_llm_message(BENCHMARK_PROMPT, image_b64)
         response = self.model.invoke(message)

mapcrunch_controller.py

@@ -140,7 +140,6 @@ class MapCrunchController:
     def get_available_actions(self) -> List[str]:
         """
         Checks for movement links via JavaScript.
-        FIXED: Removed PAN_UP and PAN_DOWN as they are not very useful.
         """
         base_actions = ["PAN_LEFT", "PAN_RIGHT", "GUESS"]
         links = self.driver.execute_script("return window.panorama.getLinks();")
@@ -155,7 +154,6 @@ class MapCrunchController:
             pov["heading"] -= degrees
         elif direction == "right":
             pov["heading"] += degrees
-        # UP/DOWN panning logic removed as actions are no longer available.
         self.driver.execute_script("window.panorama.setPov(arguments[0]);", pov)
         time.sleep(0.5)
 
@@ -191,7 +189,6 @@ class MapCrunchController:
             )
             time.sleep(2.5)
 
-    # ... a többi metódus változatlan ...
     def select_map_location_and_guess(self, lat: float, lon: float):
         """Minimalist guess confirmation."""
         self.driver.execute_script(

packages.txt

@@ -0,0 +1,2 @@
+chromium-driver
+chromium

pyproject.toml

@@ -108,6 +108,7 @@ dependencies = [
     "sniffio==1.3.1",
     "sqlalchemy==2.0.36",
     "stack-data==0.6.3",
+    "streamlit>=1.45.1",
     "tenacity==9.0.0",
     "tiktoken==0.8.0",
     "tokenizers==0.20.1",

uv.lock

@@ -98,6 +98,22 @@ wheels = [
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 ]
 
+[[package]]
+name = "altair"
+version = "5.5.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "jinja2" },
+    { name = "jsonschema" },
+    { name = "narwhals" },
+    { name = "packaging" },
+    { name = "typing-extensions", marker = "python_full_version < '3.14'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/16/b1/f2969c7bdb8ad8bbdda031687defdce2c19afba2aa2c8e1d2a17f78376d8/altair-5.5.0.tar.gz", hash = "sha256:d960ebe6178c56de3855a68c47b516be38640b73fb3b5111c2a9ca90546dd73d", size = 705305 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/aa/f3/0b6ced594e51cc95d8c1fc1640d3623770d01e4969d29c0bd09945fafefa/altair-5.5.0-py3-none-any.whl", hash = "sha256:91a310b926508d560fe0148d02a194f38b824122641ef528113d029fcd129f8c", size = 731200 },
+]
+
 [[package]]
 name = "annotated-types"
 version = "0.7.0"
@@ -169,6 +185,15 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/6a/21/5b6702a7f963e95456c0de2d495f67bf5fd62840ac655dc451586d23d39a/attrs-24.2.0-py3-none-any.whl", hash = "sha256:81921eb96de3191c8258c199618104dd27ac608d9366f5e35d011eae1867ede2", size = 63001 },
 ]
 
+[[package]]
+name = "blinker"
+version = "1.9.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/21/28/9b3f50ce0e048515135495f198351908d99540d69bfdc8c1d15b73dc55ce/blinker-1.9.0.tar.gz", hash = "sha256:b4ce2265a7abece45e7cc896e98dbebe6cead56bcf805a3d23136d145f5445bf", size = 22460 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl", hash = "sha256:ba0efaa9080b619ff2f3459d1d500c57bddea4a6b424b60a91141db6fd2f08bc", size = 8458 },
+]
+
 [[package]]
 name = "cachetools"
 version = "5.5.0"
@@ -286,6 +311,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/bf/9b/08c0432272d77b04803958a4598a51e2a4b51c06640af8b8f0f908c18bf2/charset_normalizer-3.4.0-py3-none-any.whl", hash = "sha256:fe9f97feb71aa9896b81973a7bbada8c49501dc73e58a10fcef6663af95e5079", size = 49446 },
 ]
 
+[[package]]
+name = "click"
+version = "8.2.1"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "colorama", marker = "sys_platform == 'win32'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/60/6c/8ca2efa64cf75a977a0d7fac081354553ebe483345c734fb6b6515d96bbc/click-8.2.1.tar.gz", hash = "sha256:27c491cc05d968d271d5a1db13e3b5a184636d9d930f148c50b038f0d0646202", size = 286342 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/85/32/10bb5764d90a8eee674e9dc6f4db6a0ab47c8c4d0d83c27f7c39ac415a4d/click-8.2.1-py3-none-any.whl", hash = "sha256:61a3265b914e850b85317d0b3109c7f8cd35a670f963866005d6ef1d5175a12b", size = 102215 },
+]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -516,6 +553,30 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/1d/a0/6aaea0c2fbea2f89bfd5db25fb1e3481896a423002ebe4e55288907a97a3/fsspec-2024.9.0-py3-none-any.whl", hash = "sha256:a0947d552d8a6efa72cc2c730b12c41d043509156966cca4fb157b0f2a0c574b", size = 179253 },
 ]
 
+[[package]]
+name = "gitdb"
+version = "4.0.12"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "smmap" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/72/94/63b0fc47eb32792c7ba1fe1b694daec9a63620db1e313033d18140c2320a/gitdb-4.0.12.tar.gz", hash = "sha256:5ef71f855d191a3326fcfbc0d5da835f26b13fbcba60c32c21091c349ffdb571", size = 394684 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a0/61/5c78b91c3143ed5c14207f463aecfc8f9dbb5092fb2869baf37c273b2705/gitdb-4.0.12-py3-none-any.whl", hash = "sha256:67073e15955400952c6565cc3e707c554a4eea2e428946f7a4c162fab9bd9bcf", size = 62794 },
+]
+
+[[package]]
+name = "gitpython"
+version = "3.1.44"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "gitdb" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/c0/89/37df0b71473153574a5cdef8f242de422a0f5d26d7a9e231e6f169b4ad14/gitpython-3.1.44.tar.gz", hash = "sha256:c87e30b26253bf5418b01b0660f818967f3c503193838337fe5e573331249269", size = 214196 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/1d/9a/4114a9057db2f1462d5c8f8390ab7383925fe1ac012eaa42402ad65c2963/GitPython-3.1.44-py3-none-any.whl", hash = "sha256:9e0e10cda9bed1ee64bc9a6de50e7e38a9c9943241cd7f585f6df3ed28011110", size = 207599 },
+]
+
 [[package]]
 name = "google-ai-generativelanguage"
 version = "0.6.10"
@@ -863,6 +924,18 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/20/9f/bc63f0f0737ad7a60800bfd472a4836661adae21f9c2535f3957b1e54ceb/jedi-0.19.1-py2.py3-none-any.whl", hash = "sha256:e983c654fe5c02867aef4cdfce5a2fbb4a50adc0af145f70504238f18ef5e7e0", size = 1569361 },
 ]
 
+[[package]]
+name = "jinja2"
+version = "3.1.6"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "markupsafe" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/df/bf/f7da0350254c0ed7c72f3e33cef02e048281fec7ecec5f032d4aac52226b/jinja2-3.1.6.tar.gz", hash = "sha256:0137fb05990d35f1275a587e9aee6d56da821fc83491a0fb838183be43f66d6d", size = 245115 }
+wheels = [
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+]
+
 [[package]]
 name = "jiter"
 version = "0.6.1"
@@ -928,6 +1001,33 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/71/92/5e77f98553e9e75130c78900d000368476aed74276eb8ae8796f65f00918/jsonpointer-3.0.0-py2.py3-none-any.whl", hash = "sha256:13e088adc14fca8b6aa8177c044e12701e6ad4b28ff10e65f2267a90109c9942", size = 7595 },
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+[[package]]
+name = "jsonschema"
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