Commit 1f8922a

@@ -1,5 +1,6 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
+import asyncio
 import contextlib
 import json
 from io import BytesIO
@@ -31,6 +32,7 @@ from messages.parser import parse_msg
 from messages.progress import modify_progress
 from messages.sender import send2tg
 from messages.utils import blockquote, count_without_entities, smart_split
+from networking import flatten_rediercts
 from utils import number_to_emoji, rand_string
 
 HELP = f"""🌠**AI生图**
@@ -227,8 +229,8 @@ async def gemini_stream(
                 **kwargs,
             )
         if append_grounding:  # add grounding to the response
-            answers = add_grounding_results(answers, resp["grounding_chunks"], resp["grounding_supports"])
-            runtime_texts = add_grounding_results(runtime_texts, resp["grounding_chunks"], resp["grounding_supports"])
+            answers = await add_grounding_results(answers, resp["grounding_chunks"], resp["grounding_supports"])
+            runtime_texts = await add_grounding_results(runtime_texts, resp["grounding_chunks"], resp["grounding_supports"])
         final_thoughts = "" if remove_thinking else thoughts
         if await count_without_entities(prefix + final_thoughts + answers) <= TEXT_LENGTH - 10:  # short answer in single msg
             if length > GPT.COLLAPSE_LENGTH:  # collapse the response if the answer is too long
@@ -311,7 +313,7 @@ async def gemini_nonstream(
         texts = res.get("texts", "")
         thoughts = res.get("thoughts", "")
         if append_grounding:  # add grounding to the response
-            texts = add_grounding_results(texts, res["grounding_chunks"], res["grounding_supports"])
+            texts = await add_grounding_results(texts, res["grounding_chunks"], res["grounding_supports"])
         results |= {"prefix": prefix, "model_name": model_name, "texts": texts, "thoughts": thoughts}
         media = res.get("media", [])
         total = prefix + blockquote(REASONING_BEGIN + thoughts.strip() + REASONING_END) + "\n" + texts.strip() if thoughts.strip() else prefix + texts.strip()
@@ -372,8 +374,11 @@ def parse_response(data: dict) -> dict:
     }
 
 
-def add_grounding_results(answers: str, grounding_chunks: list[dict], grounding_supports: list[dict]) -> str:
-    index2url = {idx + 1: glom(chunk, "web.uri", default="https://www.google.com") for idx, chunk in enumerate(grounding_chunks)}
+async def add_grounding_results(answers: str, grounding_chunks: list[dict], grounding_supports: list[dict]) -> str:
+    urls = [glom(chunk, "web.uri", default="https://www.google.com") for chunk in grounding_chunks]
+    tasks = [flatten_rediercts(url) for url in urls]
+    flatten_urls = await asyncio.gather(*tasks)
+    index2url = {idx + 1: url for idx, url in enumerate(flatten_urls)}
     for support in grounding_supports:
         indices: list[int] = support.get("grounding_chunk_indices", [])
         indices_with_url = " ".join([f"[[{idx + 1}]]({index2url[idx + 1]})" for idx in indices])
@@ -383,7 +388,7 @@ def add_grounding_results(answers: str, grounding_chunks: list[dict], grounding_
         if idx > 9:
             break
         title = glom(grounding, "web.title", default="Web")
-        url = glom(grounding, "web.uri", default="https://www.google.com")
+        url = flatten_urls[idx]
         if url in answers:
             answers += f"\n{number_to_emoji(idx + 1)}[{title}]({url})"
     return answers

@@ -436,6 +436,10 @@ async def flatten_rediercts(texts: str | None = None, pattern: str | None = None
     # shorturl.at
     if matched := re.search(r"(https?://)?shorturl\.at/([^.。,，?&/\s]+)", texts):
         url = matched.group(0)
+    # vertexaisearch.cloud.google.com
+    if matched := re.search(r"(https?://)?vertexaisearch\.cloud\.google\.com/([0-9a-zA-Z\-_=+/]+)", texts):
+        url = matched.group(0)
+        proxy = PROXY.GOOGLE_SEARCH
 
     # custom pattern
     if pattern and (matched := re.search(pattern, texts)):