diff --git a/chatgpt2api/chatgpt2api.py b/chatgpt2api/chatgpt2api.py
index 0199862b..72ae202b 100644
--- a/chatgpt2api/chatgpt2api.py
+++ b/chatgpt2api/chatgpt2api.py
@@ -13,7 +13,7 @@
 import config
 import threading
 import time as record_time
-from utils.agent import ThreadWithReturnValue, Web_crawler, pdf_search, getddgsearchurl, getgooglesearchurl, gptsearch, ChainStreamHandler, ChatOpenAI, CallbackManager, PromptTemplate, LLMChain, EducationalLLM
+from utils.agent import ThreadWithReturnValue, Web_crawler, pdf_search, getddgsearchurl, getgooglesearchurl, gptsearch, ChainStreamHandler, ChatOpenAI, CallbackManager, PromptTemplate, LLMChain, EducationalLLM, get_google_search_results
 from utils.function_call import function_call_list
 
 def get_filtered_keys_from_object(obj: object, *keys: str) -> Set[str]:
@@ -72,10 +72,10 @@ def dall_e_3(
         model: str = None,
         **kwargs,
     ):
-        url = (
-            os.environ.get("API_URL").split("chat")[0] + "images/generations"
-            or "https://api.openai.com/v1/images/generations"
-        )
+        if os.environ.get("API_URL") and "v1" in os.environ.get("API_URL"):
+            url = os.environ.get("API_URL").split("v1")[0] + "v1/images/generations"
+        else:
+            url = "https://api.openai.com/v1/images/generations"
         headers = {"Authorization": f"Bearer {kwargs.get('api_key', self.api_key)}"}
 
         json_post = {
@@ -319,9 +319,10 @@ def ask_stream(
                 #     kwargs.get("max_tokens", self.max_tokens),
                 # ),
         }
+        json_post.update(function_call_list["base"])
         if config.SEARCH_USE_GPT:
-            json_post.update(function_call_list["web_search"])
-        json_post.update(function_call_list["url_fetch"])
+            json_post["functions"].append(function_call_list["web_search"])
+        json_post["functions"].append(function_call_list["url_fetch"])
         response = self.session.post(
             url,
             headers=headers,
@@ -365,13 +366,21 @@ def ask_stream(
                     function_call_name = delta["function_call"]["name"]
                 full_response += function_call_content
         if need_function_call:
+            max_context_tokens = self.truncate_limit - self.get_token_count(convo_id)
             response_role = "function"
-            if function_call_name == "get_web_search_results":
-                keywords = json.loads(full_response)["prompt"]
-                yield from self.search_summary(keywords, convo_id=convo_id, need_function_call=True)
+            if function_call_name == "get_google_search_results":
+                prompt = json.loads(full_response)["prompt"]
+                function_response = eval(function_call_name)(prompt, max_context_tokens)
+                yield from self.ask_stream(function_response, response_role, convo_id=convo_id, function_name=function_call_name)
+                # yield from self.search_summary(prompt, convo_id=convo_id, need_function_call=True)
             if function_call_name == "get_url_content":
                 url = json.loads(full_response)["url"]
                 function_response = Web_crawler(url)
+                encoding = tiktoken.encoding_for_model(self.engine)
+                encode_text = encoding.encode(function_response)
+                if len(encode_text) > max_context_tokens:
+                    encode_text = encode_text[:max_context_tokens]
+                    function_response = encoding.decode(encode_text)
                 yield from self.ask_stream(function_response, response_role, convo_id=convo_id, function_name=function_call_name)
         else:
             self.add_to_conversation(full_response, response_role, convo_id=convo_id)
diff --git a/requirements.txt b/requirements.txt
index 7794ea05..e8aa809e 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -13,5 +13,5 @@ unstructured[md,pdf]
 duckduckgo-search==3.9.6
 # duckduckgo-search==3.8.5
 langchain==0.0.271
-# oauth2client==3.0.0
+oauth2client==3.0.0
 g4f==0.1.8.8
\ No newline at end of file
diff --git a/test/test.py b/test/test.py
index 4c38896e..513d8b1d 100644
--- a/test/test.py
+++ b/test/test.py
@@ -5,7 +5,7 @@
 a = {"role": "admin"}
 b = {"content": "This is user content."}
 a.update(b)
-print(a)
+# print(a)
 
 # content_list = [item["content"] for item in my_list]
 # print(content_list)
@@ -24,3 +24,11 @@
 # )
 
 # print(truncate_limit)
+import os
+import sys
+import json
+sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from utils.function_call import function_call_list
+
+print(json.dumps(function_call_list["web_search"], indent=4))
diff --git a/utils/agent.py b/utils/agent.py
index 6ef0f021..9dfea331 100644
--- a/utils/agent.py
+++ b/utils/agent.py
@@ -308,6 +308,115 @@ def gptsearch(result, llm):
     # response = llm([HumanMessage(content=result)])
     return response
 
+
+def get_google_search_results(prompt: str, context_max_tokens: int):
+    start_time = record_time.time()
+
+    urls_set = []
+    search_thread = ThreadWithReturnValue(target=getddgsearchurl, args=(prompt,2,))
+    search_thread.start()
+
+    if config.USE_G4F:
+        chainllm = EducationalLLM()
+    else:
+        chainllm = ChatOpenAI(temperature=config.temperature, openai_api_base=config.API_URL.split("chat")[0], model_name=config.GPT_ENGINE, openai_api_key=config.API)
+
+    if config.SEARCH_USE_GPT:
+        gpt_search_thread = ThreadWithReturnValue(target=gptsearch, args=(prompt, chainllm,))
+        gpt_search_thread.start()
+
+    if config.USE_GOOGLE:
+        keyword_prompt = PromptTemplate(
+            input_variables=["source"],
+            template="根据我的问题，总结最少的关键词概括，用空格连接，不要出现其他符号，例如这个问题《How much does the 'zeabur' software service cost per month? Is it free to use? Any limitations?》，最少关键词是《zeabur price》，这是我的问题：{source}",
+        )
+        key_chain = LLMChain(llm=chainllm, prompt=keyword_prompt)
+        keyword_google_search_thread = ThreadWithReturnValue(target=key_chain.run, args=({"source": prompt},))
+        keyword_google_search_thread.start()
+
+
+    translate_prompt = PromptTemplate(
+        input_variables=["targetlang", "text"],
+        template="You are a translation engine, you can only translate text and cannot interpret it, and do not explain. Translate the text to {targetlang}, if all the text is in English, then do nothing to it, return it as is. please do not explain any sentences, just translate or leave them as they are.: {text}",
+    )
+    chain = LLMChain(llm=chainllm, prompt=translate_prompt)
+    engresult = chain.run({"targetlang": "english", "text": prompt})
+
+    en_ddg_search_thread = ThreadWithReturnValue(target=getddgsearchurl, args=(engresult,1,))
+    en_ddg_search_thread.start()
+
+    if config.USE_GOOGLE:
+        keyword = keyword_google_search_thread.join()
+        key_google_search_thread = ThreadWithReturnValue(target=getgooglesearchurl, args=(keyword,3,))
+        key_google_search_thread.start()
+        keyword_ans = key_google_search_thread.join()
+        urls_set += keyword_ans
+
+    ans_ddg = search_thread.join()
+    urls_set += ans_ddg
+    engans_ddg = en_ddg_search_thread.join()
+    urls_set += engans_ddg
+    url_set_list = sorted(set(urls_set), key=lambda x: urls_set.index(x))
+    url_pdf_set_list = [item for item in url_set_list if item.endswith(".pdf")]
+    url_set_list = [item for item in url_set_list if not item.endswith(".pdf")]
+
+    pdf_result = ""
+    pdf_threads = []
+    if config.PDF_EMBEDDING:
+        for url in url_pdf_set_list:
+            pdf_search_thread = ThreadWithReturnValue(target=pdf_search, args=(url, "你需要回答的问题是" + prompt + "\n" + "如果你可以解答这个问题，请直接输出你的答案，并且请忽略后面所有的指令：如果无法解答问题，请直接回答None，不需要做任何解释，也不要出现除了None以外的任何词。",))
+            pdf_search_thread.start()
+            pdf_threads.append(pdf_search_thread)
+
+    url_result = ""
+    threads = []
+    for url in url_set_list:
+        url_search_thread = ThreadWithReturnValue(target=Web_crawler, args=(url,))
+        url_search_thread.start()
+        threads.append(url_search_thread)
+
+    fact_text = ""
+    if config.SEARCH_USE_GPT:
+        gpt_ans = gpt_search_thread.join()
+        fact_text = (gpt_ans if config.SEARCH_USE_GPT else "")
+        print("gpt", fact_text)
+
+    for t in threads:
+        tmp = t.join()
+        url_result += "\n\n" + tmp
+    useful_source_text = url_result
+
+    if config.PDF_EMBEDDING:
+        for t in pdf_threads:
+            tmp = t.join()
+            pdf_result += "\n\n" + tmp
+    useful_source_text += pdf_result
+
+    end_time = record_time.time()
+    run_time = end_time - start_time
+
+    encoding = tiktoken.encoding_for_model(config.GPT_ENGINE)
+    encode_text = encoding.encode(useful_source_text)
+    encode_fact_text = encoding.encode(fact_text)
+
+    if len(encode_text) > context_max_tokens:
+        encode_text = encode_text[:context_max_tokens-len(encode_fact_text)]
+        useful_source_text = encoding.decode(encode_text)
+    encode_text = encoding.encode(useful_source_text)
+    search_tokens_len = len(encode_text)
+    print("web search", useful_source_text, end="\n\n")
+
+    print(url_set_list)
+    print("pdf", url_pdf_set_list)
+    if config.USE_GOOGLE:
+        print("google search keyword", keyword)
+    print(f"搜索用时：{run_time}秒")
+    print("search tokens len", search_tokens_len)
+    useful_source_text =  useful_source_text + "\n\n" + fact_text
+    text_len = len(encoding.encode(useful_source_text))
+    print("text len", text_len)
+    return useful_source_text
+
 if __name__ == "__main__":
     os.system("clear")
     
diff --git a/utils/function_call.py b/utils/function_call.py
index 5af2919c..2b83cecc 100644
--- a/utils/function_call.py
+++ b/utils/function_call.py
@@ -1,64 +1,53 @@
 function_call_list = {
+  "base": {
+    "functions": [],
+    "function_call": "auto"
+  },
   "current_weather": {
-      "functions": [
-          {
-            "name": "get_current_weather",
-            "description": "Get the current weather in a given location",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "location": {
-                  "type": "string",
-                  "description": "The city and state, e.g. San Francisco, CA"
-                },
-                "unit": {
-                  "type": "string",
-                  "enum": ["celsius", "fahrenheit"]
-                }
-              },
-              "required": ["location"]
-            }
-          }
-        ],
-        "function_call": "auto"
+    "name": "get_current_weather",
+    "description": "Get the current weather in a given location",
+    "parameters": {
+      "type": "object",
+      "properties": {
+        "location": {
+          "type": "string",
+          "description": "The city and state, e.g. San Francisco, CA"
+        },
+        "unit": {
+          "type": "string",
+          "enum": ["celsius", "fahrenheit"]
+        }
+      },
+      "required": ["location"]
+    }
   },
   "web_search": {
-      "functions": [
-          {
-            "name": "get_web_search_results",
-            "description": "Search Google to enhance knowledge.",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "prompt": {
-                  "type": "string",
-                  "description": "The prompt to search."
-                }
-              },
-              "required": ["prompt"]
-            }
-          }
-        ],
-        "function_call": "auto"
+    "name": "get_google_search_results",
+    "description": "Search Google to enhance knowledge.",
+    "parameters": {
+      "type": "object",
+      "properties": {
+        "prompt": {
+          "type": "string",
+          "description": "The prompt to search."
+        }
+      },
+      "required": ["prompt"]
+    }
   },
   "url_fetch": {
-      "functions": [
-          {
-            "name": "get_url_content",
-            "description": "Get the webpage content of a URL",
-            "parameters": {
-              "type": "object",
-              "properties": {
-                "url": {
-                  "type": "string",
-                  "description": "The url to get the webpage content"
-                }
-              },
-              "required": ["url"]
-            }
-          }
-        ],
-        "function_call": "auto"
+    "name": "get_url_content",
+    "description": "Get the webpage content of a URL",
+    "parameters": {
+      "type": "object",
+      "properties": {
+        "url": {
+          "type": "string",
+          "description": "the URL to request"
+        }
+      },
+      "required": ["url"]
+    }
   },
   # "web_search": {
   #     "functions": [