Add Support for Gemini 1.5 Pro & Gemini 1.5 Flash (#1926)

* Add Support for Gemini 1.5 Pro & 1.5 Flash.

* Update bridge_all.py

fix a spelling error in comments.

* Add Support for Gemini 1.5 Pro & Gemini 1.5 Flash

request_llms/bridge_google_gemini.py

@@ -8,15 +8,15 @@ import os
 import time
 from request_llms.com_google import GoogleChatInit
 from toolbox import ChatBotWithCookies
-from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat
+from toolbox import get_conf, update_ui, update_ui_lastest_msg, have_any_recent_upload_image_files, trimmed_format_exc, log_chat, encode_image
 
 proxies, TIMEOUT_SECONDS, MAX_RETRY = get_conf('proxies', 'TIMEOUT_SECONDS', 'MAX_RETRY')
 timeout_bot_msg = '[Local Message] Request timeout. Network error. Please check proxy settings in config.py.' + \
                   '网络错误，检查代理服务器是否可用，以及代理设置的格式是否正确，格式须是[协议]://[地址]:[端口]，缺一不可。'
 
 
-def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="", observe_window=None,
-                                  console_slience=False):
+def predict_no_ui_long_connection(inputs:str, llm_kwargs:dict, history:list=[], sys_prompt:str="", observe_window:list=[],
+                                  console_slience:bool=False):
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
         raise ValueError(f"请配置 GEMINI_API_KEY。")
@@ -44,9 +44,20 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",
             raise RuntimeError(f'{gpt_replying_buffer} 对话错误')
     return gpt_replying_buffer
 
+def make_media_input(inputs, image_paths):
+    image_base64_array = []
+    for image_path in image_paths:
+        path = os.path.abspath(image_path)
+        inputs = inputs + f'<br/><br/><div align="center"><img src="file={path}"></div>'
+        base64 = encode_image(path)
+        image_base64_array.append(base64)
+    return inputs, image_base64_array
 
 def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWithCookies,
             history:list=[], system_prompt:str='', stream:bool=True, additional_fn:str=None):
+    
+    from .bridge_all import model_info
+
     # 检查API_KEY
     if get_conf("GEMINI_API_KEY") == "":
         yield from update_ui_lastest_msg(f"请配置 GEMINI_API_KEY。", chatbot=chatbot, history=history, delay=0)
@@ -57,18 +68,17 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
         from core_functional import handle_core_functionality
         inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
 
-    if "vision" in llm_kwargs["llm_model"]:
-        have_recent_file, image_paths = have_any_recent_upload_image_files(chatbot)
-        if not have_recent_file:
-            chatbot.append((inputs, "没有检测到任何近期上传的图像文件，请上传jpg格式的图片，此外，请注意拓展名需要小写"))
-            yield from update_ui(chatbot=chatbot, history=history, msg="等待图片") # 刷新界面
-            return
-        def make_media_input(inputs, image_paths):
-            for image_path in image_paths:
-                inputs = inputs + f'<br/><br/><div align="center"><img src="file={os.path.abspath(image_path)}"></div>'
-            return inputs
-        if have_recent_file:
-            inputs = make_media_input(inputs, image_paths)
+    # multimodal capacity
+    # inspired by codes in bridge_chatgpt
+    has_multimodal_capacity = model_info[llm_kwargs['llm_model']].get('has_multimodal_capacity', False)
+    if has_multimodal_capacity:
+        has_recent_image_upload, image_paths = have_any_recent_upload_image_files(chatbot, pop=True)
+    else:
+        has_recent_image_upload, image_paths = False, []
+    if has_recent_image_upload:
+        inputs, image_base64_array = make_media_input(inputs, image_paths)
+    else:
+        inputs, image_base64_array = inputs, []
 
     chatbot.append((inputs, ""))
     yield from update_ui(chatbot=chatbot, history=history)
@@ -76,7 +86,7 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
     retry = 0
     while True:
         try:
-            stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt)
+            stream_response = genai.generate_chat(inputs, llm_kwargs, history, system_prompt, image_base64_array, has_multimodal_capacity)
             break
         except Exception as e:
             retry += 1
@@ -112,7 +122,6 @@ def predict(inputs:str, llm_kwargs:dict, plugin_kwargs:dict, chatbot:ChatBotWith
         yield from update_ui(chatbot=chatbot, history=history)
 
 
-
 if __name__ == '__main__':
     import sys
     llm_kwargs = {'llm_model': 'gemini-pro'}