gpt4free supports langchain search

agent.py

@@ -180,6 +180,27 @@ def pdf_search(docurl, query_message, model="gpt-3.5-turbo"):
     result = qa({"query": query_message})
     return result['result']
 
+from typing import Optional, List
+from langchain.llms.base import LLM
+import g4f
+class EducationalLLM(LLM):
+
+    @property
+    def _llm_type(self) -> str:
+        return "custom"
+
+    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
+        out = g4f.ChatCompletion.create(
+            model=config.GPT_ENGINE,
+            messages=[{"role": "user", "content": prompt}],
+        )  #
+        if stop:
+            stop_indexes = (out.find(s) for s in stop if s in out)
+            min_stop = min(stop_indexes, default=-1)
+            if min_stop > -1:
+                out = out[:min_stop]
+        return out
+
 class ChainStreamHandler(StreamingStdOutCallbackHandler):
     def __init__(self):
         self.tokens = []
@@ -268,8 +289,11 @@ def getgooglesearchurl(result, numresults=3):
 def gptsearch(result, llm):
     result = "你需要回答的问题是" + result + "\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。"
     # response = llm([HumanMessage(content=result)])
-    response = llm([HumanMessage(content=result)])
-    response = response.content
+    if config.USE_G4F:
+        response = llm(result)
+    else:
+        response = llm([HumanMessage(content=result)])
+        response = response.content
     # result = "你需要回答的问题是" + result + "\n" + "参考资料：" + response + "如果参考资料无法解答问题，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。"
     # response = llm([HumanMessage(content=result)])
     return response

bot.py

@@ -101,7 +101,7 @@ async def getChatGPT(update, context, title, robot, message, use_search=config.S
         get_answer = robot.search_summary
     else:
         get_answer = robot.ask_stream
-    if not config.API or config.USE_G4F:
+    if not config.API or (config.USE_G4F and not config.SEARCH_USE_GPT):
         import gpt4free
         get_answer = gpt4free.get_response
 

chatgpt2api/chatgpt2api.py

@@ -13,7 +13,7 @@
 import config
 import threading
 import time as record_time
-from agent import ThreadWithReturnValue, Web_crawler, pdf_search, getddgsearchurl, getgooglesearchurl, gptsearch, ChainStreamHandler, ChatOpenAI, CallbackManager, PromptTemplate, LLMChain
+from agent import ThreadWithReturnValue, Web_crawler, pdf_search, getddgsearchurl, getgooglesearchurl, gptsearch, ChainStreamHandler, ChatOpenAI, CallbackManager, PromptTemplate, LLMChain, EducationalLLM
 
 def get_filtered_keys_from_object(obj: object, *keys: str) -> Set[str]:
     """
@@ -433,8 +433,12 @@ def search_summary(
         search_thread.start()
 
         chainStreamHandler = ChainStreamHandler()
-        chatllm = ChatOpenAI(streaming=True, callback_manager=CallbackManager([chainStreamHandler]), temperature=config.temperature, openai_api_base=config.API_URL.split("chat")[0], model_name=self.engine, openai_api_key=config.API)
-        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.USE_G4F:
+            chatllm = EducationalLLM(callback_manager=CallbackManager([chainStreamHandler]))
+            chainllm = EducationalLLM()
+        else:
+            chatllm = ChatOpenAI(streaming=True, callback_manager=CallbackManager([chainStreamHandler]), temperature=config.temperature, openai_api_base=config.API_URL.split("chat")[0], model_name=self.engine, openai_api_key=config.API)
+            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,))

test/test_gpt4free_langchain_agent.py

@@ -23,10 +23,12 @@ def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
 
 
 llm = EducationalLLM()
+# print(llm("今天的微博热搜有哪些？"))
 tools = load_tools(["ddg-search", "llm-math"], llm=llm)
 agent = initialize_agent(tools, llm, agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION, verbose=True)
 agent.run("今天的微博热搜有哪些？")
 
+
 # def duckduckgo_search(searchtext, model="gpt-3.5-turbo", temperature=0.5):
 #     llm = ChatOpenAI(temperature=temperature, openai_api_base='https://api.ohmygpt.com/v1/', model_name=model, openai_api_key=API)
 #     tools = load_tools(["ddg-search", "llm-math"], llm=llm)