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Fix web search and template max tokens (#1564)
### What problem does this PR solve? ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
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@ -188,6 +188,7 @@ class Canvas(ABC):
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def prepare2run(cpns):
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nonlocal ran, ans
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for c in cpns:
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if self.path[-1] and c == self.path[-1][-1]: continue
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cpn = self.components[c]["obj"]
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if cpn.component_name == "Answer":
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self.answer.append(c)
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@ -43,7 +43,7 @@ class Baidu(ComponentBase, ABC):
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ans = self.get_input()
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ans = " - ".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return Baidu.be_output(self._param.no)
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return Baidu.be_output("")
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url = 'https://www.baidu.com/s?wd=' + ans + '&rn=' + str(self._param.top_n)
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headers = {
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@ -56,8 +56,10 @@ class Baidu(ComponentBase, ABC):
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baidu_res = [{"content": re.sub('<em>|</em>', '', '<a href="' + url + '">' + title + '</a> ' + body)} for url, title, body in zip(url_res, title_res, body_res)]
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del body_res, url_res, title_res
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df = pd.DataFrame(baidu_res)
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print(df, ":::::::::::::::::::::::::::::::::")
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if not baidu_res:
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return Baidu.be_output("")
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df = pd.DataFrame(baidu_res)
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if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
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return df
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@ -44,7 +44,7 @@ class DuckDuckGo(ComponentBase, ABC):
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ans = self.get_input()
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ans = " - ".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return DuckDuckGo.be_output(self._param.no)
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return DuckDuckGo.be_output("")
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if self._param.channel == "text":
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with DDGS() as ddgs:
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@ -57,6 +57,9 @@ class DuckDuckGo(ComponentBase, ABC):
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duck_res = [{"content": '<a href="' + i["url"] + '">' + i["title"] + '</a> ' + i["body"]} for i in
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ddgs.news(ans, max_results=self._param.top_n)]
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if not duck_res:
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return DuckDuckGo.be_output("")
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df = pd.DataFrame(duck_res)
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print(df, ":::::::::::::::::::::::::::::::::")
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if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
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return df
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@ -72,14 +72,14 @@ class Generate(ComponentBase):
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prompt = self._param.prompt
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retrieval_res = self.get_input()
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input = "\n- ".join(retrieval_res["content"]) if "content" in retrieval_res else ""
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input = (" - " + "\n - ".join(retrieval_res["content"])) if "content" in retrieval_res else ""
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for para in self._param.parameters:
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cpn = self._canvas.get_component(para["component_id"])["obj"]
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_, out = cpn.output(allow_partial=False)
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if "content" not in out.columns:
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kwargs[para["key"]] = "Nothing"
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else:
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kwargs[para["key"]] = "\n - ".join(out["content"])
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kwargs[para["key"]] = " - " + "\n - ".join(out["content"])
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kwargs["input"] = input
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for n, v in kwargs.items():
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@ -30,7 +30,7 @@ class WikipediaParam(ComponentParamBase):
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def __init__(self):
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super().__init__()
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self.top_n = 10
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self.language = 'en'
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self.language = "en"
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def check(self):
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self.check_positive_integer(self.top_n, "Top N")
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@ -49,7 +49,7 @@ class Wikipedia(ComponentBase, ABC):
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ans = self.get_input()
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ans = " - ".join(ans["content"]) if "content" in ans else ""
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if not ans:
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return Wikipedia.be_output(self._param.no)
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return Wikipedia.be_output("")
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wiki_res = []
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wikipedia.set_lang(self._param.language)
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@ -63,7 +63,7 @@ class Wikipedia(ComponentBase, ABC):
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pass
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if not wiki_res:
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return Wikipedia.be_output(self._param.no)
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return Wikipedia.be_output("")
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df = pd.DataFrame(wiki_res)
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if DEBUG: print(df, ":::::::::::::::::::::::::::::::::")
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@ -59,7 +59,6 @@
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"cite": true,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat",
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"max_tokens": 2048,
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"message_history_window_size": 12,
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"parameters": [
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{
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@ -108,7 +107,7 @@
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"frequencyPenaltyEnabled": true,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat",
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"maxTokensEnabled": false,
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"maxTokensEnabled": true,
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"max_tokens": 256,
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"parameter": "Precise",
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"presencePenaltyEnabled": true,
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@ -366,7 +365,7 @@
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"frequencyPenaltyEnabled": true,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat",
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"maxTokensEnabled": false,
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"maxTokensEnabled": true,
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"max_tokens": 256,
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"parameter": "Precise",
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"presencePenaltyEnabled": true,
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@ -510,8 +509,6 @@
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"frequencyPenaltyEnabled": true,
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"frequency_penalty": 0.7,
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"llm_id": "deepseek-chat",
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"maxTokensEnabled": true,
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"max_tokens": 2048,
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"message_history_window_size": 12,
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"parameter": "Precise",
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"parameters": [
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@ -538,7 +535,7 @@
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],
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"presencePenaltyEnabled": true,
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"presence_penalty": 0.4,
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"prompt": "Role: You are an intelligent assistant. \nTask: Chat with user. Answer the question based on the provided content from: Knowledge Base, Wikipedia, Duckduckgo, Baidu.\nRequirements:\n - Answer should be in markdown format.\n - Summarize and label the sources of the cited content separately: (Knowledge Base, Wikipedia, Duckduckgo, Baidu).\n - Attach URL links to the content which is quoted from Wikipedia, DuckDuckGo or Baidu.\n - Do not make thing up when there's no relevant information to user's question. \n\n## Knowledge base content\n {kb_input}\n\n\n## Wikipedia content\n{wikipedia}\n\n\n## Duckduckgo content\n{duckduckgo}\n\n\n## Baidu content\n{baidu}",
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"prompt": "Role: You are an intelligent assistant. \nTask: Chat with user. Answer the question based on the provided content from: Knowledge Base, Wikipedia, Duckduckgo, Baidu.\nRequirements:\n - Answer should be in markdown format.\n - Answer should include all sources(Knowledge Base, Wikipedia, Duckduckgo, Baidu) as long as they are relevant, and label the sources of the cited content separately.\n - Attach URL links to the content which is quoted from Wikipedia, DuckDuckGo or Baidu.\n - Do not make thing up when there's no relevant information to user's question. \n\n## Knowledge base content\n {kb_input}\n\n\n## Wikipedia content\n{wikipedia}\n\n\n## Duckduckgo content\n{duckduckgo}\n\n\n## Baidu content\n{baidu}",
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"temperature": 0.1,
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"temperatureEnabled": true,
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"topPEnabled": true,
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