Some fixes in lang, field size and search

app.py

@@ -146,6 +146,7 @@ Reranker = CrossEncoder("mixedbread-ai/mxbai-rerank-large-v1", activation_fn=nn.
 
 class rfTranslatedText(BaseModel):
     text: str = Field(description='Translated text')
+    lang: str = Field(description='source language')
     
 class rfGenericText(BaseModel):
     text: str = Field(description='The text result')
@@ -197,7 +198,7 @@ def ChatFunc(message, history):
          m = BotMessage(msg);
          return ChatBotOutput();
      
-     m = BotMessage("",metadata={"title":"Procurando scripts...","status":"pending"});
+     m = BotMessage("",metadata={"title":"Searching scripts...","status":"pending"});
      
      
      def OnConnError(err):
@@ -208,26 +209,29 @@ def ChatFunc(message, history):
          # Responder algo sobre o historico!
          if IsNewSearch:
              
-             yield m("Melhorando o prompt")
+             yield m("Enhancing the prompt...")
              
-
              LLMResult = ai("""
                 Translate the user's message to English.
                 The message is a question related to a SQL Server T-SQL script that the user is searching for.
-                You only need to translate the message to English.
+                You must do following actions:
+                    - Identify the language of user text, using BCP 47 code (example: pt-BR, en-US, ja-JP, etc.)
+                    - Generate translated user text to english
+                Return both source language and translated text.
              """,message, rfTranslatedText)
              Question = LLMResult.message.parsed.text;
+             SourceLang = LLMResult.message.parsed.lang;
              
-             yield m(f"Melhorado: {Question}")
+             yield m(f"Lang:{SourceLang}, English Prompt: {Question}")
                       
-             yield m("Procurando scripts...")
+             yield m("searching...")
              try:
-                FoundScripts =  search(message, onConnectionError = OnConnError)
+                FoundScripts =  search(Question, onConnectionError = OnConnError)
              except:
                  yield m("Houve alguma falha ao executar a consulta no banco. Tente novamente. Se persistir, veja orientações na aba Help!")
                  return;
              
-             yield m("Fazendo o rerank");
+             yield m("Doing rerank");
              doclist = [doc['ScriptContent'] for doc in FoundScripts]
             
              # Faz o reranker!
@@ -253,20 +257,21 @@ def ChatFunc(message, history):
              
              
              CurrentTable = pd.DataFrame(ScriptTable)
-             yield m("Script encontrados, a aba Rank atualizada!")
+             yield m("Found scripts, check Rank tab for details!")
              
              
-             WaitMessage = ai("""
+             WaitMessage = ai(f"""
                 You will analyze some T-SQL scripts in order to check which is best for the user.
                 You found scripts, presented them to the user, and now will do some work that takes time.
                 Generate a message to tell the user to wait while you work, in the same language as the user.
                 You will receive the question the user sent that triggered this process.
                 Use the user’s original question to customize the message.
+                Answer in lang: {SourceLang}
              """,message,rfGenericText).message.parsed.text
              
              yield Reply(WaitMessage);
              
-             yield m(f"Analisando scripts...")
+             yield m(f"Analyzing scripts...")
              
              
              ResultJson = json.dumps(RankedScripts);
@@ -290,7 +295,6 @@ def ChatFunc(message, history):
                 Re-rank the results if necessary, presenting them from the most to the least relevant.  
                 You may filter out scripts that appear unrelated to the user query.
 
-                Respond in the user's original language.
                 ---
                 ### Output Rules
 
@@ -298,7 +302,8 @@ def ChatFunc(message, history):
                 - Summarize each script, ordering from the most relevant to the least relevant.  
                 - Write personalized and informative review text for each recommendation.  
                 - If applicable, explain how the user should run the script, including parameters or sections (like `WHERE` clauses) they might need to customize.  
-                - When referencing a script, include the link provided in the JSON — all scripts are hosted on GitHub.
+                - When referencing a script, include the link provided in the JSON — all scripts are hosted on GitHub
+                - YOU MUST ANSWER THAT LANGUAGE: {SourceLang}
              """
 
              ScriptPrompt = [
@@ -328,7 +333,7 @@ with gr.Blocks(fill_height=True) as demo:
     with gr.Column():
 
         with gr.Tab("Chat", scale = 1):
-            ChatTextBox = gr.Textbox(max_length = 100, info = "Que script precisa?", submit_btn = True);
+            ChatTextBox = gr.Textbox(max_length = 500, info = "Which script are you looking for?", submit_btn = True);
             
             gr.ChatInterface(
                 ChatFunc