fix: language answer from bot

database/4a5944a6-5c35-44f8-88be-78ce2e35028c/data_level0.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:d3c9fd302f000d7790aa403c2d0d8fec363fe46f30b07d53020b6e33b22435a9
+oid sha256:438a50d5e22300bf69cf65a069fdab5d99af120fa635fa9444d3ae52ffcf23d1
 size 1676000

database/4a5944a6-5c35-44f8-88be-78ce2e35028c/length.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5b8e0bc4024bd2c60f910c5ea628a6b78cab039442c2c1e1576985ca11d8ab69
+oid sha256:40616716b33e9e16756c831d8097b709a29c0c3b0c182e61ed8516183883b5c3
 size 4000

src/control/control.py

@@ -12,8 +12,8 @@ class Chatbot:
 
     def get_response(self, query, histo):
         histo_conversation, histo_queries = self._get_histo(histo)
-        langage_of_query = self.llm.detect_language(query)
-        queries = self.llm.translate(text=histo_queries) if langage_of_query.lower() == 'fr' else histo_queries
+        langage_of_query = self.llm.detect_language(query).lower()
+        queries = self.llm.translate(text=histo_queries)
         block_sources = self.retriever.similarity_search(query=queries)
         block_sources = self._select_best_sources(block_sources)
         sources_contents = [s.content for s in block_sources]

src/tools/llm.py

@@ -10,16 +10,16 @@ class LlmAgent:
                     f"\\n ``` {query} ```\\n"
                     f"Your answer is based on the context delimited by triple backticks: "
                     f"\\n ``` {context} ```\\n"
-                    f"You are consistent and avoid redundancies with the rest of the initial conversation"
+                    f" You are consistent and avoid redundancies with the rest of the initial conversation "
                     f"delimited by triple backticks: "
                     f"\\n ``` {histo} ```\\n"
                     f"Your response shall be in {language} and shall be concise")
 
         p = self.llm(template)
-        print("****************")
-        print(template)
-        print("----")
-        print(p)
+        # print("****************")
+        # print(template)
+        # print("----")
+        # print(p)
         return p
 
     def translate(self, text: str, language="en") -> str:
@@ -27,20 +27,20 @@ class LlmAgent:
 
         languages = "`French to English" if language == "en" else "English to French"
 
-        template = (f"    Your task consists in translating {languages}\\n"
+        template = (f"    Your task consists in translating in English\\n"
                     f"    the following text delimited by by triple backticks: ```{text}```\n"
                     )
 
         p = self.llm(template)
         return p
 
-    def generate_answer(self, query: str, answer: str, histo: str, context: str, language: str) -> str:
-        """provides the final answer based on the initial query and the answer"""
+    def generate_answer(self, query: str, answer: str, histo: str, context: str,language : str) -> str:
+        """provides the final answer in French based on the initial query and the answer in english"""
 
         def _cut_unfinished_sentence(s: str):
             return '.'.join(s.split('.')[:-1])
 
-        template = (f"Your task consists in answering to the query from users in {language} "
+        template = (f"Your task consists in translating the answer in {language}, if its not already the case, to the query "
                     f"delimited by triple backticks: ```{query}``` \\n"
                     f"You are given the answer in {language} delimited by triple backticks: ```{answer}```"
                     f"\\n You don't add new content to the answer but: "
@@ -48,7 +48,6 @@ class LlmAgent:
                     f"```{context}```"
                     f"\\n 2 You are consistent and avoid redundancies with the rest of the initial"
                     f" conversation delimited by triple backticks: ```{histo}```"
-                    f" If the langage of the answer is the same as the langage of the query, you shall be concise but keep the meaning of the answer"
                     )
 
         p = self.llm(template)
@@ -59,7 +58,7 @@ class LlmAgent:
         """detects the language"""
         template = (f"Your task consists in detecting the language of the following text delimited by triple backticks: "
                     f"```{text}```"
-                    f"Your answer shall be the two letters code of the language"
+                    f" Your answer shall be the two letters code of the language"
                     )
         p = self.llm(template)
         return p