add property source and id to respose

Dockerfile

@@ -2,7 +2,6 @@ FROM python:3.10
 
 WORKDIR /tiledesk-llm
 
-COPY .environ /tiledesk-llm/.environ
 COPY log_conf.yaml /tiledesk-llm/log_conf.yaml
 COPY pyproject.toml /tiledesk-llm/pyproject.toml
 COPY ./tilellm /tiledesk-llm/tilellm
@@ -19,5 +18,5 @@ EXPOSE 8000
 COPY entrypoint.sh /tiledesk-llm/entrypoint.sh
 RUN chmod +x /tiledesk-llm/entrypoint.sh
 
-ENTRYPOINT ["/tiledesk-llm/entrypoint.sh", "--redis_url", "redis://redis:6379/0"]
+ENTRYPOINT ["/tiledesk-llm/entrypoint.sh"]
 

tilellm/__main__.py

@@ -151,6 +151,7 @@ async def create_scrape_item_main(item: ItemSingle, redis_client: aioredis.clien
 
 @app.post("/api/qa")
 async def post_ask_with_memory_main(question_answer:QuestionAnswer ):
+    print(question_answer)
     logger.debug(question_answer) 
     result = ask_with_memory(question_answer)
     logger.debug(result)

tilellm/controller/openai_controller.py

@@ -1,3 +1,4 @@
+import fastapi
 from langchain.chains import ConversationalRetrievalChain, LLMChain # Per la conversazione va usata questa classe
 from langchain_core.prompts import PromptTemplate, SystemMessagePromptTemplate
 from langchain_openai import ChatOpenAI
@@ -15,7 +16,6 @@ def ask_with_memory(question_answer):
 
     try:
         logger.info(question_answer)
-
         #question = str
         #namespace: str
         #gptkey: str
@@ -50,9 +50,10 @@ def ask_with_memory(question_answer):
 
         retriever = vector_store.as_retriever(search_type='similarity', search_kwargs={'k': question_answer.top_k, 'namespace':question_answer.namespace})
 
-        mydocs = retriever.get_relevant_documents( question_answer.question)
+        #mydocs = retriever.get_relevant_documents( question_answer.question)
         #from pprint import pprint
-        #pprint(mydocs)
+        #pprint(len(mydocs))
+
 
 
 
@@ -89,7 +90,7 @@ def ask_with_memory(question_answer):
             crc = ConversationalRetrievalChain.from_llm(llm=llm,
                                                         retriever=retriever,
                                                         return_source_documents=True)
-        
+
             result = crc.invoke({'question': question_answer.question, 'chat_history': question_answer_list})
 
         docs = result["source_documents"]
@@ -102,6 +103,8 @@ def ask_with_memory(question_answer):
 
         ids = list(set(ids))
         sources = list(set(sources))
+        source = " ".join(sources)
+        id = ids[0]
 
         logger.info(result)
 
@@ -116,17 +119,19 @@ def ask_with_memory(question_answer):
 
         result_to_return = RetrievalResult(
             answer=result['answer'],
-            sources=sources,
             namespace=question_answer.namespace,
+            sources=sources,
             ids=ids,
+            source= source,
+            id=id,
             prompt_token_size=prompt_token_size,
             success=success,
             error_message = None, 
             chat_history_dict = chat_history_dict
 
         )
 
-
+        return result_to_return.dict()
     except Exception as e:
         import traceback 
         traceback.print_exc() 
@@ -143,10 +148,9 @@ def ask_with_memory(question_answer):
             chat_history_dict = chat_history_dict
 
         )
+        raise fastapi.exceptions.HTTPException(status_code=400, detail=result_to_return.model_dump())
+
 
-    #print("Prompt tokens:", openai_callback_handler.prompt_tokens)
-    #print("Completion tokens:", openai_callback_handler.total_cost)
-    return result_to_return.dict()
 
 def add_pc_item(item):
     return pinecone_add_item(item)

tilellm/models/item_model.py

@@ -73,6 +73,8 @@ def top_k_range(cls, v):
 class RetrievalResult(BaseModel):
     answer:str = Field(default="No answer")
     sources: Optional[List[str]]|None =None
+    source:str |None= None
+    id:str |None= None
     namespace: str
     ids: Optional[List[str]]|None =None
     prompt_token_size: int = Field(default=0)

tilellm/shared/const.py

@@ -7,10 +7,12 @@
 PINECONE_API_KEY = None
 PINECONE_INDEX = None
 PINECONE_TEXT_KEY = None
+
 def populate_constant():
     global PINECONE_API_KEY, PINECONE_INDEX, PINECONE_TEXT_KEY
     PINECONE_API_KEY = os.environ.get("PINECONE_API_KEY")
     PINECONE_INDEX = os.environ.get("PINECONE_INDEX")
     PINECONE_TEXT_KEY = os.environ.get("PINECONE_TEXT_KEY")
 
 
+