bug fix

app.py

@@ -10,7 +10,6 @@ from langchain.schema.runnable import RunnablePassthrough
 from langchain_openai import ChatOpenAI
 from langchain.schema.runnable.config import RunnableConfig
 from langchain_core.output_parsers import StrOutputParser
-from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.document_loaders import UnstructuredPDFLoader
 
 
@@ -57,36 +56,9 @@ text_splitter = RecursiveCharacterTextSplitter(
     ],
 )
 
-# bnb_config = BitsAndBytesConfig(
-#     load_in_4bit=True,
-#     bnb_4bit_quant_type="nf4",
-#     bnb_double_quant=True,
-#     bnb_4bit_compute_dtype=torch.float16,
-# )
-
-
-# tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct", 
-#                                           trust_remote_code=True,
-#                                           quantization_config=bnb_config,
-#                                           attn_implementation='eager',
-#                                           device_map='auto',)
-# model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct", trust_remote_code=True)
-
-
-# hf = HuggingFacePipeline.from_model_id(
-#     model_id="microsoft/Phi-3-mini-4k-instruct",
-#     task="text-generation",
-#     device_map="auto",
-#     pipeline_kwargs={"max_new_tokens": 10},
-# )
 
-
-# loader = PyPDFLoader("https://w2l.sbst.dk/file/502104/br_femogfirs.pdf")
 loader = UnstructuredPDFLoader("br_femogfirs.pdf",  strategy="fast")
 data = loader.load_and_split(text_splitter)
-# data = loader.load()
-
-
 
 rag_prompt = ChatPromptTemplate.from_template(RAG_PROMPT)
 
@@ -107,13 +79,12 @@ async def main():
             vector_store = Pinecone.from_documents(data, embedding_model, index_name="bygnings-regl-rag-1")
             retriever = vector_store.as_retriever()
 
-
             mecanic_qa_chain = (
             {"context": itemgetter("question") | retriever, "question": itemgetter("question")}
             | RunnablePassthrough.assign(context=itemgetter("context"))
             | rag_prompt | model | StrOutputParser())
 
-    cl.user_session.set("runnable", mecanic_qa_chain)
+            cl.user_session.set("runnable", mecanic_qa_chain)