Merge pull request #49 from almutareb/26-add-a-function-for-query-rewriting

config.py

@@ -8,15 +8,18 @@ load_dotenv()
 SQLITE_FILE_NAME = os.getenv('SOURCES_CACHE')
 PERSIST_DIRECTORY = os.getenv('VECTOR_DATABASE_LOCATION')
 EMBEDDING_MODEL = os.getenv("EMBEDDING_MODEL")
-SECONDARY_LLM_MODEL = os.getenv("SECONDARY_LLM_MODEL")
+SEVEN_B_LLM_MODEL = os.getenv("SEVEN_B_LLM_MODEL")
 
 
 db = DataBaseHandler()
 
 db.create_all_tables()
 
-SECONDARY_LLM = HuggingFaceEndpoint(
-        repo_id=SECONDARY_LLM_MODEL, 
+# This model is used for task that a larger model may not need to do
+# as of currently we have been getting MODEL OVERLOADED errors
+# with huggingface
+SEVEN_B_LLM_MODEL = HuggingFaceEndpoint(
+        repo_id=SEVEN_B_LLM_MODEL, 
         temperature=0.1,         # Controls randomness in response generation (lower value means less random)
         max_new_tokens=1024,     # Maximum number of new tokens to generate in responses
         repetition_penalty=1.2,  # Penalty for repeating the same words (higher value increases penalty)

example.env

@@ -25,3 +25,5 @@ EMBEDDING_MODEL="sentence-transformers/distiluse-base-multilingual-cased-v2"
 #EMBEDDING_MODEL="sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2" 
 LLM_MODEL="mistralai/Mixtral-8x7B-Instruct-v0.1"
 LLM_MODEL_ARGS=
+
+SEVEN_B_LLM_MODEL="mistralai/Mistral-7B-Instruct-v0.3"

rag_app/chains/__init__.py

@@ -1,2 +1,3 @@
 from rag_app.chains.user_response_sentiment_chain import user_response_sentiment_prompt
-from rag_app.chains.generate_document_summary import generate_document_summary_prompt
+from rag_app.chains.generate_document_summary import generate_document_summary_prompt
+from rag_app.chains.query_rewritten_chain import query_rewritting_prompt

rag_app/chains/query_rewritten_chain.py

@@ -0,0 +1,16 @@
+from langchain_core.prompts import PromptTemplate
+
+
+query_rewritting_template = """ 
+You will be given a query from a user
+=================
+{user_query} 
+====================
+
+You must improve the query to optimize the result
+  
+
+"""
+
+query_rewritting_prompt = PromptTemplate.from_template(query_rewritting_template)
+

rag_app/knowledge_base/utils.py

@@ -1,6 +1,6 @@
 from langchain_core.documents import Document
 from chains import generate_document_summary_prompt
-from config import SECONDARY_LLM
+from config import SEVEN_B_LLM_MODEL
 
 
 def generate_document_summaries(
@@ -27,7 +27,7 @@ def generate_document_summaries(
     
     for doc in new_docs:
         
-        genrate_summary_chain = generate_document_summary_prompt | SECONDARY_LLM
+        genrate_summary_chain = generate_document_summary_prompt | SEVEN_B_LLM_MODEL
         summary = genrate_summary_chain.invoke(
             {"document":str(doc.metadata)}
         )        

requirements.txt

@@ -1,6 +1,6 @@
 langchain
 langchain-community 
-langchain-HuggingFace
+langchain-huggingface
 langchain-text-splitters
 langchain_google_community
 beautifulsoup4 
@@ -15,5 +15,4 @@ gradio
 boto3
 rich
 sqlmodel
-python-dotenv
-langchain_huggingface
+python-dotenv