Hello,
Trying to implement a way to question PDFs locally and get answers only based on data from the docs. I have already find a way to embed the data into a vector db (using Chroma) and then retrieve with a "similarity_search" the most relevant data from our query into the doc. I would like now to find a way to give to my model this context to generate answer on it, maybe by using a prompt into the generate call ?
query = "What is the date of the start of the battle ?"
docs = db.similarity_search(query)
print(docs[0].page_content)
llm = Ollama(
model=llm_model_name,
callbacks=[StreamingStdOutCallbackHandler()],
)
my_retriever = db.as_retriever(search_kwargs={"k": 8})
response = ollama.generate(
"model": llm_model_name,
)```
Thank you for your help !
Hello, Trying to implement a way to question PDFs locally and get answers only based on data from the docs. I have already find a way to embed the data into a vector db (using Chroma) and then retrieve with a "similarity_search" the most relevant data from our query into the doc. I would like now to find a way to give to my model this context to generate answer on it, maybe by using a prompt into the generate call ?