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9d84a1e 2fb3630 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | from model import get_gemma
from rag_utils import generate_context
def generate_response(history=[], temperature: float=0.0, top_k=None, top_p=None):
gemma_model = get_gemma(temperature=temperature, top_k=top_k, top_p=top_p)
response = gemma_model.invoke(history).content
return response
def generate_RAG_response(query: str, file_path, history=[]):
gemma_model = get_gemma()
query, context = generate_context(query, file_path)
if len(history) > 1:
prompt = history[:-1]
prompt = prompt.append({"role" : "user", "content" : f"INSTRUCTION: Answer the query with given context in mind.\nQUERY: {query}\n\nCONTEXT : {context}"})
else:
prompt = [{"role" : "user", "content" : f"INSTRUCTION: Answer the query with given context in mind.\nQUERY: {query}\n\nCONTEXT : {context}"}]
response = gemma_model.invoke(history).content
return response |