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import tempfile, os | |
from pdfs.serializer import PDFUploadSerializer | |
from setup.environment import default_model | |
from drf_spectacular.utils import extend_schema | |
from rest_framework.decorators import api_view, parser_classes | |
from rest_framework.parsers import MultiPartParser | |
from rest_framework.response import Response | |
from _utils.main import get_llm_answer | |
def getPDF(request): | |
if request.method == "POST": | |
serializer = PDFUploadSerializer(data=request.data) | |
if serializer.is_valid(raise_exception=True): | |
listaPDFs = [] | |
print('\n\n') | |
data = request.data | |
print('data: ', data) | |
embedding = serializer.validated_data.get("embedding", "gpt") | |
model = serializer.validated_data.get("model", default_model) | |
# pdf_file = serializer.validated_data['file'] | |
for file in serializer.validated_data['files']: | |
print("file: ", file) | |
file.seek(0) | |
# Create a temporary file to save the uploaded PDF | |
with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as temp_file: | |
# Write the uploaded file content to the temporary file | |
for chunk in file.chunks(): | |
temp_file.write(chunk) | |
temp_file_path = temp_file.name # Get the path of the temporary file | |
listaPDFs.append(temp_file_path) | |
# print('temp_file_path: ', temp_file_path) | |
print('listaPDFs: ', listaPDFs) | |
resposta_llm = None | |
# resposta_llm = get_llm_answer(data["system_prompt"], data["user_message"], temp_file_path, model=model, embedding=embedding) | |
resposta_llm = get_llm_answer(data["system_prompt"], data["user_message"], listaPDFs, model=model, embedding=embedding) | |
for file in listaPDFs: | |
os.remove(file) | |
# os.remove(temp_file_path) | |
return Response({ | |
"Resposta": resposta_llm | |
}) |