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from fastapi import Body, Request, HTTPException, status | |
from fastapi.encoders import jsonable_encoder | |
import sys | |
from ..models.calls import UpdateCall, UserCall, UserCaptions | |
from ..operations.users import * | |
from openai import OpenAI | |
from time import sleep | |
import os | |
from dotenv import dotenv_values | |
# Used within calls to create call record in main.py | |
def create_calls(collection, user: UserCall = Body(...)): | |
calls = jsonable_encoder(user) | |
new_calls = collection.insert_one(calls) | |
created_calls = collection.find_one({"_id": new_calls.inserted_id}) | |
return created_calls | |
def list_calls(collection, limit: int): | |
try: | |
calls = collection.find(limit = limit) | |
return list(calls) | |
except: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"No existing call records yet.") | |
'''Finding calls based on call id''' | |
def find_call(collection, call_id: str): | |
user_calls = collection.find_one({"call_id": call_id}) | |
if user_calls is not None: | |
return user_calls | |
else: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call with ID: '{call_id}' not found.") | |
'''Finding calls based on user id''' | |
def find_user_calls(collection, user_id: str): | |
user_calls = list(collection.find({"$or": [{"caller_id": user_id}, {"callee_id": user_id}]})) # match on caller or callee ID | |
if len(user_calls): | |
return user_calls | |
else: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"User with ID: '{user_id}' has no calls yet.") | |
'''Finding calls based on key terms list''' | |
def list_transcripts_by_key_terms(collection, key_terms_list: list[str] = Body(...)): | |
key_terms_list = jsonable_encoder(key_terms_list) | |
call_records = list(collection.find({"key_terms": {"$in": key_terms_list}}, {'_id': 0})) # exclude returning ObjectID in find() | |
# Check if any call records were returned | |
if len(call_records): | |
return call_records | |
else: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call with key terms: '{key_terms_list}' not found!") | |
'''Finding calls based on date ranges''' | |
def list_transcripts_by_dates(collection, start_date: str, end_date: str): | |
# print(start_date, end_date) | |
# Convert strings to date string in YYYY-MM-ddT00:00:00 format | |
start_date = f'{start_date}T00:00:00' | |
end_date = f'{end_date}T00:00:00' | |
call_records = list(collection.find({"date":{"$gte": start_date, "$lte": end_date}})) | |
if len(call_records): | |
return call_records | |
else: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call with creation date between: '{start_date} - {end_date}' not found!") | |
'''Finding calls based on call lengths''' | |
def list_transcripts_by_duration(collection, min_len: int, max_len: int): | |
call_records = list(collection.find({"duration":{"$gte": min_len, "$lte": max_len}})) | |
if len(call_records): | |
return call_records | |
else: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call with duration between: '{min_len} - {max_len}' milliseconds not found!") | |
def update_calls(collection, call_id: str, calls: UpdateCall = Body(...)): | |
# calls = {k: v for k, v in calls.model_dump().items() if v is not None} #loop in the dict | |
calls = {k: v for k, v in calls if v is not None} #loop in the dict | |
print(calls) | |
if len(calls) >= 1: | |
update_result = collection.update_one({"call_id": call_id}, {"$set": calls}) | |
if update_result.modified_count == 0: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call not updated!") | |
if (existing_item := collection.find_one({"call_id": call_id})) is not None: | |
return existing_item | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call not found!") | |
def update_captions(call_collection, user_collection, call_id: str, captions: UserCaptions = Body(...)): | |
# captions = {k: v for k, v in calls.model_dump().items() if v is not None} | |
captions = {k: v for k, v in captions if v is not None} | |
print(captions) | |
# index user_id from caption object | |
userID = captions["author_id"] | |
print(userID) | |
# use user id to get user name | |
username = find_name_from_id(user_collection, userID) | |
print(username) | |
# add user name to captions json/object | |
captions["author_username"] = username | |
print(captions) | |
if len(captions) >= 1: | |
update_result = call_collection.update_one({"call_id": call_id}, | |
{"$push": {"captions": captions}}) | |
if update_result.modified_count == 0: | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Captions not updated!") | |
if (existing_item := call_collection.find_one({"call_id": call_id})) is not None: | |
return existing_item | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Captions not found!") | |
def delete_calls(collection, call_id: str): | |
deleted_calls = collection.delete_one({"call_id": call_id}) | |
if deleted_calls.deleted_count == 1: | |
return f"Call deleted sucessfully!" | |
raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Call not found!") | |
def get_caption_text(collection, call_id): | |
call_record = find_call((collection), call_id) | |
try: # Check if call has any captions first | |
caption_records = call_record['captions'] | |
except KeyError: | |
return None | |
# iterate through caption embedded document and store original text | |
combined_text = [caption['original_text'] for caption in caption_records] | |
return " ".join(combined_text) | |
# standard exact match based full text search | |
def full_text_search(collection, query): | |
# drop any existing indexes and create new one | |
collection.drop_indexes() | |
collection.create_index([('captions.original_text', 'text'), ('captions.tranlated_text', 'text')], | |
name='captions') | |
# print(collection.index_information()) | |
results = list(collection.find({"$text": {"$search": query}})) | |
return results | |
def summarise(collection, call_id): | |
# client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY")) | |
config = dotenv_values(".env") | |
client = OpenAI(api_key=config["OPENAI_API_KEY"]) | |
# get caption text using call_id | |
caption_text = get_caption_text(collection, call_id) | |
chat_completion = client.chat.completions.create( | |
messages=[ | |
{ | |
"role": "user", | |
"content": f"The following is an extract from a call transcript. Rewrite this as a structured, clear summary. \ | |
\n\Call Transcript Extract: \"\"\"\n{caption_text}\n\"\"\"\n" | |
} | |
], | |
model="gpt-3.5-turbo", | |
) | |
result = chat_completion.choices[0].message.content.removeprefix("Summary:\n") | |
return result | |