diff --git a/ai_ta_backend/main.py b/ai_ta_backend/main.py index ef311b6c..77bfeea5 100644 --- a/ai_ta_backend/main.py +++ b/ai_ta_backend/main.py @@ -1,5 +1,4 @@ import os -import threading import time from typing import List @@ -112,10 +111,7 @@ def getTopContexts(service: RetrievalService) -> Response: f"Missing one or more required parameters: 'search_query' and 'course_name' must be provided. Search query: `{search_query}`, Course name: `{course_name}`" ) - print("NUM ACTIVE THREADS (top of getTopContexts):", threading.active_count()) - found_documents = service.getTopContexts(search_query, course_name, token_limit) - print("NUM ACTIVE THREADS (after instantiating Ingest() class in getTopContexts):", threading.active_count()) response = jsonify(found_documents) response.headers.add('Access-Control-Allow-Origin', '*') diff --git a/ai_ta_backend/service/export_service.py b/ai_ta_backend/service/export_service.py index 3e4925af..5253d0c0 100644 --- a/ai_ta_backend/service/export_service.py +++ b/ai_ta_backend/service/export_service.py @@ -42,9 +42,8 @@ def export_documents_json(self, course_name: str, from_date='', to_date=''): s3_filepath = f"courses/{course_name}/{filename}" # background task of downloading data - map it with above ID executor = ProcessPoolExecutor() - executor.submit(export_data_in_bg, response, "documents", course_name, s3_filepath) - return {"response": 'Download from S3', - "s3_path": s3_filepath} + executor.submit(self.export_data_in_bg, response, "documents", course_name, s3_filepath) + return {"response": 'Download from S3', "s3_path": s3_filepath} else: # Fetch data @@ -96,7 +95,113 @@ def export_documents_json(self, course_name: str, from_date='', to_date=''): else: return {"response": "No data found between the given dates."} - + def export_data_in_bg(self, response, download_type, course_name, s3_path): + """ + This function is called in export_documents_csv() to upload the documents to S3. + 1. download the documents in batches of 100 and upload them to S3. + 2. generate a pre-signed URL for the S3 file. + 3. send an email to the course admins with the pre-signed URL. + + Args: + response (dict): The response from the Supabase query. + download_type (str): The type of download - 'documents' or 'conversations'. + course_name (str): The name of the course. + s3_path (str): The S3 path where the file will be uploaded. + """ + total_doc_count = response.count + first_id = response.data[0]['id'] + print("total_doc_count: ", total_doc_count) + print("pre-defined s3_path: ", s3_path) + + curr_doc_count = 0 + filename = s3_path.split('/')[-1].split('.')[0] + '.json' + file_path = os.path.join(os.getcwd(), filename) + + # download data in batches of 100 + while curr_doc_count < total_doc_count: + print("Fetching data from id: ", first_id) + response = self.sql.getAllFromTableForDownloadType(course_name, download_type, first_id) + df = pd.DataFrame(response.data) + curr_doc_count += len(response.data) + + # writing to file + if not os.path.isfile(file_path): + df.to_json(file_path, orient='records') + else: + df.to_json(file_path, orient='records', lines=True, mode='a') + + if len(response.data) > 0: + first_id = response.data[-1]['id'] + 1 + + # zip file + zip_filename = filename.split('.')[0] + '.zip' + zip_file_path = os.path.join(os.getcwd(), zip_filename) + + with zipfile.ZipFile(zip_file_path, 'w', compression=zipfile.ZIP_DEFLATED) as zipf: + zipf.write(file_path, filename) + + print("zip file created: ", zip_file_path) + + try: + # upload to S3 + + #s3_file = f"courses/{course_name}/exports/{os.path.basename(zip_file_path)}" + s3_file = f"courses/{course_name}/{os.path.basename(zip_file_path)}" + self.s3.upload_file(zip_file_path, os.environ['S3_BUCKET_NAME'], s3_file) + + # remove local files + os.remove(file_path) + os.remove(zip_file_path) + + print("file uploaded to s3: ", s3_file) + + # generate presigned URL + s3_url = self.s3.generatePresignedUrl('get_object', os.environ['S3_BUCKET_NAME'], s3_path, 3600) + + # get admin email IDs + headers = { + "Authorization": f"Bearer {os.environ['VERCEL_READ_ONLY_API_KEY']}", + "Content-Type": "application/json" + } + + hget_url = str(os.environ['VERCEL_BASE_URL']) + "course_metadatas/" + course_name + response = requests.get(hget_url, headers=headers) + course_metadata = response.json() + course_metadata = json.loads(course_metadata['result']) + admin_emails = course_metadata['course_admins'] + bcc_emails = [] + + # check for Kastan's email and move to bcc + if 'kvday2@illinois.edu' in admin_emails: + admin_emails.remove('kvday2@illinois.edu') + bcc_emails.append('kvday2@illinois.edu') + + # add course owner email to admin_emails + admin_emails.append(course_metadata['course_owner']) + admin_emails = list(set(admin_emails)) + print("admin_emails: ", admin_emails) + print("bcc_emails: ", bcc_emails) + + # add a check for emails, don't send email if no admin emails + if len(admin_emails) == 0: + return "No admin emails found. Email not sent." + + # send email to admins + if download_type == "documents": + subject = "UIUC.chat Documents Export Complete for " + course_name + elif download_type == "conversations": + subject = "UIUC.chat Conversation History Export Complete for " + course_name + else: + subject = "UIUC.chat Export Complete for " + course_name + body_text = "The data export for " + course_name + " is complete.\n\nYou can download the file from the following link: \n\n" + s3_url + "\n\nThis link will expire in 48 hours." + email_status = send_email(subject, body_text, os.environ['EMAIL_SENDER'], admin_emails, bcc_emails) + print("email_status: ", email_status) + + return "File uploaded to S3. Email sent to admins." + + except Exception as e: + print(e) + return "Error: " + str(e) def export_convo_history_json(self, course_name: str, from_date='', to_date=''): """ @@ -169,6 +274,7 @@ def export_convo_history_json(self, course_name: str, from_date='', to_date=''): # Encountered pickling error while running the background task. So, moved the function outside the class. + def export_data_in_bg(response, download_type, course_name, s3_path): """ This function is called in export_documents_csv() to upload the documents to S3. @@ -184,7 +290,7 @@ def export_data_in_bg(response, download_type, course_name, s3_path): """ s3 = AWSStorage() sql = SQLDatabase() - + total_doc_count = response.count first_id = response.data[0]['id'] print("total_doc_count: ", total_doc_count) @@ -203,7 +309,7 @@ def export_data_in_bg(response, download_type, course_name, s3_path): # writing to file if not os.path.isfile(file_path): - df.to_json(file_path, orient='records', lines=True) + df.to_json(file_path, orient='records', lines=True) else: df.to_json(file_path, orient='records', lines=True, mode='a') @@ -237,10 +343,7 @@ def export_data_in_bg(response, download_type, course_name, s3_path): #print("s3_url: ", s3_url) # get admin email IDs - headers = { - "Authorization": f"Bearer {os.environ['VERCEL_READ_ONLY_API_KEY']}", - "Content-Type": "application/json" - } + headers = {"Authorization": f"Bearer {os.environ['VERCEL_READ_ONLY_API_KEY']}", "Content-Type": "application/json"} hget_url = str(os.environ['VERCEL_BASE_URL']) + "course_metadatas/" + course_name response = requests.get(hget_url, headers=headers) @@ -274,4 +377,4 @@ def export_data_in_bg(response, download_type, course_name, s3_path): except Exception as e: print(e) - return "Error: " + str(e) \ No newline at end of file + return "Error: " + str(e) diff --git a/ai_ta_backend/utils/filtering_contexts.py b/ai_ta_backend/utils/filtering_contexts.py index 476df3d0..380dd946 100644 --- a/ai_ta_backend/utils/filtering_contexts.py +++ b/ai_ta_backend/utils/filtering_contexts.py @@ -137,8 +137,6 @@ # langsmith_prompt_obj = filter_unrelated_contexts_zephyr # posthog = Posthog(sync_mode=True, project_api_key=os.environ['POSTHOG_API_KEY'], host='https://app.posthog.com') -# print("NUM ACTIVE THREADS (top of filtering_contexts):", threading.active_count()) - # max_concurrency = min(100, len(contexts)) # print("max_concurrency is max of 100, or len(contexts), whichever is less ---- Max concurrency:", max_concurrency) # print("Num contexts to filter:", len(contexts)) @@ -153,14 +151,12 @@ # timeout=timeout, # fetch_local=False) -# print("NUM ACTIVE THREADS (before cleanup filtering_contexts):", threading.active_count()) # # Cleanup # for task in in_progress: # ray.cancel(task) # results = ray.get(done_tasks) -# print("NUM ACTIVE THREADS (before kill filtering_contexts):", threading.active_count()) +# print(" THREADS (before kill filtering_contexts):", threading.active_count()) # ray.kill(actor) -# print("NUM ACTIVE THREADS (after kill filtering_contexts):", threading.active_count()) # best_contexts_to_keep = [ # r['context'] for r in results if r and 'context' in r and 'completion' in r and parse_result(r['completion'])