diff --git a/.changeset/nice-coins-mix.md b/.changeset/nice-coins-mix.md new file mode 100644 index 0000000000..b84112ca18 --- /dev/null +++ b/.changeset/nice-coins-mix.md @@ -0,0 +1,6 @@ +--- +"infrastructure": minor +"chatbot": minor +--- + +Implemented llm monitoring with LangFuse diff --git a/.gitmodules b/.gitmodules index 871ef6b87b..3e82eeea1e 100644 --- a/.gitmodules +++ b/.gitmodules @@ -1,3 +1,3 @@ [submodule "apps/nextjs-website/.tmp-docs"] path = apps/nextjs-website/.tmp-docs - url = https://github.com/pagopa/devportal-docs.git \ No newline at end of file + url = https://github.com/pagopa/devportal-docs.git diff --git a/apps/chatbot/.dockerignore b/apps/chatbot/.dockerignore index c694205073..efb4c09adc 100644 --- a/apps/chatbot/.dockerignore +++ b/apps/chatbot/.dockerignore @@ -2,3 +2,4 @@ build-devp .pytest_cache load-test +*.ipynb \ No newline at end of file diff --git a/apps/chatbot/.env.example b/apps/chatbot/.env.example index 7006ba44f8..2ca70aad6c 100644 --- a/apps/chatbot/.env.example +++ b/apps/chatbot/.env.example @@ -1,31 +1,66 @@ -environment=local -CORS_DOMAINS=["*"] -PYTHONPATH=app-path -LOG_LEVEL=DEBUG +AUTH_COGNITO_ALLOW_ACCOUNT_LINKING=true +AUTH_COGNITO_CLIENT_ID=... +AUTH_COGNITO_CLIENT_SECRET= +AUTH_COGNITO_ISSUER=https://cognito-idp.eu-south-1.amazonaws.com/eu-south-1_xxxxxxxx +AUTH_DISABLE_SIGNUP=false +AUTH_DISABLE_USERNAME_PASSWORD=true CHB_AWS_ACCESS_KEY_ID=... -CHB_AWS_SECRET_ACCESS_KEY=... +CHB_AWS_BEDROCK_EMBED_REGION=eu-central-1 +CHB_AWS_BEDROCK_LLM_REGION=eu-west-3 CHB_AWS_DEFAULT_REGION=eu-south-1 -CHB_AWS_BEDROCK_REGION=eu-west-3 CHB_AWS_GUARDRAIL_ID=... CHB_AWS_GUARDRAIL_VERSION=... -CHB_REDIS_URL=... -CHB_WEBSITE_URL=... -CHB_REDIS_INDEX_NAME=... -CHB_LLAMAINDEX_INDEX_ID=... +CHB_AWS_SECRET_ACCESS_KEY=... CHB_DOCUMENTATION_DIR=... -CHB_USE_PRESIDIO=... -CHB_GOOGLE_API_KEY=... -CHB_PROVIDER=... -CHB_MODEL_ID=... -CHB_MODEL_TEMPERATURE=... -CHB_MODEL_MAXTOKENS=... +CHB_DYNAMODB_URL=http://locahost:8080 CHB_EMBED_MODEL_ID=... -CHB_ENGINE_SIMILARITY_TOPK=... CHB_ENGINE_SIMILARITY_CUTOFF=... +CHB_ENGINE_SIMILARITY_TOPK=... CHB_ENGINE_USE_ASYNC=True CHB_ENGINE_USE_STREAMING=... -CHB_ENGINE_USE_CHAT_ENGINE=... +CHB_GOOGLE_API_KEY=... +CHB_LANGFUSE_HOST=http://localhost:3000 +CHB_LANGFUSE_PUBLIC_KEY=/nonexistent/ssmpath +CHB_LANGFUSE_SECRET_KEY=/nonexistent/ssmpath +CHB_LLAMAINDEX_INDEX_ID=... +CHB_MODEL_ID=... +CHB_MODEL_MAXTOKENS=... +CHB_MODEL_TEMPERATURE=... +CHB_PROVIDER=... CHB_QUERY_TABLE_PREFIX=chatbot-local -CHB_DYNAMODB_URL=http://locahost:8080 -CHB_USE_PRESIDIO=True +CHB_REDIS_INDEX_NAME=... +CHB_REDIS_URL=... CHB_SESSION_MAX_DURATION_DAYS=1 +CHB_USE_CHAT_ENGINE=True +CHB_USE_PRESIDIO=True +CHB_WEBSITE_URL=... +CORS_DOMAINS=["*"] +ENCRYPTION_KEY=0000000000000000000000000000000000000000000000000000000000000000 +environment=local +LAMBDA_TASK_ROOT=app-dir +LANGFUSE_ENABLE_EXPERIMENTAL_FEATURES=false +LANGFUSE_INIT_ORG_ID=... +LANGFUSE_INIT_ORG_NAME=... +LANGFUSE_INIT_PROJECT_ID=monitor-123 +LANGFUSE_INIT_PROJECT_NAME=Monitor +LANGFUSE_INIT_PROJECT_PUBLIC_KEY=pk-xxx +LANGFUSE_INIT_PROJECT_SECRET_KEY=sk-xxx +LANGFUSE_INIT_USER_EMAIL=... +LANGFUSE_INIT_USER_NAME=... +LANGFUSE_INIT_USER_PASSWORD=... +LANGFUSE_TAG=development +LANGFUSE_USER_EMAIL=user@example.com +LANGFUSE_USER_NAME=User +LANGFUSE_USER_PASSWORD=... +LOG_LEVEL=DEBUG +NEXTAUTH_SECRET=mysecret +NEXTAUTH_URL=http://localhost:3001 +POSTGRES_DB=postgres +POSTGRES_HOST=localhost +POSTGRES_PASSWORD=postgres +POSTGRES_PORT=5432 +POSTGRES_USER=postgres +DATABASE_URL=postgresql://${POSTGRES_USER}:${POSTGRES_PASSWORD}@${POSTGRES_HOST}:${POSTGRES_PORT}/${POSTGRES_DB} +PYTHONPATH=app-path +SALT=mysalt +TELEMETRY_ENABLED=true diff --git a/apps/chatbot/README.md b/apps/chatbot/README.md index 27e5b40194..1d212ccb90 100644 --- a/apps/chatbot/README.md +++ b/apps/chatbot/README.md @@ -7,10 +7,16 @@ Even though the provider is the Google one, we stored its API key in AWS. So, be The Retrieval-Augmented Generation (RAG) was implemented using [llama-index](https://docs.llamaindex.ai/en/stable/). All the parameters and prompts used are stored in `config`. +The monitoring is done using [Langfuse](https://langfuse.com/) deployed on AWS. + ## Environment Variables Create a `.env` file inside this folder and store the environment variables listed in `.env.example`. +cp .env.example .env + +Note that the envirables inside `.env` file should be pointing to the AWS infrastructure.s + ## Virtual environment Before creating your virtual environment, install [Miniconda](https://docs.anaconda.com/miniconda/#quick-command-line-install) and [Poetry](https://python-poetry.org/docs/main#installation) on your device. @@ -36,30 +42,44 @@ In this way, `PYTHONPATH` points to where the Python packages and modules are, n To reach the remote redis instance, it is necessary to open a tunnel: -``` ./scripts/redis-tunnel.sh -``` Verify that the HTML files that compose the Developer Portal documentation exist in a directory. Otherwise create the documentation. Once you have the documentation directory ready, put its path in `params` and, in the end, create the vector index doing: -``` python src/modules/create_vector_index.py --params config/params.yaml -``` This script reads the documentation, split it into chucks with gerarchical organization, and stores it on Redis. Check out the params in order to store your vector index accordingly. -## test +## Test + +In order to test the chatbot and its APIs, run: + + pytest + +For more details, read [TESTBOOK.md](https://github.com/pagopa/developer-portal/blob/main/apps/chatbot/TESTBOOK.md). + +## Docker + +In order to run the chatbot locally for the first time, you need to: + +- install [Docker Compose](https://docs.docker.com/compose/install/), +- create `.env.local` file running: + + cp .env.example .env.local + + and fill it in, + +- run the following bash scripts: -``` -pytest -``` + ./docker/docker-compose-build-local.sh + ./docker/docker-compose-run-create_index.sh -## Web App +In this way, the docker images are built and the vector index is stored in Redis. - python src/webapp/app.py +Now you can start the API running: -This scripts uses [Gradio](https://www.gradio.app/) framework to lunch a web application at the [default link](http://127.0.0.1:7860) where the user can interact with the chatbot. + ./docker/docker-compose-up-api.sh -Both [`user icon`](https://www.flaticon.com/free-icon/user_1077012) and [`chatbot icon`](https://www.flaticon.com/free-icon/chatbot_8943377) are made by [Freepick](https://www.freepik.com/) and they were downloaded from [Flaticon](https://www.flaticon.com/). +Note that the `docker/compose.yaml` needs `.env.local` file with the correct environment variables. diff --git a/apps/chatbot/TESTBOOK.md b/apps/chatbot/TESTBOOK.md new file mode 100644 index 0000000000..93aeb3f730 --- /dev/null +++ b/apps/chatbot/TESTBOOK.md @@ -0,0 +1,17 @@ +# Testbook + +In order to test the chatbot functions and its APIs, run: + + pytest + +the command test the function explained in the table below. + +| Function | Requirements | Masked Inputs | Description | +| :------------------------------: | :-----------------------: | :---------------------------------: | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------: | +| `test_connection_redis()` | Redis client | None | Check the connection with Redis is up | +| `test_connection_langfuse()` | Langfuse client | None | Check the connection with Langfuse is up | +| `test_cloud_connection()` | AWS or Gemini credentials | LLM and Embedding model ID | Check the models' loading | +| `test_prompt_templates()` | Llama-index | `prompts.yaml` | Check the prompts have the same variables of the prompts templates | +| `test_pii_mask()` | Presidio | a string to mask | Check that Presidio works as expected | +| `test_messages_to_chathistory()` | Llama-index | chat history from the local storage | Check the write functioning of creating a chat history in Llama-index | +| `test_chat_generation()` | Llama-index | two queries | Check the chatbot generation given a query, then checks again its functioning generating a new answer usinng a second query and the previous interaction as chat history | diff --git a/apps/chatbot/config/params.yaml b/apps/chatbot/config/params.yaml index 656ed28107..58f14b2f1d 100644 --- a/apps/chatbot/config/params.yaml +++ b/apps/chatbot/config/params.yaml @@ -52,6 +52,8 @@ config_presidio: allow_list: - Discovery - discovery + - rispondo + - Rispondo - Rif - SEND - send @@ -61,8 +63,12 @@ config_presidio: - Gpd - STATO - stato - - PagoPA + - PagoPA - pagoPA + - Devportal + - devPortal + - DevPortal + - devportal - pagopa - Pagopa - Firma con IO diff --git a/apps/chatbot/config/prompts.yaml b/apps/chatbot/config/prompts.yaml index 4f51b2043d..57b12c3c10 100644 --- a/apps/chatbot/config/prompts.yaml +++ b/apps/chatbot/config/prompts.yaml @@ -36,12 +36,14 @@ qa_prompt_str: | Task: Given the query: {query_str} Reply according to the `Chatbot Policy` listed above. + If the query is a thank, transform it into a polite and contextually appropriate answer. Answer: refine_prompt_str: | - Given the original answer: {existing_answer}, we have the opportunity to refine it (only if needed) with some more context here below: + Given the original answer: {existing_answer}, + we have the opportunity to refine it (only if needed) with some more context here below: -------------------- {context_msg} -------------------- @@ -53,15 +55,15 @@ refine_prompt_str: | Answer: condense_prompt_str: | - Given a conversation (between Human and Assistant) and a follow up message from Human, rewrite the message to be a standalone question that captures all relevant context from the conversation. - - The standalone question must be in Italian. - - + Given the following chat history between a user and an AI assistant: {chat_history} - - + -------------------- + and a follow up question from user: {question} - - - + -------------------- + Task: + Rephrase the follow up question to be a standalone question. + If the follow up question is a thank, transform it into a polite and contextually appropriate standalone response. + The standalone question or response must be in Italian. + + Standalone question or response: diff --git a/apps/chatbot/docker/app.local.Dockerfile b/apps/chatbot/docker/app.local.Dockerfile index ba490b2572..b2d61ac35e 100644 --- a/apps/chatbot/docker/app.local.Dockerfile +++ b/apps/chatbot/docker/app.local.Dockerfile @@ -19,11 +19,13 @@ RUN pip install --upgrade pip \ && pip install poetry awscli WORKDIR /app -COPY pyproject.toml . -COPY poetry.lock . +COPY ./pyproject.toml . +COPY ./poetry.lock . +COPY ./src ./src +COPY ./config ./config +COPY ./scripts ./scripts + RUN poetry config virtualenvs.create false RUN poetry install -COPY . . - CMD ["fastapi", "dev", "src/app/main.py", "--port", "8080", "--host", "0.0.0.0"] diff --git a/apps/chatbot/docker/compose.test.yaml b/apps/chatbot/docker/compose.test.yaml index b696d9e324..40c242b930 100644 --- a/apps/chatbot/docker/compose.test.yaml +++ b/apps/chatbot/docker/compose.test.yaml @@ -26,13 +26,17 @@ services: - AWS_SECRET_ACCESS_KEY=dummy - AWS_DEFAULT_REGION=local healthcheck: - test: ["CMD-SHELL", '[ "$(curl -s -o /dev/null -I -w ''%{http_code}'' http://localhost:8000)" == "400" ]'] + test: + [ + "CMD-SHELL", + '[ "$(curl -s -o /dev/null -I -w ''%{http_code}'' http://localhost:8000)" == "400" ]', + ] interval: 10s timeout: 10s retries: 10 networks: - ntw - + redis: image: redis/redis-stack:7.2.0-v13 networks: diff --git a/apps/chatbot/docker/compose.yaml b/apps/chatbot/docker/compose.yaml index 7f83597df1..5fdec24110 100644 --- a/apps/chatbot/docker/compose.yaml +++ b/apps/chatbot/docker/compose.yaml @@ -1,9 +1,9 @@ +--- services: api: build: context: .. dockerfile: docker/app.local.Dockerfile - env_file: ../.env.local command: "./scripts/run.local.sh" ports: - "8080:8080" @@ -16,6 +16,25 @@ services: condition: service_started dynamodb: condition: service_started + langfuse: + condition: service_started + env_file: ../.env.local + networks: + - ntw + + postgres: + image: postgres:17.2-alpine + restart: always + healthcheck: + test: ["CMD-SHELL", "pg_isready -U postgres"] + interval: 3s + timeout: 3s + retries: 10 + ports: + - "5432:5432" + volumes: + - postgres_data:/var/lib/postgresql/data + env_file: ../.env.local networks: - ntw @@ -35,6 +54,8 @@ services: ports: - "6379:6379" - "8001:8001" + volumes: + - redis_data:/data networks: - ntw @@ -42,18 +63,36 @@ services: build: context: .. dockerfile: docker/app.local.Dockerfile + command: "python src/modules/create_vector_index.py --params config/params.yaml" ports: - "8080:8080" volumes: - ..:/app - ../../nextjs-website/out:/app/build-devp/out - command: "python src/modules/create_vector_index.py --params config/params.yaml" tty: true depends_on: redis: condition: service_started + env_file: ../.env.local + networks: + - ntw + + langfuse: + image: langfuse/langfuse:2 + depends_on: + postgres: + condition: service_healthy + ports: + - "3001:3000" + env_file: ../.env.local networks: - ntw +volumes: + postgres_data: + driver: local + redis_data: + driver: local + networks: ntw: diff --git a/apps/chatbot/docker/docker-compose-build-local.sh b/apps/chatbot/docker/docker-compose-build-local.sh index 563590505f..ac1c475f1e 100755 --- a/apps/chatbot/docker/docker-compose-build-local.sh +++ b/apps/chatbot/docker/docker-compose-build-local.sh @@ -1,2 +1,2 @@ #!/bin/bash -docker compose --env-file .env -f docker/compose.yaml -p chatbot build \ No newline at end of file +docker compose -f docker/compose.yaml -p chatbot build diff --git a/apps/chatbot/docker/docker-compose-run-create_index.sh b/apps/chatbot/docker/docker-compose-run-create_index.sh index 3e03f4f306..841345d5bc 100755 --- a/apps/chatbot/docker/docker-compose-run-create_index.sh +++ b/apps/chatbot/docker/docker-compose-run-create_index.sh @@ -1,2 +1,2 @@ #!/bin/bash -docker compose --env-file .env -f docker/compose.yaml -p chatbot run create_index +docker compose -f docker/compose.yaml -p chatbot run create_index diff --git a/apps/chatbot/docker/files/dynamodb_schemas/queries.json b/apps/chatbot/docker/files/dynamodb_schemas/queries.json index 77d652c1f6..a6674d5aa7 100644 --- a/apps/chatbot/docker/files/dynamodb_schemas/queries.json +++ b/apps/chatbot/docker/files/dynamodb_schemas/queries.json @@ -47,5 +47,5 @@ "WriteCapacityUnits": 5 }, "TableClass": "STANDARD", - "DeletionProtectionEnabled": true + "DeletionProtectionEnabled": false } diff --git a/apps/chatbot/docker/files/dynamodb_schemas/salts.json b/apps/chatbot/docker/files/dynamodb_schemas/salts.json new file mode 100644 index 0000000000..4223747933 --- /dev/null +++ b/apps/chatbot/docker/files/dynamodb_schemas/salts.json @@ -0,0 +1,21 @@ +{ + "TableName": "chatbot-local-salts", + "KeySchema": [ + { + "AttributeName": "sessionId", + "KeyType": "HASH" + } + ], + "AttributeDefinitions": [ + { + "AttributeName": "sessionId", + "AttributeType": "S" + } + ], + "ProvisionedThroughput": { + "ReadCapacityUnits": 5, + "WriteCapacityUnits": 5 + }, + "TableClass": "STANDARD", + "DeletionProtectionEnabled": false +} diff --git a/apps/chatbot/docker/files/dynamodb_schemas/sessions.json b/apps/chatbot/docker/files/dynamodb_schemas/sessions.json index 71404bbeeb..bd0f90277b 100644 --- a/apps/chatbot/docker/files/dynamodb_schemas/sessions.json +++ b/apps/chatbot/docker/files/dynamodb_schemas/sessions.json @@ -47,5 +47,5 @@ "WriteCapacityUnits": 5 }, "TableClass": "STANDARD", - "DeletionProtectionEnabled": true + "DeletionProtectionEnabled": false } diff --git a/apps/chatbot/docker/files/nextjs-website/generated/404.html b/apps/chatbot/docker/files/nextjs-website/generated/404.html new file mode 100644 index 0000000000..e0b59ef3ac --- /dev/null +++ b/apps/chatbot/docker/files/nextjs-website/generated/404.html @@ -0,0 +1 @@ +

DevPortalPagoPA

SoluzioniWebinar
404

Pagina non trovata

La pagina che stai cercando non esiste

\ No newline at end of file diff --git a/apps/chatbot/docker/files/nextjs-website/generated/case-histories/tari-cagliari.html b/apps/chatbot/docker/files/nextjs-website/generated/case-histories/tari-cagliari.html new file mode 100644 index 0000000000..0da1794de1 --- /dev/null +++ b/apps/chatbot/docker/files/nextjs-website/generated/case-histories/tari-cagliari.html @@ -0,0 +1 @@ +PagoPA DevPortal | Il processo di riscossione della TARI del Comune di Cagliari

DevPortalPagoPA

SoluzioniWebinar

Il processo di riscossione della TARI del Comune di Cagliari

Il racconto dell'esperienza del Comune di Cagliari, uno dei primi Comuni d'Italia a integrare SEND per gestire le notifiche a valore legale relative agli accertamenti Tari.

Lo scenario

Il Comune di Cagliari, che già da tempo è attivo sulla piattaforma pagoPA, è stato uno dei primi comuni a salire a bordo di SEND per gestire le notifiche a valore legale relative agli accertamenti Tari. Abbiamo incontrato Sabrina Contu e Paola Cuccureddu, rispettivamente funzionaria IMU/Tasi e funzionaria TARI del Comune di Cagliari, e abbiamo chiesto loro di raccontarci l’esperienza di onboarding e integrazione di SEND.

“Quando nel 2022 è stata pubblicata la Misura 1.4.5 Piattaforma Notifiche Digitali che consentiva alle amministrazioni di poter ricevere un finanziamento, nell’ambito del PNRR, per l'adesione a SEND” ci spiega Sabrina Contu, “abbiamo studiato il regolamento di attuazione della normativa e, prima di procedere, abbiamo fatto un'analisi degli invii di atti a valore legale effettuati nell’ultimo triennio verso società e professionisti. Questa analisi del business case è stata fondamentale perchè ci ha consentito di quantificare il valore di quegli avvisi e, nell'analisi costi / benefici, di renderci immediatamente conto degli evidenti vantaggi per l’Amministrazione nell’adesione a SEND, sia dal punto di vista economico che dal punto di vista della sicurezza dell’incasso a fronte di una maggiore probabilità di reperibilità del destinatario.

Onboarding e integrazione

“Una volta deciso di procedere con l’adesione, il passo successivo è stato la scelta del fornitore tecnologico per l’integrazione alla Piattaforma. Nel nostro caso, la software house che già gestiva l'applicativo dei tributi era anche già pronta per partire con SEND. Ci siamo quindi interfacciati con i referenti di PagoPA che ci hanno dato tutte le indicazioni utili per l’adesione: dall’accesso all'area riservata alla firma dell’accordo.

Dal canto nostro, abbiamo istituito l’apposito capitolo di spesa ed effettuato su questo l’apposito impegno di spesa per la prestazione del servizio.

Naturalmente questa nuova modalità di invio impone il rispetto di una serie di criteri e parametri: ad esempio, l’atto è nativo digitale e richiede quindi - per la versione stampata - di seguire delle specifiche precise, che ci sono state fornite e spiegate dal team di PagoPA e ci hanno consentito di procedere alla digitalizzazione degli atti con grande facilità.”

“Siamo pienamente soddisfatti di quanto fatto già lo scorso anno con SEND: abbiamo rilevato un significativo snellimento dei processi e abbiamo sperimentato i vantaggi legati al ritorno della notifica che viene automaticamente caricata in procedura.” conclude Sabrina Contu.

La risposta dei cittadini

“Abbiamo cercato di fare una comunicazione sul territorio in modo che i cittadini fossero informati di questa nuova possibilità, per accompagnarli in questo percorso di transizione digitale e consentire loro di percepire il cambio di passo del Comune come un vantaggio reale.” racconta Paola Cuccureddu. “Sappiamo bene all'interno di un comune quanto siano rilevanti - e purtroppo limitate - sia il fattore tempo che le risorse umane e tecniche disponibili. Con SEND abbiamo potuto ridurre i costi e ottimizzare al meglio le risorse disponibili, creando un servizio maggiormente di valore e impiegando quelle risorse per riuscire a fare una maggiore lotta all'evasione. Per il 2024 vogliamo continuare a notificare con SEND, forti anche dell’esperienza dello scorso anno, e contiamo di gestire circa 40.000 notifiche legate agli accertamenti TARI.”

Siamo pienamente soddisfatti di quanto fatto già lo scorso anno con SEND: abbiamo rilevato un significativo snellimento dei processi e abbiamo sperimentato i vantaggi legati al ritorno della notifica che viene automaticamente caricata in procedura.
Siamo pienamente soddisfatti di quanto fatto già lo scorso anno con SEND: abbiamo rilevato un significativo snellimento dei processi e abbiamo sperimentato i vantaggi legati al ritorno della notifica che viene automaticamente caricata in procedura.

Come integrarsi? Inizia da qui

IO, l’app dei servizi pubblici

Raccogli tutti i servizi digitali del tuo ente in un’unica piattaforma e interagisci in modo semplice e sicuro con i cittadini.

Piattaforma pagoPA

Gestisci gli incassi in modo centralizzato e con immediata riconciliazione delle posizioni debitorie.

SEND - Servizio Notifiche Digitali

Invia comunicazioni a valore legale con un processo di notificazione gestito interamente dalla piattaforma.

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b/apps/chatbot/docker/files/nextjs-website/generated/index.html @@ -0,0 +1 @@ +PagoPA DevPortal | PagoPA DevPortal

DevPortalPagoPA

SoluzioniWebinar

Tutto ciò che serve per integrarsi con i prodotti PagoPA

Tutto ciò che serve per integrarsi con i prodotti PagoPA

Invia comunicazioni a valore legale con SEND

vai a SEND
Invia comunicazioni a valore legale con SEND

Richiedi una firma su documenti e contratti

Vai a Firma con IO
Richiedi una firma su documenti e contratti

In evidenza

13 marzo 2024

Scopri la Quick Start di piattaforma pagoPA: l’integrazione in pochi semplici step

Vai alla guida

01 marzo 2024

Usa il validatore di SEND per fare una verifica sull’integrazione

Vai al validatore

01 marzo 2024

Scopri i nuovi tutorial di Firma con IO

Vai ai tutorial

Scopri il nostro ecosistema

IO, l’app dei servizi pubblici

Raccogli tutti i servizi digitali del tuo ente in un’unica piattaforma e interagisci in modo semplice e sicuro con i cittadini.

Firma con IO

Richiedi la Firma Elettronica Certificata su contratti e documenti. Le cittadine e i cittadini possono firmare direttamente sull’app IO.

Piattaforma pagoPA

Gestisci gli incassi in modo centralizzato e con immediata riconciliazione delle posizioni debitorie.

SEND - Servizio Notifiche Digitali

Invia comunicazioni a valore legale con un processo di notificazione gestito interamente dalla piattaforma.

Documentazione in arrivo

Interoperabilità. Scambia informazioni con altri enti in tutta sicurezza.
Check IBAN. Utilizza un sistema per la gestione degli incassi centralizzato e immediato.
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DevPortalPagoPA

SoluzioniWebinar
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DevPortalPagoPA

SoluzioniWebinar

Le soluzioni PagoPA: una nuova esperienza di servizi pubblici

Scopri le soluzioni, guide pratiche realizzate per supportarti nella trasformazione digitale dei tuoi servizi attraverso l’utilizzo integrato delle piattaforme PagoPA.

Multe per violazioni al Codice della Strada

In questa guida trovi i consigli utili per erogare in maniera virtuosa il servizio di sanzioni per violazione al Codice della strada, con approfondimenti sulla gestione delle diverse fasi.

IO
pagoPA
SEND
Tassa sui rifiuti (TARI)

La soluzione dedicata alle buone pratiche per gestire al meglio la riscossione della Tassa sui rifiuti (TARI), tramite un approccio automatizzato e integrato che garantisca una maggiore efficienza in termini di tempi e costi.

IO
pagoPA
SEND

I benefici della trasformazione digitale dei servizi

Comunicazione tempestiva e trasparente
Comunicazione tempestiva e trasparente

I cittadini hanno un accesso più diretto e immediato alle informazioni importanti e ai servizi che possono utilizzare

Processi di erogazione ottimizzati
Processi di erogazione ottimizzati

L'automazione dei processi e la digitalizzazione dei servizi portano una riduzione dei costi operativi associati alle procedure manuali

Riduzione dei tempi di incasso
Riduzione dei tempi di incasso

I pagamenti vengono elaborati in tempo reale, sono sempre tracciabili e possono essere facilmente aggiorati nel tempo.

Storie di successo

Le testimonianze di come gli enti hanno dato forma a servizi efficienti e accessibili, ottimizzando i processi grazie all’integrazione con le piattaforme PagoPA.

Il processo di riscossione della TARI del Comune di Cagliari

Leggi la storia

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DevPortalPagoPA

SoluzioniWebinar
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DevPortalPagoPA

SoluzioniWebinar
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package-mode = false @@ -35,13 +35,13 @@ google-generativeai = "^0.5.2" llama-index-embeddings-gemini = "^0.2.0" llama-index-llms-bedrock-converse = "^0.3.0" llama-index-postprocessor-presidio = "^0.2.0" +langfuse = "^2.53.9" [tool.poetry.group.test.dependencies] httpx = "^0.27.2" pytest = "^8.3.3" [tool.poetry.group.dev.dependencies] -gradio = "^4.36.1" jupyter = "^1.0.0" [build-system] diff --git a/apps/chatbot/scripts/dynamodb-create-table-queries-local.sh b/apps/chatbot/scripts/dynamodb-create-table-queries-local.sh deleted file mode 100755 index d9d351cae4..0000000000 --- a/apps/chatbot/scripts/dynamodb-create-table-queries-local.sh +++ /dev/null @@ -1,33 +0,0 @@ -#!/bin/bash -aws dynamodb create-table \ - --table-name chatbot-local-queries \ - --key-schema \ - AttributeName=sessionId,KeyType=HASH \ - AttributeName=id,KeyType=RANGE \ - --attribute-definitions \ - AttributeName=id,AttributeType=S \ - AttributeName=sessionId,AttributeType=S \ - AttributeName=createdAt,AttributeType=S \ - --local-secondary-indexes '[ - { - "IndexName": "QueriesByCreatedAtIndex", - "KeySchema": [ - { - "AttributeName": "sessionId", - "KeyType": "HASH" - }, - { - "AttributeName": "createdAt", - "KeyType": "RANGE" - } - ], - "Projection": { - "ProjectionType": "ALL" - } - } - ]' \ - --table-class STANDARD \ - --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5 \ - --endpoint-url http://localhost:8000 \ - --region eu-south-1 \ - --profile dummy diff --git a/apps/chatbot/scripts/dynamodb-create-table-sessions-local.sh b/apps/chatbot/scripts/dynamodb-create-table-sessions-local.sh deleted file mode 100755 index 52ff0505f4..0000000000 --- a/apps/chatbot/scripts/dynamodb-create-table-sessions-local.sh +++ /dev/null @@ -1,33 +0,0 @@ -#!/bin/bash -aws dynamodb create-table \ - --table-name chatbot-local-sessions \ - --key-schema \ - AttributeName=userId,KeyType=HASH \ - AttributeName=id,KeyType=RANGE \ - --attribute-definitions \ - AttributeName=id,AttributeType=S \ - AttributeName=userId,AttributeType=S \ - AttributeName=createdAt,AttributeType=S \ - --local-secondary-indexes '[ - { - "IndexName": "SessionsByCreatedAtIndex", - "KeySchema": [ - { - "AttributeName": "userId", - "KeyType": "HASH" - }, - { - "AttributeName": "createdAt", - "KeyType": "RANGE" - } - ], - "Projection": { - "ProjectionType": "ALL" - } - } - ]' \ - --table-class STANDARD \ - --provisioned-throughput ReadCapacityUnits=5,WriteCapacityUnits=5 \ - --endpoint-url http://localhost:8000 \ - --region eu-south-1 \ - --profile dummy diff --git a/apps/chatbot/scripts/dynamodb-init.sh b/apps/chatbot/scripts/dynamodb-init.sh index 6403db6937..2f2c521364 100755 --- a/apps/chatbot/scripts/dynamodb-init.sh +++ b/apps/chatbot/scripts/dynamodb-init.sh @@ -9,12 +9,11 @@ aws dynamodb create-table \ --cli-input-json file://./docker/files/dynamodb_schemas/queries.json \ --region eu-south-1 -aws dynamodb scan \ - --table-name chatbot-local-sessions \ - --endpoint-url http://dynamodb:8000 \ - --region eu-south-1 +aws dynamodb create-table \ +--endpoint-url http://dynamodb:8000 \ +--cli-input-json file://./docker/files/dynamodb_schemas/salts.json \ +--region eu-south-1 -aws dynamodb scan \ - --table-name chatbot-local-queries \ +aws dynamodb list-tables \ --endpoint-url http://dynamodb:8000 \ --region eu-south-1 diff --git a/apps/chatbot/scripts/run.local.sh b/apps/chatbot/scripts/run.local.sh index 8d39c6a4d5..95bab83f65 100755 --- a/apps/chatbot/scripts/run.local.sh +++ b/apps/chatbot/scripts/run.local.sh @@ -3,8 +3,8 @@ echo '-=-=-=-=-=-=-=-=-= init DynamoDB -==-=-=-=-=-=-=-=-' ./scripts/dynamodb-init.sh -echo '-=-=-=-=-=-=-= create redis index =-=-=-=-=-=-=-=-' -./scripts/create_redis_index.sh +#echo '-=-=-=-=-=-=-= create redis index =-=-=-=-=-=-=-=-' +#./scripts/create_redis_index.sh echo '-=-=-=-=-=-=-=-=-= run FastAPI =-==-=-=-=-=-=-=-=-' fastapi dev src/app/main.py --port 8080 --host 0.0.0.0 diff --git a/apps/chatbot/src/app/api.md b/apps/chatbot/src/app/api.md index c0a5543728..56f560f337 100644 --- a/apps/chatbot/src/app/api.md +++ b/apps/chatbot/src/app/api.md @@ -1,87 +1,94 @@ -POST /queries -{ - "sessionId": string, - "question": string, - "queriedAt": string -} +### POST /queries + + { + "sessionId": string, + "question": string, + "queriedAt": string + } response: -{ - "id": string, - "sessionId": string, - "question": string, - "answer": string, - "createdAt": string, - "queriedAt": string -} ---------------------------------------------- + { + "id": string, + "sessionId": string, + "question": string, + "answer": string, + "createdAt": string, + "queriedAt": string + } + +--- -GET /healthz +### GET /healthz response: -{ - "message": "OK" -} ---------------------------------------------- + { + "message": "OK" + } + +--- -GET /queries/{id} +### GET /queries/{id} response: -{ - "id": string, - "sessionId": string, - "question": string, - "answer": string, - "createdAt": string, - "queriedAt": string -} ---------------------------------------------- + { + "id": string, + "sessionId": string, + "question": string, + "answer": string, + "createdAt": string, + "queriedAt": string + } -GET /sessions +--- + +### GET /sessions response: -[ - { - "id": string, - "title": string, - "createdAt": string - } -] ---------------------------------------------- + [ + { + "id": string, + "title": string, + "createdAt": string + } + ] + +--- -POST /sessions +### POST /sessions response: -{ - "id": string, - "title": string, - "createdAt": string -} ---------------------------------------------- + { + "id": string, + "title": string, + "createdAt": string + } -GET /queries?sessionId={sessionId} +--- + +### GET /queries?sessionId={sessionId} response: -[ - { - "id": string, - "sessionId": string, - "question": string, - "answer": string, - "createdAt": string, - "queriedAt": string - } -] - ---------------------------------------------- - -PATCH /queries/{id} - -{ - "badAnswer": boolean -} + + [ + { + "id": string, + "sessionId": string, + "question": string, + "answer": string, + "createdAt": string, + "queriedAt": string + } + ] + +--- + +### PATCH /queries/{id} + + { + "badAnswer": boolean + } diff --git a/apps/chatbot/src/app/main.py b/apps/chatbot/src/app/main.py index 3a6b54329c..8d64f18290 100644 --- a/apps/chatbot/src/app/main.py +++ b/apps/chatbot/src/app/main.py @@ -1,8 +1,10 @@ +import os import yaml import mangum import uvicorn +import logging import json -import os +import hashlib import uuid import boto3 import datetime @@ -16,6 +18,7 @@ from src.modules.chatbot import Chatbot +logging.basicConfig(level=logging.INFO) params = yaml.safe_load(open("config/params.yaml", "r")) prompts = yaml.safe_load(open("config/prompts.yaml", "r")) AWS_DEFAULT_REGION = os.getenv('CHB_AWS_DEFAULT_REGION', os.getenv('AWS_DEFAULT_REGION', None)) @@ -58,6 +61,9 @@ class QueryFeedback(BaseModel): table_sessions = dynamodb.Table( f"{os.getenv('CHB_QUERY_TABLE_PREFIX', 'chatbot')}-sessions" ) +table_salts = dynamodb.Table( + f"{os.getenv('CHB_QUERY_TABLE_PREFIX', 'chatbot')}-salts" +) app = FastAPI() app.add_middleware( @@ -68,6 +74,10 @@ class QueryFeedback(BaseModel): allow_headers=["*"], ) +def hash_func(user_id: str, salt: str) -> str: + salted_user_id = user_id + salt + return hashlib.sha256(salted_user_id.encode()).hexdigest() + @app.get("/healthz") async def healthz (): return {"message": "OK"} @@ -78,11 +88,17 @@ async def query_creation ( authorization: Annotated[str | None, Header()] = None ): now = datetime.datetime.now(datetime.UTC) + trace_id = str(uuid.uuid4()) userId = current_user_id(authorization) session = find_or_create_session(userId, now=now) + salt = session_salt(session['id']) + answer = chatbot.chat_generate( query_str = query.question, - messages = [item.dict() for item in query.history] if query.history else None + messages = [item.dict() for item in query.history] if query.history else None, + trace_id = trace_id, + user_id = hash_func(userId, salt), + session_id = session["id"] ) @@ -92,7 +108,7 @@ async def query_creation ( queriedAt = query.queriedAt bodyToReturn = { - "id": f'{uuid.uuid4()}', + "id": trace_id, "sessionId": session['id'], "question": query.question, "answer": answer, @@ -111,7 +127,7 @@ async def query_creation ( return bodyToReturn -def current_user_id(authorization: str): +def current_user_id(authorization: str) -> str: if authorization is None: # TODO remove fake user and return None # return None @@ -155,7 +171,7 @@ def find_or_create_session(userId: str, now: datetime.datetime): "createdAt": now.isoformat() } try: - table_sessions.put_item(Item = body) + create_session_record(body) except (BotoCoreError, ClientError) as e: raise HTTPException(status_code=422, detail=f"[find_or_create_session] body: {body}, error: {e}") @@ -164,6 +180,30 @@ def find_or_create_session(userId: str, now: datetime.datetime): return body +def create_session_record(body: dict): + saltValue = str(uuid.uuid4()) + saltBody = { + 'sessionId': body['id'], + 'value': saltValue + } + # TODO: transaction https://github.com/boto/boto3/pull/4010 + table_sessions.put_item(Item = body) + table_salts.put_item(Item = saltBody) + +def session_salt(sessionId: str): + try: + dbResponse = table_salts.query( + KeyConditionExpression=Key("sessionId").eq(sessionId) + ) + except (BotoCoreError, ClientError) as e: + raise HTTPException(status_code=422, detail=f"[salts_fetching] sessionId: {sessionId}, error: {e}") + result = dbResponse.get('Items', []) + if len(result) == 0: + result = None + else: + result = result[0] + return result.get('value', None) + @app.get("/queries") async def queries_fetching( @@ -235,7 +275,7 @@ async def session_delete( KeyConditionExpression=Key("sessionId").eq(id) ) # TODO: use batch writer -# with table_sessions.batch_writer() as batch: + # with table_sessions.batch_writer() as batch: for query in dbResponse_queries['Items']: table_queries.delete_item( Key={ @@ -290,6 +330,14 @@ async def query_feedback ( }, ReturnValues='ALL_NEW' ) + + chatbot.add_langfuse_score( + trace_id = id, + name = 'user-feedback', + value = (-1 if query.badAnswer else 1), + data_type = 'NUMERIC' + ) + except (BotoCoreError, ClientError) as e: raise HTTPException(status_code=422, detail=f"[query_feedback] id: {id}, sessionId: {sessionId}, error: {e}") diff --git a/apps/chatbot/src/modules/chatbot.py b/apps/chatbot/src/modules/chatbot.py index 2a29d56fcb..7cd0d67ad3 100644 --- a/apps/chatbot/src/modules/chatbot.py +++ b/apps/chatbot/src/modules/chatbot.py @@ -1,55 +1,72 @@ import os import re -import logging -# import nest_asyncio -from typing import Union, Tuple, Optional, List +import yaml +import uuid +from pathlib import Path +from datetime import datetime +from logging import getLogger +from typing import Union, Tuple, Sequence, Optional, List, Any, Dict, Literal from llama_index.core import PromptTemplate from llama_index.core.llms import ChatMessage, MessageRole from llama_index.core.base.response.schema import Response, StreamingResponse, AsyncStreamingResponse, PydanticResponse -from llama_index.core.chat_engine.types import AgentChatResponse, StreamingAgentChatResponse +from llama_index.core.chat_engine.types import BaseChatEngine, AgentChatResponse, StreamingAgentChatResponse from llama_index.core.async_utils import asyncio_run +from langfuse import Langfuse +from langfuse.llama_index import LlamaIndexInstrumentor +from langfuse.api.resources.trace.types.traces import Traces +from langfuse.model import TraceWithFullDetails + from src.modules.models import get_llm, get_embed_model from src.modules.vector_database import load_automerging_index_redis, REDIS_KVSTORE, INDEX_ID from src.modules.engine import get_automerging_engine +from src.modules.handlers import EventHandler from src.modules.presidio import PresidioPII +from src.modules.utils import get_ssm_parameter from dotenv import load_dotenv -load_dotenv() -# nest_asyncio.apply() +load_dotenv() +logger = getLogger(__name__) +CWF = Path(__file__) +ROOT = CWF.parent.parent.parent.absolute().__str__() USE_PRESIDIO = True if (os.getenv("CHB_USE_PRESIDIO", "True")).lower() == "true" else False +USE_CHAT_ENGINE = True if (os.getenv("CHB_USE_CHAT_ENGINE", "True")).lower() == "true" else False USE_ASYNC = True if (os.getenv('CHB_ENGINE_USE_ASYNC', "True")).lower() == "true" else False USE_STREAMING = True if (os.getenv('CHB_ENGINE_USE_STREAMING', "False")).lower() == "true" else False -USE_CHAT_ENGINE = True if (os.getenv('CHB_ENGINE_USE_CHAT_ENGINE', "True")).lower() == "true" else False RESPONSE_TYPE = Union[ Response, StreamingResponse, AsyncStreamingResponse, PydanticResponse, AgentChatResponse, StreamingAgentChatResponse -] -START_CHAT_MESSAGE = [ChatMessage( - role = MessageRole.ASSISTANT, - content = ( - "Ciao! Io sono Discovery, l'assistente virtuale di PagoPA.\n" - "Rispondo solo e soltanto a domande riguardanti la documentazione di PagoPA DevPortal, " - "che puoi trovare sul sito: https://dev.developer.pagopa.it!" - ) -)] - -logging.getLogger().setLevel(os.getenv("LOG_LEVEL", "INFO")) +] +SYSTEM_PROMPT = ( + "You are the virtual PagoPA S.p.A. assistant. Your name is Discovery.\n" + "Your role is to provide accurate, professional, and helpful responses to users' queries regarding " + "the PagoPA DevPortal documentation available at: https://dev.developer.pagopa.it" +) +LANGFUSE_PUBLIC_KEY = get_ssm_parameter(os.getenv("CHB_LANGFUSE_PUBLIC_KEY"), os.getenv("LANGFUSE_INIT_PROJECT_PUBLIC_KEY")) +LANGFUSE_SECRET_KEY = get_ssm_parameter(os.getenv("CHB_LANGFUSE_SECRET_KEY"), os.getenv("LANGFUSE_INIT_PROJECT_SECRET_KEY")) +LANGFUSE_HOST = os.getenv("CHB_LANGFUSE_HOST") +LANGFUSE = Langfuse( + public_key = LANGFUSE_PUBLIC_KEY, + secret_key = LANGFUSE_SECRET_KEY, + host = LANGFUSE_HOST +) class Chatbot(): def __init__( self, - params, - prompts + params: dict | None = None, + prompts: dict | None = None, + use_chat_engine: bool | None = None ): - self.params = params - self.prompts = prompts + self.params = params if params else yaml.safe_load(open(os.path.join(ROOT, "config", "params.yaml"), "r")) + self.prompts = prompts if prompts else yaml.safe_load(open(os.path.join(ROOT, "config", "prompts.yaml"), "r")) + self.use_chat_engine = use_chat_engine if use_chat_engine else USE_CHAT_ENGINE if USE_PRESIDIO: self.pii = PresidioPII(config=params["config_presidio"]) @@ -65,17 +82,28 @@ def __init__( self.qa_prompt_tmpl, self.ref_prompt_tmpl, self.condense_prompt_tmpl = self._get_prompt_templates() self.engine = get_automerging_engine( self.index, - llm=self.model, - text_qa_template=self.qa_prompt_tmpl, - refine_template=self.ref_prompt_tmpl, - condense_template=self.condense_prompt_tmpl, - verbose=self.params["engine"]["verbose"] + llm = self.model, + text_qa_template = self.qa_prompt_tmpl, + refine_template = self.ref_prompt_tmpl, + condense_template = self.condense_prompt_tmpl, + verbose = self.params["engine"]["verbose"], + use_chat_engine = self.use_chat_engine + ) + self.system_message = ChatMessage( + role = self.model.metadata.system_role, + content = SYSTEM_PROMPT + ) if isinstance(self.engine, BaseChatEngine) else None + self.instrumentor = LlamaIndexInstrumentor( + public_key = LANGFUSE_PUBLIC_KEY, + secret_key = LANGFUSE_SECRET_KEY, + host = LANGFUSE_HOST, + mask=self._mask_trace ) + self.instrumentor._event_handler = EventHandler(langfuse_client=LANGFUSE) def _get_prompt_templates(self) -> Tuple[PromptTemplate, PromptTemplate]: - # create templates qa_prompt_tmpl = PromptTemplate( self.prompts["qa_prompt_str"], template_var_mappings={ @@ -106,18 +134,15 @@ def _get_prompt_templates(self) -> Tuple[PromptTemplate, PromptTemplate]: def _get_response_str(self, engine_response: RESPONSE_TYPE) -> str: - if USE_CHAT_ENGINE: - if isinstance(engine_response, StreamingAgentChatResponse): - response_str = "" - for token in engine_response.response_gen: - response_str += token - else: - response_str = engine_response.response + if isinstance(engine_response, StreamingAgentChatResponse): + response_str = "" + for token in engine_response.response_gen: + response_str += token + if isinstance(engine_response, AgentChatResponse): + response_str = engine_response.response else: - if isinstance(engine_response, StreamingResponse): - engine_response = engine_response.get_response() - - response_str = engine_response.response.strip() + engine_response = engine_response.get_response() + response_str = engine_response.response response_str = response_str.strip() nodes = engine_response.source_nodes @@ -137,7 +162,7 @@ def _unmask_reference(self, response_str: str, nodes) -> str: # Find all matches in the text hashed_urls = re.findall(pattern, response_str) - logging.info(f"[chatbot.py - _unmask_reference] Generated answer has {len(hashed_urls)} references taken from {len(nodes)} nodes. First node has score: {nodes[0].score:.4f}.") + logger.info(f"Generated answer has {len(hashed_urls)} references taken from {len(nodes)} nodes. First node has score: {nodes[0].score:.4f}.") for hashed_url in hashed_urls: url = REDIS_KVSTORE.get( collection=f"hash_table_{INDEX_ID}", @@ -150,8 +175,8 @@ def _unmask_reference(self, response_str: str, nodes) -> str: # remove sentences with generated masked url: {URL} parts = re.split(r"(?<=[\.\?\!\n])", response_str) - filtered_parts = [part for part in parts if "{URL}" not in part] # filter out parts containing {URL} - response_str = "".join(filtered_parts) # join the filtered parts back into a single string + filtered_parts = [part for part in parts if "{URL}" not in part] + response_str = "".join(filtered_parts) return response_str @@ -165,14 +190,14 @@ def mask_pii(self, message: str) -> str: masked_message = masked_message + "Rif:" + split_message[1] return masked_message except Exception as e: - logging.warning(f"[chatbot.py - mask_pii] exception in mask_pii: {e}") + logger.warning(f"Exception: {e}") else: return message - def _messages_to_chathistory(self, messages: Optional[List[dict]] = None) -> List[ChatMessage]: + def _messages_to_chathistory(self, messages: Optional[List[Dict[str, str]]] = None) -> List[ChatMessage]: - chat_history = [] + chat_history = [self.system_message] if messages: for message in messages: chat_history += [ @@ -182,46 +207,188 @@ def _messages_to_chathistory(self, messages: Optional[List[dict]] = None) -> Lis ), ChatMessage( role = MessageRole.ASSISTANT, - content = message["answer"] + content = message["answer"].split("Rif:")[0].strip() ) ] - - chat_history = START_CHAT_MESSAGE + chat_history return chat_history - - def generate(self, query_str: str) -> str: + + def get_trace(self, trace_id: str, as_dict: bool = False) -> TraceWithFullDetails | dict: try: - engine_response = self.engine.query(query_str) - response_str = self._get_response_str(engine_response) + trace = LANGFUSE.fetch_trace(trace_id) + trace = trace.data + except Exception as e: + logger.error(e) + + if as_dict: + return trace.dict() + else: + return trace + + def get_traces( + self, + user_id: str | None = None, + session_id: str | None = None, + from_timestamp: datetime | None = None, + to_timestamp: datetime | None = None, + order_by: str | None = None, + tags: str | Sequence[str] | None = None, + ) -> Traces: + + try: + traces = LANGFUSE.get_traces( + user_id=user_id, + session_id = session_id, + from_timestamp = from_timestamp, + to_timestamp = to_timestamp, + order_by = order_by, + tags = tags + ) except Exception as e: - response_str = "Scusa, non sono riuscito ad elaborare questa domanda.\nChiedimi un'altra domanda." - logging.info(f"[chatbot.py - generate] Exception: {e}") + logger.error(e) - return response_str + return traces - def chat_generate(self, query_str: str, messages: Optional[List[dict]] = None) -> str: + def add_langfuse_tag(self, trace_id: str, tag: str) -> None: + with self.instrumentor.observe(trace_id=trace_id) as trace: + trace_info = self.get_trace(trace_id, as_dict=False) + if tag not in trace_info.tags: + trace.update( + tags = trace_info.tags + [tag] + ) + logger.info(f"Added tag {tag} to trace {trace_id}") + else: + logger.warning(f"Tag {tag} already present in trace {trace_id}") + + + def remove_langfuse_tag(self, trace_id: str, tag: str) -> None: + with self.instrumentor.observe(trace_id=trace_id) as trace: + trace_info = self.get_trace(trace_id, as_dict=False) + if tag in trace_info.tags: + trace_info.tags.pop(trace_info.tags.index(tag)) + trace.update( + tags = trace_info.tags + ) + logger.info(f"Removed tag {tag} from trace {trace_id}") + else: + logger.warning(f"Tag {tag} not present in trace {trace_id}") + + def add_langfuse_score( + self, + trace_id: str, + name: str, + value: float, + data_type: Literal['NUMERIC', 'BOOLEAN'] | None = None + ) -> None: + + with self.instrumentor.observe(trace_id=trace_id) as trace: + trace_info = self.get_trace(trace_id, as_dict=False) + flag = True + for score in trace_info.scores: + if score.name == name: + flag = False + score_id = score.id + break + + if flag: + trace.score(name=name, value=value, data_type=data_type) + logger.warning(f"Add score {name}: {value} in trace {trace_id}") + else: + trace.score(id=score_id, name=name, value=value, data_type=data_type) + logger.warning(f"Updating score {name} to {value} in trace {trace_id}") + + + def _mask_trace(self, data: Any) -> None: + if isinstance(data, dict): + for key, value in data.items(): + + if isinstance(value, str): + data[key] = self.mask_pii(value) + + if isinstance(value, list): + for message in value: + if isinstance(message, ChatMessage): + message.content = self.mask_pii(message.content) + if isinstance(message, str): + message = self.mask_pii(message) + + if isinstance(value, dict): + for k, v in value.items(): + if isinstance(v, list): + for message in v: + if isinstance(message, ChatMessage): + message.content = self.mask_pii(message.content) + if isinstance(message, str): + message = self.mask_pii(message) + if isinstance(v, str): + value[k] = self.mask_pii(v) + + if isinstance(data, str): + data = self.mask_pii(data) + + return data + + + def chat_generate( + self, + query_str: str, + trace_id: str | None = None, + session_id: str | None = None, + user_id: str | None = None, + messages: Optional[List[Dict[str, str]]] | None = None, + tags: Optional[Union[str, List[str]]] | None = None + ) -> str: + + if isinstance(tags, str): + tags = [tags] + chat_history = self._messages_to_chathistory(messages) + + if not trace_id: + logger.debug(f"[Langfuse] Trace id not provided. Generating a new one") + trace_id = str(uuid.uuid4()) - try: - if USE_ASYNC and not USE_STREAMING: - engine_response = asyncio_run(self.engine.achat(query_str, chat_history)) - elif not USE_ASYNC and USE_STREAMING: - engine_response = self.engine.stream_chat(query_str, chat_history) - elif USE_ASYNC and USE_STREAMING: - engine_response = asyncio_run(self.engine.astream_chat(query_str, chat_history)) - else: - engine_response = self.engine.chat(query_str, chat_history) - response_str = self._get_response_str(engine_response) + logger.info(f"[Langfuse] Trace id: {trace_id}") - except Exception as e: - response_str = "Scusa, non sono riuscito ad elaborare questa domanda.\nChiedimi un'altra domanda." - logging.info(f"[chatbot.py - generate] Exception: {e}") + with self.instrumentor.observe( + trace_id = trace_id, + session_id = session_id, + user_id = user_id, + tags = tags + ) as trace: + + try: + if USE_ASYNC and not USE_STREAMING: + engine_response = asyncio_run(self.engine.achat(query_str, chat_history)) + elif not USE_ASYNC and USE_STREAMING: + engine_response = self.engine.stream_chat(query_str, chat_history) + elif USE_ASYNC and USE_STREAMING: + engine_response = asyncio_run(self.engine.astream_chat(query_str, chat_history)) + else: + engine_response = self.engine.chat(query_str, chat_history) + response_str = self._get_response_str(engine_response) + + context = "" + for node in engine_response.source_nodes: + url = REDIS_KVSTORE.get( + collection=f"hash_table_{INDEX_ID}", + key=node.metadata["filename"] + ) + context += f"URL: {url}\n\n{node.text}\n\n------------------\n\n" + + except Exception as e: + response_str = "Scusa, non posso elaborare la tua richiesta.\nProva a chierdimi una nuova domanda." + context = "" + logger.error(f"Exception: {e}") + + trace.update(output=self.mask_pii(response_str), metadata={"context": context}) + trace.score(name="user-feedback", value=0, data_type="NUMERIC") + self.instrumentor.flush() return response_str diff --git a/apps/chatbot/src/modules/create_vector_index.py b/apps/chatbot/src/modules/create_vector_index.py index 5fb0b31385..fe9767e252 100644 --- a/apps/chatbot/src/modules/create_vector_index.py +++ b/apps/chatbot/src/modules/create_vector_index.py @@ -8,8 +8,10 @@ from dotenv import load_dotenv + load_dotenv() -logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO")) +logging.basicConfig(level=logging.INFO) + DOCUMENTATION_DIR = os.getenv("CHB_DOCUMENTATION_DIR") @@ -32,4 +34,3 @@ chunk_sizes=params["vector_index"]["chunk_sizes"], chunk_overlap=params["vector_index"]["chunk_overlap"] ) - diff --git a/apps/chatbot/src/modules/engine.py b/apps/chatbot/src/modules/engine.py index 6fb199cd82..d7c54a62c5 100644 --- a/apps/chatbot/src/modules/engine.py +++ b/apps/chatbot/src/modules/engine.py @@ -3,18 +3,25 @@ from llama_index.core.llms.llm import LLM from llama_index.core.retrievers import AutoMergingRetriever from llama_index.core.query_engine import RetrieverQueryEngine -from llama_index.core.chat_engine import CondenseQuestionChatEngine +from llama_index.core.chat_engine import CondensePlusContextChatEngine from llama_index.core.postprocessor import SimilarityPostprocessor from dotenv import load_dotenv + load_dotenv() -SIMILARITY_TOPK = os.getenv('CHB_ENGINE_SIMILARITY_TOPK', "5") -SIMILARITY_CUTOFF = os.getenv('CHB_ENGINE_SIMILARITY_CUTOFF', "0.55") -USE_ASYNC = True if (os.getenv('CHB_ENGINE_USE_ASYNC', "True")).lower() == "true" else False -USE_STREAMING = True if (os.getenv('CHB_ENGINE_USE_STREAMING', "False")).lower() == "true" else False -USE_CHAT_ENGINE = True if (os.getenv('CHB_ENGINE_USE_CHAT_ENGINE', "True")).lower() == "true" else False + +USE_CHAT_ENGINE = True if (os.getenv("CHB_USE_CHAT_ENGINE", "True")).lower() == "true" else False +SIMILARITY_TOPK = os.getenv("CHB_ENGINE_SIMILARITY_TOPK", "5") +SIMILARITY_CUTOFF = os.getenv("CHB_ENGINE_SIMILARITY_CUTOFF", "0.55") +USE_ASYNC = True if (os.getenv("CHB_ENGINE_USE_ASYNC", "True")).lower() == "true" else False +USE_STREAMING = True if (os.getenv("CHB_ENGINE_USE_STREAMING", "False")).lower() == "true" else False +SYSTEM_PROMPT = ( + "You are the virtual PagoPA S.p.A. assistant. Your name is Discovery.\n" + "Your role is to provide accurate, professional, and helpful responses to users' queries regarding " + "the PagoPA DevPortal documentation available at: https://dev.developer.pagopa.it" +) def get_automerging_engine( @@ -26,10 +33,10 @@ def get_automerging_engine( condense_template: PromptTemplate | None = None, verbose: bool = True, use_chat_engine: bool | None = None - ) -> (RetrieverQueryEngine | CondenseQuestionChatEngine): + ) -> (RetrieverQueryEngine | CondensePlusContextChatEngine): - if use_chat_engine is None: - use_chat_engine = USE_CHAT_ENGINE + + use_chat_engine = use_chat_engine if use_chat_engine else USE_CHAT_ENGINE base_retriever = index.as_retriever( similarity_top_k=int(SIMILARITY_TOPK) @@ -43,23 +50,23 @@ def get_automerging_engine( similarity_cutoff=float(SIMILARITY_CUTOFF) ) - automerging_engine = RetrieverQueryEngine.from_args( + if use_chat_engine: + return CondensePlusContextChatEngine.from_defaults( + retriever = retriever, + llm = llm, + context_prompt = text_qa_template, + context_refine_prompt = refine_template, + condense_prompt = condense_template, + node_postprocessors = [similarity_postprocessor] + ) + else: + return RetrieverQueryEngine.from_args( retriever, - llm=llm, - response_mode=response_mode, - node_postprocessors=[ - similarity_postprocessor - ], - text_qa_template=text_qa_template, - refine_template=refine_template, - use_async=USE_ASYNC, - streaming=USE_STREAMING + llm = llm, + response_mode = response_mode, + node_postprocessors = [similarity_postprocessor], + text_qa_template = text_qa_template, + refine_template = refine_template, + use_async = USE_ASYNC, + streaming = USE_STREAMING ) - - if use_chat_engine: - automerging_engine = CondenseQuestionChatEngine.from_defaults( - query_engine = automerging_engine, - condense_question_prompt = condense_template - ) - - return automerging_engine \ No newline at end of file diff --git a/apps/chatbot/src/modules/evaluation.py b/apps/chatbot/src/modules/evaluation.py index 68aa118f14..9e0278933b 100644 --- a/apps/chatbot/src/modules/evaluation.py +++ b/apps/chatbot/src/modules/evaluation.py @@ -3,9 +3,8 @@ import json import yaml import datetime -import logging +from logging import getLogger import asyncio -import nest_asyncio from typing import Any import pandas as pd @@ -19,14 +18,13 @@ ContextRelevancyEvaluator ) from llama_index.core.evaluation.base import BaseEvaluator, EvaluationResult -from llama_index.core.evaluation.eval_utils import aget_responses +from llama_index.core.evaluation.eval_utils import get_responses from src.modules.chatbot import Chatbot from src.modules.models import get_llm -nest_asyncio.apply() -logging.basicConfig(level=os.getenv("LOG_LEVEL", "INFO")) +logger = getLogger(__name__) def parser_function(output_str: str): @@ -160,7 +158,7 @@ def table_results(responses, eval_results): params = yaml.safe_load(open("config/params.yaml", "r")) prompts = yaml.safe_load(open("config/prompts.yaml", "r")) eval_prompts = yaml.safe_load(open("config/eval_prompts.yaml", "r")) - bot = Chatbot(params, prompts) + bot = Chatbot(params, prompts, use_chat_engine=False) eval_model = get_llm() # load FAQs @@ -192,18 +190,18 @@ def table_results(responses, eval_results): batch_runner = BatchEvalRunner(evaluator_dict, workers=12, show_progress=True) # get predition responses - pred_responses = asyncio.run(aget_responses(questions, bot.engine._query_engine, show_progress=True)) + pred_responses = get_responses(questions, bot.engine, show_progress=True) for i, pr in enumerate(pred_responses): after = bot._get_response_str(pr) pred_responses[i].response = after # get evaluation results - eval_results = asyncio.run(batch_runner.aevaluate_responses( + eval_results = batch_runner.evaluate_responses( questions, responses=pred_responses, reference=ref_responses - )) + ) # save results now = datetime.datetime.now() @@ -224,4 +222,4 @@ def table_results(responses, eval_results): ) with open(os.path.join(results_dir, "avg_scores.json"), "w") as f: json.dump(avg_scores, f, indent=4) - logging.info(f"Results stored in {results_dir}") \ No newline at end of file + logger.info(f"Results stored in {results_dir}") \ No newline at end of file diff --git a/apps/chatbot/src/modules/handlers.py b/apps/chatbot/src/modules/handlers.py new file mode 100644 index 0000000000..5a3910c50f --- /dev/null +++ b/apps/chatbot/src/modules/handlers.py @@ -0,0 +1,259 @@ +import os +from typing import Optional, Any, Union, Mapping + +from langfuse.client import ( + Langfuse, + StatefulGenerationClient, + StateType, +) +from langfuse.utils import _get_timestamp +from langfuse.model import ModelUsage +from langfuse.llama_index._context import InstrumentorContext +from uuid import uuid4 as create_uuid + +try: + from llama_index.core.base.llms.types import ( + ChatResponse, + CompletionResponse, + ) + from llama_index.core.instrumentation.events import BaseEvent + from llama_index.core.instrumentation.events.embedding import ( + EmbeddingStartEvent, + EmbeddingEndEvent, + ) + from llama_index.core.instrumentation.event_handlers import BaseEventHandler + from llama_index.core.instrumentation.events.llm import ( + LLMCompletionEndEvent, + LLMCompletionStartEvent, + LLMChatEndEvent, + LLMChatStartEvent, + ) + from llama_index.core.utilities.token_counting import TokenCounter + +except ImportError: + raise ModuleNotFoundError( + "Please install llama-index to use the Langfuse llama-index integration: 'pip install llama-index'" + ) + +from logging import getLogger +from dotenv import load_dotenv + + +load_dotenv() +logger = getLogger(__name__) + + +MODEL_ID = os.getenv("CHB_MODEL_ID") +EMBED_MODEL_ID = os.getenv("CHB_EMBED_MODEL_ID") +LLMS_COST = { + "mistral.mistral-large-2402-v1:0": {"input_cost": 0.0052 * 1.e-3, "output_cost": 0.0156 * 1.e-3}, + "models/gemini-1.5-flash": {"input_cost": 0.075 * 1.e-6, "output_cost": 0.30 * 1.e-6} +} +EMBEDDERS_COST = { + "cohere.embed-multilingual-v3": 0.0001 * 1.e-3, + "models/models/text-embedding-004": 0 +} + + +class EventHandler(BaseEventHandler, extra="allow"): + def __init__(self, *, langfuse_client: Langfuse): + super().__init__() + + self._langfuse = langfuse_client + self._token_counter = TokenCounter() + self._context = InstrumentorContext() + + @classmethod + def class_name(cls) -> str: + """Class name.""" + return "EventHandler" + + def handle(self, event: BaseEvent) -> None: + logger.debug(f"Event {type(event).__name__} received: {event}") + + if isinstance( + event, (LLMCompletionStartEvent, LLMChatStartEvent, EmbeddingStartEvent) + ): + self.update_generation_from_start_event(event) + elif isinstance( + event, (LLMCompletionEndEvent, LLMChatEndEvent, EmbeddingEndEvent) + ): + self.update_generation_from_end_event(event) + + def update_generation_from_start_event( + self, + event: Union[LLMCompletionStartEvent, LLMChatStartEvent, EmbeddingStartEvent], + ) -> None: + if event.span_id is None: + logger.warning("Span ID is not set") + return + + model_data = event.model_dict + model = model_data.pop("model", None) or model_data.pop("model_name", None) + traced_model_data = { + k: str(v) + for k, v in model_data.items() + if v is not None + and k + in [ + "max_tokens", + "max_retries", + "temperature", + "timeout", + "strict", + "top_logprobs", + "logprobs", + "embed_batch_size", + ] + } + + self._get_generation_client(event.span_id).update( + model=model, model_parameters=traced_model_data + ) + + def update_generation_from_end_event( + self, event: Union[LLMCompletionEndEvent, LLMChatEndEvent, EmbeddingEndEvent] + ) -> None: + if event.span_id is None: + logger.warning("Span ID is not set") + return + + usage = None + + if isinstance(event, (LLMCompletionEndEvent, LLMChatEndEvent)): + if event.response: + usage = self._parse_token_usage(event.response) if event.response else None + logger.info(f"[{MODEL_ID}] Input Tokens: {usage["input"]}") + logger.info(f"[{MODEL_ID}] Output Tokens: {usage["output"]}") + + if isinstance(event, EmbeddingEndEvent): + token_count = sum( + self._token_counter.get_string_tokens(chunk) for chunk in event.chunks + ) + usage = { + "input": 0, + "output": 0, + "total": token_count or 0, + "total_cost": token_count * EMBEDDERS_COST[EMBED_MODEL_ID] if MODEL_ID in LLMS_COST.keys() else 0 + } + logger.info(f"[{EMBED_MODEL_ID}] Embedding Tokens: {usage["total"]}") + + self._get_generation_client(event.span_id).update( + usage=usage, end_time=_get_timestamp() + ) + + + def _parse_token_usage( + self, response: Union[ChatResponse, CompletionResponse] + ) -> Optional[ModelUsage]: + if ( + (raw := getattr(response, "raw", None)) + and hasattr(raw, "get") + ) and ( + (usage := raw.get("usage")) + or (usage := raw.get("usage_metadata")) + ): + return _parse_usage_from_mapping(usage) + + if additional_kwargs := getattr(response, "additional_kwargs", None): + return _parse_usage_from_mapping(additional_kwargs) + + def _get_generation_client(self, id: str) -> StatefulGenerationClient: + trace_id = self._context.trace_id + if trace_id is None: + logger.warning( + "Trace ID is not set. Creating generation client with new trace id." + ) + trace_id = str(create_uuid()) + + return StatefulGenerationClient( + client=self._langfuse.client, + id=id, + trace_id=trace_id, + task_manager=self._langfuse.task_manager, + state_type=StateType.OBSERVATION, + ) + + +def _parse_usage_from_mapping( + usage: Union[object, Mapping[str, Any]], +) -> ModelUsage: + if isinstance(usage, Mapping): + return _get_token_counts_from_mapping(usage) + + return _parse_usage_from_object(usage) + + +def _parse_usage_from_object(usage: object) -> ModelUsage: + model_usage: ModelUsage = { + "unit": None, + "input": None, + "output": None, + "total": None, + "input_cost": None, + "output_cost": None, + "total_cost": None, + } + + if ( + (prompt_tokens := getattr(usage, "prompt_tokens", None)) is not None # openai + or (prompt_tokens := getattr(usage, "inputTokens", None)) is not None # bedrock + or (prompt_tokens := getattr(usage, "prompt_token_count", None)) is not None # gemini + ): + model_usage["input"] = prompt_tokens + model_usage["input_cost"] = prompt_tokens * LLMS_COST[MODEL_ID]["input_cost"] if MODEL_ID in LLMS_COST.keys() else 0 + + if ( + (completion_tokens := getattr(usage, "completion_tokens", None)) is not None # openai + or (completion_tokens := getattr(usage, "outputTokens", None)) is not None # bedrock + or (completion_tokens := getattr(usage, "candidates_token_count", None)) is not None # gemini + ): + model_usage["output"] = completion_tokens + model_usage["output_cost"] = completion_tokens * LLMS_COST[MODEL_ID]["input_cost"] if MODEL_ID in LLMS_COST.keys() else 0 + if ( + (total_tokens := getattr(usage, "total_tokens", None)) is not None # openai + or (total_tokens := getattr(usage, "totalTokens", None)) is not None # bedrock + or (total_tokens := getattr(usage, "total_token_count", None)) is not None # gemini + ): + model_usage["total"] = total_tokens + model_usage["total_cost"] = model_usage["input_cost"] + model_usage["output_cost"] + + return model_usage + + +def _get_token_counts_from_mapping( + usage_mapping: Mapping[str, Any], +) -> ModelUsage: + model_usage: ModelUsage = { + "unit": "TOKENS", + "input": None, + "output": None, + "total": None, + "input_cost": None, + "output_cost": None, + "total_cost": None, + } + if ( + (prompt_tokens := usage_mapping.get("prompt_tokens")) is not None # openai + or (prompt_tokens := usage_mapping.get("inputTokens")) is not None # bedrock + or (prompt_tokens := usage_mapping.get("prompt_token_count")) is not None # gemini + ): + model_usage["input"] = prompt_tokens + model_usage["input_cost"] = prompt_tokens * LLMS_COST[MODEL_ID]["input_cost"] if MODEL_ID in LLMS_COST.keys() else 0 + + if ( + (completion_tokens := usage_mapping.get("completion_tokens")) is not None # openai + or (completion_tokens := usage_mapping.get("outputTokens")) is not None # bedrock + or (completion_tokens := usage_mapping.get("candidates_token_count")) is not None # gemini + ): + model_usage["output"] = completion_tokens + model_usage["output_cost"] = completion_tokens * LLMS_COST[MODEL_ID]["input_cost"] if MODEL_ID in LLMS_COST.keys() else 0 + if ( + (total_tokens := usage_mapping.get("total_tokens")) is not None # openai + or (total_tokens := usage_mapping.get("totalTokens")) is not None # bedrock + or (total_tokens := usage_mapping.get("total_token_count")) is not None # gemini + ): + model_usage["total"] = total_tokens + model_usage["total_cost"] = model_usage["input_cost"] + model_usage["output_cost"] + + return model_usage diff --git a/apps/chatbot/src/modules/models.py b/apps/chatbot/src/modules/models.py index 986a92842e..41abfc642e 100644 --- a/apps/chatbot/src/modules/models.py +++ b/apps/chatbot/src/modules/models.py @@ -1,9 +1,5 @@ import os -import logging - -from llama_index.core.instrumentation import get_dispatcher -from llama_index.core.instrumentation.event_handlers import BaseEventHandler -from llama_index.core.instrumentation.events.llm import LLMCompletionEndEvent, LLMChatEndEvent +from logging import getLogger from llama_index.llms.bedrock_converse import BedrockConverse from llama_index.embeddings.bedrock import BedrockEmbedding @@ -17,15 +13,16 @@ from src.modules.utils import get_ssm_parameter load_dotenv() +logger = getLogger(__name__) PROVIDER = os.getenv("CHB_PROVIDER", "google") assert PROVIDER in ["aws", "google"] - GOOGLE_API_KEY = get_ssm_parameter(name=os.getenv("CHB_GOOGLE_API_KEY")) AWS_ACCESS_KEY_ID = os.getenv("CHB_AWS_ACCESS_KEY_ID") AWS_SECRET_ACCESS_KEY = os.getenv("CHB_AWS_SECRET_ACCESS_KEY") -AWS_BEDROCK_REGION = os.getenv("CHB_AWS_BEDROCK_REGION") +AWS_BEDROCK_LLM_REGION = os.getenv("CHB_AWS_BEDROCK_LLM_REGION") +AWS_BEDROCK_EMBED_REGION = os.getenv("CHB_AWS_BEDROCK_EMBED_REGION") AWS_GUARDRAIL_ID = os.getenv("CHB_AWS_GUARDRAIL_ID") AWS_GUARDRAIL_VERSION = os.getenv("CHB_AWS_GUARDRAIL_VERSION") @@ -38,24 +35,6 @@ def get_llm(): if PROVIDER == "aws": - - class ModelEventHandler(BaseEventHandler): - @classmethod - def class_name(cls) -> str: - """Class name.""" - return "ModelEventHandler" - - def handle(self, event) -> None: - """Logic for handling event.""" - if isinstance(event, (LLMCompletionEndEvent, LLMChatEndEvent)): - logging.info(f"[{MODEL_ID}] Bedrock request id: {event.response.raw["ResponseMetadata"]["RequestId"]}") - logging.info(f"[{MODEL_ID}] Stop Reason: {event.response.raw["stopReason"]}") - logging.info(f"[{MODEL_ID}] Input Tokens: {event.response.raw["usage"]["inputTokens"]}") - logging.info(f"[{MODEL_ID}] Output Tokens: {event.response.raw["usage"]["outputTokens"]}") - logging.info(f"[{MODEL_ID}] Latency (ms): {event.response.raw["metrics"]["latencyMs"]}") - - root_dispatcher = get_dispatcher() - root_dispatcher.add_event_handler(ModelEventHandler()) llm = BedrockConverse( model=MODEL_ID, @@ -63,10 +42,11 @@ def handle(self, event) -> None: max_tokens=int(MODEL_MAXTOKENS), aws_access_key_id=AWS_ACCESS_KEY_ID, aws_secret_access_key=AWS_SECRET_ACCESS_KEY, - region_name=AWS_BEDROCK_REGION + region_name=AWS_BEDROCK_LLM_REGION ) else: + llm = Gemini( model=MODEL_ID, temperature=float(MODEL_TEMPERATURE), @@ -80,7 +60,7 @@ def handle(self, event) -> None: api_key=GOOGLE_API_KEY, ) - logging.info(f"[models.py - get_llm] {MODEL_ID} LLM loaded successfully!") + logger.info(f"{MODEL_ID} LLM loaded successfully!") return llm @@ -92,13 +72,13 @@ def get_embed_model(): model_name = EMBED_MODEL_ID, aws_access_key_id=AWS_ACCESS_KEY_ID, aws_secret_access_key=AWS_SECRET_ACCESS_KEY, - region_name=AWS_BEDROCK_REGION + region_name=AWS_BEDROCK_EMBED_REGION ) else: embed_model = GeminiEmbedding( api_key=GOOGLE_API_KEY, model_name=EMBED_MODEL_ID, ) - logging.info(f"[models.py - get_embed_model] {EMBED_MODEL_ID} embegging model loaded successfully!") + logger.info(f"{EMBED_MODEL_ID} embegging model loaded successfully!") return embed_model diff --git a/apps/chatbot/src/modules/presidio.py b/apps/chatbot/src/modules/presidio.py index ef0122d88f..a73471e26d 100644 --- a/apps/chatbot/src/modules/presidio.py +++ b/apps/chatbot/src/modules/presidio.py @@ -1,6 +1,5 @@ -import logging -from pathlib import Path -from typing import Any, Dict, List, Union +from logging import getLogger +from typing import Any, Dict, List from langdetect import detect_langs from presidio_anonymizer.operators import Operator, OperatorType @@ -11,6 +10,9 @@ from presidio_anonymizer.entities import OperatorConfig +logger = getLogger(__name__) + + # see supported entities by Presidio with their description at: https://microsoft.github.io/presidio/supported_entities/ GLOBAL_ENTITIES = [ "CREDIT_CARD", @@ -130,17 +132,17 @@ def detect_language(self, text: str) -> str: lang_list.append(detected_lang.lang) if not lang_list: - logging.warning("[presidio.py - detect_language] No detected language.") + logger.warning("No detected language.") lang = "it" elif "it" in lang_list: lang = "it" else: lang = lang_list[0] except: - logging.warning("[presidio.py - detect_language] No detected language.") + logger.warning("No detected language.") lang = "it" - logging.info(f"[presidio.py - detect_language] Set presidio to detect PII in {lang} language.") + logger.debug(f"Set presidio to detect PII in {lang} language.") return lang diff --git a/apps/chatbot/src/modules/test_chatbot.py b/apps/chatbot/src/modules/test_chatbot.py index 9c05322002..88220520a4 100644 --- a/apps/chatbot/src/modules/test_chatbot.py +++ b/apps/chatbot/src/modules/test_chatbot.py @@ -1,11 +1,15 @@ import os +import re import yaml -import logging +from logging import getLogger from pathlib import Path -from src.modules.chatbot import Chatbot +from src.modules.vector_database import REDIS_CLIENT +from src.modules.models import get_llm, get_embed_model +from src.modules.chatbot import Chatbot, LANGFUSE -logging.getLogger().setLevel(os.getenv("LOG_LEVEL", "INFO")) + +logger = getLogger(__name__) CWF = Path(__file__) @@ -15,18 +19,45 @@ CHATBOT = Chatbot(params=PARAMS, prompts=PROMPTS) +def test_connection_redis(): + flag = False + try: + REDIS_CLIENT.ping() + flag = True + except Exception as e: + logger.error(e) + + assert flag == True + + +def test_connection_langfuse(): + assert LANGFUSE.auth_check() == True + + +def test_cloud_connection(): + + flag = False + try: + _ = get_llm() + _ = get_embed_model() + flag = True + except Exception as e: + logger.error(e) + + assert flag == True + + def test_prompt_templates(): - qa_prompt_tmpl, ref_prompt_tmpl, condense_prompt_tmpl = CHATBOT._get_prompt_templates() + for prompt_str, template in zip(PROMPTS.values(), CHATBOT._get_prompt_templates()): + vars_str = re.findall(r'\{(.*?)\}', prompt_str) + vars_tmp = list(template.template_var_mappings.keys()) + assert vars_str == vars_tmp - p1 = PROMPTS["qa_prompt_str"].format(context_str="aaaaa", query_str="bbbbb") - p2 = qa_prompt_tmpl.format(context_str="aaaaa", query_str="bbbbb") - p3 = PROMPTS["refine_prompt_str"].format(existing_answer="aaaaa", context_msg="bbbbb") - p4 = ref_prompt_tmpl.format(existing_answer="aaaaa", context_msg="bbbbb") - p5 = PROMPTS["condense_prompt_str"].format(chat_history="aaaaa", question="bbbbb") - p6 = condense_prompt_tmpl.format(chat_history="aaaaa", question="bbbbb") - assert p1 == p2 and p3 == p4 and p5 == p6 +def test_pii_mask(): + masked_str = CHATBOT.mask_pii("Il mio nome e' Mario Rossi") + assert masked_str == "Il mio nome e' " def test_messages_to_chathistory(): @@ -34,8 +65,6 @@ def test_messages_to_chathistory(): chat_history = CHATBOT._messages_to_chathistory() assert len(chat_history) == 1 - ###########################3 - messages = [ {"question": "aaaa", "answer": "bbbb"}, {"question": "cccc", "answer": "dddd"}, @@ -46,26 +75,33 @@ def test_messages_to_chathistory(): assert len(chat_history) == 2 * len(messages) + 1 -def test_pii_mask(): - masked_str = CHATBOT.mask_pii("Il mio nome e' Mario Rossi") - assert masked_str == "Il mio nome e' " - - def test_chat_generation(): query_str = "GPD gestisce i pagamenti spontanei?" try: - res = CHATBOT.chat_generate(query_str=query_str) res = CHATBOT.chat_generate( - query_str="sai dirmi di più?", - messages=[{ - "question": query_str, - "answer": res - }] + query_str = query_str, + trace_id = "abcde", + user_id = "user-test", + session_id = "session-test", + tags = "test" ) + res = CHATBOT.chat_generate( + query_str = "sai dirmi di più?", + trace_id = "fghik", + messages = [{"question": query_str, "answer": res}], + user_id = "user-test", + session_id = "session-test", + tags = "test" + ) + + trace1 = CHATBOT.get_trace("abcde") + print("trace 1:", trace1) + trace2 = CHATBOT.get_trace("fghik") + print("trace 2:", trace2) except Exception as e: - logging.error(e) + logger.error(e) res = f"Something went wrong!" - assert res != f"Something went wrong!" \ No newline at end of file + assert res != f"Something went wrong!" diff --git a/apps/chatbot/src/modules/utils.py b/apps/chatbot/src/modules/utils.py index 1e7e1bd1d3..88e335e3ab 100644 --- a/apps/chatbot/src/modules/utils.py +++ b/apps/chatbot/src/modules/utils.py @@ -1,10 +1,10 @@ import os import boto3 -import logging +from logging import getLogger from dotenv import load_dotenv load_dotenv() - +logger = getLogger(__name__) AWS_ACCESS_KEY_ID = os.getenv("CHB_AWS_ACCESS_KEY_ID") AWS_SECRET_ACCESS_KEY = os.getenv("CHB_AWS_SECRET_ACCESS_KEY") @@ -26,7 +26,7 @@ def get_ssm_parameter(name: str, default: str | None = None) -> str | None: :return: The value of the requested parameter. """ - logging.debug(f"[utils.py - get_ssm_parameter] Getting parameter {name} from SSM") + logger.debug(f"Getting parameter {name} from SSM") try: # Get the requested parameter response = SSM_CLIENT.get_parameter( @@ -34,16 +34,16 @@ def get_ssm_parameter(name: str, default: str | None = None) -> str | None: WithDecryption=True ) except SSM_CLIENT.exceptions.ParameterNotFound: - logging.warning(f"Parameter {name} not found in SSM, returning default") + logger.warning(f"Parameter {name} not found in SSM, returning default") return default - logging.debug(f"[utils.py - get_ssm_parameter] Parameter {name} retrieved from SSM") + logger.debug(f"Parameter {name} retrieved from SSM") return response["Parameter"]["Value"] def put_ssm_parameter(name: str, value: str) -> None: - logging.debug(f"[utils.py - put_ssm_parameter] Putting parameter {name} to SSM") + logger.debug(f"Putting parameter {name} to SSM") try: # Get the requested parameter SSM_CLIENT.put_parameter( @@ -52,5 +52,5 @@ def put_ssm_parameter(name: str, value: str) -> None: Overwrite=True ) except Exception as e: - logging.error(e) - + logger.error(e) + \ No newline at end of file diff --git a/apps/chatbot/src/modules/vector_database.py b/apps/chatbot/src/modules/vector_database.py index 425936107a..c4995b26b5 100644 --- a/apps/chatbot/src/modules/vector_database.py +++ b/apps/chatbot/src/modules/vector_database.py @@ -43,17 +43,9 @@ PROVIDER = os.getenv("CHB_PROVIDER") assert PROVIDER in ["google", "aws"] -INDEX_ID = get_ssm_parameter(os.getenv("CHB_LLAMAINDEX_INDEX_ID"), 'default-index') - -def calculate_new_index_id(current_index_id): - if current_index_id == 'default-index': - return current_index_id - TODAY = datetime.now(pytz.timezone("Europe/Rome")).strftime("%Y-%m-%d--%H:%M:%S") - rtn = f"index--{TODAY}" - return rtn - -NEW_INDEX_ID = calculate_new_index_id(INDEX_ID) - +TODAY = datetime.now(pytz.timezone("Europe/Rome")).strftime("%Y-%m-%d--%H:%M:%S") +INDEX_ID = get_ssm_parameter(os.getenv("CHB_LLAMAINDEX_INDEX_ID"), "default-index") +NEW_INDEX_ID = f"index--{TODAY}" if INDEX_ID != "default-index" else "default-index" REDIS_URL = os.getenv("CHB_REDIS_URL") WEBSITE_URL = os.getenv("CHB_WEBSITE_URL") REDIS_CLIENT = Redis.from_url(REDIS_URL, socket_timeout=10) @@ -63,7 +55,8 @@ def calculate_new_index_id(current_index_id): EMBED_MODEL_ID = os.getenv("CHB_EMBED_MODEL_ID") EMBEDDING_DIMS = { "models/text-embedding-004": 768, - "cohere.embed-multilingual-v3": 1024 + "cohere.embed-multilingual-v3": 1024, + "amazon.titan-embed-text-v2:0": 1024 } REDIS_SCHEMA = IndexSchema.from_dict({ "index": {"name": f"{INDEX_ID}", "prefix": f"{INDEX_ID}/vector"}, @@ -169,6 +162,7 @@ def create_documentation( if file in dynamic_htmls or "/webinars/" in file or "/api/" in file: url = file.replace(documentation_dir, f"{website_url}/").replace(".html", "") + driver = webdriver.Chrome( options=driver_options, service=driver_service @@ -224,7 +218,7 @@ def build_automerging_index_redis( chunk_overlap: int ) -> VectorStoreIndex: - logger.info(f"Storing vector index and hash table on Redis hash_table_{NEW_INDEX_ID}..") + logger.info("Storing vector index and hash table on Redis..") Settings.llm = llm Settings.embed_model = embed_model @@ -240,7 +234,7 @@ def build_automerging_index_redis( key=key, val=value ) - logger.info(f"[vector_database.py - build_automerging_index_redis] hash_table_{NEW_INDEX_ID} is now on Redis.") + logger.info(f"hash_table_{NEW_INDEX_ID} is now on Redis.") logger.info(f"Creating index {NEW_INDEX_ID} ...") nodes = Settings.node_parser.get_nodes_from_documents(documents) @@ -277,7 +271,7 @@ def build_automerging_index_redis( ) automerging_index.set_index_id(NEW_INDEX_ID) put_ssm_parameter(os.getenv("CHB_LLAMAINDEX_INDEX_ID"), NEW_INDEX_ID) - logger.info(f"Created vector index ${NEW_INDEX_ID} successfully and stored on Redis.") + logger.info("Created vector index successfully and stored on Redis.") delete_old_index() @@ -325,7 +319,7 @@ def load_automerging_index_redis( def delete_old_index(): - if INDEX_ID: # is in ssm there is nothing, INDEX_ID = None + if INDEX_ID != "default-index": # if in ssm there is nothing, INDEX_ID = None for key in REDIS_CLIENT.scan_iter(): if f"{INDEX_ID}/vector" in str(key) or f"hash_table_{INDEX_ID}" == str(key): REDIS_CLIENT.delete(key) diff --git a/apps/chatbot/src/webapp/app.py b/apps/chatbot/src/webapp/app.py deleted file mode 100644 index 3965f60c3e..0000000000 --- a/apps/chatbot/src/webapp/app.py +++ /dev/null @@ -1,82 +0,0 @@ -import argparse -import time -import yaml -import logging -import gradio as gr -from src.modules.chatbot import Chatbot - - -logging.basicConfig(level=logging.INFO) - - -def print_like_dislike(x: gr.LikeData): - print(x.index, x.value, x.liked) - - -def add_message(history, message): - for x in message["files"]: - history.append(((x,), None)) - if message["text"] is not None: - history.append((message["text"], None)) - return history, gr.MultimodalTextbox(value=None, interactive=False) - - -def bot(history): - - response_str = chatbot.generate(history[-1][0]) - history[-1][1] = "" - for character in response_str: - history[-1][1] += character - time.sleep(0.02) - yield history - - -with gr.Blocks() as demo: - - gr.Markdown("# PagoPA Chatbot") - - gr_chatbot = gr.Chatbot( - [], - elem_id="chatbot", - avatar_images=( - "src/webapp/user.png", - "src/webapp/chatbot.png" - ), - bubble_full_width=False - ) - - chat_input = gr.MultimodalTextbox( - interactive=True, - file_types=None, - placeholder="Enter message..", - show_label=False - ) - - chat_msg = chat_input.submit(add_message, [gr_chatbot, chat_input], [gr_chatbot, chat_input]) - bot_msg = chat_msg.then(bot, gr_chatbot, gr_chatbot, api_name="bot_response") - bot_msg.then(lambda: gr.MultimodalTextbox(interactive=True), None, [chat_input]) - - gr_chatbot.like(print_like_dislike, None, None) - - clear = gr.ClearButton( - value="Clear chat", - components=[chat_input, gr_chatbot] - ) - -demo.queue() - - -if __name__ == "__main__": - - parser = argparse.ArgumentParser() - parser.add_argument("--params", type=str, default="config/params.yaml", help="params path") - parser.add_argument("--prompts", type=str, default="config/prompts.yaml", help="prompts path") - args = parser.parse_args() - - # load parameters - params = yaml.safe_load(open(args.params, "r")) - prompts = yaml.safe_load(open(args.prompts, "r")) - - chatbot = Chatbot(params, prompts) - - demo.launch() diff --git a/apps/chatbot/src/webapp/chatbot.png b/apps/chatbot/src/webapp/chatbot.png deleted file mode 100644 index 02034479b9..0000000000 Binary files a/apps/chatbot/src/webapp/chatbot.png and /dev/null differ diff --git a/apps/chatbot/src/webapp/user.png b/apps/chatbot/src/webapp/user.png deleted file mode 100644 index 4cc32ca73a..0000000000 Binary files a/apps/chatbot/src/webapp/user.png and /dev/null differ diff --git a/apps/infrastructure/src/modules/chatbot/cognito_user.tf b/apps/infrastructure/src/modules/chatbot/cognito_user.tf index 797f39629f..88b35aaa77 100644 --- a/apps/infrastructure/src/modules/chatbot/cognito_user.tf +++ b/apps/infrastructure/src/modules/chatbot/cognito_user.tf @@ -121,7 +121,7 @@ resource "aws_cognito_user_pool_client" "langfuse" { } resource "aws_cognito_user_pool_domain" "monitoring" { - domain = "monitoring" + domain = "monitoring${var.environment}" user_pool_id = aws_cognito_user_pool.monitoring.id } diff --git a/apps/infrastructure/src/modules/chatbot/data.tf b/apps/infrastructure/src/modules/chatbot/data.tf index a895dd6a5d..6aa3e88439 100644 --- a/apps/infrastructure/src/modules/chatbot/data.tf +++ b/apps/infrastructure/src/modules/chatbot/data.tf @@ -48,7 +48,9 @@ data "aws_iam_policy_document" "lambda_dynamodb_policy" { module.dynamodb_chatbot_queries.dynamodb_table_arn, "${module.dynamodb_chatbot_queries.dynamodb_table_arn}/*", module.dynamodb_chatbot_sessions.dynamodb_table_arn, - "${module.dynamodb_chatbot_sessions.dynamodb_table_arn}/*" + "${module.dynamodb_chatbot_sessions.dynamodb_table_arn}/*", + module.dynamodb_chatbot_salts.dynamodb_table_arn, + "${module.dynamodb_chatbot_salts.dynamodb_table_arn}/*" ] } } diff --git a/apps/infrastructure/src/modules/chatbot/dynamodb.tf b/apps/infrastructure/src/modules/chatbot/dynamodb.tf index 71183035be..0a2160b8d4 100644 --- a/apps/infrastructure/src/modules/chatbot/dynamodb.tf +++ b/apps/infrastructure/src/modules/chatbot/dynamodb.tf @@ -71,3 +71,21 @@ module "dynamodb_chatbot_sessions" { } ] } + +module "dynamodb_chatbot_salts" { + source = "git::github.com/terraform-aws-modules/terraform-aws-dynamodb-table.git?ref=715399dbe24f6443820bf5de80f6100b35d56355" # v4.0.0 + + billing_mode = "PAY_PER_REQUEST" + deletion_protection_enabled = false + + name = "${local.prefix}-salts" + hash_key = "sessionId" + server_side_encryption_enabled = true + + attributes = [ + { + name = "sessionId" + type = "S" + } + ] +} diff --git a/apps/infrastructure/src/modules/chatbot/lambda_chatbot.tf b/apps/infrastructure/src/modules/chatbot/lambda_chatbot.tf index 5a7331ede0..ce85cb71d6 100644 --- a/apps/infrastructure/src/modules/chatbot/lambda_chatbot.tf +++ b/apps/infrastructure/src/modules/chatbot/lambda_chatbot.tf @@ -3,7 +3,6 @@ locals { CHB_AWS_S3_BUCKET = module.s3_bucket_llamaindex.s3_bucket_id CHB_AWS_GUARDRAIL_ID = awscc_bedrock_guardrail.guardrail.guardrail_id CHB_AWS_GUARDRAIL_VERSION = awscc_bedrock_guardrail_version.guardrail.version - CHB_AWS_BEDROCK_REGION = var.aws_chatbot_region CHB_REDIS_URL = "redis://${module.nlb.dns_name}:${var.ecs_redis.port}" CHB_WEBSITE_URL = "https://${var.dns_domain_name}" CORS_DOMAINS = var.environment == "dev" ? jsonencode(["https://www.${var.dns_domain_name}", "https://${var.dns_domain_name}", "http://localhost:3000"]) : jsonencode(["https://www.${var.dns_domain_name}", "https://${var.dns_domain_name}"]) @@ -17,14 +16,16 @@ locals { # Be extremely careful when changing the provider # both the generation and the embedding models would be changed # embeddings size change would break the application and requires reindexing - CHB_PROVIDER = "aws" - CHB_MODEL_ID = "mistral.mistral-large-2402-v1:0" - CHB_EMBED_MODEL_ID = "cohere.embed-multilingual-v3" - CHB_MODEL_MAXTOKENS = "768" - CHB_MODEL_TEMPERATURE = "0.3" - CHB_GOOGLE_API_KEY = module.google_api_key_ssm_parameter.ssm_parameter_name - CHB_QUERY_TABLE_PREFIX = local.prefix - CHB_LLAMAINDEX_INDEX_ID = module.index_id_ssm_parameter.ssm_parameter_name + CHB_PROVIDER = "aws" + CHB_AWS_BEDROCK_LLM_REGION = var.aws_chatbot_region + CHB_MODEL_ID = "mistral.mistral-large-2402-v1:0" + CHB_AWS_BEDROCK_EMBED_REGION = "eu-central-1" + CHB_EMBED_MODEL_ID = "amazon.titan-embed-text-v2:0" + CHB_MODEL_MAXTOKENS = "768" + CHB_MODEL_TEMPERATURE = "0.3" + CHB_GOOGLE_API_KEY = module.google_api_key_ssm_parameter.ssm_parameter_name + CHB_QUERY_TABLE_PREFIX = local.prefix + CHB_LLAMAINDEX_INDEX_ID = module.index_id_ssm_parameter.ssm_parameter_name } } diff --git a/apps/nextjs-website/.tmp-docs b/apps/nextjs-website/.tmp-docs new file mode 160000 index 0000000000..ff6582f21f --- /dev/null +++ b/apps/nextjs-website/.tmp-docs @@ -0,0 +1 @@ +Subproject commit ff6582f21f24f5fcddc910b11b5a92aff877733d diff --git a/package-lock.json b/package-lock.json index 5e054c02bf..cb7c44223b 100644 --- a/package-lock.json +++ b/package-lock.json @@ -19222,6 +19222,66 @@ "url": "https://github.com/sponsors/isaacs" } }, + "node_modules/@next/swc-darwin-arm64": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-darwin-arm64/-/swc-darwin-arm64-13.4.19.tgz", + "integrity": "sha512-vv1qrjXeGbuF2mOkhkdxMDtv9np7W4mcBtaDnHU+yJG+bBwa6rYsYSCI/9Xm5+TuF5SbZbrWO6G1NfTh1TMjvQ==", + "cpu": [ + "arm64" + ], + "optional": true, + "os": [ + "darwin" + ], + "engines": { + "node": ">= 10" + } + }, + "node_modules/@next/swc-darwin-x64": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-darwin-x64/-/swc-darwin-x64-13.4.19.tgz", + "integrity": "sha512-jyzO6wwYhx6F+7gD8ddZfuqO4TtpJdw3wyOduR4fxTUCm3aLw7YmHGYNjS0xRSYGAkLpBkH1E0RcelyId6lNsw==", + "cpu": [ + "x64" + ], + "optional": true, + "os": [ + "darwin" + ], + "engines": { + "node": ">= 10" + } + }, + "node_modules/@next/swc-linux-arm64-gnu": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-gnu/-/swc-linux-arm64-gnu-13.4.19.tgz", + "integrity": "sha512-vdlnIlaAEh6H+G6HrKZB9c2zJKnpPVKnA6LBwjwT2BTjxI7e0Hx30+FoWCgi50e+YO49p6oPOtesP9mXDRiiUg==", + "cpu": [ + "arm64" + ], + "optional": true, + "os": [ + "linux" + ], + "engines": { + "node": ">= 10" + } + }, + "node_modules/@next/swc-linux-arm64-musl": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-linux-arm64-musl/-/swc-linux-arm64-musl-13.4.19.tgz", + "integrity": "sha512-aU0HkH2XPgxqrbNRBFb3si9Ahu/CpaR5RPmN2s9GiM9qJCiBBlZtRTiEca+DC+xRPyCThTtWYgxjWHgU7ZkyvA==", + "cpu": [ + "arm64" + ], + "optional": true, + "os": [ + "linux" + ], + "engines": { + "node": ">= 10" + } + }, "node_modules/@next/swc-linux-x64-gnu": { "version": "13.4.19", "cpu": [ @@ -19250,6 +19310,51 @@ "node": ">= 10" } }, + "node_modules/@next/swc-win32-arm64-msvc": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-win32-arm64-msvc/-/swc-win32-arm64-msvc-13.4.19.tgz", + "integrity": "sha512-bUfDevQK4NsIAHXs3/JNgnvEY+LRyneDN788W2NYiRIIzmILjba7LaQTfihuFawZDhRtkYCv3JDC3B4TwnmRJw==", + "cpu": [ + "arm64" + ], + "optional": true, + "os": [ + "win32" + ], + "engines": { + "node": ">= 10" + } + }, + "node_modules/@next/swc-win32-ia32-msvc": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-win32-ia32-msvc/-/swc-win32-ia32-msvc-13.4.19.tgz", + "integrity": "sha512-Y5kikILFAr81LYIFaw6j/NrOtmiM4Sf3GtOc0pn50ez2GCkr+oejYuKGcwAwq3jiTKuzF6OF4iT2INPoxRycEA==", + "cpu": [ + "ia32" + ], + "optional": true, + "os": [ + "win32" + ], + "engines": { + "node": ">= 10" + } + }, + "node_modules/@next/swc-win32-x64-msvc": { + "version": "13.4.19", + "resolved": "https://registry.npmjs.org/@next/swc-win32-x64-msvc/-/swc-win32-x64-msvc-13.4.19.tgz", + "integrity": "sha512-YzA78jBDXMYiINdPdJJwGgPNT3YqBNNGhsthsDoWHL9p24tEJn9ViQf/ZqTbwSpX/RrkPupLfuuTH2sf73JBAw==", + "cpu": [ + "x64" + ], + "optional": true, + "os": [ + "win32" + ], + "engines": { + "node": ">= 10" + } + }, "node_modules/@nodelib/fs.scandir": { "version": "2.1.5", "license": "MIT",