Merge branch 'main' into mmqna-phase3

Author: ashahba

AgentQnA/README.md

@@ -1,5 +1,13 @@
 # Agents for Question Answering
 
+## Table of contents
+
+1. [Overview](#overview)
+2. [Deploy with Docker](#deploy-with-docker)
+3. [Launch the UI](#launch-the-ui)
+4. [Validate Services](#validate-services)
+5. [Register Tools](#how-to-register-other-tools-with-the-ai-agent)
+
 ## Overview
 
 This example showcases a hierarchical multi-agent system for question-answering applications. The architecture diagram below shows a supervisor agent that interfaces with the user and dispatches tasks to two worker agents to gather information and come up with answers. The worker RAG agent uses the retrieval tool to retrieve relevant documents from a knowledge base - a vector database. The worker SQL agent retrieves relevant data from a SQL database. Although not included in this example by default, other tools such as a web search tool or a knowledge graph query tool can be used by the supervisor agent to gather information from additional sources.
@@ -134,7 +142,7 @@ source $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/set_env.sh
 source $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon/set_env.sh
 ```
 
-### 3. Launch the multi-agent system. </br>
+### 2. Launch the multi-agent system. </br>
 
 Two options are provided for the `llm_engine` of the agents: 1. open-source LLMs on Gaudi, 2. OpenAI models via API calls.
 
@@ -151,11 +159,19 @@ cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
 docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml up -d
 ```
 
+To enable Open Telemetry Tracing, compose.telemetry.yaml file need to be merged along with default compose.yaml file.
+Gaudi example with Open Telemetry feature:
+
+```bash
+cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/hpu/gaudi/
+docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose.yaml -f compose.telemetry.yaml up -d
+```
+
 ##### [Optional] Web Search Tool Support
 
 <details>
 <summary> Instructions </summary>
-A web search tool is supported in this example and can be enabled by running docker compose with the `compose.webtool.yaml` file.  
+A web search tool is supported in this example and can be enabled by running docker compose with the `compose.webtool.yaml` file.
 The Google Search API is used. Follow the [instructions](https://python.langchain.com/docs/integrations/tools/google_search) to create an API key and enable the Custom Search API on a Google account. The environment variables `GOOGLE_CSE_ID` and `GOOGLE_API_KEY` need to be set.
 
 ```bash
@@ -179,7 +195,7 @@ cd $WORKDIR/GenAIExamples/AgentQnA/docker_compose/intel/cpu/xeon
 docker compose -f $WORKDIR/GenAIExamples/DocIndexRetriever/docker_compose/intel/cpu/xeon/compose.yaml -f compose_openai.yaml up -d
 ```
 
-### 4. Ingest Data into the vector database
+### 3. Ingest Data into the vector database
 
 The `run_ingest_data.sh` script will use an example jsonl file to ingest example documents into a vector database. Other ways to ingest data and other types of documents supported can be found in the OPEA dataprep microservice located in the opea-project/GenAIComps repo.
 

AgentQnA/docker_compose/amd/gpu/rocm/README.md

@@ -211,11 +211,18 @@ All containers should be running and should not restart:
 
 ##### If you use TGI:
 
-- agentqna-tgi-service
-- whisper-service
-- speecht5-service
-- agentqna-backend-server
-- agentqna-ui-server
+- dataprep-redis-server
+- doc-index-retriever-server
+- embedding-server
+- rag-agent-endpoint
+- react-agent-endpoint
+- redis-vector-db
+- reranking-tei-xeon-server
+- retriever-redis-server
+- sql-agent-endpoint
+- tei-embedding-server
+- tei-reranking-server
+- tgi-service
 
 ---
 
@@ -229,7 +236,7 @@ All containers should be running and should not restart:
 DATA='{"model": "Intel/neural-chat-7b-v3-3t", '\
 '"messages": [{"role": "user", "content": "What is Deep Learning?"}], "max_tokens": 256}'
 
-curl http://${HOST_IP}:${AUDIOQNA_VLLM_SERVICE_PORT}/v1/chat/completions \
+curl http://${HOST_IP}:${VLLM_SERVICE_PORT}/v1/chat/completions \
   -X POST \
   -d "$DATA" \
   -H 'Content-Type: application/json'
@@ -270,7 +277,7 @@ then we consider the vLLM service to be successfully launched
 DATA='{"inputs":"What is Deep Learning?",'\
 '"parameters":{"max_new_tokens":256,"do_sample": true}}'
 
-curl http://${HOST_IP}:${AUDIOQNA_TGI_SERVICE_PORT}/generate \
+curl http://${HOST_IP}:${TGI_SERVICE_PORT}/generate \
   -X POST \
   -d "$DATA" \
   -H 'Content-Type: application/json'
@@ -287,48 +294,49 @@ Checking the response from the service. The response should be similar to JSON:
 If the service response has a meaningful response in the value of the "generated_text" key,
 then we consider the TGI service to be successfully launched
 
-### 2. Validate MegaServices
+### 2. Validate Agent Services
 
-Test the AgentQnA megaservice by recording a .wav file, encoding the file into the base64 format, and then sending the
-base64 string to the megaservice endpoint. The megaservice will return a spoken response as a base64 string. To listen
-to the response, decode the base64 string and save it as a .wav file.
+#### Validate Rag Agent Service
 
 ```bash
-# voice can be "default" or "male"
-curl http://${host_ip}:3008/v1/agentqna \
-  -X POST \
-  -d '{"audio": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA", "max_tokens":64, "voice":"default"}' \
-  -H 'Content-Type: application/json' | sed 's/^"//;s/"$//' | base64 -d > output.wav
+export agent_port=${WORKER_RAG_AGENT_PORT}
+prompt="Tell me about Michael Jackson song Thriller"
+python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port
 ```
 
-### 3. Validate MicroServices
+The response must contain the meaningful text of the response to the request from the "prompt" variable
+
+#### Validate Sql Agent Service
 
 ```bash
-# whisper service
-curl http://${host_ip}:7066/v1/asr \
-  -X POST \
-  -d '{"audio": "UklGRigAAABXQVZFZm10IBIAAAABAAEARKwAAIhYAQACABAAAABkYXRhAgAAAAEA"}' \
-  -H 'Content-Type: application/json'
+export agent_port=${WORKER_SQL_AGENT_PORT}
+prompt="How many employees are there in the company?"
+python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --prompt "$prompt" --agent_role "worker" --ext_port $agent_port
+```
 
-# speecht5 service
-curl http://${host_ip}:7055/v1/tts \
-  -X POST \
-  -d '{"text": "Who are you?"}' \
-  -H 'Content-Type: application/json'
+The answer should make sense - "8 employees in the company"
+
+#### Validate React (Supervisor) Agent Service
+
+```bash
+export agent_port=${SUPERVISOR_REACT_AGENT_PORT}
+python3 ~/agentqna-install/GenAIExamples/AgentQnA/tests/test.py --agent_role "supervisor" --ext_port $agent_port --stream
 ```
 
-### 4. Stop application
+The response should contain "Iron Maiden"
+
+### 3. Stop application
 
 #### If you use vLLM
 
 ```bash
 cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-docker compose -f compose_vllm.yaml down
+bash stop_agent_service_vllm_rocm.sh
 ```
 
 #### If you use TGI
 
 ```bash
 cd ~/agentqna-install/GenAIExamples/AgentQnA/docker_compose/amd/gpu/rocm
-docker compose -f compose.yaml down
+bash stop_agent_service_tgi_rocm.sh
 ```

AgentQnA/docker_compose/intel/hpu/gaudi/compose.telemetry.yaml

@@ -0,0 +1,93 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+services:
+  tei-embedding-service:
+    command: --model-id ${EMBEDDING_MODEL_ID} --auto-truncate --otlp-endpoint $OTEL_EXPORTER_OTLP_TRACES_ENDPOINT
+  tei-reranking-service:
+    command: --model-id ${RERANK_MODEL_ID} --auto-truncate --otlp-endpoint $OTEL_EXPORTER_OTLP_TRACES_ENDPOINT
+  jaeger:
+    image: jaegertracing/all-in-one:1.67.0
+    container_name: jaeger
+    ports:
+      - "16686:16686"
+      - "4317:4317"
+      - "4318:4318"
+      - "9411:9411"
+    ipc: host
+    environment:
+      no_proxy: ${no_proxy}
+      http_proxy: ${http_proxy}
+      https_proxy: ${https_proxy}
+      COLLECTOR_ZIPKIN_HOST_PORT: 9411
+    restart: unless-stopped
+  prometheus:
+    image: prom/prometheus:v2.52.0
+    container_name: prometheus
+    user: root
+    volumes:
+      - ./prometheus.yaml:/etc/prometheus/prometheus.yaml
+      - ./prometheus_data:/prometheus
+    command:
+      - '--config.file=/etc/prometheus/prometheus.yaml'
+    ports:
+      - '9091:9090'
+    ipc: host
+    restart: unless-stopped
+  grafana:
+    image: grafana/grafana:11.0.0
+    container_name: grafana
+    volumes:
+      - ./grafana_data:/var/lib/grafana
+      - ./grafana/dashboards:/var/lib/grafana/dashboards
+      - ./grafana/provisioning:/etc/grafana/provisioning
+    user: root
+    environment:
+      GF_SECURITY_ADMIN_PASSWORD: admin
+      GF_RENDERING_CALLBACK_URL: http://grafana:3000/
+      GF_LOG_FILTERS: rendering:debug
+    depends_on:
+      - prometheus
+    ports:
+      - '3000:3000'
+    ipc: host
+    restart: unless-stopped
+  node-exporter:
+    image: prom/node-exporter
+    container_name: node-exporter
+    volumes:
+      - /proc:/host/proc:ro
+      - /sys:/host/sys:ro
+      - /:/rootfs:ro
+    command:
+      - '--path.procfs=/host/proc'
+      - '--path.sysfs=/host/sys'
+      - --collector.filesystem.ignored-mount-points
+      - "^/(sys|proc|dev|host|etc|rootfs/var/lib/docker/containers|rootfs/var/lib/docker/overlay2|rootfs/run/docker/netns|rootfs/var/lib/docker/aufs)($$|/)"
+    ports:
+      - 9100:9100
+    restart: always
+    deploy:
+      mode: global
+  gaudi-exporter:
+    image: vault.habana.ai/gaudi-metric-exporter/metric-exporter:1.19.2-32
+    container_name: gaudi-exporter
+    volumes:
+      - /proc:/host/proc:ro
+      - /sys:/host/sys:ro
+      - /:/rootfs:ro
+      - /dev:/dev
+    ports:
+      - 41612:41611
+    restart: always
+    deploy:
+      mode: global
+  worker-rag-agent:
+    environment:
+      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}
+  worker-sql-agent:
+    environment:
+      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}
+  supervisor-react-agent:
+    environment:
+      - TELEMETRY_ENDPOINT=${TELEMETRY_ENDPOINT}

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/dashboards/download_opea_dashboard.sh

@@ -0,0 +1,10 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+rm *.json
+wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/chatqna_megaservice_grafana.json
+mv chatqna_megaservice_grafana.json agentqna_microervices_grafana.json
+wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/vllm_grafana.json
+wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/tgi_grafana.json
+wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/node_grafana.json
+wget https://raw.githubusercontent.com/opea-project/GenAIEval/refs/heads/main/evals/benchmark/grafana/gaudi_grafana.json

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/provisioning/dashboards/local.yaml

@@ -0,0 +1,14 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+apiVersion: 1
+
+providers:
+- name: 'default'
+  orgId: 1
+  folder: ''
+  type: file
+  disableDeletion: false
+  updateIntervalSeconds: 10 #how often Grafana will scan for changed dashboards
+  options:
+    path: /var/lib/grafana/dashboards

AgentQnA/docker_compose/intel/hpu/gaudi/grafana/provisioning/datasources/datasource.yml

@@ -0,0 +1,54 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+# config file version
+apiVersion: 1
+
+# list of datasources that should be deleted from the database
+deleteDatasources:
+  - name: Prometheus
+    orgId: 1
+
+# list of datasources to insert/update depending
+# what's available in the database
+datasources:
+  # <string, required> name of the datasource. Required
+- name: Prometheus
+  # <string, required> datasource type. Required
+  type: prometheus
+  # <string, required> access mode. direct or proxy. Required
+  access: proxy
+  # <int> org id. will default to orgId 1 if not specified
+  orgId: 1
+  # <string> url
+  url: http://prometheus:9090
+  # <string> database password, if used
+  password:
+  # <string> database user, if used
+  user:
+  # <string> database name, if used
+  database:
+  # <bool> enable/disable basic auth
+  basicAuth: false
+  # <string> basic auth username, if used
+  basicAuthUser:
+  # <string> basic auth password, if used
+  basicAuthPassword:
+  # <bool> enable/disable with credentials headers
+  withCredentials:
+  # <bool> mark as default datasource. Max one per org
+  isDefault: true
+  # <map> fields that will be converted to json and stored in json_data
+  jsonData:
+     httpMethod: GET
+     graphiteVersion: "1.1"
+     tlsAuth: false
+     tlsAuthWithCACert: false
+  # <string> json object of data that will be encrypted.
+  secureJsonData:
+    tlsCACert: "..."
+    tlsClientCert: "..."
+    tlsClientKey: "..."
+  version: 1
+  # <bool> allow users to edit datasources from the UI.
+  editable: true

AgentQnA/docker_compose/intel/hpu/gaudi/prometheus.yaml

@@ -0,0 +1,55 @@
+# Copyright (C) 2025 Intel Corporation
+# SPDX-License-Identifier: Apache-2.0
+
+global:
+  scrape_interval: 5s
+  external_labels:
+    monitor: "my-monitor"
+scrape_configs:
+  - job_name: "prometheus"
+    static_configs:
+      - targets: ["prometheus:9090"]
+  - job_name: "vllm"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["vllm-gaudi-server:8000"]
+  - job_name: "tgi"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["tgi-gaudi-server:80"]
+  - job_name: "tei-embedding"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["tei-embedding-server:80"]
+  - job_name: "tei-reranking"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["tei-reranking-server:80"]
+  - job_name: "retriever"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["retriever:7000"]
+  - job_name: "dataprep-redis-service"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["dataprep-redis-service:5000"]
+  - job_name: "prometheus-node-exporter"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["node-exporter:9100"]
+  - job_name: "prometheus-gaudi-exporter"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["gaudi-exporter:41611"]
+  - job_name: "supervisor-react-agent"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["react-agent-endpoint:9090"]
+  - job_name: "worker-rag-agent"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["rag-agent-endpoint:9095"]
+  - job_name: "worker-sql-agent"
+    metrics_path: /metrics
+    static_configs:
+      - targets: ["sql-agent-endpoint:9096"]