Add AQUA skills directory for coding agents

skills/aqua-cli/SKILL.md

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+---
+name: aqua-cli
+description: Complete CLI reference for the ADS AQUA command-line interface (ads aqua). Covers all model, deployment, evaluation, and fine-tuning commands with full parameter documentation. Triggered when user asks about CLI commands, wants to run AQUA operations from terminal, or needs command syntax.
+user-invocable: true
+disable-model-invocation: false
+---
+
+# ADS AQUA CLI Reference
+
+The `ads aqua` CLI provides command-line access to all AI Quick Actions operations. It uses Python Fire under the hood.
+
+## Installation
+
+```bash
+pip install oracle-ads[aqua]
+# OR for development
+pip install -e ".[aqua]"
+```
+
+## Authentication Setup
+
+```bash
+# For OCI Notebook Sessions (Resource Principal)
+# No setup needed - automatic
+
+# For local development with security token
+export OCI_IAM_TYPE="security_token"
+export OCI_CONFIG_PROFILE=<your-profile>
+
+# For local development with API key
+export OCI_IAM_TYPE="api_key"
+export OCI_CONFIG_PROFILE=DEFAULT
+```
+
+---
+
+## Model Commands
+
+### List Models
+
+```bash
+ads aqua model list \
+  --compartment_id "ocid1.compartment.oc1..xxx"
+```
+
+### Get Model Details
+
+```bash
+ads aqua model get \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx"
+```
+
+### Register Model from HuggingFace
+
+```bash
+ads aqua model register \
+  --model "meta-llama/Llama-3.1-8B-Instruct" \
+  --os_path "oci://my-bucket@my-namespace/models/llama-3.1-8b/" \
+  --compartment_id "ocid1.compartment.oc1..xxx" \
+  --project_id "ocid1.datascienceproject.oc1.iad.xxx" \
+  --inference_container "odsc-vllm-serving" \
+  --download_from_hf True
+```
+
+Full parameter reference: `references/params.md`
+
+### Register from Object Storage
+
+```bash
+ads aqua model register \
+  --model "my-custom-model" \
+  --os_path "oci://my-bucket@my-namespace/models/custom-model/" \
+  --inference_container "odsc-vllm-serving"
+```
+
+### Register GGUF Model
+
+```bash
+ads aqua model register \
+  --model "TheBloke/Llama-2-7B-Chat-GGUF" \
+  --os_path "oci://my-bucket@my-namespace/models/llama2-gguf/" \
+  --inference_container "odsc-llama-cpp-serving" \
+  --download_from_hf True
+```
+
+### Register with BYOC (Bring Your Own Container)
+
+```bash
+ads aqua model register \
+  --model "my-custom-model" \
+  --os_path "oci://my-bucket@my-namespace/models/custom/" \
+  --inference_container_uri "<region>.ocir.io/<namespace>/<repo>:<tag>"
+```
+
+### Convert Legacy Fine-Tuned Model
+
+```bash
+ads aqua model convert_fine_tune \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx"
+```
+
+---
+
+## Deployment Commands
+
+### Create Single Model Deployment
+
+```bash
+ads aqua deployment create \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --instance_shape "VM.GPU.A10.2" \
+  --display_name "my-deployment" \
+  --compartment_id "ocid1.compartment.oc1..xxx" \
+  --project_id "ocid1.datascienceproject.oc1.iad.xxx" \
+  --log_group_id "ocid1.loggroup.oc1.iad.xxx" \
+  --log_id "ocid1.log.oc1.iad.xxx"
+```
+
+Full parameter reference: `references/params.md`
+
+### Create with Custom vLLM Parameters
+
+```bash
+ads aqua deployment create \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --instance_shape "VM.GPU.A10.2" \
+  --display_name "my-deployment" \
+  --env_var '{"MODEL_DEPLOY_PREDICT_ENDPOINT": "/v1/chat/completions", "PARAMS": "--max-model-len 8192 --gpu-memory-utilization 0.95"}'
+```
+
+### Create Multi-Model Deployment
+
+```bash
+ads aqua deployment create \
+  --models '[
+    {"model_id": "ocid1...model1", "model_name": "llama-8b", "gpu_count": 1},
+    {"model_id": "ocid1...model2", "model_name": "mistral-7b", "gpu_count": 1}
+  ]' \
+  --instance_shape "VM.GPU.A10.2" \
+  --display_name "multi-model-deployment"
+```
+
+### Create Stacked Deployment
+
+```bash
+ads aqua deployment create \
+  --models '[
+    {
+      "model_id": "ocid1...base_model",
+      "model_name": "llama-3.1-8b",
+      "fine_tune_weights": [
+        {"model_id": "ocid1...ft1", "model_name": "ft-customer-support"},
+        {"model_id": "ocid1...ft2", "model_name": "ft-summarization"}
+      ]
+    }
+  ]' \
+  --instance_shape "VM.GPU.A10.2" \
+  --display_name "stacked-deployment" \
+  --deployment_type "STACKED"
+```
+
+### Deploy with Tool Calling
+
+```bash
+ads aqua deployment create \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --instance_shape "VM.GPU.A10.2" \
+  --display_name "tool-calling-deployment" \
+  --env_var '{"MODEL_DEPLOY_PREDICT_ENDPOINT": "/v1/chat/completions", "PARAMS": "--enable-auto-tool-choice --tool-call-parser llama3_json --max-model-len 4096"}'
+```
+
+### Deploy GGUF Model on CPU
+
+```bash
+ads aqua deployment create \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --instance_shape "VM.Standard.A1.Flex" \
+  --display_name "cpu-gguf-deployment" \
+  --env_var '{"PARAMS": "--quantization Q4_0"}'
+```
+
+### Shape Recommendation
+
+```bash
+# Table output (human-friendly default)
+ads aqua deployment recommend_shape \
+  --model_id "meta-llama/Llama-3.3-70B-Instruct"
+
+# By model OCID
+ads aqua deployment recommend_shape \
+  --model_id "ocid1.datasciencemodel.oc1.iad.xxx"
+
+# JSON output (programmatic use)
+ads aqua deployment recommend_shape \
+  --model_id "meta-llama/Llama-3.3-70B-Instruct" \
+  --generate_table False
+```
+
+Full parameter reference: `references/params.md`
+
+### List Deployments
+
+```bash
+ads aqua deployment list \
+  --compartment_id "ocid1.compartment.oc1..xxx"
+```
+
+### Get Deployment Details
+
+```bash
+ads aqua deployment get \
+  --model_deployment_id "ocid1.datasciencemodeldeployment.oc1.iad.xxx"
+```
+
+---
+
+## Fine-Tuning Commands
+
+### Create Fine-Tuning Job
+
+```bash
+ads aqua fine_tuning create \
+  --ft_source_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --ft_name "llama-3.1-8b-custom" \
+  --dataset_path "oci://my-bucket@my-namespace/datasets/train.jsonl" \
+  --report_path "oci://my-bucket@my-namespace/ft-output/" \
+  --shape_name "VM.GPU.A10.2" \
+  --replica 1 \
+  --compartment_id "ocid1.compartment.oc1..xxx" \
+  --project_id "ocid1.datascienceproject.oc1.iad.xxx" \
+  --log_group_id "ocid1.loggroup.oc1.iad.xxx" \
+  --log_id "ocid1.log.oc1.iad.xxx" \
+  --ft_parameters '{"epochs": 3, "learning_rate": 0.00002}'
+```
+
+Full parameter reference: `references/params.md`
+
+### Advanced Hyperparameters
+
+```bash
+ads aqua fine_tuning create \
+  --ft_source_id "ocid1.datasciencemodel.oc1.iad.xxx" \
+  --ft_name "llama-custom-advanced" \
+  --dataset_path "oci://bucket@ns/train.jsonl" \
+  --report_path "oci://bucket@ns/output/" \
+  --shape_name "BM.GPU.A10.4" \
+  --replica 1 \
+  --ft_parameters '{
+    "epochs": 5,
+    "learning_rate": 1e-5,
+    "batch_size": 4,
+    "sequence_len": 2048,
+    "pad_to_sequence_len": true,
+    "sample_packing": "auto",
+    "lora_r": 64,
+    "lora_alpha": 32,
+    "lora_dropout": 0.1,
+    "lora_target_linear": true
+  }'
+```
+
+---
+
+## Evaluation Commands
+
+### Create Evaluation
+
+```bash
+ads aqua evaluation create \
+  --evaluation_source_id "ocid1.datasciencemodeldeployment.oc1.iad.xxx" \
+  --evaluation_name "llama-eval-bertscore" \
+  --dataset_path "oci://my-bucket@my-namespace/datasets/eval.jsonl" \
+  --report_path "oci://my-bucket@my-namespace/eval-reports/" \
+  --model_parameters '{"max_tokens": 500, "temperature": 0.7}' \
+  --shape_name "VM.Standard.E4.Flex" \
+  --block_storage_size 50 \
+  --compartment_id "ocid1.compartment.oc1..xxx" \
+  --project_id "ocid1.datascienceproject.oc1.iad.xxx" \
+  --metrics '[{"name": "bertscore"}, {"name": "rouge"}]'
+```
+
+Full parameter reference: `references/params.md`
+
+### Evaluate Specific Model in Multi/Stacked Deployment
+
+```bash
+ads aqua evaluation create \
+  --evaluation_source_id "ocid1.datasciencemodeldeployment.oc1.iad.xxx" \
+  --evaluation_name "stacked-ft1-eval" \
+  --dataset_path "oci://bucket@ns/eval.jsonl" \
+  --report_path "oci://bucket@ns/eval-reports/" \
+  --model_parameters '{"max_tokens": 500, "temperature": 0.7, "model": "ft-customer-support"}' \
+  --shape_name "VM.Standard.E4.Flex" \
+  --block_storage_size 50 \
+  --metrics '[{"name": "bertscore"}]'
+```
+
+### List Evaluations
+
+```bash
+ads aqua evaluation list \
+  --compartment_id "ocid1.compartment.oc1..xxx"
+```
+
+### Get Evaluation Details
+
+```bash
+ads aqua evaluation get \
+  --eval_id "ocid1.datasciencemodel.oc1.iad.xxx"
+```
+
+---
+
+## Policy Verification
+
+```bash
+ads aqua verify_policies
+```
+
+---
+
+## Watching Logs
+
+```bash
+# Model deployment logs
+ads opctl watch <model_deployment_ocid> --auth resource_principal
+
+# Job run logs (fine-tuning / evaluation)
+ads opctl watch <job_run_ocid> --auth resource_principal
+```
+
+## Key Source Files
+
+- `ads/aqua/cli.py` — `AquaCommand` entry point (model, deployment, evaluation, fine_tuning)
+- `ads/aqua/app.py` — `CLIBuilderMixin` for CLI parameter handling