add a new getting started

docs/source/getting_started/new_index.md

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+# Getting Started with Llama Stack
+
+In this guide, we'll walk through using ollama as the inference provider and build a simple python application that uses the Llama Stack Client SDK
+
+Llama stack consists of a distribution server and an accompanying client SDK. The distribution server can be configured for different providers for inference, memory, agents, evals etc. This configuration is defined in a yaml file called `run.yaml`.
+
+### Start the ollama server
+```bash
+export LLAMA_STACK_PORT=5001
+export INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct"
+# ollama names this model differently, and we must use the ollama name when loading the model
+export OLLAMA_INFERENCE_MODEL="llama3.2:3b-instruct-fp16"
+ollama run $OLLAMA_INFERENCE_MODEL --keepalive 60m
+```
+
+### Start the llama stack server
+Create a run.yaml file as defined in the [run.yaml](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/templates/ollama/run.yaml)
+
+```bash
+export LLAMA_STACK_PORT=5001
+docker run \
+  -it \
+  -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
+  -v ~/.llama:/root/.llama \
+  -v ./run.yaml:/root/my-run.yaml \
+  llamastack/distribution-ollama \
+  --yaml-config /root/my-run.yaml \
+  --port $LLAMA_STACK_PORT \
+  --env INFERENCE_MODEL=$INFERENCE_MODEL \
+  --env OLLAMA_URL=http://host.docker.internal:11434
+
+```
+
+### Install the client
+```bash
+pip install llama-stack-client
+```
+
+### Check the connectivity to the server
+```bash
+llama-stack-client --endpoint http://localhost:5001 models list
+┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━┓
+┃ identifier                       ┃ provider_id ┃ provider_resource_id      ┃ metadata ┃
+┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━┩
+│ meta-llama/Llama-3.2-3B-Instruct │ ollama      │ llama3.2:3b-instruct-fp16 │ {}       │
+└──────────────────────────────────┴─────────────┴───────────────────────────┴──────────┘
+```
+
+### Sample app code
+```python
+from llama_stack_client import LlamaStackClient
+
+client = LlamaStackClient(base_url="http://localhost:5001")
+
+# List available models
+models = client.models.list()
+print(models)
+
+# Simple chat completion
+response = client.inference.chat_completion(
+    model_id="meta-llama/Llama-3.2-3B-Instruct",
+    messages=[
+        {"role": "system", "content": "You are a helpful assistant."},
+        {"role": "user", "content": "Write a haiku about coding"}
+    ]
+)
+print(response.completion_message.content)
+```
+
+## Next Steps
+
+For more advanced topics, check out:
+
+- [Tool Calling Guide]()
+- [Memory API Guide]()
+- [Safety API Guide]()
+- [Agents Guide]()
+
+For example applications and more detailed tutorials, visit our [llama-stack-apps](https://github.com/meta-llama/llama-stack-apps/tree/main/examples) repository.