llama-stack/llama_stack/templates/ollama/build.yaml
Ashwin Bharambe dc84bc755a
fix: revert to using faiss for ollama distro (#1530)
This is unfortunate because `sqlite-vec` seems promising. But its PIP
package is not quite complete. It does not have binary for arm64 (I
think, or maybe it even lacks 64 bit builds?) which results in the arm64
container resulting in
```
File "/usr/local/lib/python3.10/site-packages/sqlite_vec/init.py", line 17, in load
    conn.load_extension(loadable_path())
sqlite3.OperationalError: /usr/local/lib/python3.10/site-packages/sqlite_vec/vec0.so: wrong ELF class: ELFCLASS32
```

To get around I tried to install from source via `uv pip install
sqlite-vec --no-binary=sqlite-vec` however it even lacks a source
distribution which makes that impossible.

## Test Plan

Build the container locally using: 

```bash
LLAMA_STACK_DIR=. llama stack build --template ollama --image-type container
```

Run the container as: 

```
podman run --privileged -it -p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
   -v ~/.llama:/root/.llama \
    --env INFERENCE_MODEL=$INFERENCE_MODEL \
    --env OLLAMA_URL=http://host.containers.internal:11434 \
    -v ~/local/llama-stack:/app/llama-stack-source 
    localhost/distribution-ollama:dev --port $LLAMA_STACK_PORT
```

Verify the container starts up correctly. Without this patch, it would
encounter the ELFCLASS32 error.
2025-03-10 16:15:17 -07:00

33 lines
758 B
YAML

version: '2'
distribution_spec:
description: Use (an external) Ollama server for running LLM inference
providers:
inference:
- remote::ollama
vector_io:
- inline::faiss
- remote::chromadb
- remote::pgvector
safety:
- inline::llama-guard
agents:
- inline::meta-reference
telemetry:
- inline::meta-reference
eval:
- inline::meta-reference
datasetio:
- remote::huggingface
- inline::localfs
scoring:
- inline::basic
- inline::llm-as-judge
- inline::braintrust
tool_runtime:
- remote::brave-search
- remote::tavily-search
- inline::code-interpreter
- inline::rag-runtime
- remote::model-context-protocol
- remote::wolfram-alpha
image_type: conda