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1155 commits
| Author | SHA1 | Message | Date | |
|---|---|---|---|---|
Xi Yan
|
327be2f4f6
|
Merge branch 'main' into eval_task_api_update | ||
|
Xi Yan
|
139d5bded6 | update | ||
|
Xi Yan
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39980dc83f | openapi | ||
|
Xi Yan
|
9ce00ede9b | update | ||
|
Xi Yan
|
ceff63130d | deprecation in OpenAPI spec | ||
Yuan Tang
|
0e426d3cf8 |
chore: Link to Groq docs in the warning message for preview model (#1060)
This should be `llama-3.2-3b` instead of `llama-3.2-3b-instruct`. |
||
|
Xi Yan
|
b8a612e5bd | update | ||
Reid
|
b56465738d |
style: update model id in model list title (#1072)
# What does this PR do? [Provide a short summary of what this PR does and why. Link to relevant issues if applicable.] Since the subcommands used `MODEL_ID`, it would be better to use it in `model list` and make it easy to find it. ``` $ llama model verify-download --help usage: llama model verify-download [-h] --model-id MODEL_ID << $ llama model describe --help usage: llama model describe [-h] -m MODEL_ID << $ llama download --help --model-id MODEL_ID See `llama model list` or `llama model list --show-all` for the list of available models before: $ llama model list +-----------------------------------------+-----------------------------------------------------+----------------+ | Model Descriptor | Hugging Face Repo | Context Length | +-----------------------------------------+-----------------------------------------------------+----------------+ after: $ llama model list +-----------------------------------------+-----------------------------------------------------+----------------+ | Model Descriptor | Model ID | Context Length | +-----------------------------------------+-----------------------------------------------------+----------------+ | Llama3.1-8B | meta-llama/Llama-3.1-8B | 128K | +-----------------------------------------+-----------------------------------------------------+----------------+ ``` [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] [//]: # (## Documentation) Signed-off-by: reidliu <reid201711@gmail.com> Co-authored-by: reidliu <reid201711@gmail.com> |
||
Sébastien Han
|
40468aaa14 |
fix: improve signal handling and update dependencies (#1044)
# What does this PR do? This commit enhances the signal handling mechanism in the server by improving the `handle_signal` (previously handle_sigint) function. It now properly retrieves the signal name, ensuring clearer logging when a termination signal is received. Additionally, it cancels all running tasks and waits for their completion before stopping the event loop, allowing for a more graceful shutdown. Support for handling SIGTERM has also been added alongside SIGINT. Before the changes, handle_sigint used asyncio.run(run_shutdown()). However, asyncio.run() is meant to start a new event loop, and calling it inside an existing one (like when running Uvicorn) raises an error. The fix replaces asyncio.run(run_shutdown()) with an async function scheduled on the existing loop using loop.create_task(shutdown()). This ensures that the shutdown coroutine runs within the current event loop instead of trying to create a new one. Furthermore, this commit updates the project dependencies. `fastapi` and `uvicorn` have been added to the development dependencies in `pyproject.toml` and `uv.lock`, ensuring that the necessary packages are available for development and execution. Closes: https://github.com/meta-llama/llama-stack/issues/1043 Signed-off-by: Sébastien Han <seb@redhat.com> [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan Run a server and send SIGINT: ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" python -m llama_stack.distribution.server.server --yaml-config ./llama_stack/templates/ollama/run.yaml Using config file: llama_stack/templates/ollama/run.yaml Run configuration: apis: - agents - datasetio - eval - inference - safety - scoring - telemetry - tool_runtime - vector_io container_image: null datasets: [] eval_tasks: [] image_name: ollama metadata_store: db_path: /Users/leseb/.llama/distributions/ollama/registry.db namespace: null type: sqlite models: - metadata: {} model_id: meta-llama/Llama-3.2-3B-Instruct model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - llm provider_id: ollama provider_model_id: null - metadata: embedding_dimension: 384 model_id: all-MiniLM-L6-v2 model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - embedding provider_id: sentence-transformers provider_model_id: null providers: agents: - config: persistence_store: db_path: /Users/leseb/.llama/distributions/ollama/agents_store.db namespace: null type: sqlite provider_id: meta-reference provider_type: inline::meta-reference datasetio: - config: {} provider_id: huggingface provider_type: remote::huggingface - config: {} provider_id: localfs provider_type: inline::localfs eval: - config: {} provider_id: meta-reference provider_type: inline::meta-reference inference: - config: url: http://localhost:11434 provider_id: ollama provider_type: remote::ollama - config: {} provider_id: sentence-transformers provider_type: inline::sentence-transformers safety: - config: {} provider_id: llama-guard provider_type: inline::llama-guard scoring: - config: {} provider_id: basic provider_type: inline::basic - config: {} provider_id: llm-as-judge provider_type: inline::llm-as-judge - config: openai_api_key: '********' provider_id: braintrust provider_type: inline::braintrust telemetry: - config: service_name: llama-stack sinks: console,sqlite sqlite_db_path: /Users/leseb/.llama/distributions/ollama/trace_store.db provider_id: meta-reference provider_type: inline::meta-reference tool_runtime: - config: api_key: '********' max_results: 3 provider_id: brave-search provider_type: remote::brave-search - config: api_key: '********' max_results: 3 provider_id: tavily-search provider_type: remote::tavily-search - config: {} provider_id: code-interpreter provider_type: inline::code-interpreter - config: {} provider_id: rag-runtime provider_type: inline::rag-runtime vector_io: - config: kvstore: db_path: /Users/leseb/.llama/distributions/ollama/faiss_store.db namespace: null type: sqlite provider_id: faiss provider_type: inline::faiss scoring_fns: [] server: port: 8321 tls_certfile: null tls_keyfile: null shields: [] tool_groups: - args: null mcp_endpoint: null provider_id: tavily-search toolgroup_id: builtin::websearch - args: null mcp_endpoint: null provider_id: rag-runtime toolgroup_id: builtin::rag - args: null mcp_endpoint: null provider_id: code-interpreter toolgroup_id: builtin::code_interpreter vector_dbs: [] version: '2' INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:213: Resolved 31 providers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => ollama INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => sentence-transformers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: models => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inference => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-vector_io => faiss INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-safety => llama-guard INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: shields => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: safety => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_dbs => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_io => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => brave-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => tavily-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => code-interpreter INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => rag-runtime INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_groups => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_runtime => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: agents => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => huggingface INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => localfs INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasets => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasetio => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: telemetry => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => basic INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => llm-as-judge INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => braintrust INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring_functions => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-eval => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval_tasks => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inspect => __builtin__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:216: INFO 2025-02-12 10:21:03,723 llama_stack.providers.remote.inference.ollama.ollama:148: checking connectivity to Ollama at `http://localhost:11434`... INFO 2025-02-12 10:21:03,734 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:03,843 faiss.loader:148: Loading faiss. INFO 2025-02-12 10:21:03,865 faiss.loader:150: Successfully loaded faiss. INFO 2025-02-12 10:21:03,868 faiss:173: Failed to load GPU Faiss: name 'GpuIndexIVFFlat' is not defined. Will not load constructor refs for GPU indexes. Warning: `bwrap` is not available. Code interpreter tool will not work correctly. INFO 2025-02-12 10:21:04,315 datasets:54: PyTorch version 2.6.0 available. INFO 2025-02-12 10:21:04,556 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:04,557 llama_stack.providers.utils.inference.embedding_mixin:42: Loading sentence transformer for all-MiniLM-L6-v2... INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:210: Use pytorch device_name: mps INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:218: Load pretrained SentenceTransformer: all-MiniLM-L6-v2 INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: all-MiniLM-L6-v2 served by sentence-transformers INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: meta-llama/Llama-3.2-3B-Instruct served by ollama INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::equality served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::regex_parser_multiple_choice_answer served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::subset_of served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-correctness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-similarity served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-entity-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-precision served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::factuality served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::faithfulness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::405b-simpleqa served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::base served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::code_interpreter served by code-interpreter INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::rag served by rag-runtime INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::websearch served by tavily-search INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:106: Serving API eval POST /v1/eval/tasks/{task_id}/evaluations DELETE /v1/eval/tasks/{task_id}/jobs/{job_id} GET /v1/eval/tasks/{task_id}/jobs/{job_id}/result GET /v1/eval/tasks/{task_id}/jobs/{job_id} POST /v1/eval/tasks/{task_id}/jobs Serving API agents POST /v1/agents POST /v1/agents/{agent_id}/session POST /v1/agents/{agent_id}/session/{session_id}/turn DELETE /v1/agents/{agent_id} DELETE /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/step/{step_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id} Serving API scoring_functions GET /v1/scoring-functions/{scoring_fn_id} GET /v1/scoring-functions POST /v1/scoring-functions Serving API safety POST /v1/safety/run-shield Serving API inspect GET /v1/health GET /v1/inspect/providers GET /v1/inspect/routes GET /v1/version Serving API tool_runtime POST /v1/tool-runtime/invoke GET /v1/tool-runtime/list-tools POST /v1/tool-runtime/rag-tool/insert POST /v1/tool-runtime/rag-tool/query Serving API datasetio POST /v1/datasetio/rows GET /v1/datasetio/rows Serving API shields GET /v1/shields/{identifier} GET /v1/shields POST /v1/shields Serving API eval_tasks GET /v1/eval-tasks/{eval_task_id} GET /v1/eval-tasks POST /v1/eval-tasks Serving API models GET /v1/models/{model_id} GET /v1/models POST /v1/models DELETE /v1/models/{model_id} Serving API datasets GET /v1/datasets/{dataset_id} GET /v1/datasets POST /v1/datasets DELETE /v1/datasets/{dataset_id} Serving API vector_io POST /v1/vector-io/insert POST /v1/vector-io/query Serving API inference POST /v1/inference/chat-completion POST /v1/inference/completion POST /v1/inference/embeddings Serving API tool_groups GET /v1/tools/{tool_name} GET /v1/toolgroups/{toolgroup_id} GET /v1/toolgroups GET /v1/tools POST /v1/toolgroups DELETE /v1/toolgroups/{toolgroup_id} Serving API vector_dbs GET /v1/vector-dbs/{vector_db_id} GET /v1/vector-dbs POST /v1/vector-dbs DELETE /v1/vector-dbs/{vector_db_id} Serving API scoring POST /v1/scoring/score POST /v1/scoring/score-batch Serving API telemetry GET /v1/telemetry/traces/{trace_id}/spans/{span_id} GET /v1/telemetry/spans/{span_id}/tree GET /v1/telemetry/traces/{trace_id} POST /v1/telemetry/events GET /v1/telemetry/spans GET /v1/telemetry/traces POST /v1/telemetry/spans/export Listening on ['::', '0.0.0.0']:5001 INFO: Started server process [65372] INFO: Waiting for application startup. INFO: ASGI 'lifespan' protocol appears unsupported. INFO: Application startup complete. INFO: Uvicorn running on http://['::', '0.0.0.0']:5001 (Press CTRL+C to quit) ^CINFO: Shutting down INFO: Finished server process [65372] Received signal SIGINT (2). Exiting gracefully... INFO 2025-02-12 10:21:11,215 __main__:151: Shutting down ModelsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down InferenceRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ShieldsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down SafetyRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorDBsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolGroupsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolRuntimeRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down MetaReferenceAgentsImpl INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down TelemetryAdapter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringFunctionsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalTasksRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DistributionInspectImpl ``` [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) Signed-off-by: Sébastien Han <seb@redhat.com> |
||
Ben Browning
|
06c732a008 |
fix: logprobs support in remote-vllm provider (#1074)
# What does this PR do? The remote-vllm provider was not passing logprobs options from CompletionRequest or ChatCompletionRequests through to the OpenAI client parameters. I manually verified this, as well as observed this provider failing `TestInference::test_completion_logprobs`. This was filed as issue #1073. This fixes that by passing the `logprobs.top_k` value through to the parameters we pass into the OpenAI client. Additionally, this fixes a bug in `test_text_inference.py` where it mistakenly assumed chunk.delta were of type `ContentDelta` for completion requests. The deltas are of type `ContentDelta` for chat completion requests, but for basic completion requests the deltas are of type string. This test was likely failing for other providers that did properly support logprobs because of this latter issue in the test, which was hit while fixing the above issue with the remote-vllm provider. (Closes #1073) ## Test Plan First, you need a vllm running. I ran one locally like this: ``` vllm serve meta-llama/Llama-3.2-3B-Instruct --port 8001 --enable-auto-tool-choice --tool-call-parser llama3_json ``` Next, run test_text_inference.py against this vllm using the remote vllm provider like this: ``` VLLM_URL="http://localhost:8001/v1" python -m pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py --providers "inference=vllm_remote" ``` Before my change, the test failed with this error: ``` llama_stack/providers/tests/inference/test_text_inference.py:155: in test_completion_logprobs assert 1 <= len(response.logprobs) <= 5 E TypeError: object of type 'NoneType' has no len() ``` After my change, the test passes. [//]: # (## Documentation) Signed-off-by: Ben Browning <bbrownin@redhat.com> |
||
|
Ben Browning
|
a5d21e6f23 |
docs: Mention convential commits format in CONTRIBUTING.md (#1075)
# What does this PR do? This adds a note to ensure pull requests follow the conventional commits format, along with a link to that format, in CONTRIBUTING.md. One of the pull-request checks enforces PR titles that match this format, so it's good to be upfront about this expectation before a new developer opens a PR. Signed-off-by: Ben Browning <bbrownin@redhat.com> |
||
Ihar Hrachyshka
|
bd94769c7d |
feat: support listing all for llama stack list-providers (#1056)
# What does this PR do?
Support listing all for `llama stack list-providers`.
For ease of reading, sort the output rows by type.
Before the change.
```
llama stack list-providers
usage: llama stack list-providers [-h] {inference,safety,agents,vector_io,datasetio,scoring,eval,post_training,tool_runtime,telemetry}
llama stack list-providers: error: the following arguments are required: api
```
After the change.
```
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| API Type | Provider Type | PIP Package Dependencies |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| agents | inline::meta-reference | matplotlib,pillow,pandas,scikit-learn,aiosqlite,psycopg2-binary,redis |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| datasetio | inline::localfs | pandas |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| datasetio | remote::huggingface | datasets |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| eval | inline::meta-reference | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::meta-reference | accelerate,blobfile,fairscale,torch,torchvision,transformers,zmq,lm-format- |
| | | enforcer,sentence-transformers |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::meta-reference-quantized | accelerate,blobfile,fairscale,torch,torchvision,transformers,zmq,lm-format- |
| | | enforcer,sentence-transformers,fbgemm-gpu,torchao==0.5.0 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::sentence-transformers | sentence-transformers |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::vllm | vllm |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::bedrock | boto3 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::cerebras | cerebras_cloud_sdk |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::databricks | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::fireworks | fireworks-ai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::groq | groq |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::hf::endpoint | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::hf::serverless | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::nvidia | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::ollama | ollama,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::runpod | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::sambanova | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::tgi | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::together | together |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::vllm | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| post_training | inline::torchtune | torch,torchtune==0.5.0,torchao==0.8.0,numpy |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::code-scanner | codeshield |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::llama-guard | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::meta-reference | transformers,torch --index-url https://download.pytorch.org/whl/cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::prompt-guard | transformers,torch --index-url https://download.pytorch.org/whl/cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | remote::bedrock | boto3 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::basic | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::braintrust | autoevals,openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::llm-as-judge | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| telemetry | inline::meta-reference | opentelemetry-sdk,opentelemetry-exporter-otlp-proto-http |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | inline::code-interpreter | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | inline::rag-runtime | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::bing-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::brave-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::model-context-protocol | mcp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::tavily-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::wolfram-alpha | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::chromadb | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,chromadb |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::faiss | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,faiss-cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::meta-reference | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,faiss-cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::chromadb | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,chromadb- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::pgvector | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no- |
| | | deps,psycopg2-binary |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::qdrant | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,qdrant- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::weaviate | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,weaviate- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
```
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
Manually.
[//]: # (## Documentation)
Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
|
||
|
Yuan Tang
|
f9ca441974
|
chore: Link to Groq docs in the warning message for preview model (#1060)
This should be `llama-3.2-3b` instead of `llama-3.2-3b-instruct`. |
||
|
Xi Yan
|
2fa9e3c941
|
fix: make backslash work in GET /models/{model_id:path} (#1068) | ||
|
Reid
|
47fccf0d03
|
style: update model id in model list title (#1072)
# What does this PR do? [Provide a short summary of what this PR does and why. Link to relevant issues if applicable.] Since the subcommands used `MODEL_ID`, it would be better to use it in `model list` and make it easy to find it. ``` $ llama model verify-download --help usage: llama model verify-download [-h] --model-id MODEL_ID << $ llama model describe --help usage: llama model describe [-h] -m MODEL_ID << $ llama download --help --model-id MODEL_ID See `llama model list` or `llama model list --show-all` for the list of available models before: $ llama model list +-----------------------------------------+-----------------------------------------------------+----------------+ | Model Descriptor | Hugging Face Repo | Context Length | +-----------------------------------------+-----------------------------------------------------+----------------+ after: $ llama model list +-----------------------------------------+-----------------------------------------------------+----------------+ | Model Descriptor | Model ID | Context Length | +-----------------------------------------+-----------------------------------------------------+----------------+ | Llama3.1-8B | meta-llama/Llama-3.1-8B | 128K | +-----------------------------------------+-----------------------------------------------------+----------------+ ``` [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] [//]: # (## Documentation) Signed-off-by: reidliu <reid201711@gmail.com> Co-authored-by: reidliu <reid201711@gmail.com> |
||
|
Sébastien Han
|
418645696a
|
fix: improve signal handling and update dependencies (#1044)
# What does this PR do? This commit enhances the signal handling mechanism in the server by improving the `handle_signal` (previously handle_sigint) function. It now properly retrieves the signal name, ensuring clearer logging when a termination signal is received. Additionally, it cancels all running tasks and waits for their completion before stopping the event loop, allowing for a more graceful shutdown. Support for handling SIGTERM has also been added alongside SIGINT. Before the changes, handle_sigint used asyncio.run(run_shutdown()). However, asyncio.run() is meant to start a new event loop, and calling it inside an existing one (like when running Uvicorn) raises an error. The fix replaces asyncio.run(run_shutdown()) with an async function scheduled on the existing loop using loop.create_task(shutdown()). This ensures that the shutdown coroutine runs within the current event loop instead of trying to create a new one. Furthermore, this commit updates the project dependencies. `fastapi` and `uvicorn` have been added to the development dependencies in `pyproject.toml` and `uv.lock`, ensuring that the necessary packages are available for development and execution. Closes: https://github.com/meta-llama/llama-stack/issues/1043 Signed-off-by: Sébastien Han <seb@redhat.com> [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan Run a server and send SIGINT: ``` INFERENCE_MODEL="meta-llama/Llama-3.2-3B-Instruct" python -m llama_stack.distribution.server.server --yaml-config ./llama_stack/templates/ollama/run.yaml Using config file: llama_stack/templates/ollama/run.yaml Run configuration: apis: - agents - datasetio - eval - inference - safety - scoring - telemetry - tool_runtime - vector_io container_image: null datasets: [] eval_tasks: [] image_name: ollama metadata_store: db_path: /Users/leseb/.llama/distributions/ollama/registry.db namespace: null type: sqlite models: - metadata: {} model_id: meta-llama/Llama-3.2-3B-Instruct model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - llm provider_id: ollama provider_model_id: null - metadata: embedding_dimension: 384 model_id: all-MiniLM-L6-v2 model_type: !!python/object/apply:llama_stack.apis.models.models.ModelType - embedding provider_id: sentence-transformers provider_model_id: null providers: agents: - config: persistence_store: db_path: /Users/leseb/.llama/distributions/ollama/agents_store.db namespace: null type: sqlite provider_id: meta-reference provider_type: inline::meta-reference datasetio: - config: {} provider_id: huggingface provider_type: remote::huggingface - config: {} provider_id: localfs provider_type: inline::localfs eval: - config: {} provider_id: meta-reference provider_type: inline::meta-reference inference: - config: url: http://localhost:11434 provider_id: ollama provider_type: remote::ollama - config: {} provider_id: sentence-transformers provider_type: inline::sentence-transformers safety: - config: {} provider_id: llama-guard provider_type: inline::llama-guard scoring: - config: {} provider_id: basic provider_type: inline::basic - config: {} provider_id: llm-as-judge provider_type: inline::llm-as-judge - config: openai_api_key: '********' provider_id: braintrust provider_type: inline::braintrust telemetry: - config: service_name: llama-stack sinks: console,sqlite sqlite_db_path: /Users/leseb/.llama/distributions/ollama/trace_store.db provider_id: meta-reference provider_type: inline::meta-reference tool_runtime: - config: api_key: '********' max_results: 3 provider_id: brave-search provider_type: remote::brave-search - config: api_key: '********' max_results: 3 provider_id: tavily-search provider_type: remote::tavily-search - config: {} provider_id: code-interpreter provider_type: inline::code-interpreter - config: {} provider_id: rag-runtime provider_type: inline::rag-runtime vector_io: - config: kvstore: db_path: /Users/leseb/.llama/distributions/ollama/faiss_store.db namespace: null type: sqlite provider_id: faiss provider_type: inline::faiss scoring_fns: [] server: port: 8321 tls_certfile: null tls_keyfile: null shields: [] tool_groups: - args: null mcp_endpoint: null provider_id: tavily-search toolgroup_id: builtin::websearch - args: null mcp_endpoint: null provider_id: rag-runtime toolgroup_id: builtin::rag - args: null mcp_endpoint: null provider_id: code-interpreter toolgroup_id: builtin::code_interpreter vector_dbs: [] version: '2' INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:213: Resolved 31 providers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => ollama INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-inference => sentence-transformers INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: models => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inference => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-vector_io => faiss INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-safety => llama-guard INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: shields => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: safety => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_dbs => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: vector_io => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => brave-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => tavily-search INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => code-interpreter INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-tool_runtime => rag-runtime INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_groups => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: tool_runtime => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: agents => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => huggingface INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-datasetio => localfs INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasets => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: datasetio => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: telemetry => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => basic INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => llm-as-judge INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-scoring => braintrust INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring_functions => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: scoring => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inner-eval => meta-reference INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval_tasks => __routing_table__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: eval => __autorouted__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:215: inspect => __builtin__ INFO 2025-02-12 10:21:03,540 llama_stack.distribution.resolver:216: INFO 2025-02-12 10:21:03,723 llama_stack.providers.remote.inference.ollama.ollama:148: checking connectivity to Ollama at `http://localhost:11434`... INFO 2025-02-12 10:21:03,734 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:03,843 faiss.loader:148: Loading faiss. INFO 2025-02-12 10:21:03,865 faiss.loader:150: Successfully loaded faiss. INFO 2025-02-12 10:21:03,868 faiss:173: Failed to load GPU Faiss: name 'GpuIndexIVFFlat' is not defined. Will not load constructor refs for GPU indexes. Warning: `bwrap` is not available. Code interpreter tool will not work correctly. INFO 2025-02-12 10:21:04,315 datasets:54: PyTorch version 2.6.0 available. INFO 2025-02-12 10:21:04,556 httpx:1740: HTTP Request: GET http://localhost:11434/api/ps "HTTP/1.1 200 OK" INFO 2025-02-12 10:21:04,557 llama_stack.providers.utils.inference.embedding_mixin:42: Loading sentence transformer for all-MiniLM-L6-v2... INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:210: Use pytorch device_name: mps INFO 2025-02-12 10:21:07,202 sentence_transformers.SentenceTransformer:218: Load pretrained SentenceTransformer: all-MiniLM-L6-v2 INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: all-MiniLM-L6-v2 served by sentence-transformers INFO 2025-02-12 10:21:09,500 llama_stack.distribution.stack:102: Models: meta-llama/Llama-3.2-3B-Instruct served by ollama INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::equality served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::regex_parser_multiple_choice_answer served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: basic::subset_of served by basic INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-correctness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::answer-similarity served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-entity-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-precision served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-recall served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::context-relevancy served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::factuality served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: braintrust::faithfulness served by braintrust INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::405b-simpleqa served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Scoring_fns: llm-as-judge::base served by llm-as-judge INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::code_interpreter served by code-interpreter INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::rag served by rag-runtime INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:102: Tool_groups: builtin::websearch served by tavily-search INFO 2025-02-12 10:21:09,501 llama_stack.distribution.stack:106: Serving API eval POST /v1/eval/tasks/{task_id}/evaluations DELETE /v1/eval/tasks/{task_id}/jobs/{job_id} GET /v1/eval/tasks/{task_id}/jobs/{job_id}/result GET /v1/eval/tasks/{task_id}/jobs/{job_id} POST /v1/eval/tasks/{task_id}/jobs Serving API agents POST /v1/agents POST /v1/agents/{agent_id}/session POST /v1/agents/{agent_id}/session/{session_id}/turn DELETE /v1/agents/{agent_id} DELETE /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id}/step/{step_id} GET /v1/agents/{agent_id}/session/{session_id}/turn/{turn_id} Serving API scoring_functions GET /v1/scoring-functions/{scoring_fn_id} GET /v1/scoring-functions POST /v1/scoring-functions Serving API safety POST /v1/safety/run-shield Serving API inspect GET /v1/health GET /v1/inspect/providers GET /v1/inspect/routes GET /v1/version Serving API tool_runtime POST /v1/tool-runtime/invoke GET /v1/tool-runtime/list-tools POST /v1/tool-runtime/rag-tool/insert POST /v1/tool-runtime/rag-tool/query Serving API datasetio POST /v1/datasetio/rows GET /v1/datasetio/rows Serving API shields GET /v1/shields/{identifier} GET /v1/shields POST /v1/shields Serving API eval_tasks GET /v1/eval-tasks/{eval_task_id} GET /v1/eval-tasks POST /v1/eval-tasks Serving API models GET /v1/models/{model_id} GET /v1/models POST /v1/models DELETE /v1/models/{model_id} Serving API datasets GET /v1/datasets/{dataset_id} GET /v1/datasets POST /v1/datasets DELETE /v1/datasets/{dataset_id} Serving API vector_io POST /v1/vector-io/insert POST /v1/vector-io/query Serving API inference POST /v1/inference/chat-completion POST /v1/inference/completion POST /v1/inference/embeddings Serving API tool_groups GET /v1/tools/{tool_name} GET /v1/toolgroups/{toolgroup_id} GET /v1/toolgroups GET /v1/tools POST /v1/toolgroups DELETE /v1/toolgroups/{toolgroup_id} Serving API vector_dbs GET /v1/vector-dbs/{vector_db_id} GET /v1/vector-dbs POST /v1/vector-dbs DELETE /v1/vector-dbs/{vector_db_id} Serving API scoring POST /v1/scoring/score POST /v1/scoring/score-batch Serving API telemetry GET /v1/telemetry/traces/{trace_id}/spans/{span_id} GET /v1/telemetry/spans/{span_id}/tree GET /v1/telemetry/traces/{trace_id} POST /v1/telemetry/events GET /v1/telemetry/spans GET /v1/telemetry/traces POST /v1/telemetry/spans/export Listening on ['::', '0.0.0.0']:5001 INFO: Started server process [65372] INFO: Waiting for application startup. INFO: ASGI 'lifespan' protocol appears unsupported. INFO: Application startup complete. INFO: Uvicorn running on http://['::', '0.0.0.0']:5001 (Press CTRL+C to quit) ^CINFO: Shutting down INFO: Finished server process [65372] Received signal SIGINT (2). Exiting gracefully... INFO 2025-02-12 10:21:11,215 __main__:151: Shutting down ModelsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down InferenceRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ShieldsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down SafetyRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorDBsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down VectorIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolGroupsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ToolRuntimeRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down MetaReferenceAgentsImpl INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DatasetIORouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down TelemetryAdapter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringFunctionsRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down ScoringRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalTasksRoutingTable INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down EvalRouter INFO 2025-02-12 10:21:11,216 __main__:151: Shutting down DistributionInspectImpl ``` [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) Signed-off-by: Sébastien Han <seb@redhat.com> |
||
|
Ben Browning
|
dd1a366347
|
fix: logprobs support in remote-vllm provider (#1074)
# What does this PR do? The remote-vllm provider was not passing logprobs options from CompletionRequest or ChatCompletionRequests through to the OpenAI client parameters. I manually verified this, as well as observed this provider failing `TestInference::test_completion_logprobs`. This was filed as issue #1073. This fixes that by passing the `logprobs.top_k` value through to the parameters we pass into the OpenAI client. Additionally, this fixes a bug in `test_text_inference.py` where it mistakenly assumed chunk.delta were of type `ContentDelta` for completion requests. The deltas are of type `ContentDelta` for chat completion requests, but for basic completion requests the deltas are of type string. This test was likely failing for other providers that did properly support logprobs because of this latter issue in the test, which was hit while fixing the above issue with the remote-vllm provider. (Closes #1073) ## Test Plan First, you need a vllm running. I ran one locally like this: ``` vllm serve meta-llama/Llama-3.2-3B-Instruct --port 8001 --enable-auto-tool-choice --tool-call-parser llama3_json ``` Next, run test_text_inference.py against this vllm using the remote vllm provider like this: ``` VLLM_URL="http://localhost:8001/v1" python -m pytest -s -v llama_stack/providers/tests/inference/test_text_inference.py --providers "inference=vllm_remote" ``` Before my change, the test failed with this error: ``` llama_stack/providers/tests/inference/test_text_inference.py:155: in test_completion_logprobs assert 1 <= len(response.logprobs) <= 5 E TypeError: object of type 'NoneType' has no len() ``` After my change, the test passes. [//]: # (## Documentation) Signed-off-by: Ben Browning <bbrownin@redhat.com> |
||
|
Ben Browning
|
8c01b7f05a
|
docs: Mention convential commits format in CONTRIBUTING.md (#1075)
# What does this PR do? This adds a note to ensure pull requests follow the conventional commits format, along with a link to that format, in CONTRIBUTING.md. One of the pull-request checks enforces PR titles that match this format, so it's good to be upfront about this expectation before a new developer opens a PR. Signed-off-by: Ben Browning <bbrownin@redhat.com> |
||
|
Ihar Hrachyshka
|
cc700b2f68
|
feat: support listing all for llama stack list-providers (#1056)
# What does this PR do?
Support listing all for `llama stack list-providers`.
For ease of reading, sort the output rows by type.
Before the change.
```
llama stack list-providers
usage: llama stack list-providers [-h] {inference,safety,agents,vector_io,datasetio,scoring,eval,post_training,tool_runtime,telemetry}
llama stack list-providers: error: the following arguments are required: api
```
After the change.
```
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| API Type | Provider Type | PIP Package Dependencies |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| agents | inline::meta-reference | matplotlib,pillow,pandas,scikit-learn,aiosqlite,psycopg2-binary,redis |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| datasetio | inline::localfs | pandas |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| datasetio | remote::huggingface | datasets |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| eval | inline::meta-reference | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::meta-reference | accelerate,blobfile,fairscale,torch,torchvision,transformers,zmq,lm-format- |
| | | enforcer,sentence-transformers |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::meta-reference-quantized | accelerate,blobfile,fairscale,torch,torchvision,transformers,zmq,lm-format- |
| | | enforcer,sentence-transformers,fbgemm-gpu,torchao==0.5.0 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::sentence-transformers | sentence-transformers |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | inline::vllm | vllm |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::bedrock | boto3 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::cerebras | cerebras_cloud_sdk |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::databricks | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::fireworks | fireworks-ai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::groq | groq |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::hf::endpoint | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::hf::serverless | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::nvidia | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::ollama | ollama,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::runpod | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::sambanova | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::tgi | huggingface_hub,aiohttp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::together | together |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| inference | remote::vllm | openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| post_training | inline::torchtune | torch,torchtune==0.5.0,torchao==0.8.0,numpy |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::code-scanner | codeshield |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::llama-guard | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::meta-reference | transformers,torch --index-url https://download.pytorch.org/whl/cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | inline::prompt-guard | transformers,torch --index-url https://download.pytorch.org/whl/cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| safety | remote::bedrock | boto3 |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::basic | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::braintrust | autoevals,openai |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| scoring | inline::llm-as-judge | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| telemetry | inline::meta-reference | opentelemetry-sdk,opentelemetry-exporter-otlp-proto-http |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | inline::code-interpreter | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | inline::rag-runtime | |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::bing-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::brave-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::model-context-protocol | mcp |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::tavily-search | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| tool_runtime | remote::wolfram-alpha | requests |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::chromadb | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,chromadb |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::faiss | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,faiss-cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | inline::meta-reference | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,faiss-cpu |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::chromadb | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,chromadb- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::pgvector | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no- |
| | | deps,psycopg2-binary |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::qdrant | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,qdrant- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
| vector_io | remote::weaviate | blobfile,chardet,pypdf,tqdm,numpy,scikit- |
| | | learn,scipy,nltk,sentencepiece,transformers,torch torchvision --index-url |
| | | https://download.pytorch.org/whl/cpu,sentence-transformers --no-deps,weaviate- |
| | | client |
+---------------+----------------------------------+----------------------------------------------------------------------------------+
```
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
Manually.
[//]: # (## Documentation)
Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com>
|
||
|
Xi Yan
|
5f5a7b628f | openapi | ||
|
Xi Yan
|
234fe36d62 | fix cli download | ||
|
Xi Yan
|
76281f4de7
|
Merge branch 'main' into eval_task_api_update | ||
|
Xi Yan
|
10e8c96453 | add benchmarks | ||
|
Xi Yan
|
1395de57a6 | fix | ||
|
Xi Yan
|
2d0f6865ac | fix | ||
|
Xi Yan
|
ec721b3867 | update | ||
|
Xi Yan
|
e07776fff6 | update | ||
|
Xi Yan
|
8759196e29 | benchmark config | ||
|
Xi Yan
|
017d24fe65 | replace task_id -> benchmark_id | ||
|
Xi Yan
|
b20742fce7 | replace | ||
|
Xi Yan
|
9a8f4025c1 | naming update | ||
Francisco Arceo
|
119fe8742a
|
feat: Adding sqlite-vec as a vectordb (#1040)
# What does this PR do?
This PR adds `sqlite_vec` as an additional inline vectordb.
Tested with `ollama` by adding the `vector_io` object in
`./llama_stack/templates/ollama/run.yaml` :
```yaml
vector_io:
- provider_id: sqlite_vec
provider_type: inline::sqlite_vec
config:
kvstore:
type: sqlite
namespace: null
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/ollama}/sqlite_vec.db
```
I also updated the `./tests/client-sdk/vector_io/test_vector_io.py` test
file with:
```python
INLINE_VECTOR_DB_PROVIDERS = ["faiss", "sqlite_vec"]
```
And parameterized the relevant tests.
[//]: # (If resolving an issue, uncomment and update the line below)
# Closes
https://github.com/meta-llama/llama-stack/issues/1005
## Test Plan
I ran the tests with:
```bash
INFERENCE_MODEL=llama3.2:3b-instruct-fp16 LLAMA_STACK_CONFIG=ollama pytest -s -v tests/client-sdk/vector_io/test_vector_io.py
```
Which outputs:
```python
...
PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_retrieve[all-MiniLM-L6-v2-sqlite_vec] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_list PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_register[all-MiniLM-L6-v2-faiss] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_register[all-MiniLM-L6-v2-sqlite_vec] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_unregister[faiss] PASSED
tests/client-sdk/vector_io/test_vector_io.py::test_vector_db_unregister[sqlite_vec] PASSED
```
In addition, I ran the `rag_with_vector_db.py`
[example](https://github.com/meta-llama/llama-stack-apps/blob/main/examples/agents/rag_with_vector_db.py)
using the script below with `uv run rag_example.py`.
<details>
<summary>CLICK TO SHOW SCRIPT 👋 </summary>
```python
#!/usr/bin/env python3
import os
import uuid
from termcolor import cprint
# Set environment variables
os.environ['INFERENCE_MODEL'] = 'llama3.2:3b-instruct-fp16'
os.environ['LLAMA_STACK_CONFIG'] = 'ollama'
# Import libraries after setting environment variables
from llama_stack.distribution.library_client import LlamaStackAsLibraryClient
from llama_stack_client.lib.agents.agent import Agent
from llama_stack_client.lib.agents.event_logger import EventLogger
from llama_stack_client.types.agent_create_params import AgentConfig
from llama_stack_client.types import Document
def main():
# Initialize the client
client = LlamaStackAsLibraryClient("ollama")
vector_db_id = f"test-vector-db-{uuid.uuid4().hex}"
_ = client.initialize()
model_id = 'llama3.2:3b-instruct-fp16'
# Define the list of document URLs and create Document objects
urls = [
"chat.rst",
"llama3.rst",
"memory_optimizations.rst",
"lora_finetune.rst",
]
documents = [
Document(
document_id=f"num-{i}",
content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
mime_type="text/plain",
metadata={},
)
for i, url in enumerate(urls)
]
# (Optional) Use the documents as needed with your client here
client.vector_dbs.register(
provider_id='sqlite_vec',
vector_db_id=vector_db_id,
embedding_model="all-MiniLM-L6-v2",
embedding_dimension=384,
)
client.tool_runtime.rag_tool.insert(
documents=documents,
vector_db_id=vector_db_id,
chunk_size_in_tokens=512,
)
# Create agent configuration
agent_config = AgentConfig(
model=model_id,
instructions="You are a helpful assistant",
enable_session_persistence=False,
toolgroups=[
{
"name": "builtin::rag",
"args": {
"vector_db_ids": [vector_db_id],
}
}
],
)
# Instantiate the Agent
agent = Agent(client, agent_config)
# List of user prompts
user_prompts = [
"What are the top 5 topics that were explained in the documentation? Only list succinct bullet points.",
"Was anything related to 'Llama3' discussed, if so what?",
"Tell me how to use LoRA",
"What about Quantization?",
]
# Create a session for the agent
session_id = agent.create_session("test-session")
# Process each prompt and display the output
for prompt in user_prompts:
cprint(f"User> {prompt}", "green")
response = agent.create_turn(
messages=[
{
"role": "user",
"content": prompt,
}
],
session_id=session_id,
)
# Log and print events from the response
for log in EventLogger().log(response):
log.print()
if __name__ == "__main__":
main()
```
</details>
Which outputs a large summary of RAG generation.
# Documentation
Will handle documentation updates in follow-up PR.
# (- [ ] Added a Changelog entry if the change is significant)
---------
Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
|
||
Charlie Doern
|
025f615868
|
feat: add support for running in a venv (#1018)
# What does this PR do? add --image-type to `llama stack run`. Which takes conda, container or venv also add start_venv.sh which start the stack using a venv resolves #1007 ## Test Plan running locally: `llama stack build --template ollama --image-type venv` `llama stack run --image-type venv ~/.llama/distributions/ollama/ollama-run.yaml` ... ``` llama stack run --image-type venv ~/.llama/distributions/ollama/ollama-run.yaml Using run configuration: /Users/charliedoern/.llama/distributions/ollama/ollama-run.yaml + python -m llama_stack.distribution.server.server --yaml-config /Users/charliedoern/.llama/distributions/ollama/ollama-run.yaml --port 8321 Using config file: /Users/charliedoern/.llama/distributions/ollama/ollama-run.yaml Run configuration: apis: - agents - datasetio ... ``` Signed-off-by: Charlie Doern <cdoern@redhat.com> |
||
|
Charlie Doern
|
5f88ff0b6a
|
fix: show proper help text (#1065)
# What does this PR do?
when executing a sub-command like `llama model` the improper help text,
sub-commands, and flags are displayed. each command group needs to have
`.set_defaults` to display this info properly
before:
```
llama model
usage: llama [-h] {model,stack,download,verify-download} ...
Welcome to the Llama CLI
options:
-h, --help show this help message and exit
subcommands:
{model,stack,download,verify-download}
```
after:
```
llama model
usage: llama model [-h] {download,list,prompt-format,describe,verify-download} ...
Work with llama models
options:
-h, --help show this help message and exit
model_subcommands:
{download,list,prompt-format,describe,verify-download}
```
Signed-off-by: Charlie Doern <cdoern@redhat.com>
|
||
|
Yuan Tang
|
5e97dd9919
|
feat: Support tool calling for streaming chat completion in remote vLLM provider (#1063)
# What does this PR do? [Provide a short summary of what this PR does and why. Link to relevant issues if applicable.] Closes https://github.com/meta-llama/llama-stack/issues/1046. ## Test Plan [Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.*] ``` LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py ================================================================= test session starts ================================================================= platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/distribution-myenv/bin/python3.10 cachedir: .pytest_cache rootdir: /home/yutang/repos/llama-stack configfile: pyproject.toml plugins: anyio-4.8.0 collected 14 items tests/client-sdk/inference/test_text_inference.py::test_text_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 7%] tests/client-sdk/inference/test_text_inference.py::test_text_completion_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 14%] tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote:...) [ 21%] tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::vll...) [ 28%] tests/client-sdk/inference/test_text_inference.py::test_text_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 35%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet do humans live on?-Earth] PASSED [ 42%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet has rings around it with a name starting with letter S?-Saturn] PASSED [ 50%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED [ 57%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED [ 64%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 71%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 78%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 85%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[meta-llama/Llama-3.1-8B-Instruct-True] PASSED [ 92%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_tool_calling_tools_not_in_request[meta-llama/Llama-3.1-8B-Instruct-False] PASSED [100%] =============================================== 12 passed, 2 xfailed, 1 warning in 366.56s (0:06:06) ================================================ ``` --------- Signed-off-by: Yuan Tang <terrytangyuan@gmail.com> |
||
|
Sébastien Han
|
bf11cc0450
|
chore: update return type to Optional[str] (#982) | ||
|
Xi Yan
|
66d7e15c93
|
perf: ensure ToolCall in ChatCompletionResponse is subset of ChatCompletionRequest.tools (#1041)
# What does this PR do?
**Problem**
- Using script:
https://gist.github.com/thoraxe/6163b2145ce7b1c24c6026b64cf90085
- This hits an issue on server with `code_interpreter` not found, as we
do not pass "builtin::code_interpreter" in AgentConfig's `toolgroups`.
This is a general issue where model always tries to output
`code_interpreter` in `ToolCall` even when we do not have
`code_interpreter` available for execution.
**Reproduce Deeper Problem in chat-completion**
- Use script:
https://gist.github.com/yanxi0830/163a9ad7b5db10556043fbfc7ecd7603
1. We currently always populate `code_interpreter` in `ToolCall` in
ChatCompletionResponse if the model's response begins with
`<|python_tag|>`. See
|
||
|
Yuan Tang
|
dd37e58868
|
feat: Support tool calling for non-streaming chat completion in remote vLLM provider (#1034)
# What does this PR do? This PR adds support for tool calling for non-streaming chat completion. Prior to this, tool calls were not passed to chat completion requests and the tools object needs to be restructured properly to be compatible with vLLM provider. ## Test Plan ``` LLAMA_STACK_BASE_URL=http://localhost:5002 pytest -v tests/client-sdk/inference/test_text_inference.py ================================================================= test session starts ================================================================= platform linux -- Python 3.10.16, pytest-8.3.4, pluggy-1.5.0 -- /home/yutang/.conda/envs/distribution-myenv/bin/python3.10 cachedir: .pytest_cache rootdir: /home/yutang/repos/llama-stack configfile: pyproject.toml plugins: anyio-4.8.0 collected 12 items tests/client-sdk/inference/test_text_inference.py::test_text_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 8%] tests/client-sdk/inference/test_text_inference.py::test_text_completion_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 16%] tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_non_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote:...) [ 25%] tests/client-sdk/inference/test_text_inference.py::test_completion_log_probs_streaming[meta-llama/Llama-3.1-8B-Instruct] XFAIL (remote::vll...) [ 33%] tests/client-sdk/inference/test_text_inference.py::test_text_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 41%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet do humans live on?-Earth] PASSED [ 50%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_non_streaming[meta-llama/Llama-3.1-8B-Instruct-Which planet has rings around it with a name starting with letter S?-Saturn] PASSED [ 58%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What's the name of the Sun in latin?-Sol] PASSED [ 66%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_streaming[meta-llama/Llama-3.1-8B-Instruct-What is the name of the US captial?-Washington] PASSED [ 75%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_non_streaming[meta-llama/Llama-3.1-8B-Instruct] PASSED [ 83%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_with_tool_calling_and_streaming[meta-llama/Llama-3.1-8B-Instruct] FAILED [ 91%] tests/client-sdk/inference/test_text_inference.py::test_text_chat_completion_structured_output[meta-llama/Llama-3.1-8B-Instruct] PASSED [100%] ``` --------- Signed-off-by: Yuan Tang <terrytangyuan@gmail.com> |
||
|
Ihar Hrachyshka
|
24385cfd03
|
fix: filter out remote::sample providers when listing (#1057)
# What does this PR do? Before: ``` llama stack list-providers agents +------------------------+-----------------------------------------------------------------------+ | Provider Type | PIP Package Dependencies | +------------------------+-----------------------------------------------------------------------+ | inline::meta-reference | matplotlib,pillow,pandas,scikit-learn,aiosqlite,psycopg2-binary,redis | +------------------------+-----------------------------------------------------------------------+ | remote::sample | | +------------------------+-----------------------------------------------------------------------+ ``` After: ``` llama stack list-providers agents +------------------------+-----------------------------------------------------------------------+ | Provider Type | PIP Package Dependencies | +------------------------+-----------------------------------------------------------------------+ | inline::meta-reference | matplotlib,pillow,pandas,scikit-learn,aiosqlite,psycopg2-binary,redis | +------------------------+-----------------------------------------------------------------------+ ``` [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan Manually. [//]: # (## Documentation) Signed-off-by: Ihar Hrachyshka <ihar.hrachyshka@gmail.com> |
||
Dinesh Yeduguru
|
d8a20e034b
|
feat: make telemetry attributes be dict[str,PrimitiveType] (#1055)
# What does this PR do? Make attributes in telemetry be only primitive types and avoid arbitrary nesting. ## Test Plan ``` LLAMA_STACK_DISABLE_VERSION_CHECK=true llama stack run ~/.llama/distributions/fireworks/fireworks-run.yaml LLAMA_STACK_BASE_URL=http://localhost:8321 pytest -v tests/client-sdk/agents/test_agents.py -k "test_builtin_tool_web_search" # Verified that attributes still show up correclty in jaeger ``` |
||
|
Dinesh Yeduguru
|
ab7f802698
|
feat: add MetricResponseMixin to chat completion response types (#1050)
# What does this PR do?
Defines a MetricResponseMixin which can be inherited by any response
class. Adds it to chat completion response types.
This is a short term solution to allow inference API to return metrics
The ideal way to do this is to have a way for all response types to
include metrics
and all metric events logged to the telemetry API to be included with
the response
To do this, we will need to augment all response types with a metrics
field.
We have hit a blocker from stainless SDK that prevents us from doing
this.
The blocker is that if we were to augment the response types that have a
data field
in them like so
class ListModelsResponse(BaseModel):
metrics: Optional[List[MetricEvent]] = None
data: List[Models]
...
The client SDK will need to access the data by using a .data field,
which is not
ergonomic. Stainless SDK does support unwrapping the response type, but
it
requires that the response type to only have a single field.
We will need a way in the client SDK to signal that the metrics are
needed
and if they are needed, the client SDK has to return the full response
type
without unwrapping it.
## Test Plan
sh run_openapi_generator.sh ./
sh stainless_sync.sh dineshyv/dev add-metrics-to-resp-v4
LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/fireworks/fireworks-run.yaml"
pytest -v tests/client-sdk/agents/test_agents.py
|
||
ehhuang
|
96c88397da
|
fix: agent config validation (#1053)
Summary:
Fixes AgentConfig init bug introduced with ToolConfig.
Namely, the below doesn't work
```
agent_config = AgentConfig(
**common_params,
tool_config=ToolConfig(
tool_choice="required",
),
)
```
bvecause tool_choice was defaulted to 'auto' leading to validation check
failing.
Test Plan:
added unittests
LLAMA_STACK_CONFIG=fireworks pytest -s -v tests/client-sdk/
--safety-shield meta-llama/Llama-Guard-3-8B
|
||
|
Ihar Hrachyshka
|
6ad272927d
|
docs: reflect actual number of spaces for indent (#1052)
For what I see, it's all 4 spaces (as it should be for pep8[1]). [1] https://peps.python.org/pep-0008/#indentation # What does this PR do? Reflect indent reality. |
||
|
Sébastien Han
|
71cae67d7b
|
docs: remove changelog mention from PR template (#1049)
# What does this PR do?
The CHANGELOG.md was removed in
|
||
Kelly Brown
|
d947ddd255
|
docs: Updating wording and nits in the README.md (#992)
# What does this PR do? Fixing some wording nits and added small formatting suggestions in the README.md ## Before submitting - [x] This PR fixes a typo or improves the docs (you can dismiss the other checks if that's the case). - [x] Ran pre-commit to handle lint / formatting issues. - [x] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [x] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests. |
||
|
Yuan Tang
|
d954f2752e
|
fix: Added missing tool_config arg in SambaNova chat_completion() (#1042)
# What does this PR do? `tool_config` is missing from the signature but is used in `ChatCompletionRequest()`. ## Test Plan This is a small fix. I don't have SambaNova to test the change but I doubt that this is currently working. Signed-off-by: Yuan Tang <terrytangyuan@gmail.com> |
||
|
Sébastien Han
|
b34c1dd8ad
|
test: replace blocked image URLs with GitHub-hosted (#1025)
# What does this PR do?
The previous image URLs were sometimes blocked by Cloudflare, causing
test failures for some users. This update replaces them with a
GitHub-hosted image (`dog.png`) from the `llama-stack` repository,
ensuring more reliable access during testing.
Signed-off-by: Sébastien Han <seb@redhat.com>
[//]: # (If resolving an issue, uncomment and update the line below)
[//]: # (Closes #[issue-number])
## Test Plan
```
$ ollama run llama3.2-vision:latest --keep-alive 2m &
$ uv run pytest -v -s -k "ollama" --inference-model=llama3.2-vision:latest llama_stack/providers/tests/inference/test_vision_inference.py
/Users/leseb/Documents/AI/llama-stack/.venv/lib/python3.13/site-packages/pytest_asyncio/plugin.py:207: PytestDeprecationWarning: The configuration option "asyncio_default_fixture_loop_scope" is unset.
The event loop scope for asynchronous fixtures will default to the fixture caching scope. Future versions of pytest-asyncio will default the loop scope for asynchronous fixtures to function scope. Set the default fixture loop scope explicitly in order to avoid unexpected behavior in the future. Valid fixture loop scopes are: "function", "class", "module", "package", "session"
warnings.warn(PytestDeprecationWarning(_DEFAULT_FIXTURE_LOOP_SCOPE_UNSET))
============================================ test session starts =============================================
platform darwin -- Python 3.13.1, pytest-8.3.4, pluggy-1.5.0 -- /Users/leseb/Documents/AI/llama-stack/.venv/bin/python3
cachedir: .pytest_cache
metadata: {'Python': '3.13.1', 'Platform': 'macOS-15.3-arm64-arm-64bit-Mach-O', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.3', 'anyio': '4.8.0', 'nbval': '0.11.0'}}
rootdir: /Users/leseb/Documents/AI/llama-stack
configfile: pyproject.toml
plugins: html-4.1.1, metadata-3.1.1, asyncio-0.25.3, anyio-4.8.0, nbval-0.11.0
asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None
collected 39 items / 36 deselected / 3 selected
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-ollama-image0-expected_strings0] PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_non_streaming[-ollama-image1-expected_strings1]
PASSED
llama_stack/providers/tests/inference/test_vision_inference.py::TestVisionModelInference::test_vision_chat_completion_streaming[-ollama] PASSED
========================== 3 passed, 36 deselected, 2 warnings in 62.23s (0:01:02) ==========================
```
[//]: # (## Documentation)
[//]: # (- [ ] Added a Changelog entry if the change is significant)
Signed-off-by: Sébastien Han <seb@redhat.com>
|
||
Bill Murdock
|
3856927ee8
|
fix: Update Qdrant support post-refactor (#1022)
# What does this PR do? I tried running the Qdrant provider and found some bugs. See #1021 for details. @terrytangyuan wrote there: > Please feel free to submit your changes in a PR. I fixed similar issues for pgvector provider. This might be an issue introduced from a refactoring. So I am submitting this PR. Closes #1021 ## Test Plan Here are the highlights for what I did to test this: References: - https://llama-stack.readthedocs.io/en/latest/getting_started/index.html - https://github.com/meta-llama/llama-stack-apps/blob/main/examples/agents/rag_with_vector_db.py - https://github.com/meta-llama/llama-stack/blob/main/docs/zero_to_hero_guide/README.md#build-configure-and-run-llama-stack Install and run Qdrant server: ``` podman pull qdrant/qdrant mkdir qdrant-data podman run -p 6333:6333 -v $(pwd)/qdrant-data:/qdrant/storage qdrant/qdrant ``` Install and run Llama Stack from the venv-support PR (mainly because I didn't want to install conda): ``` brew install cmake # Should just need this once git clone https://github.com/meta-llama/llama-models.git gh repo clone cdoern/llama-stack cd llama-stack gh pr checkout 1018 # This is the checkout that introduces venv support for build/run. Otherwise you have to use conda. Eventually this wil be part of main, hopefully. uv sync --extra dev uv pip install -e . source .venv/bin/activate uv pip install qdrant_client LLAMA_STACK_DIR=$(pwd) LLAMA_MODELS_DIR=../llama-models llama stack build --template ollama --image-type venv ``` ``` edit llama_stack/templates/ollama/run.yaml ``` in that editor under: ``` vector_io: ``` add: ``` - provider_id: qdrant provider_type: remote::qdrant config: {} ``` see https://github.com/meta-llama/llama-stack/blob/main/llama_stack/providers/remote/vector_io/qdrant/config.py#L14 for config options (but I didn't need any) ``` LLAMA_STACK_DIR=$(pwd) LLAMA_MODELS_DIR=../llama-models llama stack run ollama --image-type venv \ --port $LLAMA_STACK_PORT \ --env INFERENCE_MODEL=$INFERENCE_MODEL \ --env SAFETY_MODEL=$SAFETY_MODEL \ --env OLLAMA_URL=$OLLAMA_URL ``` Then I tested it out in a notebook. Key highlights included: ``` qdrant_provider = None for provider in client.providers.list(): if provider.api == "vector_io" and provider.provider_id == "qdrant": qdrant_provider = provider qdrant_provider assert qdrant_provider is not None, "QDrant is not a provider. You need to edit the run yaml file you use in your `llama stack run` call" vector_db_id = f"test-vector-db-{uuid.uuid4().hex}" client.vector_dbs.register( vector_db_id=vector_db_id, embedding_model="all-MiniLM-L6-v2", embedding_dimension=384, provider_id=qdrant_provider.provider_id, ) ``` Other than that, I just followed what was in https://llama-stack.readthedocs.io/en/latest/getting_started/index.html It would be good to have automated tests for this in the future, but that would be a big undertaking. Signed-off-by: Bill Murdock <bmurdock@redhat.com> |
||
Ellis Tarn
|
36d35406a7
|
fix: a bad newline in ollama docs (#1036)
# What does this PR do? Catches a bug in the previous codegen which was removing newlines. [//]: # (If resolving an issue, uncomment and update the line below) [//]: # (Closes #[issue-number]) ## Test Plan ``` python llama_stack/scripts/distro_codegen.py ``` [//]: # (## Documentation) [//]: # (- [ ] Added a Changelog entry if the change is significant) |
||
|
Ellis Tarn
|
afca9d92f9
|
fix: Readthedocs cannot parse comments, resulting in docs bugs (#1033) |