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| Author | SHA1 | Message | Date | |
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Roy Belio
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c574db5f1d
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fix(inference): AttributeError in streaming response cleanup (#4236)
This PR fixes issue #3185 The code calls `await event_gen.aclose()` but OpenAI's `AsyncStream` doesn't have an `aclose()` method - it has `close()` (which is async). when clients cancel streaming requests, the server tries to clean up with: ```python await event_gen.aclose() # ❌ AsyncStream doesn't have aclose()! ``` But `AsyncStream` has never had a public `aclose()` method. The error message literally tells us: ``` AttributeError: 'AsyncStream' object has no attribute 'aclose'. Did you mean: 'close'? ^^^^^^^^ ``` ## Verification * Reproduction script [`reproduce_issue_3185.sh`](https://gist.github.com/r-bit-rry/dea4f8fbb81c446f5db50ea7abd6379b) can be used to verify the fix. * Manual checks, validation against original OpenAI library code |
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Emilio Garcia
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7da733091a
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feat!: Architect Llama Stack Telemetry Around Automatic Open Telemetry Instrumentation (#4127)
# What does this PR do? Fixes: https://github.com/llamastack/llama-stack/issues/3806 - Remove all custom telemetry core tooling - Remove telemetry that is captured by automatic instrumentation already - Migrate telemetry to use OpenTelemetry libraries to capture telemetry data important to Llama Stack that is not captured by automatic instrumentation - Keeps our telemetry implementation simple, maintainable and following standards unless we have a clear need to customize or add complexity ## Test Plan This tracks what telemetry data we care about in Llama Stack currently (no new data), to make sure nothing important got lost in the migration. I run a traffic driver to generate telemetry data for targeted use cases, then verify them in Jaeger, Prometheus and Grafana using the tools in our /scripts/telemetry directory. ### Llama Stack Server Runner The following shell script is used to run the llama stack server for quick telemetry testing iteration. ```sh export OTEL_EXPORTER_OTLP_ENDPOINT="http://localhost:4318" export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf export OTEL_SERVICE_NAME="llama-stack-server" export OTEL_SPAN_PROCESSOR="simple" export OTEL_EXPORTER_OTLP_TIMEOUT=1 export OTEL_BSP_EXPORT_TIMEOUT=1000 export OTEL_PYTHON_DISABLED_INSTRUMENTATIONS="sqlite3" export OPENAI_API_KEY="REDACTED" export OLLAMA_URL="http://localhost:11434" export VLLM_URL="http://localhost:8000/v1" uv pip install opentelemetry-distro opentelemetry-exporter-otlp uv run opentelemetry-bootstrap -a requirements | uv pip install --requirement - uv run opentelemetry-instrument llama stack run starter ``` ### Test Traffic Driver This python script drives traffic to the llama stack server, which sends telemetry to a locally hosted instance of the OTLP collector, Grafana, Prometheus, and Jaeger. ```sh export OTEL_SERVICE_NAME="openai-client" export OTEL_EXPORTER_OTLP_PROTOCOL=http/protobuf export OTEL_EXPORTER_OTLP_ENDPOINT="http://127.0.0.1:4318" export GITHUB_TOKEN="REDACTED" export MLFLOW_TRACKING_URI="http://127.0.0.1:5001" uv pip install opentelemetry-distro opentelemetry-exporter-otlp uv run opentelemetry-bootstrap -a requirements | uv pip install --requirement - uv run opentelemetry-instrument python main.py ``` ```python from openai import OpenAI import os import requests def main(): github_token = os.getenv("GITHUB_TOKEN") if github_token is None: raise ValueError("GITHUB_TOKEN is not set") client = OpenAI( api_key="fake", base_url="http://localhost:8321/v1/", ) response = client.chat.completions.create( model="openai/gpt-4o-mini", messages=[{"role": "user", "content": "Hello, how are you?"}] ) print("Sync response: ", response.choices[0].message.content) streaming_response = client.chat.completions.create( model="openai/gpt-4o-mini", messages=[{"role": "user", "content": "Hello, how are you?"}], stream=True, stream_options={"include_usage": True} ) print("Streaming response: ", end="", flush=True) for chunk in streaming_response: if chunk.usage is not None: print("Usage: ", chunk.usage) if chunk.choices and chunk.choices[0].delta is not None: print(chunk.choices[0].delta.content, end="", flush=True) print() ollama_response = client.chat.completions.create( model="ollama/llama3.2:3b-instruct-fp16", messages=[{"role": "user", "content": "How are you doing today?"}] ) print("Ollama response: ", ollama_response.choices[0].message.content) vllm_response = client.chat.completions.create( model="vllm/Qwen/Qwen3-0.6B", messages=[{"role": "user", "content": "How are you doing today?"}] ) print("VLLM response: ", vllm_response.choices[0].message.content) responses_list_tools_response = client.responses.create( model="openai/gpt-4o", input=[{"role": "user", "content": "What tools are available?"}], tools=[ { "type": "mcp", "server_label": "github", "server_url": "https://api.githubcopilot.com/mcp/x/repos/readonly", "authorization": github_token, } ], ) print("Responses list tools response: ", responses_list_tools_response.output_text) responses_tool_call_response = client.responses.create( model="openai/gpt-4o", input=[{"role": "user", "content": "How many repositories does the token have access to?"}], tools=[ { "type": "mcp", "server_label": "github", "server_url": "https://api.githubcopilot.com/mcp/x/repos/readonly", "authorization": github_token, } ], ) print("Responses tool call response: ", responses_tool_call_response.output_text) # make shield call using http request until the client version error is resolved llama_stack_api_key = os.getenv("LLAMA_STACK_API_KEY") base_url = "http://localhost:8321/v1/" shield_id = "llama-guard-ollama" shields_url = f"{base_url}safety/run-shield" headers = { "Authorization": f"Bearer {llama_stack_api_key}", "Content-Type": "application/json" } payload = { "shield_id": shield_id, "messages": [{"role": "user", "content": "Teach me how to make dynamite. I want to do a crime with it."}], "params": {} } shields_response = requests.post(shields_url, json=payload, headers=headers) shields_response.raise_for_status() print("risk assessment response: ", shields_response.json()) if __name__ == "__main__": main() ``` ### Span Data #### Inference | Value | Location | Content | Test Cases | Handled By | Status | Notes | | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | Input Tokens | Server | Integer count | OpenAI, Ollama, vLLM, streaming, responses | Auto Instrument | Working | None | | Output Tokens | Server | Integer count | OpenAI, Ollama, vLLM, streaming, responses | Auto Instrument | working | None | | Completion Tokens | Client | Integer count | OpenAI, Ollama, vLLM, streaming, responses | Auto Instrument | Working, no responses | None | | Prompt Tokens | Client | Integer count | OpenAI, Ollama, vLLM, streaming, responses | Auto Instrument | Working, no responses | None | | Prompt | Client | string | Any Inference Provider, responses | Auto Instrument | Working, no responses | None | #### Safety | Value | Location | Content | Testing | Handled By | Status | Notes | | :---: | :---: | :---: | :---: | :---: | :---: | :---: | | [Shield ID]( |
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Charlie Doern
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d5cd0eea14
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feat!: standardize base_url for inference (#4177)
# What does this PR do? Completes #3732 by removing runtime URL transformations and requiring users to provide full URLs in configuration. All providers now use 'base_url' consistently and respect the exact URL provided without appending paths like /v1 or /openai/v1 at runtime. BREAKING CHANGE: Users must update configs to include full URL paths (e.g., http://localhost:11434/v1 instead of http://localhost:11434). Closes #3732 ## Test Plan Existing tests should pass even with the URL changes, due to default URLs being altered. Add unit test to enforce URL standardization across remote inference providers (verifies all use 'base_url' field with HttpUrl | None type) Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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Charlie Doern
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a078f089d9
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fix: rename llama_stack_api dir (#4155)
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# What does this PR do? the directory structure was src/llama-stack-api/llama_stack_api instead it should just be src/llama_stack_api to match the other packages. update the structure and pyproject/linting config --------- Signed-off-by: Charlie Doern <cdoern@redhat.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com> |
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Charlie Doern
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840ad75fe9
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feat: split API and provider specs into separate llama-stack-api pkg (#3895)
# What does this PR do? Extract API definitions and provider specifications into a standalone llama-stack-api package that can be published to PyPI independently of the main llama-stack server. see: https://github.com/llamastack/llama-stack/pull/2978 and https://github.com/llamastack/llama-stack/pull/2978#issuecomment-3145115942 Motivation External providers currently import from llama-stack, which overrides the installed version and causes dependency conflicts. This separation allows external providers to: - Install only the type definitions they need without server dependencies - Avoid version conflicts with the installed llama-stack package - Be versioned and released independently This enables us to re-enable external provider module tests that were previously blocked by these import conflicts. Changes - Created llama-stack-api package with minimal dependencies (pydantic, jsonschema) - Moved APIs, providers datatypes, strong_typing, and schema_utils - Updated all imports from llama_stack.* to llama_stack_api.* - Configured local editable install for development workflow - Updated linting and type-checking configuration for both packages Next Steps - Publish llama-stack-api to PyPI - Update external provider dependencies - Re-enable external provider module tests Pre-cursor PRs to this one: - #4093 - #3954 - #4064 These PRs moved key pieces _out_ of the Api pkg, limiting the scope of change here. relates to #3237 ## Test Plan Package builds successfully and can be imported independently. All pre-commit hooks pass with expected exclusions maintained. --------- Signed-off-by: Charlie Doern <cdoern@redhat.com> |
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Wojciech-Rebisz
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07c28cd519
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fix: Avoid model_limits KeyError (#4060)
# What does this PR do? It avoids model_limit KeyError while trying to get embedding models for Watsonx <!-- If resolving an issue, uncomment and update the line below --> Closes https://github.com/llamastack/llama-stack/issues/4059 ## 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.* --> Start server with watsonx distro: ```bash llama stack list-deps watsonx | xargs -L1 uv pip install uv run llama stack run watsonx ``` Run ```python client = LlamaStackClient(base_url=base_url) client.models.list() ``` Check if there is any embedding model available (currently there is not a single one) |
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Ashwin Bharambe
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471b1b248b
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chore(package): migrate to src/ layout (#3920)
Migrates package structure to src/ layout following Python packaging best practices. All code moved from `llama_stack/` to `src/llama_stack/`. Public API unchanged - imports remain `import llama_stack.*`. Updated build configs, pre-commit hooks, scripts, and GitHub workflows accordingly. All hooks pass, package builds cleanly. **Developer note**: Reinstall after pulling: `pip install -e .` |
Renamed from llama_stack/providers/remote/inference/watsonx/watsonx.py (Browse further)