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# What does this PR do? PR #639 introduced the notion of Tools API and ability to invoke tools through API just as any resource. This PR changes the Agents to start using the Tools API to invoke tools. Major changes include: 1) Ability to specify tool groups with AgentConfig 2) Agent gets the corresponding tool definitions for the specified tools and pass along to the model 3) Attachements are now named as Documents and their behavior is mostly unchanged from user perspective 4) You can specify args that can be injected to a tool call through Agent config. This is especially useful in case of memory tool, where you want the tool to operate on a specific memory bank. 5) You can also register tool groups with args, which lets the agent inject these as well into the tool call. 6) All tests have been migrated to use new tools API and fixtures including client SDK tests 7) Telemetry just works with tools API because of our trace protocol decorator ## Test Plan ``` pytest -s -v -k fireworks llama_stack/providers/tests/agents/test_agents.py \ --safety-shield=meta-llama/Llama-Guard-3-8B \ --inference-model=meta-llama/Llama-3.1-8B-Instruct pytest -s -v -k together llama_stack/providers/tests/tools/test_tools.py \ --safety-shield=meta-llama/Llama-Guard-3-8B \ --inference-model=meta-llama/Llama-3.1-8B-Instruct LLAMA_STACK_CONFIG="/Users/dineshyv/.llama/distributions/llamastack-together/together-run.yaml" pytest -v tests/client-sdk/agents/test_agents.py ``` run.yaml: https://gist.github.com/dineshyv/0365845ad325e1c2cab755788ccc5994 Notebook: https://colab.research.google.com/drive/1ck7hXQxRl6UvT-ijNRZ-gMZxH1G3cN2d?usp=sharing
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Fireworks Distribution
:maxdepth: 2
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self
The llamastack/distribution-fireworks
distribution consists of the following provider configurations.
API | Provider(s) |
---|---|
agents | inline::meta-reference |
datasetio | remote::huggingface , inline::localfs |
eval | inline::meta-reference |
inference | remote::fireworks |
memory | inline::faiss , remote::chromadb , remote::pgvector |
safety | inline::llama-guard |
scoring | inline::basic , inline::llm-as-judge , inline::braintrust |
telemetry | inline::meta-reference |
tool_runtime | remote::brave-search , remote::tavily-search , inline::code-interpreter , inline::memory-runtime |
Environment Variables
The following environment variables can be configured:
LLAMASTACK_PORT
: Port for the Llama Stack distribution server (default:5001
)FIREWORKS_API_KEY
: Fireworks.AI API Key (default: ``)
Models
The following models are available by default:
meta-llama/Llama-3.1-8B-Instruct (fireworks/llama-v3p1-8b-instruct)
meta-llama/Llama-3.1-70B-Instruct (fireworks/llama-v3p1-70b-instruct)
meta-llama/Llama-3.1-405B-Instruct-FP8 (fireworks/llama-v3p1-405b-instruct)
meta-llama/Llama-3.2-1B-Instruct (fireworks/llama-v3p2-1b-instruct)
meta-llama/Llama-3.2-3B-Instruct (fireworks/llama-v3p2-3b-instruct)
meta-llama/Llama-3.2-11B-Vision-Instruct (fireworks/llama-v3p2-11b-vision-instruct)
meta-llama/Llama-3.2-90B-Vision-Instruct (fireworks/llama-v3p2-90b-vision-instruct)
meta-llama/Llama-3.3-70B-Instruct (fireworks/llama-v3p3-70b-instruct)
meta-llama/Llama-Guard-3-8B (fireworks/llama-guard-3-8b)
meta-llama/Llama-Guard-3-11B-Vision (fireworks/llama-guard-3-11b-vision)
Prerequisite: API Keys
Make sure you have access to a Fireworks API Key. You can get one by visiting fireworks.ai.
Running Llama Stack with Fireworks
You can do this via Conda (build code) or Docker which has a pre-built image.
Via Docker
This method allows you to get started quickly without having to build the distribution code.
LLAMA_STACK_PORT=5001
docker run \
-it \
-p $LLAMA_STACK_PORT:$LLAMA_STACK_PORT \
llamastack/distribution-fireworks \
--port $LLAMA_STACK_PORT \
--env FIREWORKS_API_KEY=$FIREWORKS_API_KEY
Via Conda
llama stack build --template fireworks --image-type conda
llama stack run ./run.yaml \
--port $LLAMA_STACK_PORT \
--env FIREWORKS_API_KEY=$FIREWORKS_API_KEY