agents to use tools api (#673)

# 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

llama_stack/templates/meta-reference-gpu/build.yaml

@@ -2,7 +2,6 @@ version: '2'
 name: meta-reference-gpu
 distribution_spec:
   description: Use Meta Reference for running LLM inference
-  docker_image: null
   providers:
     inference:
     - inline::meta-reference
@@ -25,4 +24,9 @@ distribution_spec:
     - inline::basic
     - inline::llm-as-judge
     - inline::braintrust
+    tool_runtime:
+    - remote::brave-search
+    - remote::tavily-search
+    - inline::code-interpreter
+    - inline::memory-runtime
 image_type: conda

llama_stack/templates/meta-reference-gpu/meta_reference.py

@@ -7,8 +7,12 @@
 from pathlib import Path
 
 from llama_stack.apis.models.models import ModelType
-
-from llama_stack.distribution.datatypes import ModelInput, Provider, ShieldInput
+from llama_stack.distribution.datatypes import (
+    ModelInput,
+    Provider,
+    ShieldInput,
+    ToolGroupInput,
+)
 from llama_stack.providers.inline.inference.meta_reference import (
     MetaReferenceInferenceConfig,
 )
@@ -29,6 +33,12 @@ def get_distribution_template() -> DistributionTemplate:
         "eval": ["inline::meta-reference"],
         "datasetio": ["remote::huggingface", "inline::localfs"],
         "scoring": ["inline::basic", "inline::llm-as-judge", "inline::braintrust"],
+        "tool_runtime": [
+            "remote::brave-search",
+            "remote::tavily-search",
+            "inline::code-interpreter",
+            "inline::memory-runtime",
+        ],
     }
     name = "meta-reference-gpu"
     inference_provider = Provider(
@@ -66,6 +76,20 @@ def get_distribution_template() -> DistributionTemplate:
         model_id="${env.SAFETY_MODEL}",
         provider_id="meta-reference-safety",
     )
+    default_tool_groups = [
+        ToolGroupInput(
+            toolgroup_id="builtin::websearch",
+            provider_id="tavily-search",
+        ),
+        ToolGroupInput(
+            toolgroup_id="builtin::memory",
+            provider_id="memory-runtime",
+        ),
+        ToolGroupInput(
+            toolgroup_id="builtin::code_interpreter",
+            provider_id="code-interpreter",
+        ),
+    ]
 
     return DistributionTemplate(
         name=name,
@@ -104,6 +128,7 @@ def get_distribution_template() -> DistributionTemplate:
                     embedding_model,
                 ],
                 default_shields=[ShieldInput(shield_id="${env.SAFETY_MODEL}")],
+                default_tool_groups=default_tool_groups,
             ),
         },
         run_config_env_vars={

llama_stack/templates/meta-reference-gpu/run-with-safety.yaml

@@ -1,6 +1,5 @@
 version: '2'
 image_name: meta-reference-gpu
-docker_image: null
 conda_env: meta-reference-gpu
 apis:
 - agents
@@ -11,6 +10,7 @@ apis:
 - safety
 - scoring
 - telemetry
+- tool_runtime
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -77,33 +77,50 @@ providers:
     provider_type: inline::braintrust
     config:
       openai_api_key: ${env.OPENAI_API_KEY:}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: code-interpreter
+    provider_type: inline::code-interpreter
+    config: {}
+  - provider_id: memory-runtime
+    provider_type: inline::memory-runtime
+    config: {}
 metadata_store:
-  namespace: null
   type: sqlite
   db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
 models:
 - metadata: {}
   model_id: ${env.INFERENCE_MODEL}
   provider_id: meta-reference-inference
-  provider_model_id: null
   model_type: llm
 - metadata: {}
   model_id: ${env.SAFETY_MODEL}
   provider_id: meta-reference-safety
-  provider_model_id: null
   model_type: llm
 - metadata:
     embedding_dimension: 384
   model_id: all-MiniLM-L6-v2
   provider_id: sentence-transformers
-  provider_model_id: null
   model_type: embedding
 shields:
-- params: null
-  shield_id: ${env.SAFETY_MODEL}
-  provider_id: null
-  provider_shield_id: null
+- shield_id: ${env.SAFETY_MODEL}
 memory_banks: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
+tool_groups:
+- toolgroup_id: builtin::websearch
+  provider_id: tavily-search
+- toolgroup_id: builtin::memory
+  provider_id: memory-runtime
+- toolgroup_id: builtin::code_interpreter
+  provider_id: code-interpreter

llama_stack/templates/meta-reference-gpu/run.yaml

@@ -1,6 +1,5 @@
 version: '2'
 image_name: meta-reference-gpu
-docker_image: null
 conda_env: meta-reference-gpu
 apis:
 - agents
@@ -11,6 +10,7 @@ apis:
 - safety
 - scoring
 - telemetry
+- tool_runtime
 providers:
   inference:
   - provider_id: meta-reference-inference
@@ -71,24 +71,39 @@ providers:
     provider_type: inline::braintrust
     config:
       openai_api_key: ${env.OPENAI_API_KEY:}
+  tool_runtime:
+  - provider_id: brave-search
+    provider_type: remote::brave-search
+    config:
+      api_key: ${env.BRAVE_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: tavily-search
+    provider_type: remote::tavily-search
+    config:
+      api_key: ${env.TAVILY_SEARCH_API_KEY:}
+      max_results: 3
+  - provider_id: code-interpreter
+    provider_type: inline::code-interpreter
+    config: {}
+  - provider_id: memory-runtime
+    provider_type: inline::memory-runtime
+    config: {}
 metadata_store:
-  namespace: null
   type: sqlite
   db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/meta-reference-gpu}/registry.db
 models:
 - metadata: {}
   model_id: ${env.INFERENCE_MODEL}
   provider_id: meta-reference-inference
-  provider_model_id: null
   model_type: llm
 - metadata:
     embedding_dimension: 384
   model_id: all-MiniLM-L6-v2
   provider_id: sentence-transformers
-  provider_model_id: null
   model_type: embedding
 shields: []
 memory_banks: []
 datasets: []
 scoring_fns: []
 eval_tasks: []
+tool_groups: []