From 62005dc1a921371c8d8be16a98ad1600d39f8aed Mon Sep 17 00:00:00 2001 From: Francisco Javier Arceo Date: Mon, 15 Dec 2025 11:39:01 -0500 Subject: [PATCH] feat: Making static prompt values in Rag/File Search configurable in Vector Store Config (#4368) # What does this PR do? - Enables users to configure prompts used throughout the File Search / Vector Retrieval - Configuration is defined in the Vector Stores Config so they can be modified at runtime - Backwards compatible, which means the fields are optional and default to the previously used values This is the summary of the new options in the `run.yaml` ```yaml vector_stores: file_search_params: header_template: 'knowledge_search tool found {num_chunks} chunks:\nBEGIN of knowledge_search tool results.\n' footer_template: 'END of knowledge_search tool results.\n' context_prompt_params: chunk_annotation_template: 'Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n' context_template: 'The above results were retrieved to help answer the user\'s query: "{query}". Use them as supporting information only in answering this query.{annotation_instruction}\n' annotation_prompt_params: enable_annotations: true annotation_instruction_template: 'Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format like \'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.\'. Do not add extra punctuation. Use only the file IDs provided, do not invent new ones.' chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|>\n{chunk_text}\n' ``` ## Test Plan Added tests. --------- Signed-off-by: Francisco Javier Arceo --- .../agents/inline_meta-reference.mdx | 1 + .../tool_runtime/inline_rag-runtime.mdx | 6 + src/llama_stack/core/datatypes.py | 141 +- src/llama_stack/core/resolver.py | 9 +- src/llama_stack/core/stack.py | 2 - .../distributions/ci-tests/config.yaml | 33 + .../ci-tests/run-with-postgres-store.yaml | 33 + .../distributions/starter-gpu/config.yaml | 33 + .../starter-gpu/run-with-postgres-store.yaml | 33 + .../distributions/starter/config.yaml | 33 + .../starter/run-with-postgres-store.yaml | 33 + .../inline/agents/meta_reference/agents.py | 1 + .../inline/agents/meta_reference/config.py | 7 +- .../responses/openai_responses.py | 2 + .../meta_reference/responses/tool_executor.py | 53 +- .../inline/tool_runtime/rag/config.py | 9 +- .../inline/tool_runtime/rag/memory.py | 20 +- .../providers/utils/memory/constants.py | 14 + ...8b41f62662aab6d30c0af57da645edbbe84b6.json | 2152 +++++++ ...6f8989621648e55c78588b033a64040266f49.json | 5076 +++++++++++++++++ ...3023c38e865065de8ade26677251fdcb4e456.json | 2036 +++++++ ...078d4b5e96f823be88e4463707d499e013262.json | 1712 ++++++ ...1d5e86dafd5e23479728505924440ce9b11d6.json | 1780 ++++++ ...2b63fbc42df98f9612af5eef7613e2b967900.json | 631 ++ ...6c6b5307261c8f4a54bd08786e386f745ab74.json | 763 +++ ...7bffe012b864e04f6df6f52adadfd3a50896e.json | 668 +++ ...a353cef0e3ea0e3c6044c04018e1718853084.json | 925 +++ ...e9f6bdb8710a974804a5bc79fd8bca669464f.json | 2738 +++++++++ ...d9b804be74e28c36069860db48e39e36b080c.json | 1091 ++++ ...83e9deb599d5b51001b6f4c13f32342011b26.json | 1315 +++++ ...86a2c7c5817e07e150f92a61c84c97b5c3618.json | 1060 ++++ ...e9037a6d27d9426a6e68cc65ff538af8d748d.json | 1627 ++++++ ...e30a76a68f00a023ec0cf4815afeafc83fc79.json | 2792 +++++++++ ...b6ff44f001c5de5a24118d0fa51dc216e1917.json | 2765 +++++++++ ...a1b338ba57f16540ee60d77cd3563eddc801e.json | 925 +++ ...2f4284013f6472db141a339b3e54ea62b4827.json | 1645 ++++++ ...5d55137e8e85e36c7adc10d0421f6912cd883.json | 763 +++ ...8bc6f61fb809b4e648f48477ba4cd9c81a216.json | 1820 ++++++ ...306df8117cf7c14b3087e9cdea23ceb8c8104.json | 1091 ++++ ...2f1ad2d83aec3532ef10c5cfcab2e637ee94c.json | 4455 +++++++++++++++ ...c176a6120fca9786d83807719f1a-fc0119e1.json | 547 ++ ...b1c1d3714fa8a3acaac3d476e481-fc0119e1.json | 547 ++ ...0864901048f21574b80ff24fb75d-fc0119e1.json | 547 ++ ...1b77fa24864ac237da21d62a8ced-fc0119e1.json | 547 ++ tests/unit/core/test_stack_validation.py | 12 +- tests/unit/core/test_vector_stores_config.py | 170 + tests/unit/rag/test_rag_query.py | 17 +- 47 files changed, 42640 insertions(+), 40 deletions(-) create mode 100644 tests/integration/responses/recordings/02b32fe03919cf862d4f97088b58b41f62662aab6d30c0af57da645edbbe84b6.json create mode 100644 tests/integration/responses/recordings/02e846d83678946e7b7dd7610496f8989621648e55c78588b033a64040266f49.json create mode 100644 tests/integration/responses/recordings/0652618307804555ec2837e1bd33023c38e865065de8ade26677251fdcb4e456.json create mode 100644 tests/integration/responses/recordings/0b45257ef8ece1b2ae98dc4f3fb078d4b5e96f823be88e4463707d499e013262.json create mode 100644 tests/integration/responses/recordings/17cf0143efe13139537802fe97b1d5e86dafd5e23479728505924440ce9b11d6.json create mode 100644 tests/integration/responses/recordings/1e171766576921b1462c0773e012b63fbc42df98f9612af5eef7613e2b967900.json create mode 100644 tests/integration/responses/recordings/256215277d288407e08176fe22b6c6b5307261c8f4a54bd08786e386f745ab74.json create mode 100644 tests/integration/responses/recordings/29ab0b407d3d3f6bb893470702b7bffe012b864e04f6df6f52adadfd3a50896e.json create mode 100644 tests/integration/responses/recordings/2dc865d055f3ce6d4438143a67da353cef0e3ea0e3c6044c04018e1718853084.json create mode 100644 tests/integration/responses/recordings/2fa72534cefd5c8baeb7e65efd1e9f6bdb8710a974804a5bc79fd8bca669464f.json create mode 100644 tests/integration/responses/recordings/3ad5c85a4df455be7cc724d789dd9b804be74e28c36069860db48e39e36b080c.json create mode 100644 tests/integration/responses/recordings/4f46489a9532e9f6c0b8457067383e9deb599d5b51001b6f4c13f32342011b26.json create mode 100644 tests/integration/responses/recordings/556bb5a135769252ddb4232a07a86a2c7c5817e07e150f92a61c84c97b5c3618.json create mode 100644 tests/integration/responses/recordings/65d67bc8aa00d27af1e9f5ca584e9037a6d27d9426a6e68cc65ff538af8d748d.json create mode 100644 tests/integration/responses/recordings/81c896a41bb1ff7107978b7f759e30a76a68f00a023ec0cf4815afeafc83fc79.json create mode 100644 tests/integration/responses/recordings/99f6a59ebd00d6fcbf93a7cde22b6ff44f001c5de5a24118d0fa51dc216e1917.json create mode 100644 tests/integration/responses/recordings/9b13d4fa1a58ff6bce3ae987031a1b338ba57f16540ee60d77cd3563eddc801e.json create mode 100644 tests/integration/responses/recordings/a5a92ca10e1cf3901daeb8a2f862f4284013f6472db141a339b3e54ea62b4827.json create mode 100644 tests/integration/responses/recordings/a85a6b4b83b5cc55c03d941a9e35d55137e8e85e36c7adc10d0421f6912cd883.json create mode 100644 tests/integration/responses/recordings/abdc464d8573d03c671266b602b8bc6f61fb809b4e648f48477ba4cd9c81a216.json create mode 100644 tests/integration/responses/recordings/eddd68f1cd5c593ed7b6cb4b4b2306df8117cf7c14b3087e9cdea23ceb8c8104.json create mode 100644 tests/integration/responses/recordings/fcff32ffee8ecdc771165eff7e82f1ad2d83aec3532ef10c5cfcab2e637ee94c.json create mode 100644 tests/integration/responses/recordings/models-48e344be78178094bdd599f7cf97f076fdd1c176a6120fca9786d83807719f1a-fc0119e1.json create mode 100644 tests/integration/responses/recordings/models-54503512995f4c6db759e2e7f2580f445f42b1c1d3714fa8a3acaac3d476e481-fc0119e1.json create mode 100644 tests/integration/responses/recordings/models-875254c069dcb861033e5a4e9100179cc21c0864901048f21574b80ff24fb75d-fc0119e1.json create mode 100644 tests/integration/responses/recordings/models-cc7501817830a20cc746a1d560a75f58b9111b77fa24864ac237da21d62a8ced-fc0119e1.json create mode 100644 tests/unit/core/test_vector_stores_config.py diff --git a/docs/docs/providers/agents/inline_meta-reference.mdx b/docs/docs/providers/agents/inline_meta-reference.mdx index 99a67feb4..d90cffdc2 100644 --- a/docs/docs/providers/agents/inline_meta-reference.mdx +++ b/docs/docs/providers/agents/inline_meta-reference.mdx @@ -15,6 +15,7 @@ Meta's reference implementation of an agent system that can use tools, access ve | Field | Type | Required | Default | Description | |-------|------|----------|---------|-------------| | `persistence` | `AgentPersistenceConfig` | No | | | +| `vector_stores_config` | `VectorStoresConfig \| None` | No | | Configuration for vector store prompt templates and behavior | ## Sample Configuration diff --git a/docs/docs/providers/tool_runtime/inline_rag-runtime.mdx b/docs/docs/providers/tool_runtime/inline_rag-runtime.mdx index 97428c2e3..26c65b1a2 100644 --- a/docs/docs/providers/tool_runtime/inline_rag-runtime.mdx +++ b/docs/docs/providers/tool_runtime/inline_rag-runtime.mdx @@ -10,6 +10,12 @@ title: inline::rag-runtime RAG (Retrieval-Augmented Generation) tool runtime for document ingestion, chunking, and semantic search. +## Configuration + +| Field | Type | Required | Default | Description | +|-------|------|----------|---------|-------------| +| `vector_stores_config` | `VectorStoresConfig` | No | `default_provider_id=None default_embedding_model=None rewrite_query_params=None file_search_params=FileSearchParams(header_template='knowledge_search tool found {num_chunks} chunks:\nBEGIN of knowledge_search tool results.\n', footer_template='END of knowledge_search tool results.\n') context_prompt_params=ContextPromptParams(chunk_annotation_template='Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n', context_template='The above results were retrieved to help answer the user\'s query: "{query}". Use them as supporting information only in answering this query.{annotation_instruction}\n') annotation_prompt_params=AnnotationPromptParams(enable_annotations=True, annotation_instruction_template=" Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format like 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'. Do not add extra punctuation. Use only the file IDs provided, do not invent new ones.", chunk_annotation_template='[{index}] {metadata_text} cite as <|{file_id}|>\n{chunk_text}\n')` | Configuration for vector store prompt templates and behavior | + ## Sample Configuration ```yaml diff --git a/src/llama_stack/core/datatypes.py b/src/llama_stack/core/datatypes.py index c184bbaac..08d43fce9 100644 --- a/src/llama_stack/core/datatypes.py +++ b/src/llama_stack/core/datatypes.py @@ -18,7 +18,15 @@ from llama_stack.core.storage.datatypes import ( StorageConfig, ) from llama_stack.log import LoggingConfig -from llama_stack.providers.utils.memory.constants import DEFAULT_QUERY_REWRITE_PROMPT +from llama_stack.providers.utils.memory.constants import ( + DEFAULT_ANNOTATION_INSTRUCTION_TEMPLATE, + DEFAULT_CHUNK_ANNOTATION_TEMPLATE, + DEFAULT_CHUNK_WITH_SOURCES_TEMPLATE, + DEFAULT_CONTEXT_TEMPLATE, + DEFAULT_FILE_SEARCH_FOOTER_TEMPLATE, + DEFAULT_FILE_SEARCH_HEADER_TEMPLATE, + DEFAULT_QUERY_REWRITE_PROMPT, +) from llama_stack_api import ( Api, Benchmark, @@ -371,6 +379,125 @@ class RewriteQueryParams(BaseModel): description="Temperature for query expansion model (0.0 = deterministic, 1.0 = creative).", ) + @field_validator("prompt") + @classmethod + def validate_prompt(cls, v: str) -> str: + if "{query}" not in v: + raise ValueError("prompt must contain {query} placeholder") + return v + + @field_validator("max_tokens") + @classmethod + def validate_max_tokens(cls, v: int) -> int: + if v <= 0: + raise ValueError("max_tokens must be positive") + if v > 4096: + raise ValueError("max_tokens should not exceed 4096") + return v + + @field_validator("temperature") + @classmethod + def validate_temperature(cls, v: float) -> float: + if v < 0.0 or v > 2.0: + raise ValueError("temperature must be between 0.0 and 2.0") + return v + + +class FileSearchParams(BaseModel): + """Configuration for file search tool output formatting.""" + + header_template: str = Field( + default=DEFAULT_FILE_SEARCH_HEADER_TEMPLATE, + description="Template for the header text shown before search results. Available placeholders: {num_chunks} number of chunks found.", + ) + footer_template: str = Field( + default=DEFAULT_FILE_SEARCH_FOOTER_TEMPLATE, + description="Template for the footer text shown after search results.", + ) + + @field_validator("header_template") + @classmethod + def validate_header_template(cls, v: str) -> str: + if len(v) == 0: + raise ValueError("header_template must not be empty") + if "{num_chunks}" not in v: + raise ValueError("header_template must contain {num_chunks} placeholder") + if "knowledge_search" not in v.lower(): + raise ValueError( + "header_template must contain 'knowledge_search' keyword to ensure proper tool identification" + ) + return v + + +class ContextPromptParams(BaseModel): + """Configuration for LLM prompt content and chunk formatting.""" + + chunk_annotation_template: str = Field( + default=DEFAULT_CHUNK_ANNOTATION_TEMPLATE, + description="Template for formatting individual chunks in search results. Available placeholders: {index} 1-based chunk index, {chunk.content} chunk content, {metadata} chunk metadata dict.", + ) + context_template: str = Field( + default=DEFAULT_CONTEXT_TEMPLATE, + description="Template for explaining the search results to the model. Available placeholders: {query} user's query, {num_chunks} number of chunks.", + ) + + @field_validator("chunk_annotation_template") + @classmethod + def validate_chunk_annotation_template(cls, v: str) -> str: + if len(v) == 0: + raise ValueError("chunk_annotation_template must not be empty") + if "{chunk.content}" not in v: + raise ValueError("chunk_annotation_template must contain {chunk.content} placeholder") + if "{index}" not in v: + raise ValueError("chunk_annotation_template must contain {index} placeholder") + return v + + @field_validator("context_template") + @classmethod + def validate_context_template(cls, v: str) -> str: + if len(v) == 0: + raise ValueError("context_template must not be empty") + if "{query}" not in v: + raise ValueError("context_template must contain {query} placeholder") + return v + + +class AnnotationPromptParams(BaseModel): + """Configuration for source annotation and attribution features.""" + + enable_annotations: bool = Field( + default=True, + description="Whether to include annotation information in results.", + ) + annotation_instruction_template: str = Field( + default=DEFAULT_ANNOTATION_INSTRUCTION_TEMPLATE, + description="Instructions for how the model should cite sources. Used when enable_annotations is True.", + ) + chunk_annotation_template: str = Field( + default=DEFAULT_CHUNK_WITH_SOURCES_TEMPLATE, + description="Template for chunks with annotation information. Available placeholders: {index} 1-based chunk index, {metadata_text} formatted metadata, {file_id} document identifier, {chunk_text} chunk content.", + ) + + @field_validator("chunk_annotation_template") + @classmethod + def validate_chunk_annotation_template(cls, v: str) -> str: + if len(v) == 0: + raise ValueError("chunk_annotation_template must not be empty") + if "{index}" not in v: + raise ValueError("chunk_annotation_template must contain {index} placeholder") + if "{chunk_text}" not in v: + raise ValueError("chunk_annotation_template must contain {chunk_text} placeholder") + if "{file_id}" not in v: + raise ValueError("chunk_annotation_template must contain {file_id} placeholder") + return v + + @field_validator("annotation_instruction_template") + @classmethod + def validate_annotation_instruction_template(cls, v: str) -> str: + if len(v) == 0: + raise ValueError("annotation_instruction_template must not be empty") + return v + class VectorStoresConfig(BaseModel): """Configuration for vector stores in the stack.""" @@ -387,6 +514,18 @@ class VectorStoresConfig(BaseModel): default=None, description="Parameters for query rewriting/expansion. None disables query rewriting.", ) + file_search_params: FileSearchParams = Field( + default_factory=FileSearchParams, + description="Configuration for file search tool output formatting.", + ) + context_prompt_params: ContextPromptParams = Field( + default_factory=ContextPromptParams, + description="Configuration for LLM prompt content and chunk formatting.", + ) + annotation_prompt_params: AnnotationPromptParams = Field( + default_factory=AnnotationPromptParams, + description="Configuration for source annotation and attribution features.", + ) class SafetyConfig(BaseModel): diff --git a/src/llama_stack/core/resolver.py b/src/llama_stack/core/resolver.py index c5599aa51..a04ad6216 100644 --- a/src/llama_stack/core/resolver.py +++ b/src/llama_stack/core/resolver.py @@ -3,6 +3,7 @@ # # This source code is licensed under the terms described in the LICENSE file in # the root directory of this source tree. + import importlib import importlib.metadata import inspect @@ -406,13 +407,17 @@ async def instantiate_provider( args = [provider_spec.api, inner_impls, deps, dist_registry, policy] else: method = "get_provider_impl" + provider_config = provider.config.copy() + # Inject vector_stores_config for providers that need it (introspection-based) config_type = instantiate_class_type(provider_spec.config_class) - config = config_type(**provider.config) + if hasattr(config_type, "__fields__") and "vector_stores_config" in config_type.__fields__: + provider_config["vector_stores_config"] = run_config.vector_stores + + config = config_type(**provider_config) args = [config, deps] if "policy" in inspect.signature(getattr(module, method)).parameters: args.append(policy) - fn = getattr(module, method) impl = await fn(*args) impl.__provider_id__ = provider.provider_id diff --git a/src/llama_stack/core/stack.py b/src/llama_stack/core/stack.py index 6237e05c6..c2a1c5030 100644 --- a/src/llama_stack/core/stack.py +++ b/src/llama_stack/core/stack.py @@ -229,8 +229,6 @@ async def validate_vector_stores_config(vector_stores_config: VectorStoresConfig if vector_stores_config.rewrite_query_params: if vector_stores_config.rewrite_query_params.model: await _validate_rewrite_query_model(vector_stores_config.rewrite_query_params.model, impls) - if "{query}" not in vector_stores_config.rewrite_query_params.prompt: - raise ValueError("'{query}' placeholder is required in the prompt template") async def _validate_embedding_model(embedding_model: QualifiedModel, impls: dict[Api, Any]) -> None: diff --git a/src/llama_stack/distributions/ci-tests/config.yaml b/src/llama_stack/distributions/ci-tests/config.yaml index e83fc7fb5..00bf40916 100644 --- a/src/llama_stack/distributions/ci-tests/config.yaml +++ b/src/llama_stack/distributions/ci-tests/config.yaml @@ -277,5 +277,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml b/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml index 8414dcae5..e3db814ea 100644 --- a/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml +++ b/src/llama_stack/distributions/ci-tests/run-with-postgres-store.yaml @@ -286,5 +286,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/distributions/starter-gpu/config.yaml b/src/llama_stack/distributions/starter-gpu/config.yaml index 9ef5b3f6d..2e90e032e 100644 --- a/src/llama_stack/distributions/starter-gpu/config.yaml +++ b/src/llama_stack/distributions/starter-gpu/config.yaml @@ -280,5 +280,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml b/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml index 0662986f1..a245317b5 100644 --- a/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml +++ b/src/llama_stack/distributions/starter-gpu/run-with-postgres-store.yaml @@ -289,5 +289,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/distributions/starter/config.yaml b/src/llama_stack/distributions/starter/config.yaml index 3e6cde13a..59e1acc6a 100644 --- a/src/llama_stack/distributions/starter/config.yaml +++ b/src/llama_stack/distributions/starter/config.yaml @@ -277,5 +277,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/distributions/starter/run-with-postgres-store.yaml b/src/llama_stack/distributions/starter/run-with-postgres-store.yaml index 1da4f0da7..fa99647af 100644 --- a/src/llama_stack/distributions/starter/run-with-postgres-store.yaml +++ b/src/llama_stack/distributions/starter/run-with-postgres-store.yaml @@ -286,5 +286,38 @@ vector_stores: default_embedding_model: provider_id: sentence-transformers model_id: nomic-ai/nomic-embed-text-v1.5 + file_search_params: + header_template: 'knowledge_search tool found {num_chunks} chunks: + + BEGIN of knowledge_search tool results. + + ' + footer_template: 'END of knowledge_search tool results. + + ' + context_prompt_params: + chunk_annotation_template: 'Result {index} + + Content: {chunk.content} + + Metadata: {metadata} + + ' + context_template: 'The above results were retrieved to help answer the user''s + query: "{query}". Use them as supporting information only in answering this + query.{annotation_instruction} + + ' + annotation_prompt_params: + enable_annotations: true + annotation_instruction_template: ' Cite sources immediately at the end of sentences + before punctuation, using `<|file-id|>` format like ''This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.''. + Do not add extra punctuation. Use only the file IDs provided, do not invent + new ones.' + chunk_annotation_template: '[{index}] {metadata_text} cite as <|{file_id}|> + + {chunk_text} + + ' safety: default_shield_id: llama-guard diff --git a/src/llama_stack/providers/inline/agents/meta_reference/agents.py b/src/llama_stack/providers/inline/agents/meta_reference/agents.py index 39cc22be7..1c88ddcc1 100644 --- a/src/llama_stack/providers/inline/agents/meta_reference/agents.py +++ b/src/llama_stack/providers/inline/agents/meta_reference/agents.py @@ -78,6 +78,7 @@ class MetaReferenceAgentsImpl(Agents): conversations_api=self.conversations_api, prompts_api=self.prompts_api, files_api=self.files_api, + vector_stores_config=self.config.vector_stores_config, ) async def shutdown(self) -> None: diff --git a/src/llama_stack/providers/inline/agents/meta_reference/config.py b/src/llama_stack/providers/inline/agents/meta_reference/config.py index a800b426b..5034bbf25 100644 --- a/src/llama_stack/providers/inline/agents/meta_reference/config.py +++ b/src/llama_stack/providers/inline/agents/meta_reference/config.py @@ -6,8 +6,9 @@ from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field +from llama_stack.core.datatypes import VectorStoresConfig from llama_stack.core.storage.datatypes import KVStoreReference, ResponsesStoreReference @@ -20,6 +21,10 @@ class AgentPersistenceConfig(BaseModel): class MetaReferenceAgentsImplConfig(BaseModel): persistence: AgentPersistenceConfig + vector_stores_config: VectorStoresConfig | None = Field( + default=None, + description="Configuration for vector store prompt templates and behavior", + ) @classmethod def sample_run_config(cls, __distro_dir__: str) -> dict[str, Any]: diff --git a/src/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py b/src/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py index 68e6e3eb2..4b3c6fc0f 100644 --- a/src/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py +++ b/src/llama_stack/providers/inline/agents/meta_reference/responses/openai_responses.py @@ -80,6 +80,7 @@ class OpenAIResponsesImpl: conversations_api: Conversations, prompts_api: Prompts, files_api: Files, + vector_stores_config=None, ): self.inference_api = inference_api self.tool_groups_api = tool_groups_api @@ -92,6 +93,7 @@ class OpenAIResponsesImpl: tool_groups_api=tool_groups_api, tool_runtime_api=tool_runtime_api, vector_io_api=vector_io_api, + vector_stores_config=vector_stores_config, ) self.prompts_api = prompts_api self.files_api = files_api diff --git a/src/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py b/src/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py index d27a0f8ad..1be7c2d7b 100644 --- a/src/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py +++ b/src/llama_stack/providers/inline/agents/meta_reference/responses/tool_executor.py @@ -12,6 +12,10 @@ from typing import Any from opentelemetry import trace from llama_stack.log import get_logger +from llama_stack.providers.utils.memory.constants import ( + DEFAULT_ANNOTATION_INSTRUCTION_TEMPLATE, + DEFAULT_CHUNK_WITH_SOURCES_TEMPLATE, +) from llama_stack_api import ( ImageContentItem, OpenAIChatCompletionContentPartImageParam, @@ -52,10 +56,12 @@ class ToolExecutor: tool_groups_api: ToolGroups, tool_runtime_api: ToolRuntime, vector_io_api: VectorIO, + vector_stores_config=None, ): self.tool_groups_api = tool_groups_api self.tool_runtime_api = tool_runtime_api self.vector_io_api = vector_io_api + self.vector_stores_config = vector_stores_config async def execute_tool_call( self, @@ -148,13 +154,33 @@ class ToolExecutor: for results in all_results: search_results.extend(results) - content_items = [] - content_items.append( - TextContentItem( - text=f"knowledge_search tool found {len(search_results)} chunks:\nBEGIN of knowledge_search tool results.\n" - ) + # Get templates from vector stores config, fallback to constants + + # Check if annotations are enabled + enable_annotations = ( + self.vector_stores_config + and self.vector_stores_config.annotation_prompt_params + and self.vector_stores_config.annotation_prompt_params.enable_annotations ) + # Get templates + header_template = self.vector_stores_config.file_search_params.header_template + footer_template = self.vector_stores_config.file_search_params.footer_template + context_template = self.vector_stores_config.context_prompt_params.context_template + + # Get annotation templates (use defaults if annotations disabled) + if enable_annotations: + chunk_annotation_template = self.vector_stores_config.annotation_prompt_params.chunk_annotation_template + annotation_instruction_template = ( + self.vector_stores_config.annotation_prompt_params.annotation_instruction_template + ) + else: + chunk_annotation_template = DEFAULT_CHUNK_WITH_SOURCES_TEMPLATE + annotation_instruction_template = DEFAULT_ANNOTATION_INSTRUCTION_TEMPLATE + + content_items = [] + content_items.append(TextContentItem(text=header_template.format(num_chunks=len(search_results)))) + unique_files = set() for i, result_item in enumerate(search_results): chunk_text = result_item.content[0].text if result_item.content else "" @@ -166,22 +192,23 @@ class ToolExecutor: if result_item.attributes: metadata_text += f", attributes: {result_item.attributes}" - text_content = f"[{i + 1}] {metadata_text} (cite as <|{file_id}|>)\n{chunk_text}\n" + text_content = chunk_annotation_template.format( + index=i + 1, metadata_text=metadata_text, file_id=file_id, chunk_text=chunk_text + ) content_items.append(TextContentItem(text=text_content)) unique_files.add(file_id) - content_items.append(TextContentItem(text="END of knowledge_search tool results.\n")) + content_items.append(TextContentItem(text=footer_template)) - citation_instruction = "" + annotation_instruction = "" if unique_files: - citation_instruction = ( - " Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format (e.g., 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'). " - "Do not add extra punctuation. Use only the file IDs provided (do not invent new ones)." - ) + annotation_instruction = annotation_instruction_template content_items.append( TextContentItem( - text=f'The above results were retrieved to help answer the user\'s query: "{query}". Use them as supporting information only in answering this query.{citation_instruction}\n', + text=context_template.format( + query=query, num_chunks=len(search_results), annotation_instruction=annotation_instruction + ) ) ) diff --git a/src/llama_stack/providers/inline/tool_runtime/rag/config.py b/src/llama_stack/providers/inline/tool_runtime/rag/config.py index 43ba78e65..62b0a9918 100644 --- a/src/llama_stack/providers/inline/tool_runtime/rag/config.py +++ b/src/llama_stack/providers/inline/tool_runtime/rag/config.py @@ -6,10 +6,17 @@ from typing import Any -from pydantic import BaseModel +from pydantic import BaseModel, Field + +from llama_stack.core.datatypes import VectorStoresConfig class RagToolRuntimeConfig(BaseModel): + vector_stores_config: VectorStoresConfig = Field( + default_factory=VectorStoresConfig, + description="Configuration for vector store prompt templates and behavior", + ) + @classmethod def sample_run_config(cls, __distro_dir__: str, **kwargs: Any) -> dict[str, Any]: return {} diff --git a/src/llama_stack/providers/inline/tool_runtime/rag/memory.py b/src/llama_stack/providers/inline/tool_runtime/rag/memory.py index afb54a8a9..c3f9882d0 100644 --- a/src/llama_stack/providers/inline/tool_runtime/rag/memory.py +++ b/src/llama_stack/providers/inline/tool_runtime/rag/memory.py @@ -221,11 +221,15 @@ class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime): chunks = chunks[: query_config.max_chunks] tokens = 0 - picked: list[InterleavedContentItem] = [ - TextContentItem( - text=f"knowledge_search tool found {len(chunks)} chunks:\nBEGIN of knowledge_search tool results.\n" - ) - ] + + # Get templates from vector stores config + vector_stores_config = self.config.vector_stores_config + header_template = vector_stores_config.file_search_params.header_template + footer_template = vector_stores_config.file_search_params.footer_template + chunk_template = vector_stores_config.context_prompt_params.chunk_annotation_template + context_template = vector_stores_config.context_prompt_params.context_template + + picked: list[InterleavedContentItem] = [TextContentItem(text=header_template.format(num_chunks=len(chunks)))] for i, chunk in enumerate(chunks): metadata = chunk.metadata tokens += metadata.get("token_count", 0) @@ -255,13 +259,13 @@ class MemoryToolRuntimeImpl(ToolGroupsProtocolPrivate, ToolRuntime): if k not in metadata_keys_to_exclude_from_context: metadata_for_context[k] = metadata[k] - text_content = query_config.chunk_template.format(index=i + 1, chunk=chunk, metadata=metadata_for_context) + text_content = chunk_template.format(index=i + 1, chunk=chunk, metadata=metadata_for_context) picked.append(TextContentItem(text=text_content)) - picked.append(TextContentItem(text="END of knowledge_search tool results.\n")) + picked.append(TextContentItem(text=footer_template)) picked.append( TextContentItem( - text=f'The above results were retrieved to help answer the user\'s query: "{interleaved_content_as_str(content)}". Use them as supporting information only in answering this query.\n', + text=context_template.format(query=interleaved_content_as_str(content), annotation_instruction="") ) ) diff --git a/src/llama_stack/providers/utils/memory/constants.py b/src/llama_stack/providers/utils/memory/constants.py index 1f6e2cef6..b5a318bd8 100644 --- a/src/llama_stack/providers/utils/memory/constants.py +++ b/src/llama_stack/providers/utils/memory/constants.py @@ -6,3 +6,17 @@ # Default prompt template for query rewriting in vector search DEFAULT_QUERY_REWRITE_PROMPT = "Expand this query with relevant synonyms and related terms. Return only the improved query, no explanations:\n\n{query}\n\nImproved query:" + +# Default templates for file search tool output formatting +DEFAULT_FILE_SEARCH_HEADER_TEMPLATE = ( + "knowledge_search tool found {num_chunks} chunks:\nBEGIN of knowledge_search tool results.\n" +) +DEFAULT_FILE_SEARCH_FOOTER_TEMPLATE = "END of knowledge_search tool results.\n" + +# Default templates for LLM prompt content and chunk formatting +DEFAULT_CHUNK_ANNOTATION_TEMPLATE = "Result {index}\nContent: {chunk.content}\nMetadata: {metadata}\n" +DEFAULT_CONTEXT_TEMPLATE = 'The above results were retrieved to help answer the user\'s query: "{query}". Use them as supporting information only in answering this query.{annotation_instruction}\n' + +# Default templates for source annotation and attribution features +DEFAULT_ANNOTATION_INSTRUCTION_TEMPLATE = " Cite sources immediately at the end of sentences before punctuation, using `<|file-id|>` format like 'This is a fact <|file-Cn3MSNn72ENTiiq11Qda4A|>.'. Do not add extra punctuation. Use only the file IDs provided, do not invent new ones." +DEFAULT_CHUNK_WITH_SOURCES_TEMPLATE = "[{index}] {metadata_text} cite as <|{file_id}|>\n{chunk_text}\n" diff --git a/tests/integration/responses/recordings/02b32fe03919cf862d4f97088b58b41f62662aab6d30c0af57da645edbbe84b6.json b/tests/integration/responses/recordings/02b32fe03919cf862d4f97088b58b41f62662aab6d30c0af57da645edbbe84b6.json new file mode 100644 index 000000000..2e53862f6 --- /dev/null +++ b/tests/integration/responses/recordings/02b32fe03919cf862d4f97088b58b41f62662aab6d30c0af57da645edbbe84b6.json @@ -0,0 +1,2152 @@ +{ + "test_id": "tests/integration/responses/test_file_search.py::test_response_file_search_streaming_events[client_with_models-txt=openai/gpt-4o]", + "request": { + "method": "POST", + "url": "https://api.openai.com/v1/v1/chat/completions", + "headers": {}, + "body": { + "model": "gpt-4o", + "messages": [ + { + "role": "user", + "content": "What are the marketing updates?" + }, + { + "role": "assistant", + "content": "", + "tool_calls": [ + { + "index": 0, + "id": "call_yrecP7RchFwSrzeZd9oqtJEN", + "type": "function", + "function": { + "name": "knowledge_search", + "arguments": "{\"query\":\"marketing updates\"}" + } + } + ] + }, + { + "role": "tool", + "tool_call_id": "call_yrecP7RchFwSrzeZd9oqtJEN", + "content": [ + { + "type": "text", + "text": "knowledge_search tool found 4 chunks:\nBEGIN of knowledge_search tool results.\n" + }, + { + "type": "text", + "text": "[1] document_id: file-450428750203, score: 0.0030630310621710803, attributes: {'region': 'us', 'category': 'engineering', 'date': 1680307200.0, 'filename': 'us_engineering_q2.txt', 'chunk_id': '084e15ad-480a-eae8-9242-391c53854867', 'document_id': 'file-450428750203', 'token_count': 18.0, 'metadata_token_count': 32.0} cite as <|file-450428750203|>\nUS technical updates for Q2 2023. 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active parameters and 128 experts. \n" + }, + { + "type": "text", + "text": "[2] document_id: file-156847829497, score: 0.0032793158911516916, attributes: {'filename': 'llama_stack_and_models.pdf', 'chunk_id': '16d99c69-8323-27ce-3bd7-7b51dcac2735', 'document_id': 'file-156847829497', 'token_count': 498.0, 'metadata_token_count': 11.0} cite as <|file-156847829497|>\nLlama Stack \nLlama Stack Overview \nLlama Stack standardizes the core building blocks that simplify AI application development. It codifies best \npractices\n \nacross\n \nthe\n \nLlama\n \necosystem.\n \nMore\n \nspecifically,\n \nit\n \nprovides\n \u25cf Unified API layer for Inference, RAG, Agents, Tools, Safety, Evals, and Telemetry. \u25cf Plugin architecture to support the rich ecosystem of different API implementations in various \nenvironments,\n \nincluding\n \nlocal\n \ndevelopment,\n \non-premises,\n \ncloud,\n \nand\n \nmobile.\n \u25cf Prepackaged verified distributions which offer a one-stop solution for developers to get started quickly \nand\n \nreliably\n \nin\n \nany\n \nenvironment.\n \u25cf Multiple developer interfaces like CLI and SDKs for Python, Typescript, iOS, and Android. \u25cf Standalone applications as examples for how to build production-grade AI applications with Llama \nStack.\n \nLlama Stack Benefits \n\u25cf Flexible Options: Developers can choose their preferred infrastructure without changing APIs and enjoy \nflexible\n \ndeployment\n \nchoices.\n \u25cf Consistent Experience: With its unified APIs, Llama Stack makes it easier to build, test, and deploy AI \napplications\n \nwith\n \nconsistent\n \napplication\n \nbehavior.\n \u25cf Robust Ecosystem: Llama Stack is already integrated with distribution partners (cloud providers, \nhardware\n \nvendors,\n \nand\n \nAI-focused\n \ncompanies)\n \nthat\n \noffer\n \ntailored\n \ninfrastructure,\n \nsoftware,\n \nand\n \nservices\n \nfor\n \ndeploying\n \nLlama\n \nmodels.\n \nLlama 4 Maverick \n Llama 4 Maverick is a Mixture-of-Experts (MoE) model with 17 billion active parameters and 128 experts. \n" + }, + { + "type": "text", + "text": "END of knowledge_search tool results.\n" + }, + { + "type": "text", + "text": "The above results were retrieved to help answer the user's query: \"Llama 4 Maverick model experts\". 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standardizes the core building blocks that simplify AI application development. 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"owned_by": "google", + "display_name": "Veo 3 fast" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "models/veo-3.1-generate-preview", + "created": null, + "object": "model", + "owned_by": "google", + "display_name": "Veo 3.1" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "models/veo-3.1-fast-generate-preview", + "created": null, + "object": "model", + "owned_by": "google", + "display_name": "Veo 3.1 fast" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "models/gemini-2.5-flash-native-audio-latest", + "created": null, + "object": "model", + "owned_by": "google", + "display_name": "Gemini 2.5 Flash Native Audio Latest" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "models/gemini-2.5-flash-native-audio-preview-09-2025", + "created": null, + "object": "model", + "owned_by": "google", + "display_name": "Gemini 2.5 Flash Native Audio Preview 09-2025" + } + }, + { + "__type__": "openai.types.model.Model", + "__data__": { + "id": "models/lyria-realtime-exp", + "created": null, + "object": "model", + "owned_by": "google", + "display_name": "Lyria Realtime Experimental" + } + } + ], + "is_streaming": false + }, + "id_normalization_mapping": {} +} diff --git a/tests/unit/core/test_stack_validation.py b/tests/unit/core/test_stack_validation.py index d63eac034..9b7f4ca9f 100644 --- a/tests/unit/core/test_stack_validation.py +++ b/tests/unit/core/test_stack_validation.py @@ -90,14 +90,12 @@ class TestVectorStoresValidation: async def test_validate_rewrite_query_prompt_missing_placeholder(self): """Test validation fails when prompt template is missing {query} placeholder.""" - config = VectorStoresConfig( - rewrite_query_params=RewriteQueryParams( - prompt="This prompt has no placeholder", - ), - ) + from pydantic import ValidationError - with pytest.raises(ValueError, match="'\\{query\\}' placeholder is required"): - await validate_vector_stores_config(config, {}) + with pytest.raises(ValidationError, match=r"prompt must contain \{query\} placeholder"): + RewriteQueryParams( + prompt="This prompt has no placeholder", + ) class TestSafetyConfigValidation: diff --git a/tests/unit/core/test_vector_stores_config.py b/tests/unit/core/test_vector_stores_config.py new file mode 100644 index 000000000..f17e70fa7 --- /dev/null +++ b/tests/unit/core/test_vector_stores_config.py @@ -0,0 +1,170 @@ +# Copyright (c) Meta Platforms, Inc. and affiliates. +# All rights reserved. +# +# This source code is licensed under the terms described in the LICENSE file in +# the root directory of this source tree. + +import pytest +from pydantic import ValidationError + +from llama_stack.core.datatypes import QualifiedModel, RewriteQueryParams, VectorStoresConfig + + +class TestVectorStoresConfigValidation: + """Test validation of VectorStoresConfig prompt templates.""" + + def test_default_config_is_valid(self): + """Test that default configuration passes all validation.""" + config = VectorStoresConfig() + + # Verify all sub-configs exist with valid templates + assert config.file_search_params.header_template is not None + assert config.context_prompt_params.chunk_annotation_template is not None + assert config.annotation_prompt_params.chunk_annotation_template is not None + + # Verify required placeholders are present + assert "{num_chunks}" in config.file_search_params.header_template + assert "knowledge_search" in config.file_search_params.header_template.lower() + assert "{chunk.content}" in config.context_prompt_params.chunk_annotation_template + assert "{query}" in config.context_prompt_params.context_template + + def test_template_validation_errors(self): + """Test that templates fail validation for common errors.""" + from llama_stack.core.datatypes import AnnotationPromptParams, ContextPromptParams, FileSearchParams + + # Empty templates fail + with pytest.raises(ValidationError, match="must not be empty"): + FileSearchParams(header_template="") + + # Missing required placeholders fail + with pytest.raises(ValidationError, match="must contain {num_chunks} placeholder"): + FileSearchParams(header_template="search found results") + + with pytest.raises(ValidationError, match="must contain 'knowledge_search' keyword"): + FileSearchParams(header_template="search found {num_chunks} results") + + with pytest.raises(ValidationError, match="must contain {chunk.content} placeholder"): + ContextPromptParams(chunk_annotation_template="Result {index}: some content") + + with pytest.raises(ValidationError, match="must contain {query} placeholder"): + ContextPromptParams(context_template="Retrieved results. Use as context.") + + with pytest.raises(ValidationError, match="must contain {file_id} placeholder"): + AnnotationPromptParams(chunk_annotation_template="[{index}] {chunk_text}") + + def test_rewrite_query_params_validation(self): + """Test RewriteQueryParams validation.""" + model = QualifiedModel(provider_id="test", model_id="test-model") + + # Valid config works + valid_params = RewriteQueryParams( + model=model, prompt="Expand this query: {query}", max_tokens=100, temperature=0.5 + ) + assert valid_params.prompt == "Expand this query: {query}" + + # Invalid configurations fail + with pytest.raises(ValidationError, match="prompt must contain \\{query\\} placeholder"): + RewriteQueryParams(model=model, prompt="No placeholder here") + + with pytest.raises(ValidationError, match="max_tokens must be positive"): + RewriteQueryParams(model=model, max_tokens=0) + + with pytest.raises(ValidationError, match="temperature must be between 0.0 and 2.0"): + RewriteQueryParams(model=model, temperature=3.0) + + def test_custom_configuration(self): + """Test complete custom configuration.""" + from llama_stack.core.datatypes import AnnotationPromptParams, ContextPromptParams, FileSearchParams + + config = VectorStoresConfig( + default_provider_id="test-provider", + default_embedding_model=QualifiedModel(provider_id="test", model_id="embedding-model"), + file_search_params=FileSearchParams( + header_template="Custom knowledge_search found {num_chunks} items:\nSTART\n", footer_template="END\n" + ), + context_prompt_params=ContextPromptParams( + chunk_annotation_template="Item {index}: {chunk.content} | Meta: {metadata}\n", + context_template='Results for "{query}": Use carefully.\n', + ), + annotation_prompt_params=AnnotationPromptParams( + enable_annotations=False, + annotation_instruction_template=" Custom citation format.", + chunk_citation_template="[{index}] {metadata_text} --> {file_id}\n{chunk_text}\n", + ), + ) + + assert config.default_provider_id == "test-provider" + assert "Custom knowledge_search" in config.file_search_params.header_template + assert config.annotation_prompt_params.enable_annotations is False + + +class TestOptionalArchitecture: + """Test optional sub-config architecture and constants fallback.""" + + def test_guaranteed_defaults_behavior(self): + """Test that sub-configs are always instantiated with defaults.""" + # Sub-configs are always instantiated due to default_factory + config = VectorStoresConfig() + assert config.file_search_params is not None + assert config.context_prompt_params is not None + assert config.annotation_prompt_params is not None + assert "{num_chunks}" in config.file_search_params.header_template + + def test_guaranteed_defaults_match_constants(self): + """Test that guaranteed defaults match expected constant values.""" + from llama_stack.providers.utils.memory.constants import ( + DEFAULT_CONTEXT_TEMPLATE, + DEFAULT_FILE_SEARCH_HEADER_TEMPLATE, + ) + + # Create config with guaranteed defaults + config = VectorStoresConfig() + + # Verify defaults match constants + header_template = config.file_search_params.header_template + context_template = config.context_prompt_params.context_template + + assert header_template == DEFAULT_FILE_SEARCH_HEADER_TEMPLATE + assert context_template == DEFAULT_CONTEXT_TEMPLATE + + # Verify templates can be formatted successfully + formatted_header = header_template.format(num_chunks=3) + assert "3" in formatted_header + assert "knowledge_search" in formatted_header.lower() + + formatted_context = context_template.format( + query="test query", annotation_instruction=" Cite sources properly." + ) + assert "test query" in formatted_context + + def test_end_to_end_template_usage(self): + """Test that guaranteed defaults lead to working template output.""" + # Create config with guaranteed defaults + config = VectorStoresConfig() + + header_template = config.file_search_params.header_template + chunk_template = config.context_prompt_params.chunk_annotation_template + + # Generate realistic output + test_chunks = [ + {"content": "Paris is the capital of France.", "metadata": {"doc": "geo.pdf"}}, + {"content": "London is the capital of England.", "metadata": {"doc": "cities.txt"}}, + ] + + header_output = header_template.format(num_chunks=len(test_chunks)) + chunk_outputs = [] + for i, chunk_data in enumerate(test_chunks): + + class MockChunk: + content = chunk_data["content"] + + chunk_output = chunk_template.format(index=i + 1, chunk=MockChunk(), metadata=chunk_data["metadata"]) + chunk_outputs.append(chunk_output) + + complete_output = header_output + "".join(chunk_outputs) + + # Verify output is substantial and contains expected content + assert len(complete_output) > 100 + assert "knowledge_search" in complete_output.lower() + assert "Paris is the capital" in complete_output + assert "London is the capital" in complete_output diff --git a/tests/unit/rag/test_rag_query.py b/tests/unit/rag/test_rag_query.py index 7eb17b74b..a84c6fde8 100644 --- a/tests/unit/rag/test_rag_query.py +++ b/tests/unit/rag/test_rag_query.py @@ -8,21 +8,26 @@ from unittest.mock import AsyncMock, MagicMock import pytest +from llama_stack.providers.inline.tool_runtime.rag.config import RagToolRuntimeConfig from llama_stack.providers.inline.tool_runtime.rag.memory import MemoryToolRuntimeImpl from llama_stack_api import Chunk, ChunkMetadata, QueryChunksResponse, RAGQueryConfig class TestRagQuery: async def test_query_raises_on_empty_vector_store_ids(self): + config = RagToolRuntimeConfig() rag_tool = MemoryToolRuntimeImpl( - config=MagicMock(), vector_io_api=MagicMock(), inference_api=MagicMock(), files_api=MagicMock() + config=config, vector_io_api=MagicMock(), inference_api=MagicMock(), files_api=MagicMock() ) with pytest.raises(ValueError): await rag_tool.query(content=MagicMock(), vector_store_ids=[]) async def test_query_chunk_metadata_handling(self): + # Create config with default templates + config = RagToolRuntimeConfig() + rag_tool = MemoryToolRuntimeImpl( - config=MagicMock(), vector_io_api=MagicMock(), inference_api=MagicMock(), files_api=MagicMock() + config=config, vector_io_api=MagicMock(), inference_api=MagicMock(), files_api=MagicMock() ) content = "test query content" vector_store_ids = ["db1"] @@ -33,9 +38,8 @@ class TestRagQuery: source="test_source", metadata_token_count=5, ) - interleaved_content = MagicMock() chunk = Chunk( - content=interleaved_content, + content="This is test chunk content from document 1", chunk_id="chunk1", metadata={ "key1": "value1", @@ -78,8 +82,11 @@ class TestRagQuery: RAGQueryConfig(mode="wrong_mode") async def test_query_adds_vector_store_id_to_chunk_metadata(self): + # Create config with default templates + config = RagToolRuntimeConfig() + rag_tool = MemoryToolRuntimeImpl( - config=MagicMock(), + config=config, vector_io_api=MagicMock(), inference_api=MagicMock(), files_api=MagicMock(),