Fix docs search #311
Fix docs search #311
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👍 Looks good to me! Reviewed everything up to 250fc30 in 1 minute and 31 seconds
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1. agents-api/agents_api/models/entry/proc_mem_context.py:32:
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The change in VECTOR_SIZE from 768 to 1024 needs to be reflected in all embedding generation and usage processes. Ensure that all related functions and processes are updated accordingly to handle the new embedding size. - Reasoning:
The change in VECTOR_SIZE from 768 to 1024 in proc_mem_context.py is significant as it affects the assertion that checks the length of embeddings. This change should be reflected in all places where embeddings are generated or used to ensure consistency. It's important to verify if the embedding generation process and any other related processes or functions are updated to produce or handle embeddings of size 1024 instead of the previous 768.
2. agents-api/agents_api/routers/agents/routers.py:250:
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Ensure that the transformation ofcontenthandles all edge cases correctly, especially when dealing with different types of content. Consider adding more robust error handling and validation to prevent issues. - Reasoning:
The transformation of the content in the create_agent function in routers.py is complex and may introduce bugs or unexpected behavior. The transformation checks if the content is a string and wraps it in a list, or uses it as is if it's already a list. Then, it checks if each item is an instance of ContentItem and calls model_dump on it. This could lead to issues if the content is not properly formatted or if the model_dump method does not behave as expected. It's important to ensure that the content transformation is robust and handles all edge cases correctly.
3. agents-api/agents_api/routers/sessions/session.py:208:
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Verify that theembedding_service_urlandembedding_model_nameare correctly configured and that the embedding service is fully operational and capable of handling the embedding requests as expected. - Reasoning:
The addition ofembedding_service_urlandembedding_model_namein the forward function in session.py is a significant change that affects how embeddings are generated. It's crucial to ensure that these new environment variables are properly configured and that the embedding service is capable of handling the requests correctly. This change could potentially introduce issues if the service URL or model ID are incorrect or if the service does not respond as expected.
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❌ Changes requested. Incremental review on 79eeeb6 in 1 minute and 20 seconds
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| @@ -185,7 +185,7 @@ def _(): | |||
| result = proc_mem_context_query( | |||
| session_id=session_id, | |||
| tool_query_embedding=[0.9] * 768, | |||
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The tool_query_embedding size should be updated to 1024 to match the new VECTOR_SIZE defined in proc_mem_context.py.
| tool_query_embedding=[0.9] * 768, | |
| tool_query_embedding=[0.9] * 1024, |
| for function in functions | ||
| ] | ||
| ) | ||
| # embeddings = await embed( |
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The embedding functionality is commented out here and in several other places. If embedding is supposed to be integrated as per the PR description, these should be enabled or correctly implemented. Please review and ensure the embedding integration is complete.
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❌ Changes requested. Incremental review on 6d8caba in 1 minute and 36 seconds
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1. agents-api/agents_api/routers/agents/routers.py:265:
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The embedding code is commented out and replaced with a placeholder embedding of zeros. This might be for testing, but if it's meant to be final, it should be reconsidered or properly implemented as per the PR description about integrating embedding services.
embeddings = await embed(
[
function_embed_instruction
+ f"{function.name}, {function.description}, "
+ "required_params:"
+ function.parameters.model_dump_json()
for function in functions
]
)
create_tools_query(
new_agent_id,
functions,
embeddings,
)
- Reasoning:
The PR description mentions integrating embedding service URL and model ID in the forward function in session.py, but there are no changes related to this in the provided diffs. It's possible that the changes are not included in the diff or the description might be incorrect. This needs to be verified for consistency and correctness of the PR description.
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| @@ -185,7 +185,7 @@ def _(): | |||
| result = proc_mem_context_query( | |||
| session_id=session_id, | |||
| tool_query_embedding=[0.9] * 768, | |||
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The tool_query_embedding size should be updated to 1024 to match the new VECTOR_SIZE in proc_mem_context.py.
| tool_query_embedding=[0.9] * 768, | |
| tool_query_embedding=[0.9] * 1024, |
| create_tools_query( | ||
| new_agent_id, | ||
| functions, | ||
| embeddings, | ||
| [[0.0] * 768], |
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Should be 1024 or no? Just heads up
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👍 Looks good to me! Incremental review on 3545c1c in 1 minute and 5 seconds
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1additional comments because they didn't meet confidence threshold of50%.
1. agents-api/agents_api/models/entry/proc_mem_context.py:131:
- Assessed confidence :
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0% - Comment:
Ensure that the commented-out code for the embedding space search for tools is intentionally disabled and correctly handled elsewhere as per the PR's intent to shift to static embeddings. Verify that the commenting syntax used ('#') is appropriate for the context or query language. - Reasoning:
The commented-out code in the diff seems to be disabling the embedding space search for tools, which might be intentional as per the PR description about shifting to static embeddings. However, it's important to ensure that the functionality is correctly replaced or handled elsewhere if needed. The comment character '#' is used to comment out the lines, which is not typical for Python and might be specific to the internal DSL or query language used here. It's crucial to verify that this change aligns with the intended functionality and doesn't inadvertently disable necessary features.
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👍 Looks good to me! Incremental review on 4e9799f in 1 minute and 5 seconds
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1. model-serving/model_api/protocol.py:96:
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Making theidfield optional in theToolclass could potentially lead to issues with tool identification and management if other parts of the system expect every tool to have a non-null ID. Please ensure that all parts of the system that interact with theToolclass can handle aNonevalue for theidfield. - Reasoning:
The change in the Tool class to make the 'id' field optional (str | None = None) might have implications on how tools are identified and managed. If the 'id' is used as a unique identifier in other parts of the system, making it optional could lead to issues where tools are not correctly identified or handled. It's important to ensure that all parts of the system that interact with the Tool class can handle a None value for the 'id'. This change should be carefully reviewed to ensure it does not introduce bugs or inconsistencies in tool management.
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Summary:
Enhanced document search capabilities by updating embedding vector sizes, refining content handling, integrating embedding services, and shifting to static embeddings.
Key points:
VECTOR_SIZEinproc_mem_context.pyfrom 768 to 1024.create_agentfunction inrouters.pyto supportContentIteminstances.forwardfunction insession.py.create_agentandcreate_toolfunctions inrouters.py, using static embeddings instead.idfield optional inToolclass inprotocol.py.Generated with ❤️ by ellipsis.dev