Fix docs search #311

whiterabbit1983 · 2024-05-06T16:26:39Z

🚀 This description was created by Ellipsis for commit `4e9799f`

Summary:

Enhanced document search capabilities by updating embedding vector sizes, refining content handling, integrating embedding services, and shifting to static embeddings.

Key points:

Updated VECTOR_SIZE in proc_mem_context.py from 768 to 1024.
Modified content handling in create_agent function in routers.py to support ContentItem instances.
Integrated embedding service URL and model ID in forward function in session.py.
Commented out dynamic embedding integration in create_agent and create_tool functions in routers.py, using static embeddings instead.
Made id field optional in Tool class in protocol.py.

Generated with ❤️ by ellipsis.dev

agents-api/agents_api/models/entry/proc_mem_context.py

agents-api/agents_api/routers/sessions/session.py

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1. agents-api/agents_api/models/entry/proc_mem_context.py:32:

Assessed confidence : 100%
Grade: 0%
Comment:
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:

Assessed confidence : 100%
Grade: 0%
Comment:
Ensure that the transformation of content handles 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:

Assessed confidence : 100%
Grade: 0%
Comment:
Verify that the embedding_service_url and embedding_model_name are correctly configured and that the embedding service is fully operational and capable of handling the embedding requests as expected.
Reasoning:
The addition of embedding_service_url and embedding_model_name in 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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ellipsis-dev · 2024-05-07T06:46:39Z

agents-api/agents_api/models/entry/test_entry_queries.py

@@ -185,7 +185,7 @@ def _():
    result = proc_mem_context_query(
        session_id=session_id,
        tool_query_embedding=[0.9] * 768,


The tool_query_embedding size should be updated to 1024 to match the new VECTOR_SIZE defined in proc_mem_context.py.

Suggested change

tool_query_embedding=[0.9] * 768,

tool_query_embedding=[0.9] * 1024,

ellipsis-dev · 2024-05-07T06:46:39Z

agents-api/agents_api/routers/agents/routers.py

-                for function in functions
-            ]
-        )
+        # embeddings = await embed(


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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1. agents-api/agents_api/routers/agents/routers.py:265:

Assessed confidence : 100%
Grade: 0%
Comment:
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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ellipsis-dev · 2024-05-07T06:51:51Z

agents-api/agents_api/models/entry/test_entry_queries.py

@@ -185,7 +185,7 @@ def _():
    result = proc_mem_context_query(
        session_id=session_id,
        tool_query_embedding=[0.9] * 768,


The tool_query_embedding size should be updated to 1024 to match the new VECTOR_SIZE in proc_mem_context.py.

Suggested change

tool_query_embedding=[0.9] * 768,

tool_query_embedding=[0.9] * 1024,

creatorrr · 2024-05-07T09:38:37Z

agents-api/agents_api/routers/agents/routers.py

        create_tools_query(
            new_agent_id,
            functions,
-            embeddings,
+            [[0.0] * 768],


Should be 1024 or no? Just heads up

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1. agents-api/agents_api/models/entry/proc_mem_context.py:131:

Assessed confidence : 66%
Grade: 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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1. model-serving/model_api/protocol.py:96:

Assessed confidence : 66%
Grade: 0%
Comment:
Making the id field optional in the Tool class 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 the Tool class can handle a None value for the id field.
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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whiterabbit1983 added 3 commits May 6, 2024 19:21

fix: Increase vector size

e185f09

fix: Dump ContentItem

fe60735

fix: Embed with custom model

250fc30

whiterabbit1983 commented May 6, 2024

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fix: Disable tools embeddings

6d8caba

whiterabbit1983 force-pushed the x/docs-search branch from ea13b7d to 6d8caba Compare May 7, 2024 06:50

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whiterabbit1983 added 2 commits May 7, 2024 13:37

fix: Fix summarization model path

295bf3b

fix: Comment out unused query part

3545c1c

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fix: Make tool id optional

4e9799f

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whiterabbit1983 merged commit f3ac1cb into dev May 8, 2024
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whiterabbit1983 deleted the x/docs-search branch May 8, 2024 07:23

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Fix docs search #311

Fix docs search #311

whiterabbit1983 commented May 6, 2024 •

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	tool_query_embedding=[0.9] * 768,
	tool_query_embedding=[0.9] * 1024,

Fix docs search #311

Fix docs search #311

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whiterabbit1983 commented May 6, 2024 •

edited by ellipsis-dev bot

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