feat: Add doc IDs to the session chat response

[whiterabbit1983]

🚀 This description was created by Ellipsis for commit c93ef10

Summary:

Enhances data traceability in chat interactions by introducing document IDs (agent_doc_id and user_doc_id) to the session chat response.

Key points:

• Added DocIds model to openapi_model.py to include document IDs in chat responses.
• Modified proc_mem_context_query in proc_mem_context.py to fetch and pass document IDs including agent_doc_id and user_doc_id.
• Updated session_chat in routers.py to handle document IDs in the chat response.
• Adjusted session handling in session.py to include document IDs in the response setup.

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1. agents-api/agents_api/autogen/openapi_model.py:819

• Draft comment:
  The DocIds model is correctly defined with required fields agent_doc_ids and user_doc_ids as lists of strings. This aligns with the PR's goal to include document IDs in the session chat response.
• Reason this comment was not posted::
  Confidence changes required: 0%
  The PR adds document IDs to the session chat response. The changes involve modifications in the data model, session handling, and API response formatting. The main files affected are the openapi_model.py, proc_mem_context.py, routers.py, and session.py. The changes seem to align with the intended functionality of including document IDs in the chat response. However, it's crucial to ensure that the implementation correctly handles the data throughout the process, from fetching the document IDs to including them in the API response.

2. agents-api/agents_api/models/entry/proc_mem_context.py:178

• Draft comment:
  The modifications to include agent_doc_id and user_doc_id in the query results are correctly implemented. These changes are essential for capturing the document IDs related to the session's context, which are then passed to the API response.
• Reason this comment was not posted::
  Confidence changes required: 0%
  The changes in the proc_mem_context_query function in proc_mem_context.py are crucial as they involve fetching and handling the document IDs (agent_doc_id and user_doc_id). These IDs are extracted from the query results and are essential for tracking the documents related to the agents and users in the session context. It's important to ensure that these IDs are correctly fetched and passed through the system to be included in the final API response.

3. agents-api/agents_api/routers/sessions/routers.py:313

• Draft comment:
  The inclusion of doc_ids in the API response is correctly implemented here. This ensures that the document IDs are returned as part of the session chat response, aligning with the PR's objectives.
• Reason this comment was not posted::
  Confidence changes required: 0%
  The changes in the session_chat function in routers.py are critical as they handle the API endpoint's response. The function now includes doc_ids in the response, which is a key part of the PR's functionality. It's important to ensure that these document IDs are correctly included in the response and that the API endpoint behaves as expected.

4. agents-api/agents_api/routers/sessions/session.py:183

• Draft comment:
  The handling of doc_ids throughout the session's execution and their inclusion in the return statement of the run method are correctly implemented. This ensures that the document IDs are properly passed through the session logic and included in the final API response.
• Reason this comment was not posted::
  Confidence changes required: 0%
  The changes in the run method of the RecursiveSummarizationSession class in session.py are crucial as they handle the session's execution logic, including fetching document IDs and including them in the session response. It's important to ensure that the document IDs are correctly handled throughout the session's lifecycle and included in the final response.

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1. /agents-api/agents_api/autogen/openapi_model.py:819

• Draft comment:
  The DocIds model defines agent_doc_ids and user_doc_ids as lists of strings, but document IDs are typically UUIDs. Consider changing the type to List[UUID] to ensure type consistency across the application.

agent_doc_ids: List[UUID]
user_doc_ids: List[UUID]

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1. agents-api/agents_api/models/entry/proc_mem_context.py:178

• Draft comment:
  The tuple pattern incorrectly includes both agent_doc_id and user_doc_id for agent documents. This should be corrected to only include agent_doc_id.

        ?[role, name, content, token_count, created_at, index, agent_doc_id] :=

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2. agents-api/agents_api/models/entry/proc_mem_context.py:205

• Draft comment:
  The tuple pattern incorrectly includes both user_doc_id and agent_doc_id for user documents. This should be corrected to only include user_doc_id.

        ?[role, name, content, token_count, created_at, index, user_doc_id] :=

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1. agents-api/agents_api/models/entry/proc_mem_context.py:178

• Draft comment:
  The tuple unpacking for agent and user documents incorrectly includes both agent_doc_id and user_doc_id. Each document type should only include its respective document ID to avoid confusion and potential data handling errors. Here's a corrected version for agent documents:

        ?[role, name, content, token_count, created_at, index, agent_doc_id] :=

And ensure to apply a similar correction for user documents on line 205.

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1. agents-api/agents_api/models/entry/proc_mem_context.py:186

• Draft comment:
  Renaming doc_id to agent_doc_id and user_doc_id directly in the query might cause issues if other parts of the system expect a doc_id field. Consider keeping the original doc_id and handling the differentiation in the application logic if necessary.

                doc_id,

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1. agents-api/agents_api/models/entry/proc_mem_context.py:172

• Draft comment:
  The modifications to include agent_doc_id and user_doc_id in the session chat response are correctly implemented in the proc_mem_context_query function. The function now handles these IDs appropriately by using separate temporary tables for agent and user documents, which aligns with the PR's goal of enhancing data traceability.
• Reason this comment was not posted:
  Confidence changes required: 0%
  The PR description mentions the addition of agent_doc_id and user_doc_id to the session chat response. The changes in the proc_mem_context_query function reflect this by modifying the query to fetch and handle these document IDs. The function now includes separate temporary tables for agent and user documents (_agent_docs and _user_docs), and the query sections have been adjusted to populate these tables with the respective document IDs. This is a logical extension of the existing functionality to include document IDs in the chat response, enhancing data traceability as described in the PR summary.

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1. agents-api/agents_api/models/entry/proc_mem_context.py:172

• Draft comment:
  The changes to include agent_doc_id and user_doc_id in the query results are crucial for the feature. However, ensure that these IDs are correctly handled in all parts of the query to maintain data consistency and avoid any potential data mismatches or errors.
• Reason this comment was not posted:
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2. agents-api/agents_api/models/entry/proc_mem_context.py:12

• Draft comment:
  The change in the k_docs parameter from 2 to 3 should be validated for its impact on performance and relevance of the query results. Ensure that this adjustment aligns with the intended enhancements and does not introduce inefficiencies.
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