Testing

[harshhsahu]

No description provided.

[walkover101]

Rejected.

Why (short):

• Violates the rule: "All new code must be TypeScript" — this patch adds dozens of new Python modules. Unacceptable.
• Inconsistent naming & casing (get_text_from_vectorsQuery, ownerId, inbuild_tools, Gtwy_Web_Search). Many identifiers are not self-explanatory or follow project conventions.
• Duplicate batch implementations (OpenAI/Groq/Mistral/Gemini/Anthropic/Mistral/etc.) — copy/paste everywhere. Should be a single reusable Batch interface + provider adapters.
• Missing/unclear dependencies and imports (Config, index, OpenAIEmbeddings, logger, client, uploadDoc signatures, fetch implementation). This will break at runtime.
• Error handling/logging leaks and is inconsistent: raw tracebacks/print statements, printing exceptions with potential secrets, inconsistent HTTPException usage.
• Security/concurrency issues: Redis lock is naive (set/delete race). Should use unique token + safe release (LUA) or Redlock library.
• API contract inconsistencies: mixing bytes, URLs, base64 for uploads without clear, typed helpers. uploadDoc usage is inconsistent.
• Naming fixes are partial (Anthropic rename ok), but many new files and exports lack clear purpose statements and types.
• No tests, no type checking, no docs for new endpoints or behaviors (hippocampus integration, Firecrawl, built-in tools, owner_id logic).

What to do next (actionable):

1. Revert Python additions. Implement new features in TypeScript as required by project policy.
2. Create a single Batch abstraction (TypeScript) and provider adapters for each LLM/batch service — share upload/download/monitor logic.
3. Standardize naming: snake_case for functions, camelCase for variables if project style requires, PascalCase for classes. Ensure every exported name is self-explanatory or has a one-line purpose.
4. Replace naive Redis lock with proven pattern (unique token + compare-and-delete or Redlock). Add types.
5. Centralize file upload/download helpers with typed interfaces; ensure consistent handling of url vs bytes vs base64.
6. Remove prints; use structured logger and redact secrets.
7. Add unit + integration tests for new features and CI type checks.
8. Provide missing imports/types and validate runtime globals (Config, index, OpenAIEmbeddings, client, logger).

Fix these and resubmit. Fast, focused, no fluff.

[walkover101]

Reject.

Why — short and brutal:

• You added a lot of new Python code. Developer rule: "All new code must be written in TypeScript." This alone is a hard blocker.
• You removed the orchestrator implementation (big chunk) without a clear replacement — likely breaks orchestration features across the app.
• get_text_from_vectorsQuery:
  • Hardcoded hippocampus URL; should come from Config/env.
  • Uses Config.HIPPOCAMPUS_API_KEY and fetch — ensure Config is imported and fetch signature matches (you didn't show imports).
  • Changed tool schema and removed MongoDB lookups; but tool clients (LLM functions / tool definitions) may still expect the old Document_id flow. Inconsistent contract.
• Tool schema change for get_knowledge_base_data: required params changed to resource_id and collection_id — must ensure LLM function mapping and the actual functions that implement that tool are updated to match.
• Image pipeline:
  • New gemini_image_utils is Python new code (violates TS rule).
  • handle_imagen_generation / handle_gemini_generation rely on google.genai types — verify API compatibility with bumped google-genai version.
• Unconditional latency creation in image handler: create_latency_object(timer, params) is now called without checking params exist — possible NameError.
• Error handling changes sometimes send result.get("error") where previous behavior used modelResponse — could return unexpected payloads.
• Mongo/MongoId conversion logic in aggregation updated — check all input shapes because you now branch on "$$doc_id" being an object expecting resource_id field. Risk of pipeline failures if earlier shape persists.
• Minor: file preview blacklist is aggressive; consider driving from accepted list instead of long blacklist.

Actionable fixes (do these, then resubmit):

1. Convert all newly added modules/files to TypeScript per policy OR mark exception with clear justification and get approval.
2. Ensure Config and fetch are imported where used; move hippocampus URL to Config.
3. Reconcile tool schema change: update the tool implementation get_knowledge_base_data to accept resource_id & collection_id, and update any LLM tool definitions to match.
4. Restore or replace orchestrator flow intentionally — don’t partially delete it. If removing, remove all references and tests that expect it.
5. Guard create_latency_object calls with existence checks for params/local variable.
6. Run an integration test for RAG tool calls and image generation (Gemini/Imagen) with the new google-genai version.
7. Tighten file preview logic: prefer allow-list, or at least log/return consistent errors.

Fix the TS-rule violation first. Resubmit when the above are addressed.

[walkover101]

Rejected.

Fixes required before approval:

1. Major policy break — new code added in Python. The project rule says "All new code must be written in TypeScript." You added new Python module(s) and Python changes. Convert new modules/logic to TypeScript or get explicit exception.

2. Naming / consistency issues

   • get_text_from_vectorsQuery: camelCase in Python. Rename to snake_case (get_text_from_vectors_query) for consistency and clarity. Ensure all callers updated.
   • ownerId vs owner_id: inconsistent variable naming inside get_text_from_vectorsQuery. Use owner_id everywhere.
   • add_rag_tool description text is unclear/grammatically wrong. Make it explicit: "Use this function to fetch resource content by resource_id from the knowledge base."
   • rag_data vs doc_ids mismatch: you changed rag_data source to bridge.get('doc_ids') but other code expects rag_data. Either keep naming consistent or propagate name change everywhere.

3. Unused / extraneous imports

   • Added import resource (crypto file) but it is unused. Remove it.

4. Robustness / error handling

   • get_text_from_vectorsQuery assumes fetch returns (api_response, headers). Make return contract explicit and add type checks and retries/fail paths.
   • file_processing: rejecting a broad list of extensions is OK but message hard-coded; consider centralizing allowed-preview list and tests.

5. Backwards compatibility

   • You removed orchestrator_chat implementations and references in some places — ensure no other modules still call it (search/CI tests). If removal intentional, update docs and remove dead imports.

Make these changes, convert new code to TypeScript (or get approved exception), and re-submit. Short. Fix it.

[walkover101]

Rejected.

Why (short and brutal):

• You added a bunch of new modules/logic in Python — but the rule in this repo for all new code is TypeScript. That alone is a hard stop.
• Naming inconsistencies that will cause runtime/contract bugs: owner_id vs ownerId, resource_id vs resourceId, payload keys vs function parameters — unify to one style and document the contract.
• You changed the RAG tool contract (Document_id → resource_id) but didn’t update all call sites/consumers — this will break callers. Tool description text and prompt generation are inconsistent with how the data is looked up.
• Large orchestration chunk removed (orchestrator_chat/orchestrator_agent_chat). If intentional, must be justified and reflected across the codebase and tests. If accidental, revert.
• Error handling now returns combined raw exception strings to clients (may leak internals). Use structured errors and logging instead.
• New utility file lacks TypeScript typing, exports, and tests. Also camelCase vs snake_case mismatch across modules.
• Minor but important: ensure fetch/hippocampus contract (headers, payload fields, returned shape) is explicitly typed and validated.

What I want to see to approve (actionable checklist):

1. Convert all newly added files to TypeScript with proper types/exports. No new Python files.
2. Standardize naming (recommend snake_case for internal Python-style if you keep any Python — but repo rule is TypeScript). Pick one: owner_id OR ownerId — apply everywhere.
3. Update and document the RAG tool contract (field names, required params), and update every call site.
4. Restore or explicitly remove orchestration flows with tests and a clear migration note.
5. Replace raw exception strings sent to users with structured error objects; log internals separately.
6. Add unit/integration tests for:
   • get_text_from_vectorsQuery against mocked hippocampus response
   • gemini/imagen image flow (or TS equivalent)
   • RAG tool interface changes
7. Run lint/typecheck and include output in PR.

Fix those, resubmit. Fast, precise, and no excuses.