LCORE-3582: fix compacted-mode 500s in the agent pipeline by max-svistunov · Pull Request #2451 · lightspeed-core/lightspeed-stack

max-svistunov · 2026-08-17T10:00:59Z

Description

Fix LCORE-3582: once a conversation compacted (LCORE-1572), every subsequent request on it failed with HTTP 500 on both /v1/query and /v1/streaming_query, permanently bricking the conversation. In compacted mode CompactionResult.params.input is an explicit item list (summaries + recent turns + new query) with the conversation parameter omitted, but the pydantic-ai agent pipeline did prompt = cast(str, responses_params.input) and handed the list to agent.run(), which dies client-side before any request reaches Llama Stack. The A2A executor had a quieter variant: it passes raw user text as the prompt, so compacted A2A turns silently lost all conversation context.

The fix routes the explicit input through the existing params→model-settings seam:

_model_settings_from_responses_params (src/pydantic_ai_lightspeed/llamastack/_model.py): in compacted mode the dumped input list is added to extra_body, which the OpenAI SDK merges into the request body with precedence — the wire request matches what the non-agent /v1/responses path sends. This also fixes the A2A context loss with no a2a.py changes.
OgxResponsesModel._prepare_compacted_input (applied in request() and request_stream()): drops the override once a ModelResponse exists in the message history, so client-side tool-loop iterations keep pydantic-ai's mapped messages (which carry tool results).
New agent_prompt_text() (src/utils/conversation_compaction.py) replaces cast(str, ...) at all four call sites: returns string input unchanged, else the text of the trailing message item.
The blocked-moderation path in retrieve_agent_response now skips append_turn_items_to_conversation in compacted mode (mirrors the streaming path), preventing summary/history duplication into the conversation.
map_agent_inference_error now logs the original exception with traceback at error level — previously these failures produced a generic 500 with nothing in the logs.

Known limitation (noted on the Jira): image attachments are not folded into the overridden explicit input, so a compacted turn with images sends the text-only explicit list (before this fix, compaction+images hard-failed with 500).

Post-review changes (2026-08-27)

Rebased onto current main (was 21 commits behind; merges clean) and addressed two review findings:

Log level now matches the cause. map_agent_inference_error logged every mapped failure at error level with a traceback, but it also maps caller-caused and upstream conditions — 413 for an over-long prompt, 429 for a provider rate limit, 503 for a backend outage — and is called from the shield path too. That noise buries the unclassified 500s the logging was added to surface. Sub-500 responses and 503 now log a single warning line; everything else keeps error level and the traceback, with an unreadable status treated as unclassified so it fails towards more diagnostics. The connection-error test now asserts the warning and the absence of an error record, and a new test covers the unclassified case including the attached traceback.
agent_prompt_text no longer degrades silently. Its empty-string fallback should be unreachable (compaction always appends the new query as the trailing item); reaching it now logs a warning instead of quietly handing the agent an empty prompt that still drives capability selection and multimodal construction.

Type of change

Tools used to create PR

Identify any AI code assistants used in this PR (for transparency and review context)

Assisted-by: Claude Opus 4.8
Generated by: Claude Opus 4.8

Related Tickets & Documents

Related Issue # LCORE-3582
Closes # LCORE-3582

Checklist before requesting a review

I have performed a self-review of my code.
PR has passed all pre-merge test jobs.
If it is a core feature, I have added thorough tests.

Testing

Scope of these results. The live runs in steps 2 and 3 were performed against llama-stack 0.6.0 before this branch was rebased onto the OGX rename and the LCORE-1426 RAG refactor. Unit suites and linters have been re-run on the current head; the live stack runs have not. Treat steps 2–3 as the last known live state.

Start the local stack with compaction configured to trigger aggressively:

compaction:
  enabled: true
  threshold_ratio: 0.0
  token_floor: 0
  buffer_turns: 0
inference:
  default_provider: openai
  default_model: gpt-4o-mini
  context_windows:
    openai/gpt-4o-mini: 128000

plus a sqlite conversation_cache, and set OTEL_ANONYMIZATION_SECRET in the environment.

Send a first /v1/query (new conversation), then follow-up queries with the returned conversation_id.
Expected: every turn returns 200 (turn 2+ previously returned the generic 500).
Actual (verified live against llama-stack 0.6.0):
- Turn 2 (triggers summarization): 200, answer returned.
- Turn 3 (marker-exists path): asked "What was my very first question in this conversation about?" → "Your very first question in this conversation was about asking for a one-sentence definition of Kubernetes." — the summary context demonstrably reaches the model.

Connect to /v1/streaming_query on the compacted conversation.
Expected: compaction event, token stream, end event (previously an error event with status 500).
Actual:

start -> {"conversation_id": "556a...", ...}
compaction -> {"status": "started", ...}
end -> {"referenced_documents": [], "truncated": null, "input_tokens": 184, "output_tokens": 3}
ANSWER: OpenShift.   (contextual follow-up answered correctly)

Run the tests specific to this change:

uv run pytest tests/unit/pydantic_ai_lightspeed/llamastack/test_model.py \
  tests/unit/utils/test_conversation_compaction.py tests/unit/utils/agents/ -q

Result, re-run on the current head (2026-08-27): 175 passed.

Full suites:

uv run make test-unit          # 3487 passed, 1 skipped (re-run 2026-08-27 on the rebased head)
uv run python -m pytest tests/integration --ignore=tests/integration/container_lifecycle -q
                               # 260 passed, 1 xfailed (container_lifecycle needs a container runtime)

Summary by CodeRabbit

New Features
- Added support for compacted conversation inputs while preserving the latest user prompt.
- Improved tool-loop continuations by preventing duplicated conversation content.
- Extended compacted-input support to both standard and streaming agent responses.
Bug Fixes
- Moderation refusals no longer alter conversation history when conversation omission is enabled.
- Improved handling of inference failures with clearer warning and error logging.

coderabbitai · 2026-08-17T10:01:21Z

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Reviewing files that changed from the base of the PR and between 274d838 and 0e8d545.

📒 Files selected for processing (4)

src/utils/agents/query.py
src/utils/agents/streaming.py
src/utils/conversation_compaction.py
tests/unit/utils/test_conversation_compaction.py

Walkthrough

Adds compacted input support for OGX requests and agent execution. It derives prompts from the latest explicit message, preserves tool-loop message handling, skips configured conversation appends, and logs inference failures by response class.

Changes

Compacted agent flow

Layer / File(s)	Summary
Model compacted-input handling `src/pydantic_ai_lightspeed/llamastack/_model.py`, `tests/unit/pydantic_ai_lightspeed/llamastack/test_model.py`	The model carries explicit compacted input in `extra_body["input"]`. It removes this override for tool-loop continuations. Tests cover serialization, preservation, removal, and immutability.
Agent prompt and inference handling `src/utils/conversation_compaction.py`, `src/utils/agents/query.py`, `src/utils/agents/streaming.py`, `src/utils/agents/error_handler.py`, `tests/unit/utils/agents/test_query.py`, `tests/unit/utils/agents/test_streaming.py`, `tests/unit/utils/test_conversation_compaction.py`	Agent execution uses the latest textual message from explicit input. Moderation skips conversation appends when `omit_conversation` is enabled. Inference errors receive status-based logging. Tests cover query, streaming, prompt extraction, moderation, and logging behavior.

Estimated code review effort: 3 (Moderate) | ~25 minutes

Merge Risk: 🟡 Moderate · up to 274d8

Compacted conversations now avoid the existing 500s, but image attachments can still be omitted from compacted requests and successful turns may not be written back to authoritative conversation history, causing multimodal requests or later follow-ups to lose context. Merge should wait for these bounded correctness risks to be addressed or explicitly accepted.

Sequence Diagram(s)

sequenceDiagram
  participant Client
  participant agent_response_generator
  participant agent_prompt_text
  participant agent
  Client->>agent_response_generator: submit compacted explicit input
  agent_response_generator->>agent_prompt_text: extract latest message text
  agent_prompt_text-->>agent_response_generator: return agent prompt
  agent_response_generator->>agent: run with latest user question
  agent-->>Client: return agent response

Suggested reviewers: asimurka

🚥 Pre-merge checks | ✅ 7

✅ Passed checks (7 passed)

Check name	Status	Explanation
Description Check	✅ Passed	Check skipped - CodeRabbit’s high-level summary is enabled.
Title check	✅ Passed	The title clearly identifies the main change: fixing HTTP 500 errors in compacted mode within the agent pipeline. It is concise and specific.
Docstring Coverage	✅ Passed	Docstring coverage is 100.00% which is sufficient. The required threshold is 80.00%. Docstring coverage is scoped to functions touched by this diff. Analyzed 33 functions across 9 files.
Linked Issues check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Out of Scope Changes check	✅ Passed	Check skipped because no linked issues were found for this pull request.
Performance And Algorithmic Complexity	✅ Passed	No meaningful performance regression is introduced. The new `agent_prompt_text` scan in `src/utils/conversation_compaction.py:252-288` is linear over the explicit input list and makes only a shallow l…
Security And Secret Handling	✅ Passed	PASSED. The PR diff adds no credentials, tokens, or secret literals. The new log records contain only the HTTP status and exception text, and the compaction warning is fixed text; no prompt, input lis…

Full details: Performance And Algorithmic Complexity

Explanation

No meaningful performance regression is introduced. The new agent_prompt_text scan in src/utils/conversation_compaction.py:252-288 is linear over the explicit input list and makes only a shallow list copy. _prepare_compacted_input in src/pydantic_ai_lightspeed/llamastack/_model.py:348-375 performs one linear any() scan and bounded dictionary copies; it adds no nested scan or per-item I/O. The error logging adds no loop or request work. The moderation change removes an append API call in compacted mode. No new cache, watcher, buffer, or list endpoint is added. The existing get_all_conversation_items path already paginates, and the pull request does not modify it.

Full details: Security And Secret Handling

Explanation

PASSED. The PR diff adds no credentials, tokens, or secret literals. The new log records contain only the HTTP status and exception text, and the compaction warning is fixed text; no prompt, input list, authorization header, or token is logged directly. No API endpoint or authentication/authorization code changes. No SQL, command, or path-handling primitives were introduced. No Kubernetes or RH Secret manifests changed.

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Once a conversation compacted, every subsequent request on it failed with HTTP 500 on both /v1/query and /v1/streaming_query, permanently bricking the conversation. Root cause: in compacted mode (LCORE-1572) CompactionResult.params.input is an explicit item list (summaries + recent verbatim turns + new query) with the conversation parameter omitted, but the pydantic-ai agent pipeline did prompt = cast(str, responses_params.input) and handed the list to agent.run(), which dies client-side before any request reaches Llama Stack. The A2A executor had a quieter variant of the same gap: it passes the raw user text as the prompt, so compacted A2A turns silently lost all conversation context. The fix makes the explicit input reach the wire through the existing params-to-model-settings seam: - _model_settings_from_responses_params (pydantic_ai_lightspeed/ llamastack/_model.py): when omit_conversation is set and input is an item list, the dumped list is added to extra_body. The OpenAI SDK merges extra_body into the request body with precedence (_merge_mappings: "the second mapping takes precedence"), so the explicit list replaces the prompt-derived input — the request body matches what the non-agent /v1/responses path sends. This also fixes the A2A context loss with no a2a.py changes, since build_agent already routes params through this seam. - OgxResponsesModel gains _prepare_compacted_input, applied in both request() and request_stream() after the conversation-continuation trim: once a ModelResponse exists in the message history (a client-side tool-loop continuation), the input override is dropped so pydantic-ai's mapped messages — which carry the tool results — win. - New agent_prompt_text() helper (utils/conversation_compaction.py) replaces the cast(str, ...) at all four call sites (non-streaming and streaming, plain and multimodal): returns input unchanged when it is a string, else the text of the trailing message item of the explicit list. The prompt still drives capabilities and multimodal input construction; the wire input comes from the override. - The blocked-moderation path in retrieve_agent_response now skips append_turn_items_to_conversation when omit_conversation is set, mirroring the streaming path — appending the full explicit list would duplicate summaries and history into the conversation. - map_agent_inference_error now logs the original exception at error level with the traceback before mapping. Previously the mapped HTTPException discarded it and callers raised without logging, so these failures produced a generic 500 with nothing in the logs — which is what made this bug expensive to diagnose. Verified live against llama-stack 0.6.0: on a compacted conversation, turn after turn returns 200 on both endpoints (previously 500), the streaming path emits compaction/token/end events, and the model correctly answers questions about pre-compaction turns, proving the summary context reaches the model. Known limitation: image attachments are not folded into the overridden explicit input, so a compacted turn with images sends the text-only list (compaction+images previously hard -failed; noted in LCORE-3582). Unit tests cover the extra_body override (present in compacted mode, absent otherwise), the tool-loop guard, agent_prompt_text, the prompt threading through both retrieve paths, the moderation-append guard, and the error logging.

…ause map_agent_inference_error logged every failure at error level with a full traceback. The function also maps conditions that are not service faults: a context-length failure becomes HTTP 413 (the caller sent too much), an upstream 429 becomes a quota response, and a connection failure becomes 503 (the backend is down). It is called from the shield path too, so shield-model rate limits took the same treatment. Logging those at error level with stack traces buries the unclassified 500s this logging was added to surface, which is the opposite of the intent — in a service with quotas, 429s are routine traffic, not incidents. Classify from the mapped response instead: anything below 500, plus 503, logs a single warning line without a traceback; everything else keeps the error level and the traceback. A response whose status cannot be read as an int is treated as unclassified and logged loudly, so an unexpected mapping fails towards more diagnostics rather than fewer. Update the connection-error test to assert the warning and the absence of an error record, and add the unclassified-failure case it never covered, asserting both the error level and that the traceback is attached.

agent_prompt_text falls back to an empty string when the explicit compacted input carries no textual message item. The request itself still succeeds — the real input reaches the wire through the extra_body override — but the prompt drives capability selection and multimodal input construction, so an empty one silently degrades those while the turn appears to work. That fallback should never be reached: compaction always appends the new user query as the trailing message item. Reaching it means compaction produced something unexpected, so log a warning rather than absorbing it.

max-svistunov · 2026-08-27T16:10:10Z

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coderabbitai · 2026-08-27T16:10:16Z

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Inline comments:
In `@src/pydantic_ai_lightspeed/llamastack/_model.py`:
- Around line 77-86: Update the compacted-input handling in the
omit_conversation branch to preserve image_attachments when assigning
extra_body["input"]. Merge the generated multimodal attachment parts into the
explicit compacted item list, or skip the override when it would discard them,
while retaining the existing compacted text and conversation items.

Apply the same fix in `@src/utils/agents/query.py` around lines 304 - 310: The
same compacted-input override affects the blocking and streaming request
preparation paths.

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src/pydantic_ai_lightspeed/llamastack/_model.py
src/utils/agents/error_handler.py
src/utils/agents/query.py
src/utils/agents/streaming.py
src/utils/conversation_compaction.py
tests/unit/pydantic_ai_lightspeed/llamastack/test_model.py
tests/unit/utils/agents/test_query.py
tests/unit/utils/agents/test_streaming.py
tests/unit/utils/test_conversation_compaction.py

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GitHub Actions: E2E Tests for Lightspeed Evaluation / 0_E2E Tests for Lightspeed Evaluation job.txt: LCORE-3582: fix compacted-mode 500s in the agent pipeline

Conclusion: failure

View job details

 lightspeed-stack  | ERROR      Application startup failed. Exiting.  category=server
 Still waiting...
   % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                  Dload  Upload   Total   Spent    Left  Speed
   0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
   0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
 curl: (7) Failed to connect to localhost port 8080 after 0 ms: Couldn't connect to server
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/fastapi/routing.py", line 240, in merged_lifespan
 lightspeed-stack  |              async with original_context(app) as maybe_original_state:
 lightspeed-stack  |                         ^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/usr/lib64/python3.12/contextlib.py", line 210, in __aenter__
 lightspeed-stack  |              return await anext(self.gen)
 lightspeed-stack  |                     ^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/app-root/src/app/main.py", line 87, in lifespan
 lightspeed-stack  |              await AsyncOgxClientHolder().load(ogx_config)
 lightspeed-stack  |            File "/app-root/src/client.py", line 49, in load
 lightspeed-stack  |              await self._load_library_client(ogx_config)
 lightspeed-stack  |            File "/app-root/src/client.py", line 82, in _load_library_client
 lightspeed-stack  |              await client.initialize()
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/ogx/core/library_client.py", line 413, in initialize
 lightspeed-stack  |              await self.stack.initialize()  # type: ignore
 lightspeed-stack  |              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/ogx/core/stack.py", line 753, in initialize
 lightspeed-stack  |              impls = await resolve_impls(
 ligh...

GitHub Actions: E2E Tests for Lightspeed Evaluation / E2E Tests for Lightspeed Evaluation job: LCORE-3582: fix compacted-mode 500s in the agent pipeline

Conclusion: failure

View job details

 lightspeed-stack  | ERROR      Application startup failed. Exiting.  category=server
 Still waiting...
   % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                  Dload  Upload   Total   Spent    Left  Speed
   0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
   0     0    0     0    0     0      0      0 --:--:-- --:--:-- --:--:--     0
 curl: (7) Failed to connect to localhost port 8080 after 0 ms: Couldn't connect to server
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/fastapi/routing.py", line 240, in merged_lifespan
 lightspeed-stack  |              async with original_context(app) as maybe_original_state:
 lightspeed-stack  |                         ^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/usr/lib64/python3.12/contextlib.py", line 210, in __aenter__
 lightspeed-stack  |              return await anext(self.gen)
 lightspeed-stack  |                     ^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/app-root/src/app/main.py", line 87, in lifespan
 lightspeed-stack  |              await AsyncOgxClientHolder().load(ogx_config)
 lightspeed-stack  |            File "/app-root/src/client.py", line 49, in load
 lightspeed-stack  |              await self._load_library_client(ogx_config)
 lightspeed-stack  |            File "/app-root/src/client.py", line 82, in _load_library_client
 lightspeed-stack  |              await client.initialize()
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/ogx/core/library_client.py", line 413, in initialize
 lightspeed-stack  |              await self.stack.initialize()  # type: ignore
 lightspeed-stack  |              ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 lightspeed-stack  |            File "/app-root/.venv/lib64/python3.12/site-packages/ogx/core/stack.py", line 753, in initialize
 lightspeed-stack  |              impls = await resolve_impls(
 ligh...

GitHub Actions: E2E Tests for Lightspeed Evaluation / E2E Tests for Lightspeed Evaluation job: LCORE-3582: fix compacted-mode 500s in the agent pipeline

Conclusion: failure

View job details

##[group]Run echo "=== Test failure logs ==="
 �[36;1mecho "=== Test failure logs ==="�[0m
 �[36;1mecho "=== lightspeed-stack (library mode) logs ==="�[0m
 �[36;1mdocker compose -f docker-compose-library.yaml logs lightspeed-stack�[0m
 shell: /usr/bin/bash -e {0}
 env:
   OPENAI_***REDACTED_SECRET_ASSIGNMENT***
   E2E_OPENAI_MODEL: gpt-4o-mini
   FAISS_VECTOR_STORE_ID: vs_8c94967b-81cc-4028-a294-9cfac6fd9ae2
 ##[endgroup]
 === Test failure logs ===
 === lightspeed-stack (library mode) logs ===
 lightspeed-stack  | .385 INFO:     Lightspeed Core Stack startup  [lightspeed_stack.__main__:160]
 lightspeed-stack  | .388 INFO:     Configuration: name='Lightspeed Core Service (LCS)' config_format_version=None service=ServiceConfiguration(host='0.0.0.0', port=8080, base_url=None, auth_enabled=False, workers=1, color_log=True, access_log=True, tls_config=TLSConfiguration(tls_certificate_path=None, tls_key_path=None, tls_key_***REDACTED_SECRET_ASSIGNMENT*** root_path='', cors=CORSConfiguration(allow_origins=['*'], allow_credentials=False, allow_methods=['*'], allow_headers=['*'])) llama_stack=OgxConfiguration(url=AnyHttpUrl('http://localhost:8321/'), ***REDACTED_SECRET_ASSIGNMENT*** use_as_library_client=True, library_client_config_path='/app-root/run.yaml', timeout=180, max_retries=5, retry_delay=2, allow_degraded_mode=False, config=None) user_data_collection=UserDataCollection(feedback_enabled=True, feedback_storage='/tmp/data/feedback', transcripts_enabled=True, transcripts_storage='/tmp/data/transcripts') database=DatabaseConfiguration(sqlite=SQLiteDatabaseConfiguration(db_path='/tmp/lightspeed-stack.db'), postgres=None) mcp_servers=[] authentication=AuthenticationConfiguration(module='noop', skip_tls_verification=False, skip_for_health_probes=False, skip_for_metrics=False, k8s_cluster_api=None, k8s_ca_cert_path=None, jwk_config=None, api_key_config=None, rh_identity_config=None, trusted_proxy_config=None) authorization=None customization=None inference=InferenceConfi...

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Flag meaningful O(n^2)+ algorithms on non-trivial inputs, including handlers and Kubernetes list operations.

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Files:

tests/unit/utils/test_conversation_compaction.py
tests/unit/utils/agents/test_streaming.py
src/utils/agents/error_handler.py
src/utils/agents/query.py
src/utils/conversation_compaction.py
tests/unit/pydantic_ai_lightspeed/llamastack/test_model.py
src/pydantic_ai_lightspeed/llamastack/_model.py
src/utils/agents/streaming.py
tests/unit/utils/agents/test_query.py

🧠 Learnings (1)

📚 Learning: 2026-06-24T13:45:37.249Z

Learnt from: Jdubrick
Repo: lightspeed-core/lightspeed-stack PR: 1971
File: src/utils/markdown_repair.py:31-36
Timestamp: 2026-06-24T13:45:37.249Z
Learning: In the lightspeed-stack repository, docstrings must use the section header name "Parameters:" (not "Args:") for function arguments, even if the project references Google Python docstring conventions. Ensure docstrings follow the project’s established "Parameters:" header format for any documented function parameters.

Applied to files:

src/utils/conversation_compaction.py

🔇 Additional comments (6)

src/utils/conversation_compaction.py (2)
252-261: LGTM!

Also applies to: 265-286

262-263: 📐 Maintainability & Code Quality | 🟡 Minor | ⚡ Quick win

Use the repository parameter header.

Replace Args: with Parameters: in this docstring.

Based on learnings, documented function parameters use the Parameters: header.
Proposed fix
-    Args:
+    Parameters:
         params: Prepared (possibly compaction-rewritten) request parameters.
			> Likely an incorrect or invalid review comment.
Source: Learnings
src/utils/agents/query.py (1)

6-6: LGTM!

Also applies to: 39-39, 280-286

src/utils/agents/streaming.py (1)

11-11: LGTM!

Also applies to: 63-63

src/utils/agents/error_handler.py (1)

3-3: LGTM!

Also applies to: 55-83

tests/unit/utils/agents/test_query.py (1)

9-9: LGTM!

Also applies to: 431-564

In compacted mode the wire input is overridden with the explicit item list, which is text-only. Image attachments are converted into pydantic-ai ImageUrl parts on the prompt, and the override replaces the prompt-derived input wholesale, so those parts never reach the request body: the model answers having never seen the image. Before this branch that combination failed outright, because every compacted turn died client-side. Restoring the turn therefore changed a loud failure into a silent one — the caller gets a confident answer about an image the model was never sent, with nothing indicating the attachment was dropped. A wrong answer presented as correct is worse than the error it replaced. Reject the combination with 422 until the explicit input can carry input_image content parts of its own (LCORE-3789), telling the caller why and what to do instead. The guard lives beside the explicit-input builders that create the constraint, and both the blocking and streaming paths call it, so the two cannot drift. Every other combination is unaffected: images without compaction, compaction without images, and neither.

max-svistunov force-pushed the lcore-3582-compacted-mode-input branch 2 times, most recently from 9e67633 to 73f9458 Compare August 27, 2026 07:28

max-svistunov added 3 commits August 27, 2026 17:07

max-svistunov force-pushed the lcore-3582-compacted-mode-input branch from 73f9458 to 274d838 Compare August 27, 2026 15:26

max-svistunov mentioned this pull request Aug 27, 2026

LCORE-1574: Integration tests for conversation compaction #2427

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LCORE-3582: fix compacted-mode 500s in the agent pipeline - #2451

LCORE-3582: fix compacted-mode 500s in the agent pipeline#2451
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max-svistunov commented Aug 17, 2026 •

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