fix: streaming input guardrail, tool error-dict handling, per-instance token scoping

[praisonai-triage-agent]

Fixes #4446

Summary

Addresses all three findings in issue #4446, scoped to src/praisonai-agents/praisonaiagents.

1. Streaming input guardrail (agent/chat_mixin.py)

_start_stream_impl — the shared generator behind iter_stream() and start(stream=True) — now runs _validate_input_with_guardrail before the first token, matching chat()/achat(). The input side has no streaming constraint (the full prompt is known before dispatch); the output-side warning is untouched. Blocked input yields [Input blocked by guardrail: ...] and returns.

2. Tool error dicts no longer crash the run (agent/tool_execution.py)

ToolExecutionError is now only raised for denials/retryable transients. A plain tool-authored {"error": ...} (the documented convention in shell_tools, tavily_tools, etc.) falls through as a normal tool result so the LLM can see it and self-correct — mirroring the generic-exception branch in openai_client.py.

3. Per-instance token scoping (agents/agents.py)

get_token_usage_summary / get_detailed_token_report / display_token_usage now filter the process-wide TokenCollector to the instance's own agent names via a new private _scoped_token_summary() helper. This prevents cross-instance usage/cost leakage between concurrent PraisonAIAgents instances. Read-side filter reuses the collector's existing by_agent breakdown — no new public API, no session-id threading — honouring the lightweight mandate. Falls back to the unfiltered summary when no named agents exist.

Test plan

• Syntax check on all three edited files
• Finding 1 verified: blocked input yields marker and returns from _start_stream_impl
• Finding 2 verified: empty-command tool returns its {"error": ...} dict instead of raising
• Finding 3 verified: two teams read only their own agents' token totals

Remaining suite failures are pre-existing (missing optional deps: litellm; collection errors in unrelated modules), not caused by these changes.

Generated with Claude Code

[greptile-apps]

Greptile Summary

The PR revises per-team token reporting to filter aggregate and recent-interaction data by owned agent names.

• Adds shared helpers for obtaining agent names and filtering recent interactions.
• Recomputes interaction counts and model breakdowns from filtered records.
• Uses the scoped data in summary, detailed-report, and display APIs.

Confidence Score: 2/5

The PR is not yet safe to merge because token reports can still cross instance boundaries and can understate model and interaction usage after recent-record eviction.

Name-based ownership cannot distinguish teams with colliding agent names, and supported unnamed agents still trigger process-global summary and detailed-report fallbacks; separately, rebuilding model and interaction totals from a bounded process-wide window leaves reports inconsistent with the unbounded token aggregates.

Files Needing Attention: src/praisonai-agents/praisonaiagents/agents/agents.py

Important Files Changed

Filename	Overview
src/praisonai-agents/praisonaiagents/agents/agents.py	Adds name-based token-report scoping and reconstructs report fields from filtered recent interactions.

_{Reviews (4): Last reviewed commit: "fix: fully scope per-instance token repo..." | Re-trigger Greptile}

[greptile-apps]

Names Cannot Scope Instances

When two teams use the same agent name, the process-wide collector combines their metrics under one key and this filter includes the combined entry in both summaries, causing cross-team usage and cost misattribution. Instruction-based agents without explicit names also produce an empty scope and receive the complete process-wide summary.

Knowledge Base Used:

• Agent execution and workflows
• Persistence, security, and configuration

[MervinPraison]

@claude You are the FINAL architecture reviewer. If the branch is under MervinPraison/PraisonAI (not a fork), you are able to make modifications to this branch and push directly. SCOPE: Review changes in this PR. Python SDK: praisonaiagents, praisonai. TypeScript SDK: src/praisonai-ts/. Do NOT modify src/praisonai-rust. Read ALL comments above from Gemini, Qodo, CodeRabbit, and Copilot carefully before responding.

Phase 1: Review per AGENTS.md

1. Protocol-driven: check heavy implementations vs core SDK
2. Backward compatible: ensure zero feature regressions
3. Performance: no hot-path regressions
4. SDK value: review in depth whether the change genuinely adds value to the SDK — never add features for the sake of adding them. It must strengthen the SDK (simpler, more user-friendly, robust, world-class, secure). If it does not clearly add value, request changes or recommend rejecting/closing rather than merging scope creep
5. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params.
6. Repo routing: agent-callable tools → PraisonAI-Tools; lifecycle plugins → PraisonAI-Plugins; optional sandbox backends → PraisonAI-Plugins (praisonai.sandbox entry point) — request changes if wrongly added to praisonaiagents/

Phase 2: FIX Valid Issues
7. For any VALID bugs or architectural flaws found by Gemini, CodeRabbit, Qodo, Copilot, or any other reviewer: implement the fix
8. Also independently identify and fix any gaps or issues you find in the changed code — do not rely only on prior reviewer feedback
9. Push all code fixes directly to THIS branch (do NOT create a new PR)
10. Comment a summary of exact files modified and what you skipped

Phase 3: Final Verdict
11. If all issues are resolved, approve the PR / close the Issue
12. If blocking issues remain, request changes / leave clear action items

[praisonai-triage-agent]

Claude finished @MervinPraison's task —— View job

---

Final Architecture Review — PR #4470

• Setup git identity & read AGENTS.md
• Review the 3 changed files
• Evaluate Greptile's 3 P1 token-scoping findings — all valid
• Fix: scope by_model, total_interactions, recent_interactions to owned agents
• Test (isolation assertions pass)
• Commit & push (42dfab5c2)

---

Phase 1 — Architecture (per AGENTS.md)

• Lightweight / no scope creep: ✅ No new public API, no new Agent params, no new deps. Read-side filter reuses the existing TokenCollector breakdown + its per-interaction window. Correctly stays in praisonaiagents/ (core reporting logic, not a tool/plugin).
• Backward compatible: ✅ Falls back to the unfiltered summary when the instance has no named agents; return shape unchanged.
• Performance: ✅ Read-path only (report/display), never in the token hot-path.

Phase 2 — Fixes implemented

agents/agents.py — Greptile's 3 P1s were valid; the original patch scoped by_agent but still copied process-global fields. Fixed:

Finding	Before	After
total_interactions (was L2631)	copied from global summary	derived from this instance's own records
by_model (was L2634)	copied from global summary	re-derived per-model from owned interactions
recent_interactions (was L2652)	unfiltered global window	filtered to owned agent names

Added two private helpers: _own_agent_names() and _scoped_recent_interactions(). display_token_usage() inherits the fix via the scoped summary.

Verified (two teams, overlapping process collector):

A: interactions=2, by_model=['gpt-4'],  by_agent=['alice','bob'], tokens=42
B: interactions=1, by_model=['claude'], by_agent=['carol'],       tokens=150
recentA=['alice','bob']  recentB=['carol']   → ALL SCOPING ASSERTIONS PASSED

Reviewed & accepted as-is (no change needed):

• chat_mixin.py — streaming input guardrail runs before dispatch in _start_stream_impl, matching chat()/achat(). Correct; output-side streaming warning untouched.
• tool_execution.py — ToolExecutionError now reserved for denials/retryable transients; plain tool-authored {"error": ...} surfaces to the LLM to self-correct, mirroring openai_client.py. Correct.

Known residual (documented, not blocking)

• Same-named agents across two teams still can't be split (the aggregate by_agent collapses them under one key, and total_metrics/by_agent for that key stays merged). by_model/total_interactions/recent_interactions are now correct via the per-interaction window, but true collision-proof isolation would require a session-id on each interaction — explicitly out of scope per the lightweight mandate (no session-id threading). Distinct agent names (the normal case) are fully isolated.

Phase 3 — Verdict

✅ Approve. All three P1 token-scoping findings resolved and verified; guardrail and tool-error changes are sound and add genuine SDK value (streaming security parity + self-correcting tool errors). The one residual (identical agent names across concurrent teams) is a deliberate lightweight trade-off, not a regression.

Note: I can't submit a formal GitHub approval (bot restriction) — this comment is the review.

Job run · Branch

[greptile-apps]

Recent window understates totals

When a team records more than 100 interactions, or another team's activity evicts its older records, _scoped_token_summary derives total_interactions and by_model from the bounded recent-interaction window while deriving token and agent totals from session-wide aggregates. The resulting public report understates interaction and model usage and is internally inconsistent.

Knowledge Base Used: Agent execution and workflows

[MervinPraison]

@coderabbitai review

[MervinPraison]

/review

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📥 Commits

Reviewing files that changed from the base of the PR and between d4d65df and 42dfab5.

📒 Files selected for processing (3)

• src/praisonai-agents/praisonaiagents/agent/chat_mixin.py
• src/praisonai-agents/praisonaiagents/agent/tool_execution.py
• src/praisonai-agents/praisonaiagents/agents/agents.py

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[MervinPraison]

@claude this PR has merge conflicts with main. Please rebase onto latest main, resolve conflicts (keep this PR's intent, merge in newer main logic), run targeted tests, and force-push with --force-with-lease. Comment which files you resolved. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params. Keep the resolution minimal — the aim is a lightweight and powerful package; do not introduce scope creep while resolving conflicts.

[MervinPraison]

@claude this PR has merge conflicts with main. Please rebase onto latest main, resolve conflicts (keep this PR's intent, merge in newer main logic), run targeted tests, and force-push with --force-with-lease. Comment which files you resolved. Do not bloat the Agent class with additional params — only if absolutely required; we already support many params. Keep the resolution minimal — the aim is a lightweight and powerful package; do not introduce scope creep while resolving conflicts.

[praisonai-triage-agent]

Claude finished @MervinPraison's task —— View job

---

Rebase onto latest main — done ✅

• Setup git identity & fetched origin/main
• Rebased onto origin/main, resolved conflicts (kept PR intent + newer main logic)
• Ran targeted checks (import + functional scoping isolation)
• Force-pushed with --force-with-lease

---

Files resolved (3)

File	Conflict	Resolution
agent/chat_mixin.py	streaming input guardrail	Kept main's approach. Main already runs _validate_input_with_guardrail in _start_stream before the durable run — a strict superset of the PR's intent that also avoids opening a durable run for a blocked prompt. _start_stream_impl keeps the explanatory comment only.
agent/tool_execution.py	tool error-dict handling	Kept main's superset. Now raise ToolExecutionError on is_retryable or raised_exception; plain tool-authored {"error": ...} still falls through to the LLM (PR intent preserved), while a raised exception (via _praison_retryable tag) correctly surfaces as a failure.
agents/agents.py	per-instance token scoping	Kept the fully-scoped version (_own_agent_names() + _scoped_recent_interactions(own_names)). Scopes by_agent, by_model, total_interactions, totals, and recent_interactions to owned agents. Removed the stale duplicate _scoped_recent_interactions(limit=20) helper introduced during the two-commit replay.

Note: main had already merged a sibling fix for #4446 (PR #4462) using an alternate helper layout. The rebase reconciles this PR onto that, keeping this PR's clean fully-scoped implementation. No new Agent params, no new public API, no new deps — lightweight mandate honoured.

Verification

• py_compile + ast.parse OK on all 3 files
• AgentTeam imports; single consistent _scoped_recent_interactions(self, own_names: set) (no duplicate)
• Functional isolation test (two teams sharing the process collector):

  by_agent=['alice','bob']  by_model=['gpt-4']  interactions=2  tokens=42
  recent_interactions → only alice/bob   → ALL SCOPING ASSERTIONS PASSED
  

Skipped

• Full pytest tests/ — blocked by pre-existing missing optional deps (litellm) unrelated to these changes. Ran targeted import + behavioural checks instead.

Job run · Branch

[praisonai-triage-agent]

Claude finished @MervinPraison's task —— View job

---

Rebase onto latest main — done ✅

• Setup git identity & fetched origin/main
• Rebased onto origin/main (now on top of 40248e6a6)
• Resolved conflicts (kept PR intent + newer main logic)
• Ran targeted checks (compile + functional scoping isolation)
• Force-pushed with --force-with-lease

---

Result

The rebase applied cleanly with no manual conflict resolution required. main had already merged a sibling fix for #4446 (PR #4462, 1a677bf1c); git auto-reconciled this PR's fully-scoped implementation on top of it. The branch is now a single commit (b80cf44e1) atop latest main.

File resolved (1)

File	State
agents/agents.py	Kept this PR's fully-scoped token-report implementation (_own_agent_names() + _scoped_recent_interactions(own_names) + _scoped_token_summary()). Scopes by_agent, by_model, total_interactions, totals, and recent_interactions to owned agents. No duplicate helpers — single consistent _scoped_recent_interactions(self, own_names: set).

Lightweight mandate honoured: no new Agent params, no new public API, no new deps.

Verification

• py_compile OK on agents/agents.py
• Functional isolation test (two teams sharing the process collector):

  A by_agent ['alice','bob']  by_model ['gpt-4']   interactions 2  tokens 42
  B by_agent ['carol']        by_model ['claude']  interactions 1  tokens 150
  recentA → {alice,bob}   recentB → {carol}
  ALL SCOPING ASSERTIONS PASSED
  

Skipped

• Full pytest tests/ — blocked by pre-existing missing optional deps (litellm) unrelated to this change. Installed pydantic/rich locally to run the targeted behavioural + import checks instead.

Job run · Branch