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📝 WalkthroughWalkthroughAdds SKALE integration notes to payment docs and introduces a new RAG Router Agent example that implements intent classification, DB routing, keyword-based retrieval, domain-agent delegation, and LLM-driven answer generation returning structured JSON. Changes
Sequence Diagram(s)sequenceDiagram
participant User as User
participant Agent as RAG Agent\n(agent.py)
participant Router as Intent Router\n(router.py)
participant Retriever as Document Retriever\n(retriever.py)
participant Domain as Domain Agent\n(agents/*)
participant LLM as OpenRouter LLM
participant DB as Knowledge DB\n(db/*.txt)
User->>Agent: Send messages (last contains query)
activate Agent
Agent->>Router: classify_intent(query)
Router-->>Agent: intent
Agent->>Router: route_db(intent)
Router-->>Agent: db_path
Agent->>Retriever: retrieve_docs(db_path, query, k=2)
Retriever->>DB: Read and score lines
Retriever-->>Agent: top-k docs
Agent->>Domain: route_agent(intent) -> domain agent(context, query)
Domain-->>Agent: agent_response
Agent->>LLM: compose final prompt (query + agent_response + context)
LLM-->>Agent: generated result
Agent-->>User: {answer, intent, agent_used, db_used, docs_used}
deactivate Agent
Estimated code review effort🎯 3 (Moderate) | ⏱️ ~25 minutes Suggested reviewers
Poem
🚥 Pre-merge checks | ✅ 1 | ❌ 2❌ Failed checks (1 warning, 1 inconclusive)
✅ Passed checks (1 passed)
✏️ Tip: You can configure your own custom pre-merge checks in the settings. ✨ Finishing Touches🧪 Generate unit tests (beta)
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Actionable comments posted: 8
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@docs/PAYMENT.md`:
- Around line 273-280: Add a single explicit sentence to the paragraph
clarifying Bindu’s current default RPC mapping: state that the configuration key
rpc_urls_by_network in Bindu defaults to include base-sepolia, base, and
ethereum (and does not include Avalanche by default), so readers won’t confuse
upstream x402 entries with Bindu’s own defaults; update the docs near the
discussion of skale and x402 to mention rpc_urls_by_network and these three
networks by name.
In `@examples/rag_router_agent/agent.py`:
- Around line 64-73: The current try/except around agent.run(result) returns the
raw exception string (variable e) to callers, which may leak provider/config
details; instead, catch exceptions from agent.run, log the full exception
internally using your logger (e.g., logger.exception or similar) and return a
generic error message in the "answer" field (e.g., "An error occurred while
generating the response") while still returning intent, db_path and docs; if
this catch is intentional at the handler boundary, add an explicit lint
rationale comment above the except to justify the broad catch and masking
behavior.
- Around line 84-93: The config dict currently contains a personal email in the
"author" field; replace the hardcoded address in the config (variable name
config, key "author") with a non-sensitive placeholder or read from an
environment variable (e.g., os.getenv("EXAMPLE_AUTHOR", "example@example.com"))
so no personal identifiers are committed; update any README or comments to
indicate contributors should set EXAMPLE_AUTHOR in their environment if needed.
- Around line 21-25: The handler currently only catches KeyError/IndexError
while extracting query from messages[-1]["content"]; update handler to first
validate the message shape: ensure messages is a list and not None, that it has
at least one item, that last_item := messages[-1] is a dict, that "content" in
last_item and isinstance(last_item["content"], str), then assign query =
last_item["content"] or otherwise handle invalid input (raise a descriptive
error or return a safe default); reference the handler function and the query
extraction so you add these checks before the current try/except block.
In `@examples/rag_router_agent/README.md`:
- Around line 15-27: Add a quickstart section to the README that documents the
required local setup: show how to set the OPENROUTER_API_KEY environment
variable on Windows (powershell) and macOS/Linux (bash) and the exact command to
run the example script (python test_local.py). Update README.md near the example
flow (the section containing "User Query → Intent Detection → DB Routing →
Retrieval → LLM Response" and the "🔍 Example") to include these two environment
variable examples and the command to run test_local.py so users can reproduce
the sample locally.
In `@examples/rag_router_agent/retriever.py`:
- Around line 1-15: The retrieve_docs function currently lowercases docs but not
the query and returns top-k even when scores are zero; update retrieve_docs to
normalize the query (e.g., lower().split() or simple tokenization) and compare
against lowercased doc text, compute scores as you already do, then filter out
any (score, doc) pairs with score == 0 before sorting and slicing so only
positively-scored docs (up to k) are returned; adjust use of the scored list and
return expression accordingly to reference retrieve_docs, docs and scored.
In `@examples/rag_router_agent/router.py`:
- Around line 13-14: The route_db function returns a relative path that only
works when the process cwd is the example folder; update route_db to build the
path relative to this module's location (use __file__ /
pathlib.Path(__file__).parent) and join "db" and f"{intent}.txt" so lookups
succeed regardless of process cwd; modify the route_db implementation to compute
the absolute/relative-to-module path using Path(__file__).parent.joinpath("db",
f"{intent}.txt") (or equivalent) to locate files reliably.
- Around line 3-10: The current intent routing lowercases the raw query and uses
substring checks (e.g., checking "act") which misroutes words like "React";
update the classifier to tokenize the query into whole-word tokens (split on
whitespace and strip punctuation or use a word-boundary regex) and then perform
exact-term membership checks against the intent keyword lists (the same lists
currently used in the any(...) checks) so only whole-word matches (e.g., "act"
as a standalone token) map to "legal" while "react" remains "tech"; apply this
change where the query variable is lowercased and the intent branches are
checked.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
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📒 Files selected for processing (9)
docs/PAYMENT.mdexamples/rag_router_agent/README.mdexamples/rag_router_agent/agent.pyexamples/rag_router_agent/db/finance.txtexamples/rag_router_agent/db/legal.txtexamples/rag_router_agent/db/tech.txtexamples/rag_router_agent/retriever.pyexamples/rag_router_agent/router.pyexamples/rag_router_agent/test_local.py
Comment on lines
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| These upstream `x402` constraints are separate from Bindu's own runtime | ||
| configuration, where RPC endpoint configuration can be defined independently. | ||
|
|
||
| ### What this means | ||
|
|
||
| On the Bindu side, the payment middleware and RPC configuration model are | ||
| already flexible enough for future network expansion. However, adding `skale` | ||
| only in Bindu configuration is not sufficient yet, because the upstream `x402` |
There was a problem hiding this comment.
Clarify the currently configured Bindu defaults to avoid network support ambiguity.
Please add one explicit line here that Bindu’s default rpc_urls_by_network currently includes base-sepolia, base, and ethereum (not Avalanche by default). Right now, readers may infer Avalanche is preconfigured because it appears in the upstream list.
Suggested doc patch
These upstream `x402` constraints are separate from Bindu's own runtime
configuration, where RPC endpoint configuration can be defined independently.
+As of now, Bindu's default RPC configuration includes `base-sepolia`, `base`,
+and `ethereum`; Avalanche/SKALE require explicit configuration (and SKALE also
+requires upstream `x402` support work).📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
Suggested change
| These upstream `x402` constraints are separate from Bindu's own runtime | |
| configuration, where RPC endpoint configuration can be defined independently. | |
| ### What this means | |
| On the Bindu side, the payment middleware and RPC configuration model are | |
| already flexible enough for future network expansion. However, adding `skale` | |
| only in Bindu configuration is not sufficient yet, because the upstream `x402` | |
| These upstream `x402` constraints are separate from Bindu's own runtime | |
| configuration, where RPC endpoint configuration can be defined independently. | |
| As of now, Bindu's default RPC configuration includes `base-sepolia`, `base`, | |
| and `ethereum`; Avalanche/SKALE require explicit configuration (and SKALE also | |
| requires upstream `x402` support work). | |
| ### What this means | |
| On the Bindu side, the payment middleware and RPC configuration model are | |
| already flexible enough for future network expansion. However, adding `skale` | |
| only in Bindu configuration is not sufficient yet, because the upstream `x402` |
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@docs/PAYMENT.md` around lines 273 - 280, Add a single explicit sentence to
the paragraph clarifying Bindu’s current default RPC mapping: state that the
configuration key rpc_urls_by_network in Bindu defaults to include base-sepolia,
base, and ethereum (and does not include Avalanche by default), so readers won’t
confuse upstream x402 entries with Bindu’s own defaults; update the docs near
the discussion of skale and x402 to mention rpc_urls_by_network and these three
networks by name.
Contributor
Author
|
Added a small README improvement with example output + run instructions to make it easier to try locally. Happy to extend this into:
Would love feedback on where this fits best. |
Contributor
Author
|
Noticed CI unit tests are failing, but this seems unrelated to my changes. This PR only adds an example under Locally verified:
Happy to adjust if needed. |
Contributor
Author
|
Thanks for the detailed feedback—this is really helpful! I’ll address the suggestions around:
Will push updates shortly. |
There was a problem hiding this comment.
♻️ Duplicate comments (1)
examples/rag_router_agent/retriever.py (1)
11-24:⚠️ Potential issue | 🟠 MajorUse document tokens for scoring instead of substring checks.
Line 20 still treats any query token found inside a larger word as a match, so short terms can return irrelevant context and bypass the “no relevant information” path.
Proposed fix
# 🔤 Normalize query (fix punctuation + case issues) - query_words = re.findall(r"\w+", query.lower()) + query_words = set(re.findall(r"\w+", query.lower())) scored = [] for doc in docs: - doc_lower = doc.lower() + doc_words = set(re.findall(r"\w+", doc.lower())) # 📊 Compute score (token-based match) - score = sum(1 for word in query_words if word in doc_lower) + score = len(query_words & doc_words) # ❗ Filter irrelevant docs (IMPORTANT FIX) if score > 0: - scored.append((score, doc)) + scored.append((score, doc.strip()))🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/retriever.py` around lines 11 - 24, The current scoring uses substring checks (word in doc_lower) which matches tokens inside larger words; instead, tokenize each document into normalized tokens and do exact token membership checks: create doc_words (e.g., using re.findall(r"\w+", doc.lower())) and a set_doc_words for fast lookup, then compute score as sum(1 for word in query_words if word in set_doc_words) before appending to scored; update references to doc_lower and score logic accordingly to ensure only whole-token matches count.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Duplicate comments:
In `@examples/rag_router_agent/retriever.py`:
- Around line 11-24: The current scoring uses substring checks (word in
doc_lower) which matches tokens inside larger words; instead, tokenize each
document into normalized tokens and do exact token membership checks: create
doc_words (e.g., using re.findall(r"\w+", doc.lower())) and a set_doc_words for
fast lookup, then compute score as sum(1 for word in query_words if word in
set_doc_words) before appending to scored; update references to doc_lower and
score logic accordingly to ensure only whole-token matches count.
ℹ️ Review info
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Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: 216dca32-4ef8-4df9-967e-5b778487b5d0
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examples/rag_router_agent/retriever.py
Contributor
Author
|
Addressed all review feedback:
Would love any further feedback! |
There was a problem hiding this comment.
Actionable comments posted: 2
🧹 Nitpick comments (1)
examples/rag_router_agent/agent.py (1)
6-7: Sibling imports may break when module is imported from another cwd.
from router import .../from retriever import ...resolve only whenexamples/rag_router_agent/is onsys.path(e.g., runningpython agent.pyfrom that dir, ortest_local.pylocated alongside). Importingagentfrom a parent directory or as part of a larger harness will raiseModuleNotFoundError. Since this file is used as an example and its companiontest_local.pyimportshandlerfrom here, consider making the module location self-resolving.♻️ Proposed fix
import os +import sys +from pathlib import Path + +sys.path.insert(0, str(Path(__file__).resolve().parent)) + from bindu.penguin.bindufy import bindufy from agno.agent import Agent from agno.models.openai import OpenAIChat from router import classify_intent, route_db from retriever import retrieve_docs🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/agent.py` around lines 6 - 7, The sibling imports in agent.py (from router import classify_intent, route_db and from retriever import retrieve_docs) can break when agent is imported from a different CWD; update agent.py to resolve its companion modules reliably by either converting to package-relative imports (e.g., from .router import classify_intent, route_db and from .retriever import retrieve_docs) if you make examples a package, or add a short robust sys.path bootstrap at the top that computes the examples/rag_router_agent directory from __file__ and inserts it into sys.path before importing router/retriever so classify_intent, route_db and retrieve_docs always resolve for imports like test_local.py importing handler.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@examples/rag_router_agent/agent.py`:
- Line 112: The file is missing a trailing newline causing the pre-commit hook
to fail; add a single newline at EOF immediately after the final call
bindufy(config, handler) so the file ends with a newline, then run pre-commit
locally to verify the end-of-file-fixer passes before pushing.
- Around line 78-87: The except block around agent.run(prompt) is swallowing all
exceptions; change it to capture the exception (e.g., except Exception as e) and
log the full error/stack trace (using logging.exception or a module-level
logger) before returning the generic error response so failures (bad
OPENROUTER_API_KEY, network, rate limits) are debuggable; update references in
the block that return {"answer": ..., "intent": intent, "db_used": db_path,
"docs_used": docs} to keep behavior identical while ensuring the exception is
recorded (reference: agent.run, result, prompt, intent, db_path, docs).
---
Nitpick comments:
In `@examples/rag_router_agent/agent.py`:
- Around line 6-7: The sibling imports in agent.py (from router import
classify_intent, route_db and from retriever import retrieve_docs) can break
when agent is imported from a different CWD; update agent.py to resolve its
companion modules reliably by either converting to package-relative imports
(e.g., from .router import classify_intent, route_db and from .retriever import
retrieve_docs) if you make examples a package, or add a short robust sys.path
bootstrap at the top that computes the examples/rag_router_agent directory from
__file__ and inserts it into sys.path before importing router/retriever so
classify_intent, route_db and retrieve_docs always resolve for imports like
test_local.py importing handler.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: a4f1bf22-e051-457f-8921-5191dc44bb7f
📒 Files selected for processing (6)
examples/rag_router_agent/agent.pyexamples/rag_router_agent/db/finance.txtexamples/rag_router_agent/db/legal.txtexamples/rag_router_agent/db/tech.txtexamples/rag_router_agent/router.pyexamples/rag_router_agent/test_local.py
✅ Files skipped from review due to trivial changes (4)
- examples/rag_router_agent/db/tech.txt
- examples/rag_router_agent/db/finance.txt
- examples/rag_router_agent/db/legal.txt
- examples/rag_router_agent/test_local.py
🚧 Files skipped from review as they are similar to previous changes (1)
- examples/rag_router_agent/router.py
Comment on lines
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| try: | ||
| result = agent.run(prompt) | ||
| answer = result.content if hasattr(result, "content") else str(result) | ||
| except Exception: | ||
| return { | ||
| "answer": "Error generating response. Please try again.", | ||
| "intent": intent, | ||
| "db_used": db_path, | ||
| "docs_used": docs, | ||
| } |
There was a problem hiding this comment.
Log the swallowed exception so failures are debuggable.
Returning a generic "Error generating response." is correct for the caller (addresses the earlier leakage concern), but currently the underlying error (bad OPENROUTER_API_KEY, network failure, provider rate limit, etc.) is silently dropped — making the example very hard to troubleshoot. At minimum, log the exception internally. This also lets you silence Ruff BLE001 with an explicit rationale.
🛠️ Proposed fix
+import logging
import os
from bindu.penguin.bindufy import bindufy
from agno.agent import Agent
from agno.models.openai import OpenAIChat
from router import classify_intent, route_db
from retriever import retrieve_docs
+
+logger = logging.getLogger(__name__) try:
result = agent.run(prompt)
answer = result.content if hasattr(result, "content") else str(result)
- except Exception:
+ except Exception: # noqa: BLE001 - keep handler response structured at the service boundary
+ logger.exception("agent.run failed for intent=%s db=%s", intent, db_path)
return {
"answer": "Error generating response. Please try again.",
"intent": intent,
"db_used": db_path,
"docs_used": docs,
}📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
Suggested change
| try: | |
| result = agent.run(prompt) | |
| answer = result.content if hasattr(result, "content") else str(result) | |
| except Exception: | |
| return { | |
| "answer": "Error generating response. Please try again.", | |
| "intent": intent, | |
| "db_used": db_path, | |
| "docs_used": docs, | |
| } | |
| try: | |
| result = agent.run(prompt) | |
| answer = result.content if hasattr(result, "content") else str(result) | |
| except Exception: # noqa: BLE001 - keep handler response structured at the service boundary | |
| logger.exception("agent.run failed for intent=%s db=%s", intent, db_path) | |
| return { | |
| "answer": "Error generating response. Please try again.", | |
| "intent": intent, | |
| "db_used": db_path, | |
| "docs_used": docs, | |
| } |
🧰 Tools
🪛 Ruff (0.15.10)
[warning] 81-81: Do not catch blind exception: Exception
(BLE001)
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@examples/rag_router_agent/agent.py` around lines 78 - 87, The except block
around agent.run(prompt) is swallowing all exceptions; change it to capture the
exception (e.g., except Exception as e) and log the full error/stack trace
(using logging.exception or a module-level logger) before returning the generic
error response so failures (bad OPENROUTER_API_KEY, network, rate limits) are
debuggable; update references in the block that return {"answer": ..., "intent":
intent, "db_used": db_path, "docs_used": docs} to keep behavior identical while
ensuring the exception is recorded (reference: agent.run, result, prompt,
intent, db_path, docs).
|
|
||
| # 🚀 Start agent only when run directly | ||
| if __name__ == "__main__": | ||
| bindufy(config, handler) No newline at end of file |
There was a problem hiding this comment.
CI failing: add trailing newline at end of file.
The end-of-file-fixer pre-commit hook rewrote this file in CI and failed the job. Append a newline after line 112 and re-run pre-commit locally (pre-commit run --files examples/rag_router_agent/agent.py) before pushing.
🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed.
In `@examples/rag_router_agent/agent.py` at line 112, The file is missing a
trailing newline causing the pre-commit hook to fail; add a single newline at
EOF immediately after the final call bindufy(config, handler) so the file ends
with a newline, then run pre-commit locally to verify the end-of-file-fixer
passes before pushing.
There was a problem hiding this comment.
Actionable comments posted: 1
🧹 Nitpick comments (5)
examples/rag_router_agent/agents/tech_agent.py (1)
1-2: Unusedqueryparameter.
queryis accepted but never used in the response. If the signature is intentional for uniform dispatch fromroute_agent, consider prefixing it with_or adding a brief comment to document the convention; otherwise the domain agent can't meaningfully differentiate its behavior based on the user's query.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/agents/tech_agent.py` around lines 1 - 2, The tech_agent function currently accepts a query parameter but never uses it; either make the parameter explicitly unused by renaming it to _query (or add a comment like "# query kept for uniform dispatch") to document the convention, or update tech_agent to incorporate the query into its output (e.g., include the query in the returned string) so the agent can differentiate responses; locate the function named tech_agent and apply one of these fixes to resolve the unused parameter warning.examples/rag_router_agent/router.py (2)
5-13: Intent classifier has notechkeywords and falls through for unrelated queries.Any query without finance/legal tokens silently maps to
"tech", so "What's the weather today?" will be classified as tech and route todb/tech.txt. That's acceptable for an example, but consider either (a) adding explicit tech keywords and returning an"unknown"/Noneintent for no-match (lettinghandlershort-circuit with a "no relevant domain" message), or (b) documenting the default-to-tech behavior in the README so users aren't surprised.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/router.py` around lines 5 - 13, The classify_intent function currently defaults every non-finance/legal query to "tech", which misroutes unrelated queries; update classify_intent to either include explicit tech keywords (e.g., "computer", "program", "api", "server", "network") so tech is matched intentionally, or change it to return a sentinel like None/"unknown" on no match and update the caller/handler to short-circuit and respond with a "no relevant domain" message; reference the classify_intent function in your changes and ensure any dependent routing logic checks for the new None/"unknown" value before selecting db/tech.txt.
25-28: Top-level imports placed mid-file and relying onsys.pathcontaining the example dir.Two concerns:
- Imports are below code rather than at the top of the module — Ruff/
isort/PEP 8 would flag this (E402).from agents.finance_agent import finance_agentonly resolves whenexamples/rag_router_agentis onsys.path(i.e., runningpython agent.pyfrom that directory). Running from the repo root or via a different launcher willImportError. Sinceroute_dbwas fixed to be cwd-independent via__file__, it's inconsistent to leave the agent imports cwd-dependent.Suggested fix
Move imports to the top and make them robust to cwd. One option using an
__init__.pyinagents/and a path shim:import os import re +import sys + +BASE_DIR = os.path.dirname(os.path.abspath(__file__)) +if BASE_DIR not in sys.path: + sys.path.insert(0, BASE_DIR) + +from agents.finance_agent import finance_agent +from agents.legal_agent import legal_agent +from agents.tech_agent import tech_agent @@ -# 📁 Resolve base directory safely -BASE_DIR = os.path.dirname(os.path.abspath(__file__)) @@ -# 🤖 Import domain agents (A2A delegation) -from agents.finance_agent import finance_agent -from agents.legal_agent import legal_agent -from agents.tech_agent import tech_agent - - # 🔀 Route to correct agent🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/router.py` around lines 25 - 28, Move the three domain-agent imports (finance_agent, legal_agent, tech_agent) to the top of the module and stop relying on the current working directory being on sys.path; either make the agents directory a proper package (add an __init__.py) so you can use stable absolute imports like from agents.finance_agent import finance_agent, or add a small deterministic path shim right before the imports that appends the project root (computed from Path(__file__).resolve().parents[...] ) to sys.path so the imports always resolve regardless of CWD, keeping this behavior consistent with the route_db __file__-based fix.examples/rag_router_agent/agents/legal_agent.py (1)
1-2: Same unusedqueryas the other domain agents.All three domain agents (
finance_agent,legal_agent,tech_agent) are near-identical stubs that only echocontextwith a different prefix. For an example demonstrating A2A delegation, consider collapsing them into a single parameterized helper (e.g.,make_domain_agent(name)) or having each actually usequeryto shape its response — otherwise the "multi-agent routing" aspect is cosmetic.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/agents/legal_agent.py` around lines 1 - 2, The three near-identical stubs finance_agent, legal_agent, and tech_agent ignore the query parameter; replace them with a single parameterized factory (e.g., make_domain_agent(name)) that returns an agent function which uses both query and context to produce a name-prefixed response, or alternatively update each existing function (finance_agent, legal_agent, tech_agent) to incorporate the query into the returned string so routing is meaningful; locate the functions by name in the diff and either implement make_domain_agent(name) to generate the agent closures or modify each agent to reference the query when building its response.examples/rag_router_agent/agent.py (1)
6-7: Module imports assume cwd isexamples/rag_router_agent/.
from router import ...andfrom retriever import ...only resolve when the example directory is onsys.path. Ifbindufyor a future launcher imports this file from elsewhere, both imports fail. For an example this is acceptable, but documenting it in the README ("run fromexamples/rag_router_agent/") or adding asys.pathshim (as suggested forrouter.py) would prevent confused users.🤖 Prompt for AI Agents
Verify each finding against the current code and only fix it if needed. In `@examples/rag_router_agent/agent.py` around lines 6 - 7, The imports in agent.py (classify_intent, route_db, route_agent, retrieve_docs) assume the example directory is on sys.path; add the same sys.path shim used in router.py at the top of agent.py so these relative module imports work when the file is executed or imported from elsewhere (or alternatively add a one-line README note instructing users to run from examples/rag_router_agent/). Specifically, add the sys.path insertion that prepends the example directory to sys.path before the from router import ... and from retriever import ... lines so classify_intent, route_db, route_agent and retrieve_docs resolve reliably.
🤖 Prompt for all review comments with AI agents
Verify each finding against the current code and only fix it if needed.
Inline comments:
In `@examples/rag_router_agent/agent.py`:
- Around line 11-18: The Agent is being constructed at import time using
OpenAIChat(api_key=os.getenv("OPENROUTER_API_KEY")) which can be None when the
env var is unset; add an explicit startup check that reads
os.getenv("OPENROUTER_API_KEY") into a variable, validate it's non-empty, and
raise or log a clear error (or exit) before constructing OpenAIChat/Agent; also
ensure the response-generation path does not swallow the underlying exception so
the missing API key is visible to users (adjust the error handling where
responses are generated to re-raise or include the underlying error).
---
Nitpick comments:
In `@examples/rag_router_agent/agent.py`:
- Around line 6-7: The imports in agent.py (classify_intent, route_db,
route_agent, retrieve_docs) assume the example directory is on sys.path; add the
same sys.path shim used in router.py at the top of agent.py so these relative
module imports work when the file is executed or imported from elsewhere (or
alternatively add a one-line README note instructing users to run from
examples/rag_router_agent/). Specifically, add the sys.path insertion that
prepends the example directory to sys.path before the from router import ... and
from retriever import ... lines so classify_intent, route_db, route_agent and
retrieve_docs resolve reliably.
In `@examples/rag_router_agent/agents/legal_agent.py`:
- Around line 1-2: The three near-identical stubs finance_agent, legal_agent,
and tech_agent ignore the query parameter; replace them with a single
parameterized factory (e.g., make_domain_agent(name)) that returns an agent
function which uses both query and context to produce a name-prefixed response,
or alternatively update each existing function (finance_agent, legal_agent,
tech_agent) to incorporate the query into the returned string so routing is
meaningful; locate the functions by name in the diff and either implement
make_domain_agent(name) to generate the agent closures or modify each agent to
reference the query when building its response.
In `@examples/rag_router_agent/agents/tech_agent.py`:
- Around line 1-2: The tech_agent function currently accepts a query parameter
but never uses it; either make the parameter explicitly unused by renaming it to
_query (or add a comment like "# query kept for uniform dispatch") to document
the convention, or update tech_agent to incorporate the query into its output
(e.g., include the query in the returned string) so the agent can differentiate
responses; locate the function named tech_agent and apply one of these fixes to
resolve the unused parameter warning.
In `@examples/rag_router_agent/router.py`:
- Around line 5-13: The classify_intent function currently defaults every
non-finance/legal query to "tech", which misroutes unrelated queries; update
classify_intent to either include explicit tech keywords (e.g., "computer",
"program", "api", "server", "network") so tech is matched intentionally, or
change it to return a sentinel like None/"unknown" on no match and update the
caller/handler to short-circuit and respond with a "no relevant domain" message;
reference the classify_intent function in your changes and ensure any dependent
routing logic checks for the new None/"unknown" value before selecting
db/tech.txt.
- Around line 25-28: Move the three domain-agent imports (finance_agent,
legal_agent, tech_agent) to the top of the module and stop relying on the
current working directory being on sys.path; either make the agents directory a
proper package (add an __init__.py) so you can use stable absolute imports like
from agents.finance_agent import finance_agent, or add a small deterministic
path shim right before the imports that appends the project root (computed from
Path(__file__).resolve().parents[...] ) to sys.path so the imports always
resolve regardless of CWD, keeping this behavior consistent with the route_db
__file__-based fix.
🪄 Autofix (Beta)
Fix all unresolved CodeRabbit comments on this PR:
- Push a commit to this branch (recommended)
- Create a new PR with the fixes
ℹ️ Review info
⚙️ Run configuration
Configuration used: defaults
Review profile: CHILL
Plan: Pro
Run ID: 7749f739-8948-4dad-87df-dac8df40563e
📒 Files selected for processing (6)
examples/rag_router_agent/README.mdexamples/rag_router_agent/agent.pyexamples/rag_router_agent/agents/finance_agent.pyexamples/rag_router_agent/agents/legal_agent.pyexamples/rag_router_agent/agents/tech_agent.pyexamples/rag_router_agent/router.py
✅ Files skipped from review due to trivial changes (1)
- examples/rag_router_agent/README.md
Contributor
Author
|
Extended this agent from a single RAG pipeline into a multi-agent system. Key upgrade:
This introduces a simple A2A-style coordination pattern, where agents act as modular components rather than a single monolithic responder. Happy to extend this further into full agent-to-agent communication using Bindu protocol if aligned. |
Contributor
Author
|
Addressed final review comments:
Happy to iterate further if needed! |
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Summary
rag_router_agent) implementing intent classification, database routing, and context-aware response generation using LLM.Change Type (select all that apply)
Scope (select all touched areas)
Linked Issue/PR
User-Visible / Behavior Changes
Added a new example agent under
examples/rag_router_agent/Demonstrates:
Security Impact (required)
Verification
Environment
Steps to Test
Navigate to
examples/rag_router_agent/Set
OPENROUTER_API_KEYRun:
Optionally run:
Expected Behavior
Actual Behavior
Verified correct routing and response generation
Output includes:
Evidence (attach at least one)
Example output:
Human Verification (required)
Verified scenarios:
Edge cases checked:
What you did NOT verify:
Compatibility / Migration
Failure Recovery (if this breaks)
How to disable/revert:
examples/rag_router_agent/directoryFiles/config to restore:
Known bad symptoms:
Risks and Mitigations
Risk: Example may not cover all real-world edge cases
Checklist
Summary by CodeRabbit
New Features
Documentation