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Author SHA1 Message Date
c0f6ca9fc2 [claude] Add web_fetch tool (trafilatura) for full-page content extraction (#973) (#1004)
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2026-03-22 23:03:38 +00:00
9656a5e0d0 [claude] Add connection leak and pragma unit tests for db_pool.py (#944) (#1001)
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2026-03-22 22:56:58 +00:00
Alexander Whitestone
e35a23cefa [claude] Add research prompt template library (#974) (#999)
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Co-authored-by: Alexander Whitestone <alexpaynex@gmail.com>
Co-committed-by: Alexander Whitestone <alexpaynex@gmail.com>
2026-03-22 22:44:02 +00:00
Alexander Whitestone
3ab180b8a7 [claude] Add Gitea backup script (#990) (#996)
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Co-authored-by: Alexander Whitestone <alexpaynex@gmail.com>
Co-committed-by: Alexander Whitestone <alexpaynex@gmail.com>
2026-03-22 22:36:51 +00:00
11 changed files with 858 additions and 0 deletions

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@@ -50,6 +50,7 @@ sounddevice = { version = ">=0.4.6", optional = true }
sentence-transformers = { version = ">=2.0.0", optional = true }
numpy = { version = ">=1.24.0", optional = true }
requests = { version = ">=2.31.0", optional = true }
trafilatura = { version = ">=1.6.0", optional = true }
GitPython = { version = ">=3.1.40", optional = true }
pytest = { version = ">=8.0.0", optional = true }
pytest-asyncio = { version = ">=0.24.0", optional = true }
@@ -67,6 +68,7 @@ voice = ["pyttsx3", "openai-whisper", "piper-tts", "sounddevice"]
celery = ["celery"]
embeddings = ["sentence-transformers", "numpy"]
git = ["GitPython"]
research = ["requests", "trafilatura"]
dev = ["pytest", "pytest-asyncio", "pytest-cov", "pytest-timeout", "pytest-randomly", "pytest-xdist", "selenium"]
[tool.poetry.group.dev.dependencies]

83
scripts/gitea_backup.sh Executable file
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@@ -0,0 +1,83 @@
#!/bin/bash
# Gitea backup script — run on the VPS before any hardening changes.
# Usage: sudo bash scripts/gitea_backup.sh [off-site-dest]
#
# off-site-dest: optional rsync/scp destination for off-site copy
# e.g. user@backup-host:/backups/gitea/
#
# Refs: #971, #990
set -euo pipefail
BACKUP_DIR="/opt/gitea/backups"
TIMESTAMP=$(date +"%Y%m%d_%H%M%S")
GITEA_CONF="/etc/gitea/app.ini"
GITEA_WORK_DIR="/var/lib/gitea"
OFFSITE_DEST="${1:-}"
echo "=== Gitea Backup — $TIMESTAMP ==="
# Ensure backup directory exists
mkdir -p "$BACKUP_DIR"
cd "$BACKUP_DIR"
# Run the dump
echo "[1/4] Running gitea dump..."
gitea dump -c "$GITEA_CONF"
# Find the newest zip (gitea dump names it gitea-dump-*.zip)
BACKUP_FILE=$(ls -t "$BACKUP_DIR"/gitea-dump-*.zip 2>/dev/null | head -1)
if [ -z "$BACKUP_FILE" ]; then
echo "ERROR: No backup zip found in $BACKUP_DIR"
exit 1
fi
BACKUP_SIZE=$(stat -c%s "$BACKUP_FILE" 2>/dev/null || stat -f%z "$BACKUP_FILE")
echo "[2/4] Backup created: $BACKUP_FILE ($BACKUP_SIZE bytes)"
if [ "$BACKUP_SIZE" -eq 0 ]; then
echo "ERROR: Backup file is 0 bytes"
exit 1
fi
# Lock down permissions
chmod 600 "$BACKUP_FILE"
# Verify contents
echo "[3/4] Verifying backup contents..."
CONTENTS=$(unzip -l "$BACKUP_FILE" 2>/dev/null || true)
check_component() {
if echo "$CONTENTS" | grep -q "$1"; then
echo " OK: $2"
else
echo " WARN: $2 not found in backup"
fi
}
check_component "gitea-db.sql" "Database dump"
check_component "gitea-repo" "Repositories"
check_component "custom" "Custom config"
check_component "app.ini" "app.ini"
# Off-site copy
if [ -n "$OFFSITE_DEST" ]; then
echo "[4/4] Copying to off-site: $OFFSITE_DEST"
rsync -avz "$BACKUP_FILE" "$OFFSITE_DEST"
echo " Off-site copy complete."
else
echo "[4/4] No off-site destination provided. Skipping."
echo " To copy later: scp $BACKUP_FILE user@backup-host:/backups/gitea/"
fi
echo ""
echo "=== Backup complete ==="
echo "File: $BACKUP_FILE"
echo "Size: $BACKUP_SIZE bytes"
echo ""
echo "To verify restore on a clean instance:"
echo " 1. Copy zip to test machine"
echo " 2. unzip $BACKUP_FILE"
echo " 3. gitea restore --from <extracted-dir> -c /etc/gitea/app.ini"
echo " 4. Verify repos and DB are intact"

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@@ -0,0 +1,67 @@
---
name: Architecture Spike
type: research
typical_query_count: 2-4
expected_output_length: 600-1200 words
cascade_tier: groq_preferred
description: >
Investigate how to connect two systems or components. Produces an integration
architecture with sequence diagram, key decisions, and a proof-of-concept outline.
---
# Architecture Spike: Connect {system_a} to {system_b}
## Context
We need to integrate **{system_a}** with **{system_b}** in the context of
**{project_context}**. This spike answers: what is the best way to wire them
together, and what are the trade-offs?
## Constraints
- Prefer approaches that avoid adding new infrastructure dependencies.
- The integration should be **{sync_or_async}** (synchronous / asynchronous).
- Must work within: {environment_constraints}.
## Research Steps
1. Identify the APIs / protocols exposed by both systems.
2. List all known integration patterns (direct API, message queue, webhook, SDK, etc.).
3. Evaluate each pattern for complexity, reliability, and latency.
4. Select the recommended approach and outline a proof-of-concept.
## Output Format
### Integration Options
| Pattern | Complexity | Reliability | Latency | Notes |
|---------|-----------|-------------|---------|-------|
| ... | ... | ... | ... | ... |
### Recommended Approach
**Pattern:** {pattern_name}
**Why:** One paragraph explaining the choice.
### Sequence Diagram
```
{system_a} -> {middleware} -> {system_b}
```
Describe the data flow step by step:
1. {system_a} does X...
2. {middleware} transforms / routes...
3. {system_b} receives Y...
### Proof-of-Concept Outline
- Files to create or modify
- Key libraries / dependencies needed
- Estimated effort: {effort_estimate}
### Open Questions
Bullet list of decisions that need human input before proceeding.

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@@ -0,0 +1,74 @@
---
name: Competitive Scan
type: research
typical_query_count: 3-5
expected_output_length: 800-1500 words
cascade_tier: groq_preferred
description: >
Compare a project against its alternatives. Produces a feature matrix,
strengths/weaknesses analysis, and positioning summary.
---
# Competitive Scan: {project} vs Alternatives
## Context
Compare **{project}** against **{alternatives}** (comma-separated list of
competitors). The goal is to understand where {project} stands and identify
differentiation opportunities.
## Constraints
- Comparison date: {date}.
- Focus areas: {focus_areas} (e.g., features, pricing, community, performance).
- Perspective: {perspective} (user, developer, business).
## Research Steps
1. Gather key facts about {project} (features, pricing, community size, release cadence).
2. Gather the same data for each alternative in {alternatives}.
3. Build a feature comparison matrix.
4. Identify strengths and weaknesses for each entry.
5. Summarize positioning and recommend next steps.
## Output Format
### Overview
One paragraph: what space does {project} compete in, and who are the main players?
### Feature Matrix
| Feature / Attribute | {project} | {alt_1} | {alt_2} | {alt_3} |
|--------------------|-----------|---------|---------|---------|
| {feature_1} | ... | ... | ... | ... |
| {feature_2} | ... | ... | ... | ... |
| Pricing | ... | ... | ... | ... |
| License | ... | ... | ... | ... |
| Community Size | ... | ... | ... | ... |
| Last Major Release | ... | ... | ... | ... |
### Strengths & Weaknesses
#### {project}
- **Strengths:** ...
- **Weaknesses:** ...
#### {alt_1}
- **Strengths:** ...
- **Weaknesses:** ...
_(Repeat for each alternative)_
### Positioning Map
Describe where each project sits along the key dimensions (e.g., simplicity
vs power, free vs paid, niche vs general).
### Recommendations
Bullet list of actions based on the competitive landscape:
- **Differentiate on:** {differentiator}
- **Watch out for:** {threat}
- **Consider adopting from {alt}:** {feature_or_approach}

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@@ -0,0 +1,68 @@
---
name: Game Analysis
type: research
typical_query_count: 2-3
expected_output_length: 600-1000 words
cascade_tier: local_ok
description: >
Evaluate a game for AI agent playability. Assesses API availability,
observation/action spaces, and existing bot ecosystems.
---
# Game Analysis: {game}
## Context
Evaluate **{game}** to determine whether an AI agent can play it effectively.
Focus on programmatic access, observation space, action space, and existing
bot/AI ecosystems.
## Constraints
- Platform: {platform} (PC, console, mobile, browser).
- Agent type: {agent_type} (reinforcement learning, rule-based, LLM-driven, hybrid).
- Budget for API/licenses: {budget}.
## Research Steps
1. Identify official APIs, modding support, or programmatic access methods for {game}.
2. Characterize the observation space (screen pixels, game state JSON, memory reading, etc.).
3. Characterize the action space (keyboard/mouse, API calls, controller inputs).
4. Survey existing bots, AI projects, or research papers for {game}.
5. Assess feasibility and difficulty for the target agent type.
## Output Format
### Game Profile
| Property | Value |
|-------------------|------------------------|
| Game | {game} |
| Genre | {genre} |
| Platform | {platform} |
| API Available | Yes / No / Partial |
| Mod Support | Yes / No / Limited |
| Existing AI Work | Extensive / Some / None|
### Observation Space
Describe what data the agent can access and how (API, screen capture, memory hooks, etc.).
### Action Space
Describe how the agent can interact with the game (input methods, timing constraints, etc.).
### Existing Ecosystem
List known bots, frameworks, research papers, or communities working on AI for {game}.
### Feasibility Assessment
- **Difficulty:** Easy / Medium / Hard / Impractical
- **Best approach:** {recommended_agent_type}
- **Key challenges:** Bullet list
- **Estimated time to MVP:** {time_estimate}
### Recommendation
One paragraph: should we proceed, and if so, what is the first step?

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@@ -0,0 +1,79 @@
---
name: Integration Guide
type: research
typical_query_count: 3-5
expected_output_length: 1000-2000 words
cascade_tier: groq_preferred
description: >
Step-by-step guide to wire a specific tool into an existing stack,
complete with code samples, configuration, and testing steps.
---
# Integration Guide: Wire {tool} into {stack}
## Context
Integrate **{tool}** into our **{stack}** stack. The goal is to
**{integration_goal}** (e.g., "add vector search to the dashboard",
"send notifications via Telegram").
## Constraints
- Must follow existing project conventions (see CLAUDE.md).
- No new cloud AI dependencies unless explicitly approved.
- Environment config via `pydantic-settings` / `config.py`.
## Research Steps
1. Review {tool}'s official documentation for installation and setup.
2. Identify the minimal dependency set required.
3. Map {tool}'s API to our existing patterns (singletons, graceful degradation).
4. Write integration code with proper error handling.
5. Define configuration variables and their defaults.
## Output Format
### Prerequisites
- Dependencies to install (with versions)
- External services or accounts required
- Environment variables to configure
### Configuration
```python
# In config.py — add these fields to Settings:
{config_fields}
```
### Implementation
```python
# {file_path}
{implementation_code}
```
### Graceful Degradation
Describe how the integration behaves when {tool} is unavailable:
| Scenario | Behavior | Log Level |
|-----------------------|--------------------|-----------|
| {tool} not installed | {fallback} | WARNING |
| {tool} unreachable | {fallback} | WARNING |
| Invalid credentials | {fallback} | ERROR |
### Testing
```python
# tests/unit/test_{tool_snake}.py
{test_code}
```
### Verification Checklist
- [ ] Dependency added to pyproject.toml
- [ ] Config fields added with sensible defaults
- [ ] Graceful degradation tested (service down)
- [ ] Unit tests pass (`tox -e unit`)
- [ ] No new linting errors (`tox -e lint`)

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@@ -0,0 +1,67 @@
---
name: State of the Art
type: research
typical_query_count: 4-6
expected_output_length: 1000-2000 words
cascade_tier: groq_preferred
description: >
Comprehensive survey of what currently exists in a given field or domain.
Produces a structured landscape overview with key players, trends, and gaps.
---
# State of the Art: {field} (as of {date})
## Context
Survey the current landscape of **{field}**. Identify key players, recent
developments, dominant approaches, and notable gaps. This is a point-in-time
snapshot intended to inform decision-making.
## Constraints
- Focus on developments from the last {timeframe} (e.g., 12 months, 2 years).
- Prioritize {priority} (open-source, commercial, academic, or all).
- Target audience: {audience} (technical team, leadership, general).
## Research Steps
1. Identify the major categories or sub-domains within {field}.
2. For each category, list the leading projects, companies, or research groups.
3. Note recent milestones, releases, or breakthroughs.
4. Identify emerging trends and directions.
5. Highlight gaps — things that don't exist yet but should.
## Output Format
### Executive Summary
Two to three sentences: what is the state of {field} right now?
### Landscape Map
| Category | Key Players | Maturity | Trend |
|---------------|--------------------------|-------------|-------------|
| {category_1} | {player_a}, {player_b} | Early / GA | Growing / Stable / Declining |
| {category_2} | {player_c}, {player_d} | Early / GA | Growing / Stable / Declining |
### Recent Milestones
Chronological list of notable events in the last {timeframe}:
- **{date_1}:** {event_description}
- **{date_2}:** {event_description}
### Trends
Numbered list of the top 3-5 trends shaping {field}:
1. **{trend_name}** — {one-line description}
2. **{trend_name}** — {one-line description}
### Gaps & Opportunities
Bullet list of things that are missing, underdeveloped, or ripe for innovation.
### Implications for Us
One paragraph: what does this mean for our project? What should we do next?

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@@ -0,0 +1,52 @@
---
name: Tool Evaluation
type: research
typical_query_count: 3-5
expected_output_length: 800-1500 words
cascade_tier: groq_preferred
description: >
Discover and evaluate all shipping tools/libraries/services in a given domain.
Produces a ranked comparison table with pros, cons, and recommendation.
---
# Tool Evaluation: {domain}
## Context
You are researching tools, libraries, and services for **{domain}**.
The goal is to find everything that is currently shipping (not vaporware)
and produce a structured comparison.
## Constraints
- Only include tools that have public releases or hosted services available today.
- If a tool is in beta/preview, note that clearly.
- Focus on {focus_criteria} when evaluating (e.g., cost, ease of integration, community size).
## Research Steps
1. Identify all actively-maintained tools in the **{domain}** space.
2. For each tool, gather: name, URL, license/pricing, last release date, language/platform.
3. Evaluate each tool against the focus criteria.
4. Rank by overall fit for the use case: **{use_case}**.
## Output Format
### Summary
One paragraph: what the landscape looks like and the top recommendation.
### Comparison Table
| Tool | License / Price | Last Release | Language | {focus_criteria} Score | Notes |
|------|----------------|--------------|----------|----------------------|-------|
| ... | ... | ... | ... | ... | ... |
### Top Pick
- **Recommended:** {tool_name} — {one-line reason}
- **Runner-up:** {tool_name} — {one-line reason}
### Risks & Gaps
Bullet list of things to watch out for (missing features, vendor lock-in, etc.).

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@@ -473,6 +473,69 @@ def consult_grok(query: str) -> str:
return response
def web_fetch(url: str, max_tokens: int = 4000) -> str:
"""Fetch a web page and return its main text content.
Downloads the URL, extracts readable text using trafilatura, and
truncates to a token budget. Use this to read full articles, docs,
or blog posts that web_search only returns snippets for.
Args:
url: The URL to fetch (must start with http:// or https://).
max_tokens: Maximum approximate token budget (default 4000).
Text is truncated to max_tokens * 4 characters.
Returns:
Extracted text content, or an error message on failure.
"""
if not url or not url.startswith(("http://", "https://")):
return f"Error: invalid URL — must start with http:// or https://: {url!r}"
try:
import requests as _requests
except ImportError:
return "Error: 'requests' package is not installed. Install with: pip install requests"
try:
import trafilatura
except ImportError:
return (
"Error: 'trafilatura' package is not installed. Install with: pip install trafilatura"
)
try:
resp = _requests.get(
url,
timeout=15,
headers={"User-Agent": "TimmyResearchBot/1.0"},
)
resp.raise_for_status()
except _requests.exceptions.Timeout:
return f"Error: request timed out after 15 seconds for {url}"
except _requests.exceptions.HTTPError as exc:
return f"Error: HTTP {exc.response.status_code} for {url}"
except _requests.exceptions.RequestException as exc:
return f"Error: failed to fetch {url}{exc}"
text = trafilatura.extract(resp.text, include_tables=True, include_links=True)
if not text:
return f"Error: could not extract readable content from {url}"
char_budget = max_tokens * 4
if len(text) > char_budget:
text = text[:char_budget] + f"\n\n[…truncated to ~{max_tokens} tokens]"
return text
def _register_web_fetch_tool(toolkit: Toolkit) -> None:
"""Register the web_fetch tool for full-page content extraction."""
try:
toolkit.register(web_fetch, name="web_fetch")
except Exception as exc:
logger.warning("Tool execution failed (web_fetch registration): %s", exc)
def _register_core_tools(toolkit: Toolkit, base_path: Path) -> None:
"""Register core execution and file tools."""
# Python execution
@@ -672,6 +735,7 @@ def create_full_toolkit(base_dir: str | Path | None = None):
base_path = Path(base_dir) if base_dir else Path(settings.repo_root)
_register_core_tools(toolkit, base_path)
_register_web_fetch_tool(toolkit)
_register_grok_tool(toolkit)
_register_memory_tools(toolkit)
_register_agentic_loop_tool(toolkit)
@@ -829,6 +893,11 @@ def _analysis_tool_catalog() -> dict:
"description": "Evaluate mathematical expressions with exact results",
"available_in": ["orchestrator"],
},
"web_fetch": {
"name": "Web Fetch",
"description": "Fetch a web page and extract clean readable text (trafilatura)",
"available_in": ["orchestrator"],
},
}

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@@ -242,6 +242,145 @@ class TestCloseAll:
conn.execute("SELECT 1")
class TestConnectionLeaks:
"""Test that connections do not leak."""
def test_get_connection_after_close_returns_fresh_connection(self, tmp_path):
"""After close, get_connection() returns a new working connection."""
pool = ConnectionPool(tmp_path / "test.db")
conn1 = pool.get_connection()
pool.close_connection()
conn2 = pool.get_connection()
assert conn2 is not conn1
# New connection must be usable
cursor = conn2.execute("SELECT 1")
assert cursor.fetchone()[0] == 1
pool.close_connection()
def test_context_manager_does_not_leak_connection(self, tmp_path):
"""After context manager exit, thread-local conn is cleared."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection():
pass
# Thread-local should be cleaned up
assert pool._local.conn is None
def test_context_manager_exception_does_not_leak_connection(self, tmp_path):
"""Connection is cleaned up even when an exception occurs."""
pool = ConnectionPool(tmp_path / "test.db")
try:
with pool.connection():
raise RuntimeError("boom")
except RuntimeError:
pass
assert pool._local.conn is None
def test_threads_do_not_leak_into_each_other(self, tmp_path):
"""A connection opened in one thread is invisible to another."""
pool = ConnectionPool(tmp_path / "test.db")
# Open a connection on main thread
pool.get_connection()
visible_from_other_thread = []
def check():
has_conn = hasattr(pool._local, "conn") and pool._local.conn is not None
visible_from_other_thread.append(has_conn)
t = threading.Thread(target=check)
t.start()
t.join()
assert visible_from_other_thread == [False]
pool.close_connection()
def test_repeated_open_close_cycles(self, tmp_path):
"""Repeated open/close cycles do not accumulate leaked connections."""
pool = ConnectionPool(tmp_path / "test.db")
for _ in range(50):
with pool.connection() as conn:
conn.execute("SELECT 1")
# After each cycle, connection should be cleaned up
assert pool._local.conn is None
class TestPragmaApplication:
"""Test that SQLite pragmas can be applied and persist on pooled connections.
The codebase uses WAL journal mode and busy_timeout pragmas on connections
obtained from the pool. These tests verify that pattern works correctly.
"""
def test_wal_journal_mode_persists(self, tmp_path):
"""WAL journal mode set on a pooled connection persists for its lifetime."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
conn.execute("PRAGMA journal_mode=WAL")
mode = conn.execute("PRAGMA journal_mode").fetchone()[0]
assert mode == "wal"
# Same connection should retain the pragma
same_conn = pool.get_connection()
mode2 = same_conn.execute("PRAGMA journal_mode").fetchone()[0]
assert mode2 == "wal"
pool.close_connection()
def test_busy_timeout_persists(self, tmp_path):
"""busy_timeout pragma set on a pooled connection persists."""
pool = ConnectionPool(tmp_path / "test.db")
conn = pool.get_connection()
conn.execute("PRAGMA busy_timeout=5000")
timeout = conn.execute("PRAGMA busy_timeout").fetchone()[0]
assert timeout == 5000
pool.close_connection()
def test_pragmas_apply_per_connection(self, tmp_path):
"""Pragmas set on one thread's connection are independent of another's."""
pool = ConnectionPool(tmp_path / "test.db")
conn_main = pool.get_connection()
conn_main.execute("PRAGMA cache_size=9999")
other_cache = []
def check_pragma():
conn = pool.get_connection()
# Don't set cache_size — should get the default, not 9999
val = conn.execute("PRAGMA cache_size").fetchone()[0]
other_cache.append(val)
pool.close_connection()
t = threading.Thread(target=check_pragma)
t.start()
t.join()
# Other thread's connection should NOT have our custom cache_size
assert other_cache[0] != 9999
pool.close_connection()
def test_session_pragma_resets_on_new_connection(self, tmp_path):
"""Session-level pragmas (cache_size) reset on a new connection."""
pool = ConnectionPool(tmp_path / "test.db")
conn1 = pool.get_connection()
conn1.execute("PRAGMA cache_size=9999")
assert conn1.execute("PRAGMA cache_size").fetchone()[0] == 9999
pool.close_connection()
conn2 = pool.get_connection()
cache = conn2.execute("PRAGMA cache_size").fetchone()[0]
# New connection gets default cache_size, not the previous value
assert cache != 9999
pool.close_connection()
def test_wal_mode_via_context_manager(self, tmp_path):
"""WAL mode can be set within a context manager block."""
pool = ConnectionPool(tmp_path / "test.db")
with pool.connection() as conn:
conn.execute("PRAGMA journal_mode=WAL")
mode = conn.execute("PRAGMA journal_mode").fetchone()[0]
assert mode == "wal"
class TestIntegration:
"""Integration tests for real-world usage patterns."""

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@@ -0,0 +1,158 @@
"""Unit tests for the web_fetch tool in timmy.tools."""
from __future__ import annotations
from unittest.mock import MagicMock, patch
from timmy.tools import web_fetch
class TestWebFetch:
"""Tests for web_fetch function."""
def test_invalid_url_no_scheme(self):
"""URLs without http(s) scheme are rejected."""
result = web_fetch("example.com")
assert "Error: invalid URL" in result
def test_invalid_url_empty(self):
"""Empty URL is rejected."""
result = web_fetch("")
assert "Error: invalid URL" in result
def test_invalid_url_ftp(self):
"""Non-HTTP schemes are rejected."""
result = web_fetch("ftp://example.com")
assert "Error: invalid URL" in result
@patch("timmy.tools.trafilatura", create=True)
@patch("timmy.tools._requests", create=True)
def test_successful_fetch(self, mock_requests, mock_trafilatura):
"""Happy path: fetch + extract returns text."""
# We need to patch at import level inside the function
mock_resp = MagicMock()
mock_resp.text = "<html><body><p>Hello world</p></body></html>"
with patch.dict(
"sys.modules", {"requests": mock_requests, "trafilatura": mock_trafilatura}
):
mock_requests.get.return_value = mock_resp
mock_requests.exceptions = _make_exceptions()
mock_trafilatura.extract.return_value = "Hello world"
result = web_fetch("https://example.com")
assert result == "Hello world"
@patch.dict("sys.modules", {"requests": MagicMock(), "trafilatura": MagicMock()})
def test_truncation(self):
"""Long text is truncated to max_tokens * 4 chars."""
import sys
mock_trafilatura = sys.modules["trafilatura"]
mock_requests = sys.modules["requests"]
long_text = "a" * 20000
mock_resp = MagicMock()
mock_resp.text = "<html><body>" + long_text + "</body></html>"
mock_requests.get.return_value = mock_resp
mock_requests.exceptions = _make_exceptions()
mock_trafilatura.extract.return_value = long_text
result = web_fetch("https://example.com", max_tokens=100)
# 100 tokens * 4 chars = 400 chars max
assert len(result) < 500
assert "[…truncated" in result
@patch.dict("sys.modules", {"requests": MagicMock(), "trafilatura": MagicMock()})
def test_extraction_failure(self):
"""Returns error when trafilatura can't extract text."""
import sys
mock_trafilatura = sys.modules["trafilatura"]
mock_requests = sys.modules["requests"]
mock_resp = MagicMock()
mock_resp.text = "<html></html>"
mock_requests.get.return_value = mock_resp
mock_requests.exceptions = _make_exceptions()
mock_trafilatura.extract.return_value = None
result = web_fetch("https://example.com")
assert "Error: could not extract" in result
@patch.dict("sys.modules", {"trafilatura": MagicMock()})
def test_timeout(self):
"""Timeout errors are handled gracefully."""
mock_requests = MagicMock()
exc_mod = _make_exceptions()
mock_requests.exceptions = exc_mod
mock_requests.get.side_effect = exc_mod.Timeout("timed out")
with patch.dict("sys.modules", {"requests": mock_requests}):
result = web_fetch("https://example.com")
assert "timed out" in result
@patch.dict("sys.modules", {"trafilatura": MagicMock()})
def test_http_error(self):
"""HTTP errors (404, 500, etc.) are handled gracefully."""
mock_requests = MagicMock()
exc_mod = _make_exceptions()
mock_requests.exceptions = exc_mod
mock_response = MagicMock()
mock_response.status_code = 404
mock_requests.get.return_value.raise_for_status.side_effect = exc_mod.HTTPError(
response=mock_response
)
with patch.dict("sys.modules", {"requests": mock_requests}):
result = web_fetch("https://example.com/nope")
assert "404" in result
def test_missing_requests(self):
"""Graceful error when requests not installed."""
with patch.dict("sys.modules", {"requests": None}):
result = web_fetch("https://example.com")
assert "requests" in result and "not installed" in result
def test_missing_trafilatura(self):
"""Graceful error when trafilatura not installed."""
mock_requests = MagicMock()
with patch.dict("sys.modules", {"requests": mock_requests, "trafilatura": None}):
result = web_fetch("https://example.com")
assert "trafilatura" in result and "not installed" in result
def test_catalog_entry_exists(self):
"""web_fetch should appear in the tool catalog."""
from timmy.tools import get_all_available_tools
catalog = get_all_available_tools()
assert "web_fetch" in catalog
assert "orchestrator" in catalog["web_fetch"]["available_in"]
def _make_exceptions():
"""Create a mock exceptions module with real exception classes."""
class Timeout(Exception):
pass
class HTTPError(Exception):
def __init__(self, *args, response=None, **kwargs):
super().__init__(*args, **kwargs)
self.response = response
class RequestException(Exception):
pass
mod = MagicMock()
mod.Timeout = Timeout
mod.HTTPError = HTTPError
mod.RequestException = RequestException
return mod