test: implement unit tests for knowledge-space api logic #63

[ulekarsiddhant0-boop]

This PR addresses Issue #63 by implementing a comprehensive testing suite for the KnowledgeSpace API backend. It ensures that the data retrieval and formatting logic are reliable and handles edge cases appropriately.

Key Changes was :
1]Testing Infrastructure: Added init.py files to the backend/ and tests/ directories to enable standard Python module discovery.

2]API Mocking: Utilized pytest-mock to simulate external API responses from api.knowledge-space.org. This allows tests to run without an internet connection and prevents hitting rate limits.

3]Data Validation: Added unit tests for format_datasets_list and list_datasources to verify that JSON responses are correctly parsed into human-readable strings.

4]Edge Case Handling: Added a specific test case for empty search results to ensure the system returns a graceful "No datasets found" message rather than crashing.

Verification Results:
I have verified the changes locally using the following command:
python -m pytest tests/

Result: 3 passed in 0.14s

[ulekarsiddhant0-boop]

[SandeepChauhan00]

Nice work on the KS API tests @ulekarsiddhant0-boop! These complement my PR #64 well — my tests cover the API endpoints (health, chat, session reset) while yours cover the internal KS API logic.

One suggestion: it might be cleaner to place the tests inside backend/tests/ (same directory structure as PR #64) rather than a separate tests/ folder, so all backend tests stay together. That way both PRs can coexist once merged.