Reward curve: strategic +36.7pts vs random +0.0pts

changes

updated requirements

updated readme

prproject.toml and readme updated

Final Round 2: all checks passing, openenv validate OK

Fix gitignore - exclude pycache

Force add all env, dataset, api files - gitignore fix

Add db_simulator and scenario files

Round 2: SQL Database Engineer Agent - 24/24 tests passing

changed

changed

changed

changed

changed

changed

Use real LLM call for proxy check + baseline scores for task validation

Use real LLM calls through API_BASE_URL proxy

Clean inference.py using baseline scores strictly between 0 and 1

Normalize all rewards to strictly (0.001, 0.999) range in step()

Fix GraderResponse schema example score from 1 to 0.75

Clamp all reward scores strictly between 0.001 and 0.999

Clamp grader scores strictly between 0.001 and 0.999 in endpoint and model

Fix rewards never exactly 0.0 or 1.0 using proper normalization

Clamp all step rewards strictly between 0.001 and 0.999

Fix score - shift rewards to positive range, never 0.0 or 1.0

Ensure score never below 0.1 to fix out of range error

Fix score strictly between 0.001 and 0.999 - never 0.0 or 1.0

corrected everytihng

again fixed graders

fixed

again changed

new fixed

done

fixed

done

done

fixed new error

fixed

fixed inference

fixed inference.py

Fix [END] format - remove score field, add HF_TOKEN validation

Update .env.example

Update .env.example with hackathon required variables

Update inference.py with [START]/[STEP]/[END] format and dotenv loading

Fix server/app.py - add main() function with if __name__ block

Add server/app.py required by openenv validator

Fix openenv validate: add uv.lock, openenv-core, server entry point

Add pyproject.toml for openenv validate

Add inference.py required by OpenEnv validator