16.12.2025 - project analysis

CHANGELOG.md

@@ -0,0 +1,22 @@
+# Session Changelog
+
+**Session Date:** [YYYY-MM-DD]
+**Dev Record:** [link to dev/dev_YYMMDD_##_concise_title.md]
+
+## Changes Made
+
+### Created Files
+
+- [file path] - [Purpose/description]
+
+### Modified Files
+
+- [file path] - [What was changed]
+
+### Deleted Files
+
+- [file path] - [Reason for deletion]
+
+## Notes
+
+[Any additional context about the session's work]

CLAUDE.md

@@ -0,0 +1,4 @@
+# Project-Specific Instructions
+
+[Leave empty unless project requires special behavior]
+[Inherits all rules from ~/.claude/CLAUDE.md]

PLAN.md

@@ -0,0 +1,25 @@
+# Implementation Plan
+
+**Date:** [YYYY-MM-DD]
+**Dev Record:** [link to dev/dev_YYMMDD_##_concise_title.md]
+**Status:** [Planning | In Progress | Completed]
+
+## Objective
+
+[Clear goal statement from task description]
+
+## Steps
+
+1. [Step 1]
+2. [Step 2]
+3. [Step 3]
+
+## Files to Modify
+
+- [file1.py]
+- [file2.md]
+
+## Success Criteria
+
+- [ ] [Criterion 1]
+- [ ] [Criterion 2]

README.md

@@ -12,4 +12,243 @@ hf_oauth: true
 hf_oauth_expiration_minutes: 480
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+Check out the configuration reference at <https://huggingface.co/docs/hub/spaces-config-reference>
+
+## Project Overview
+
+**Project Name:** Final_Assignment_Template
+
+**Purpose:** Course assignment template for building an AI agent that passes the GAIA benchmark (General AI Assistants). This project serves as a learning-focused workspace to support iterative agent development and experimentation.
+
+**Target Users:** Students learning agent development through hands-on implementation
+
+**Key Objectives:**
+
+- Build production-ready code that passes GAIA test requirements
+- Learn agent development through discovery-based implementation
+- Develop systematic approach to complex AI task solving
+- Document learning process and key decisions
+
+## Project Architecture
+
+**Technology Stack:**
+
+- Platform: Hugging Face Spaces with OAuth integration
+- Framework: Gradio (UI), Requests (API communication)
+- Language: Python 3.x
+
+**Project Structure:**
+
+```
+Final_Assignment_Template/
+├── archive/         # Reference materials, previous solutions, static resources
+├── input/           # Input files, configuration, raw data
+├── output/          # Generated files, results, processed data
+├── test/            # Testing files, test scripts, development records
+├── dev/             # Development records (permanent knowledge packages)
+├── app.py           # Main application file with BasicAgent and Gradio UI
+├── requirements.txt # Python dependencies
+├── README.md        # Project overview, architecture, workflow, specification
+├── CLAUDE.md        # Project-specific AI instructions
+├── PLAN.md          # Active implementation plan (temporary workspace)
+├── TODO.md          # Active task tracking (temporary workspace)
+└── CHANGELOG.md     # Session changelog (temporary workspace)
+```
+
+**Core Components:**
+
+- BasicAgent class: Student-customizable template for agent logic implementation
+- run_and_submit_all function: Evaluation orchestration (question fetching, submission, scoring)
+- Gradio UI: Login button + evaluation trigger + results display
+- API integration: Connection to external scoring service
+
+**System Architecture Diagram:**
+
+```mermaid
+---
+config:
+  layout: elk
+---
+graph TB
+    subgraph "Student Development"
+        BasicAgent[BasicAgent Class<br/>__call__ method<br/>Custom logic here]
+    end
+
+    subgraph "Provided Infrastructure"
+        GradioUI[Gradio UI<br/>Login + Run Button<br/>Results Display]
+        Orchestrator[run_and_submit_all Function<br/>Workflow orchestration]
+        OAuth[HF OAuth<br/>User authentication]
+    end
+
+    subgraph "External Services"
+        API[Scoring API<br/>agents-course-unit4-scoring.hf.space]
+        QEndpoint["/questions endpoint"]
+        SEndpoint["/submit endpoint"]
+    end
+
+    subgraph "HF Space Environment"
+        EnvVars[Environment Variables<br/>SPACE_ID, SPACE_HOST]
+    end
+
+    GradioUI --> OAuth
+    OAuth -->|Authenticated| Orchestrator
+    Orchestrator --> QEndpoint
+    QEndpoint -->|GAIA questions| Orchestrator
+    Orchestrator -->|For each question| BasicAgent
+    BasicAgent -->|Answer| Orchestrator
+    Orchestrator -->|All answers| SEndpoint
+    SEndpoint -->|Score & results| Orchestrator
+    Orchestrator --> GradioUI
+    EnvVars -.->|Used by| Orchestrator
+
+    style BasicAgent fill:#ffcccc
+    style GradioUI fill:#cce5ff
+    style Orchestrator fill:#cce5ff
+    style API fill:#d9f2d9
+```
+
+## Project Specification
+
+**Project Context:**
+
+This is a course assignment template for building an AI agent that passes the GAIA benchmark (General AI Assistants). The project was recently started as a learning-focused workspace to support iterative agent development and experimentation.
+
+**Current State:**
+
+- **Status:** Early development phase (within first week)
+- **Purpose:** Build production-ready code that passes GAIA test requirements
+- **Learning Objective:** Discovery-based development where students design and implement agent capabilities themselves
+
+**Data & Workflows:**
+
+- **Input Data:** GAIA test questions fetched from external scoring API (`agents-course-unit4-scoring.hf.space`)
+- **Processing:** BasicAgent class processes questions and generates answers
+- **Output:** Agent responses submitted to scoring endpoint for evaluation
+- **Development Workflow:**
+  1. Local development and testing
+  2. Deploy to Hugging Face Space
+  3. Submit via integrated evaluation UI
+
+**User Workflow Diagram:**
+
+```mermaid
+---
+config:
+  layout: fixed
+---
+flowchart TB
+    Start(["Student starts assignment"]) --> Clone["Clone HF Space template"]
+    Clone --> LocalDev["Local development:<br>Implement BasicAgent logic"]
+    LocalDev --> LocalTest{"Test locally?"}
+    LocalTest -- Yes --> RunLocal["Run app locally"]
+    RunLocal --> Debug{"Works?"}
+    Debug -- No --> LocalDev
+    Debug -- Yes --> Deploy["Deploy to HF Space"]
+    LocalTest -- Skip --> Deploy
+    Deploy --> Login["Login with HF OAuth"]
+    Login --> RunEval@{ label: "Click 'Run Evaluation'<br>button in UI" }
+    RunEval --> FetchQ["System fetches GAIA<br>questions from API"]
+    FetchQ --> RunAgent["Agent processes<br>each question"]
+    RunAgent --> Submit["Submit answers<br>to scoring API"]
+    Submit --> Display["Display score<br>and results"]
+    Display --> Iterate{"Satisfied with<br>score?"}
+    Iterate -- "No - improve agent" --> LocalDev
+    Iterate -- Yes --> Complete(["Assignment complete"])
+
+    RunEval@{ shape: rect}
+    style Start fill:#e1f5e1
+    style LocalDev fill:#fff4e1
+    style Deploy fill:#e1f0ff
+    style RunAgent fill:#ffe1f0
+    style Complete fill:#e1f5e1
+```
+
+**Technical Architecture:**
+
+- **Platform:** Hugging Face Spaces with OAuth integration
+- **Framework:** Gradio for UI, Requests for API communication
+- **Core Component:** BasicAgent class (student-customizable template)
+- **Evaluation Infrastructure:** Pre-built orchestration (question fetching, submission, scoring display)
+- **Deployment:** HF Space with environment variables (SPACE_ID, SPACE_HOST)
+
+**Requirements & Constraints:**
+
+- **Constraint Type:** Minimal at current stage
+- **Infrastructure:** Must run on Hugging Face Spaces platform
+- **Integration:** Fixed scoring API endpoints (cannot modify evaluation system)
+- **Flexibility:** Students have full freedom to design agent capabilities
+
+**Integration Points:**
+
+- **External API:** `https://agents-course-unit4-scoring.hf.space`
+  - `/questions` endpoint: Fetch GAIA test questions
+  - `/submit` endpoint: Submit answers and receive scores
+- **Authentication:** Hugging Face OAuth for student identification
+- **Deployment:** HF Space runtime environment variables
+
+**Development Goals:**
+
+- **Primary:** Organized development environment supporting iterative experimentation
+- **Focus:** Learning process - students discover optimal approaches through implementation
+- **Structure:** Workspace that tracks experiments, tests, and development progress
+- **Documentation:** Capture decisions and learnings throughout development cycle
+
+## Workflow
+
+### Dev Record Workflow
+
+**Philosophy:** Dev records are the single source of truth. CHANGELOG/PLAN/TODO are temporary workspace files.
+
+**Dev Record Types:**
+
+- 🐞 **Issue:** Problem-solving, bug fixes, error resolution
+- 🔨 **Development:** Feature development, enhancements, new functionality
+
+### Session Start Workflow
+
+#### Phase 1: Planning (Explicit)
+
+1. **Create or identify dev record:** `dev/dev_YYMMDD_##_concise_title.md`
+   - Choose type: 🐞 Issue or 🔨 Development
+2. **Create PLAN.md ONLY:** Use `/plan` command or write directly
+   - Document implementation approach, steps, files to modify
+   - DO NOT create TODO.md or CHANGELOG.md yet
+
+#### Phase 2: Development (Automatic)
+
+3. **Create TODO.md:** Automatically populate as you start implementing
+   - Track tasks in real-time using TodoWrite tool
+   - Mark in_progress/completed as you work
+4. **Create CHANGELOG.md:** Automatically populate as you make changes
+   - Record file modifications/creations/deletions as they happen
+5. **Work on solution:** Update all three files during development
+
+### Session End Workflow
+
+#### Phase 3: Completion (Manual)
+
+After AI completes all work and updates PLAN/TODO/CHANGELOG:
+
+- AI stops and waits for user review (Checkpoint 3)
+- User reviews PLAN.md, TODO.md, and CHANGELOG.md
+- User manually runs `/update-dev dev_YYMMDD_##` when satisfied
+
+When /update-dev runs:
+
+1. Distills PLAN decisions → dev record "Key Decisions" section
+2. Distills TODO deliverables → dev record "Outcome" section
+3. Distills CHANGELOG changes → dev record "Changelog" section
+4. Empties PLAN.md, TODO.md, CHANGELOG.md back to templates
+5. Marks dev record status as ✅ Resolved
+
+### AI Context Loading
+
+**When new AI session starts:**
+
+- Read last 2-3 dev records for recent context (NOT CHANGELOG)
+  - Dev records sorted by date: newest `dev_YYMMDD_##_title.md` files first
+- Read README.md for project structure
+- Read CLAUDE.md for coding standards
+- Check PLAN.md/TODO.md for active work (if any)
+
+**Do NOT read entire CHANGELOG for context** - it's a temporary workspace, not a historical record.

TODO.md

@@ -0,0 +1,14 @@
+# TODO List
+
+**Session Date:** [YYYY-MM-DD]
+**Dev Record:** [link to dev/dev_YYMMDD_##_concise_title.md]
+
+## Active Tasks
+
+- [ ] [Task 1]
+- [ ] [Task 2]
+- [ ] [Task 3]
+
+## Completed Tasks
+
+- [x] [Completed task 1]

app.py

@@ -8,27 +8,30 @@ import pandas as pd
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
+
 # --- Basic Agent Definition ---
 # ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 class BasicAgent:
     def __init__(self):
         print("BasicAgent initialized.")
+
     def __call__(self, question: str) -> str:
         print(f"Agent received question (first 50 chars): {question[:50]}...")
         fixed_answer = "This is a default answer."
         print(f"Agent returning fixed answer: {fixed_answer}")
         return fixed_answer
 
-def run_and_submit_all( profile: gr.OAuthProfile | None):
+
+def run_and_submit_all(profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID")  # Get the SPACE_ID for sending link to the code
 
     if profile:
-        username= f"{profile.username}"
+        username = f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -55,16 +58,16 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
         response.raise_for_status()
         questions_data = response.json()
         if not questions_data:
-             print("Fetched questions list is empty.")
-             return "Fetched questions list is empty or invalid format.", None
+            print("Fetched questions list is empty.")
+            return "Fetched questions list is empty or invalid format.", None
         print(f"Fetched {len(questions_data)} questions.")
     except requests.exceptions.RequestException as e:
         print(f"Error fetching questions: {e}")
         return f"Error fetching questions: {e}", None
     except requests.exceptions.JSONDecodeError as e:
-         print(f"Error decoding JSON response from questions endpoint: {e}")
-         print(f"Response text: {response.text[:500]}")
-         return f"Error decoding server response for questions: {e}", None
+        print(f"Error decoding JSON response from questions endpoint: {e}")
+        print(f"Response text: {response.text[:500]}")
+        return f"Error decoding server response for questions: {e}", None
     except Exception as e:
         print(f"An unexpected error occurred fetching questions: {e}")
         return f"An unexpected error occurred fetching questions: {e}", None
@@ -81,18 +84,36 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             continue
         try:
             submitted_answer = agent(question_text)
-            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
-            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+            answers_payload.append(
+                {"task_id": task_id, "submitted_answer": submitted_answer}
+            )
+            results_log.append(
+                {
+                    "Task ID": task_id,
+                    "Question": question_text,
+                    "Submitted Answer": submitted_answer,
+                }
+            )
         except Exception as e:
-             print(f"Error running agent on task {task_id}: {e}")
-             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
+            print(f"Error running agent on task {task_id}: {e}")
+            results_log.append(
+                {
+                    "Task ID": task_id,
+                    "Question": question_text,
+                    "Submitted Answer": f"AGENT ERROR: {e}",
+                }
+            )
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission 
-    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
+    # 4. Prepare Submission
+    submission_data = {
+        "username": username.strip(),
+        "agent_code": agent_code,
+        "answers": answers_payload,
+    }
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
@@ -162,20 +183,19 @@ with gr.Blocks() as demo:
 
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
-    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
+    status_output = gr.Textbox(
+        label="Run Status / Submission Result", lines=5, interactive=False
+    )
     # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
-    run_button.click(
-        fn=run_and_submit_all,
-        outputs=[status_output, results_table]
-    )
+    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
 
 if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
+    print("\n" + "-" * 30 + " App Starting " + "-" * 30)
     # Check for SPACE_HOST and SPACE_ID at startup for information
     space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
+    space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -183,14 +203,18 @@ if __name__ == "__main__":
     else:
         print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup: # Print repo URLs if SPACE_ID is found
+    if space_id_startup:  # Print repo URLs if SPACE_ID is found
         print(f"✅ SPACE_ID found: {space_id_startup}")
         print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
+        print(
+            f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
+        )
     else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
+        print(
+            "ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
+        )
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
+    print("-" * (60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+    demo.launch(debug=True, share=False)

requirements.txt

@@ -1,2 +1,3 @@
 gradio
+gradio[oauth]
 requests