debug: log full transcript content for debugging

Add comprehensive logging to see exact LLM context during synthesis:
- Log full evidence content in answer_node (before synthesis)
- Log full system + user prompts in synthesize_answer_hf
- Helps debug why LLM says "Unable to answer" despite having transcript

Co-Authored-By: Claude <noreply@anthropic.com>

WORKSPACE.md

@@ -0,0 +1,67 @@
+2026-01-13 02:26:34,425 - src.agent.graph - INFO - [plan_node] ========== PLAN NODE START ==========
+2026-01-13 02:26:34,426 - src.agent.graph - INFO - [plan_node] Question: In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?
+2026-01-13 02:26:34,426 - src.agent.graph - INFO - [plan_node] File paths: None
+2026-01-13 02:26:34,426 - src.agent.graph - INFO - [plan_node] Available tools: ['web_search', 'parse_file', 'calculator', 'vision', 'youtube_transcript', 'transcribe_audio']
+2026-01-13 02:26:34,427 - src.agent.graph - INFO - [plan_node] Calling plan_question() with LLM...
+2026-01-13 02:26:34,428 - src.agent.llm_client - INFO - [plan_question] Using provider: huggingface
+2026-01-13 02:26:34,428 - src.agent.llm_client - INFO - Initializing HuggingFace Inference client with model: Qwen/Qwen2.5-72B-Instruct
+2026-01-13 02:26:34,428 - src.agent.llm_client - INFO - [plan_question_hf] Calling HuggingFace (Qwen/Qwen2.5-72B-Instruct) for planning
+GAIAAgent processing question (first 50 chars): In the video https://www.youtube.com/watch?v=L1vXC...
+2026-01-13 02:26:42,895 - httpx - INFO - HTTP Request: POST https://router.huggingface.co/v1/chat/completions "HTTP/1.1 200 OK"
+2026-01-13 02:26:42,898 - src.agent.llm_client - INFO - [plan_question_hf] Generated plan (660 chars)
+2026-01-13 02:26:42,898 - src.agent.graph - INFO - [plan_node] ✓ Plan created successfully (660 chars)
+2026-01-13 02:26:42,899 - src.agent.graph - INFO - [plan_node] ========== PLAN NODE END ==========
+2026-01-13 02:26:42,900 - src.agent.graph - INFO - [execute_node] ========== EXECUTE NODE START ==========
+2026-01-13 02:26:42,900 - src.agent.graph - INFO - [execute_node] Plan: 1. Use the `youtube_transcript` tool to extract the transcript from the provided YouTube video URL (https://www.youtube.com/watch?v=L1vXCYZAYYM). 2. Review the extracted transcript to identify any mentions of the number of bird species seen simultaneously in the video. 3. If the transcript does not provide the specific information, use the `web_search` tool to search for any reviews, summaries, or analyses of the video that might mention the highest number of bird species seen at once. 4. If the information is still not available, note that the question cannot be answered with the available tools and may require direct observation of the video content.
+2026-01-13 02:26:42,900 - src.agent.graph - INFO - [execute_node] Question: In the video https://www.youtube.com/watch?v=L1vXCYZAYYM, what is the highest number of bird species to be on camera simultaneously?
+2026-01-13 02:26:42,901 - src.agent.graph - INFO - [execute_node] Calling select_tools_with_function_calling()...
+2026-01-13 02:26:42,901 - src.agent.llm_client - INFO - [select_tools] Using provider: huggingface
+2026-01-13 02:26:42,902 - src.agent.llm_client - INFO - Initializing HuggingFace Inference client with model: Qwen/Qwen2.5-72B-Instruct
+2026-01-13 02:26:42,902 - src.agent.llm_client - INFO - [select_tools_hf] Calling HuggingFace with function calling for 6 tools, file_paths=None
+2026-01-13 02:26:44,769 - httpx - INFO - HTTP Request: POST https://router.huggingface.co/v1/chat/completions "HTTP/1.1 200 OK"
+2026-01-13 02:26:44,771 - src.agent.llm_client - INFO - [select_tools_hf] HuggingFace selected 1 tool(s)
+2026-01-13 02:26:44,771 - src.agent.graph - INFO - [execute_node] ✓ LLM selected 1 tool(s)
+2026-01-13 02:26:44,772 - src.agent.graph - INFO - [execute_node] --- Tool 1/1: youtube_transcript ---
+2026-01-13 02:26:44,772 - src.agent.graph - INFO - [execute_node] Parameters: {'url': 'https://www.youtube.com/watch?v=L1vXCYZAYYM'}
+2026-01-13 02:26:44,773 - src.agent.graph - INFO - [execute_node] Executing youtube_transcript...
+2026-01-13 02:26:44,774 - src.tools.youtube - INFO - Processing YouTube video: L1vXCYZAYYM
+2026-01-13 02:26:44,784 - src.tools.youtube - INFO - Fetching transcript for video: L1vXCYZAYYM
+2026-01-13 02:26:45,466 - src.tools.youtube - ERROR - YouTube transcript API failed:
+Could not retrieve a transcript for the video https://www.youtube.com/watch?v=L1vXCYZAYYM! This is most likely caused by:
+
+Subtitles are disabled for this video
+
+If you are sure that the described cause is not responsible for this error and that a transcript should be retrievable, please create an issue at https://github.com/jdepoix/youtube-transcript-api/issues. Please add which version of youtube_transcript_api you are using and provide the information needed to replicate the error. Also make sure that there are no open issues which already describe your problem!
+2026-01-13 02:26:45,470 - src.tools.youtube - INFO - Transcript API failed, trying audio transcription...
+2026-01-13 02:26:45,525 - src.tools.youtube - INFO - Downloading audio from: https://www.youtube.com/watch?v=L1vXCYZAYYM
+
+2026-01-13 02:26:48,123 - src.tools.youtube - INFO - Audio downloaded: /var/folders/05/8vqqybgj751**dmlh3w536dh0000gn/T/youtube_audio_28749.mp3 (1930412 bytes)
+2026-01-13 02:26:48,123 - src.tools.audio - INFO - Transcribing audio: /var/folders/05/8vqqybgj751**dmlh3w536dh0000gn/T/youtube_audio_28749.mp3
+2026-01-13 02:26:48,354 - src.tools.audio - INFO - Loading Whisper model: small
+100%|███████████████████████████████████████| 461M/461M [00:07<00:00, 67.9MiB/s]
+2026-01-13 02:26:57,343 - src.tools.audio - INFO - Whisper model loaded on cpu
+2026-01-13 02:27:04,275 - src.tools.audio - INFO - Transcription successful: 738 characters
+2026-01-13 02:27:04,276 - src.tools.youtube - INFO - Cleaned up temp file: /var/folders/05/8vqqybgj751**dmlh3w536dh0000gn/T/youtube_audio_28749.mp3
+2026-01-13 02:27:04,276 - src.tools.youtube - INFO - Transcript retrieved via Whisper: 738 characters
+2026-01-13 02:27:04,276 - src.agent.graph - INFO - [execute_node] ✓ youtube_transcript completed successfully
+2026-01-13 02:27:04,277 - src.agent.graph - INFO - [execute_node] Summary: 1 tool(s) executed, 1 evidence items collected
+2026-01-13 02:27:04,277 - src.agent.graph - INFO - [execute_node] ========== EXECUTE NODE END ==========
+2026-01-13 02:27:04,277 - src.agent.graph - INFO - [answer_node] ========== ANSWER NODE START ==========
+2026-01-13 02:27:04,278 - src.agent.graph - INFO - [answer_node] Evidence items collected: 1
+2026-01-13 02:27:04,278 - src.agent.graph - INFO - [answer_node] Errors accumulated: 0
+2026-01-13 02:27:04,278 - src.agent.graph - INFO - [answer_node] Calling synthesize_answer() with 1 evidence items...
+2026-01-13 02:27:04,278 - src.agent.llm_client - INFO - [synthesize_answer] Using provider: huggingface
+2026-01-13 02:27:04,278 - src.agent.llm_client - INFO - Initializing HuggingFace Inference client with model: Qwen/Qwen2.5-72B-Instruct
+2026-01-13 02:27:04,278 - src.agent.llm_client - INFO - [synthesize_answer_hf] Calling HuggingFace for answer synthesis
+2026-01-13 02:27:05,281 - httpx - INFO - HTTP Request: POST https://router.huggingface.co/v1/chat/completions "HTTP/1.1 200 OK"
+2026-01-13 02:27:05,283 - src.agent.llm_client - INFO - [synthesize_answer_hf] Generated answer: Unable to answer
+2026-01-13 02:27:05,284 - src.agent.graph - INFO - [answer_node] ✓ Answer generated successfully: Unable to answer
+2026-01-13 02:27:05,284 - src.agent.graph - INFO - [answer_node] ========== ANSWER NODE END ==========
+2026-01-13 02:27:05,285 - **main** - INFO - [1/1] Completed a1e91b78
+2026-01-13 02:27:05,286 - **main** - INFO - Progress: 1/1 questions processed
+GAIAAgent returning answer: Unable to answer
+Agent finished. Submitting 1 answers for user 'mangubee'...
+Submitting 1 answers to: https://agents-course-unit4-scoring.hf.space/submit
+2026-01-13 02:27:06,261 - **main** - INFO - Total execution time: 34.76 seconds (0m 34s)
+2026-01-13 02:27:06,266 - **main\_\_ - INFO - Results exported to: /Users/mangubee/Documents/Python/16_HuggingFace/Final_Assignment_Template/\_cache/gaia_results_20260113_022706.json
+Submission successful.

src/agent/graph.py

@@ -483,8 +483,24 @@ def answer_node(state: AgentState) -> AgentState:
     """
     logger.info(f"[answer_node] ========== ANSWER NODE START ==========")
     logger.info(f"[answer_node] Evidence items collected: {len(state['evidence'])}")
-    logger.debug(f"[answer_node] Evidence: {state['evidence']}")
     logger.info(f"[answer_node] Errors accumulated: {len(state['errors'])}")
+
+    # ============================================================================
+    # FULL EVIDENCE LOGGING - Debug what evidence is being passed to synthesis
+    # ============================================================================
+    logger.info("=" * 80)
+    logger.info("[EVIDENCE] Full evidence content being passed to synthesis:")
+    logger.info("=" * 80)
+    for i, ev in enumerate(state['evidence']):
+        logger.info(f"[EVIDENCE {i+1}/{len(state['evidence'])}]")
+        logger.info(f"{ev[:500]}..." if len(ev) > 500 else f"{ev}")
+        logger.info("-" * 80)
+    logger.info("=" * 80)
+    logger.info("[EVIDENCE] End of evidence content")
+    logger.info("=" * 80)
+    # ============================================================================
+
+    logger.debug(f"[answer_node] Evidence: {state['evidence']}")
     if state["errors"]:
         logger.warning(f"[answer_node] Error list: {state['errors']}")
 

src/agent/llm_client.py

@@ -1114,6 +1114,20 @@ Extract the factoid answer from the evidence above. Return only the factoid, not
         {"role": "user", "content": user_prompt},
     ]
 
+    # ============================================================================
+    # FULL CONTEXT LOGGING - Debug LLM synthesis failures
+    # ============================================================================
+    logger.info("=" * 80)
+    logger.info("[LLM CONTEXT] Full synthesis prompt being sent to LLM:")
+    logger.info("=" * 80)
+    logger.info(f"[SYSTEM PROMPT]\n{system_prompt}")
+    logger.info("-" * 80)
+    logger.info(f"[USER PROMPT]\n{user_prompt}")
+    logger.info("=" * 80)
+    logger.info("[LLM CONTEXT] End of full context")
+    logger.info("=" * 80)
+    # ============================================================================
+
     response = client.chat_completion(
         messages=messages,
         max_tokens=256,  # Factoid answers are short