HuggingMes sync [r-louissoume-huggingmes-dx429e5k-01cd1-nxm6w] 2026-05-11T08:47:47Z

.skills_prompt_snapshot.json

@@ -2,475 +2,475 @@
   "version": 1,
   "manifest": {
     "apple/apple-notes/SKILL.md": [
-      1778488086546281705,
+      1778486749846642088,
       2169
     ],
     "apple/apple-reminders/SKILL.md": [
-      1778488086556281456,
+      1778486749876641258,
       2530
     ],
     "apple/findmy/SKILL.md": [
-      1778488086556281456,
+      1778486749856641811,
       3709
     ],
     "apple/imessage/SKILL.md": [
-      1778488086566281206,
+      1778486749866641535,
       2442
     ],
     "apple/macos-computer-use/SKILL.md": [
-      1778488086576280960,
+      1778486749976638496,
       7309
     ],
     "autonomous-ai-agents/claude-code/SKILL.md": [
-      1778488086616279967,
+      1778486749906640429,
       34288
     ],
     "autonomous-ai-agents/codex/SKILL.md": [
-      1778488086596280462,
+      1778486749916640153,
       4557
     ],
     "autonomous-ai-agents/hermes-agent/SKILL.md": [
-      1778488086626279717,
+      1778486749946639324,
       45630
     ],
     "autonomous-ai-agents/opencode/SKILL.md": [
-      1778488086606280216,
+      1778486750226631588,
       7259
     ],
     "creative/architecture-diagram/SKILL.md": [
-      1778488086626279717,
+      1778486749986638219,
       5830
     ],
     "creative/ascii-art/SKILL.md": [
-      1778488086726277236,
+      1778486750156633522,
       10556
     ],
     "creative/ascii-video/SKILL.md": [
-      1778488086656278975,
+      1778486750216631862,
       14864
     ],
     "creative/baoyu-comic/SKILL.md": [
-      1778488086726277236,
+      1778486750426626060,
       14621
     ],
     "creative/baoyu-infographic/SKILL.md": [
-      1778488087016270041,
+      1778486750996610312,
       10434
     ],
     "creative/claude-design/SKILL.md": [
-      1778488087406260363,
+      1778486751836587100,
       19859
     ],
     "creative/comfyui/SKILL.md": [
-      1778488087406260363,
+      1778486751856586550,
       23856
     ],
     "creative/creative-ideation/SKILL.md": [
-      1778488087736252173,
+      1778486752346573011,
       6318
     ],
     "creative/design-md/SKILL.md": [
-      1778488087766251428,
+      1778486752326573563,
       7023
     ],
     "creative/excalidraw/SKILL.md": [
-      1778488087756251678,
+      1778486752336573285,
       7300
     ],
     "creative/humanizer/SKILL.md": [
-      1778488087816250189,
+      1778486752526568037,
       30025
     ],
     "creative/manim-video/SKILL.md": [
-      1778488087816250189,
+      1778486752466569696,
       12023
     ],
     "creative/p5js/SKILL.md": [
-      1778488087986245968,
+      1778486752776561130,
       27494
     ],
     "creative/pixel-art/SKILL.md": [
-      1778488088076243737,
+      1778486753096552288,
       7581
     ],
     "creative/popular-web-designs/SKILL.md": [
-      1778488088156241752,
+      1778486753246548141,
       9722
     ],
     "creative/pretext/SKILL.md": [
-      1778488088566231578,
+      1778486754356517519,
       14168
     ],
     "creative/sketch/SKILL.md": [
-      1778488088576231329,
+      1778486754446515042,
       9304
     ],
     "creative/songwriting-and-ai-music/SKILL.md": [
-      1778488088576231329,
+      1778486754356517519,
       10206
     ],
     "creative/touchdesigner-mcp/SKILL.md": [
-      1778488088606230585,
+      1778486754366517244,
       15429
     ],
     "data-science/jupyter-live-kernel/SKILL.md": [
-      1778488088756226863,
+      1778486754806505132,
       5285
     ],
     "devops/kanban-orchestrator/SKILL.md": [
-      1778488088766226614,
+      1778486754786505685,
       13371
     ],
     "devops/kanban-worker/SKILL.md": [
-      1778488088776226364,
+      1778486754846504033,
       10030
     ],
     "devops/webhook-subscriptions/SKILL.md": [
-      1778488088786226118,
+      1778486754886502930,
       6836
     ],
     "dogfood/SKILL.md": [
-      1778488088816225374,
+      1778486754886502930,
       6270
     ],
     "email/himalaya/SKILL.md": [
-      1778488088826225124,
+      1778486755086497425,
       6902
     ],
     "gaming/minecraft-modpack-server/SKILL.md": [
-      1778488088906223140,
+      1778486755066497975,
       6559
     ],
     "gaming/pokemon-player/SKILL.md": [
-      1778488088866224133,
+      1778486754996499902,
       8709
     ],
     "github/codebase-inspection/SKILL.md": [
-      1778488088886223635,
+      1778486755236493298,
       3628
     ],
     "github/github-auth/SKILL.md": [
-      1778488088916222890,
+      1778486755086497425,
       7546
     ],
     "github/github-code-review/SKILL.md": [
-      1778488088916222890,
+      1778486755206494122,
       13565
     ],
     "github/github-issues/SKILL.md": [
-      1778488088916222890,
+      1778486755426488068,
       9265
     ],
     "github/github-pr-workflow/SKILL.md": [
-      1778488088996220905,
+      1778486755246493020,
       9985
     ],
     "github/github-repo-management/SKILL.md": [
-      1778488088976221404,
+      1778486755646482010,
       13683
     ],
     "mcp/native-mcp/SKILL.md": [
-      1778488089066219170,
+      1778486756286464393,
       12365
     ],
     "media/gif-search/SKILL.md": [
-      1778488089026220160,
+      1778486755656481735,
       2704
     ],
     "media/heartmula/SKILL.md": [
-      1778488089036219914,
+      1778486756106469348,
       6412
     ],
     "media/songsee/SKILL.md": [
-      1778488089046219664,
+      1778486755986472651,
       2336
     ],
     "media/spotify/SKILL.md": [
-      1778488089066219170,
+      1778486756216466320,
       6319
     ],
     "media/youtube-content/SKILL.md": [
-      1778488089056219418,
+      1778486755906474853,
       3218
     ],
     "mlops/evaluation/lm-evaluation-harness/SKILL.md": [
-      1778488089096218425,
+      1778486756056470725,
       12020
     ],
     "mlops/evaluation/weights-and-biases/SKILL.md": [
-      1778488089176216440,
+      1778486756186467146,
       12395
     ],
     "mlops/gemini-key-rotator/SKILL.md": [
-      1778488089156216935,
+      1778486756236465770,
       6256
     ],
     "mlops/huggingface-hub/SKILL.md": [
-      1778488089216215445,
+      1778486756266464946,
       3674
     ],
     "mlops/inference/llama-cpp/SKILL.md": [
-      1778488089206215695,
+      1778486756276464668,
       8880
     ],
     "mlops/inference/obliteratus/SKILL.md": [
-      1778488089236214950,
+      1778486756376461916,
       15464
     ],
     "mlops/inference/outlines/SKILL.md": [
-      1778488089446209740,
+      1778486756436460265,
       15803
     ],
     "mlops/inference/vllm/SKILL.md": [
-      1778488089306213214,
+      1778486756586456136,
       9071
     ],
     "mlops/models/audiocraft/SKILL.md": [
-      1778488089376211475,
+      1778486756656454211,
       16189
     ],
     "mlops/models/segment-anything/SKILL.md": [
-      1778488089436209989,
+      1778486756706452833,
       13372
     ],
     "mlops/research/dspy/SKILL.md": [
-      1778488089486208745,
+      1778486756846448981,
       15220
     ],
     "mlops/training/axolotl/SKILL.md": [
-      1778488089506208251,
+      1778486756796450354,
       4895
     ],
     "mlops/training/trl-fine-tuning/SKILL.md": [
-      1778488089576206514,
+      1778486756906447328,
       11971
     ],
     "mlops/training/unsloth/SKILL.md": [
-      1778488089606205770,
+      1778486757216438794,
       2272
     ],
     "note-taking/obsidian/SKILL.md": [
-      1778488089646204775,
+      1778486757256437693,
       2919
     ],
     "productivity/airtable/SKILL.md": [
-      1778488089676204031,
+      1778486757286436868,
       11302
     ],
     "productivity/google-workspace/SKILL.md": [
-      1778488089706203286,
+      1778486757306436316,
       13411
     ],
     "productivity/linear/SKILL.md": [
-      1778488089746202295,
+      1778486757326435766,
       14782
     ],
     "productivity/maps/SKILL.md": [
-      1778488089766201800,
+      1778486757386434114,
       6726
     ],
     "productivity/nano-pdf/SKILL.md": [
-      1778488089766201800,
+      1778486757406433564,
       1414
     ],
     "productivity/notion/SKILL.md": [
-      1778488089776201551,
+      1778486757396433839,
       5236
     ],
     "productivity/ocr-and-documents/SKILL.md": [
-      1778488089786201301,
+      1778486757446432463,
       5280
     ],
     "productivity/powerpoint/SKILL.md": [
-      1778488089816200556,
+      1778486757636427233,
       9298
     ],
     "productivity/teams-meeting-pipeline/SKILL.md": [
-      1778488090286188896,
+      1778486758266409894,
       6867
     ],
     "red-teaming/godmode/SKILL.md": [
-      1778488090296188647,
+      1778486758256410167,
       20059
     ],
     "research/arxiv/SKILL.md": [
-      1778488090356187156,
+      1778486758456404662,
       10085
     ],
     "research/blogwatcher/SKILL.md": [
-      1778488090366186910,
+      1778486758456404662,
       5111
     ],
     "research/llm-wiki/SKILL.md": [
-      1778488090376186662,
+      1778486758536402459,
       20113
     ],
     "research/polymarket/SKILL.md": [
-      1778488090376186662,
+      1778486758526402737,
       2985
     ],
     "research/research-paper-writing/SKILL.md": [
-      1778488090406185917,
+      1778486758566401634,
       103375
     ],
     "smart-home/openhue/SKILL.md": [
-      1778488090916173262,
+      1778486759546374659,
       2713
     ],
     "social-media/xurl/SKILL.md": [
-      1778488090936172766,
+      1778486759546374659,
       13993
     ],
     "software-development/debugging-hermes-tui-commands/SKILL.md": [
-      1778488090946172517,
+      1778486759586373557,
       7910
     ],
     "software-development/hermes-agent-skill-authoring/SKILL.md": [
-      1778488090946172517,
+      1778486759596373282,
       7618
     ],
     "software-development/node-inspect-debugger/SKILL.md": [
-      1778488090976171772,
+      1778486759596373282,
       10929
     ],
     "software-development/plan/SKILL.md": [
-      1778488090986171523,
+      1778486759626372458,
       2016
     ],
     "software-development/python-debugpy/SKILL.md": [
-      1778488090976171772,
+      1778486759666371355,
       13172
     ],
     "software-development/requesting-code-review/SKILL.md": [
-      1778488090976171772,
+      1778486759646371905,
       8483
     ],
     "software-development/spike/SKILL.md": [
-      1778488090996171277,
+      1778486759646371905,
       8753
     ],
     "software-development/subagent-driven-development/SKILL.md": [
-      1778488090996171277,
+      1778486759636372180,
       10742
     ],
     "software-development/systematic-debugging/SKILL.md": [
-      1778488091036170282,
+      1778486759676371080,
       10480
     ],
     "software-development/test-driven-development/SKILL.md": [
-      1778488091036170282,
+      1778486759716369979,
       9573
     ],
     "software-development/writing-plans/SKILL.md": [
-      1778488091046170036,
+      1778486759726369704,
       7229
     ],
     "yuanbao/SKILL.md": [
-      1778488091036170282,
+      1778486759746369154,
       3795
     ],
     "apple/DESCRIPTION.md": [
-      1778488086536281951,
+      1778486749776644022,
       152
     ],
     "autonomous-ai-agents/DESCRIPTION.md": [
-      1778488086576280960,
+      1778486749916640153,
       211
     ],
     "creative/DESCRIPTION.md": [
-      1778488086616279967,
+      1778486750096635180,
       116
     ],
     "data-science/DESCRIPTION.md": [
-      1778488088746227109,
+      1778486754746506783,
       137
     ],
     "diagramming/DESCRIPTION.md": [
-      1778488088796225870,
+      1778486754836504307,
       159
     ],
     "domain/DESCRIPTION.md": [
-      1778488088816225374,
+      1778486755136496048,
       1142
     ],
     "email/DESCRIPTION.md": [
-      1778488088806225620,
+      1778486754896502655,
       101
     ],
     "gaming/DESCRIPTION.md": [
-      1778488088856224379,
+      1778486755006499627,
       129
     ],
     "gifs/DESCRIPTION.md": [
-      1778488088856224379,
+      1778486755086497425,
       109
     ],
     "github/DESCRIPTION.md": [
-      1778488088876223885,
+      1778486755186494672,
       167
     ],
     "inference-sh/DESCRIPTION.md": [
-      1778488088996220905,
+      1778486755926474303,
       706
     ],
     "mcp/DESCRIPTION.md": [
-      1778488089016220410,
+      1778486755856476230,
       216
     ],
     "media/DESCRIPTION.md": [
-      1778488089026220160,
+      1778486755726479808,
       139
     ],
     "mlops/DESCRIPTION.md": [
-      1778488089076218920,
+      1778486755966473201,
       162
     ],
     "mlops/evaluation/DESCRIPTION.md": [
-      1778488089086218674,
+      1778486756026471550,
       126
     ],
     "mlops/inference/DESCRIPTION.md": [
-      1778488089166216689,
+      1778486756256465220,
       161
     ],
     "mlops/models/DESCRIPTION.md": [
-      1778488089416210485,
+      1778486756656454211,
       253
     ],
     "mlops/research/DESCRIPTION.md": [
-      1778488089466209244,
+      1778486756736452006,
       113
     ],
     "mlops/training/DESCRIPTION.md": [
-      1778488089506208251,
+      1778486756836449255,
       150
     ],
     "mlops/vector-databases/DESCRIPTION.md": [
-      1778488089646204775,
+      1778486757176439897,
       125
     ],
     "note-taking/DESCRIPTION.md": [
-      1778488089656204529,
+      1778486757246437968,
       146
     ],
     "productivity/DESCRIPTION.md": [
-      1778488089716203040,
+      1778486757236438246,
       114
     ],
     "productivity/ocr-and-documents/DESCRIPTION.md": [
-      1778488089816200556,
+      1778486757456432188,
       147
     ],
     "research/DESCRIPTION.md": [
-      1778488090346187406,
+      1778486758376406864,
       179
     ],
     "smart-home/DESCRIPTION.md": [
-      1778488090916173262,
+      1778486759526375209,
       123
     ],
     "social-media/DESCRIPTION.md": [
-      1778488090936172766,
+      1778486759536374934,
       151
     ]
   },

channel_directory.json

@@ -1,5 +1,5 @@
 {
-  "updated_at": "2026-05-11T08:37:20.667671",
+  "updated_at": "2026-05-11T08:47:02.073750",
   "platforms": {
     "telegram": [
       {

config.yaml

@@ -1,5 +1,5 @@
 model:
-  default: gemini-2.5-flash
+  default: gemini-2.5-flash-lite
   provider: gemini
   base_url: ''
 providers: {}
@@ -82,6 +82,7 @@ terminal:
   container_persistent: true
   docker_volumes: []
   docker_mount_cwd_to_workspace: false
+  docker_extra_args: []
   docker_run_as_host_user: false
   persistent_shell: true
   lifetime_seconds: 300
@@ -137,6 +138,7 @@ prompt_caching:
 openrouter:
   response_cache: true
   response_cache_ttl: 300
+  min_coding_score: 0.65
 bedrock:
   region: ''
   discovery:
@@ -230,6 +232,7 @@ display:
   bell_on_complete: false
   show_reasoning: false
   streaming: true
+  timestamps: false
   final_response_markdown: strip
   persistent_output: true
   persistent_output_max_lines: 200
@@ -386,6 +389,7 @@ approvals:
   timeout: 60
   cron_mode: deny
   mcp_reload_confirm: true
+  destructive_slash_confirm: true
 command_allowlist: []
 quick_commands: {}
 hooks: {}
@@ -471,3 +475,25 @@ platforms:
     extra:
       base_url: https://louissoume-huggingmes-proxy.louissoume.workers.dev/bot
       base_file_url: https://louissoume-huggingmes-proxy.louissoume.workers.dev/file/bot
+
+# ── Fallback Model ────────────────────────────────────────────────────
+# Automatic provider failover when primary is unavailable.
+# Uncomment and configure to enable. Triggers on rate limits (429),
+# overload (529), service errors (503), or connection failures.
+#
+# Supported providers:
+#   openrouter   (OPENROUTER_API_KEY)  — routes to any model
+#   openai-codex (OAuth — hermes auth) — OpenAI Codex
+#   nous         (OAuth — hermes auth) — Nous Portal
+#   zai          (ZAI_API_KEY)         — Z.AI / GLM
+#   kimi-coding  (KIMI_API_KEY)        — Kimi / Moonshot
+#   kimi-coding-cn (KIMI_CN_API_KEY)   — Kimi / Moonshot (China)
+#   minimax      (MINIMAX_API_KEY)     — MiniMax
+#   minimax-cn   (MINIMAX_CN_API_KEY)  — MiniMax (China)
+#   bedrock      (AWS IAM / boto3)     — AWS Bedrock (Converse API)
+#
+# For custom OpenAI-compatible endpoints, add base_url and key_env.
+#
+# fallback_model:
+#   provider: openrouter
+#   model: anthropic/claude-sonnet-4

gateway.lock

@@ -1 +1 @@
-{"pid": 125, "kind": "hermes-gateway", "argv": ["/opt/hermes/.venv/bin/hermes", "gateway", "run"], "start_time": 39957857}
+{"pid": 121, "kind": "hermes-gateway", "argv": ["/opt/hermes/.venv/bin/hermes", "gateway", "run"], "start_time": 223664529}

gateway_state.json

@@ -1 +1 @@
-{"pid":125,"kind":"hermes-gateway","argv":["/opt/hermes/.venv/bin/hermes","gateway","run"],"start_time":39957857,"gateway_state":"stopped","exit_reason":null,"restart_requested":false,"active_agents":0,"platforms":{"telegram":{"state":"disconnected","error_code":null,"error_message":null,"updated_at":"2026-05-11T08:37:56.548687+00:00"},"api_server":{"state":"disconnected","error_code":null,"error_message":null,"updated_at":"2026-05-11T08:37:56.552235+00:00"}},"updated_at":"2026-05-11T08:37:56.564345+00:00"}
+{"pid":121,"kind":"hermes-gateway","argv":["/opt/hermes/.venv/bin/hermes","gateway","run"],"start_time":223664529,"gateway_state":"stopped","exit_reason":null,"restart_requested":false,"active_agents":0,"platforms":{"telegram":{"state":"disconnected","error_code":null,"error_message":null,"updated_at":"2026-05-11T08:47:46.003614+00:00"},"api_server":{"state":"disconnected","error_code":null,"error_message":null,"updated_at":"2026-05-11T08:47:46.008734+00:00"}},"updated_at":"2026-05-11T08:47:46.013598+00:00"}

ollama_cloud_models_cache.json

@@ -1 +1 @@
-{"models": ["minimax-m2.7", "gpt-oss:20b", "kimi-k2.5", "glm-4.7", "gemma4:31b", "gpt-oss:120b", "qwen3.5:397b", "deepseek-v3.1:671b", "glm-5", "qwen3-vl:235b-instruct", "gemini-3-flash-preview", "ministral-3:14b", "minimax-m2", "qwen3-next:80b", "qwen3-vl:235b", "rnj-1:8b", "minimax-m2.1", "glm-5.1", "mistral-large-3:675b", "ministral-3:8b", "qwen3-coder:480b", "kimi-k2.6", "nemotron-3-nano:30b", "deepseek-v4-flash", "glm-4.6", "ministral-3:3b", "devstral-2:123b", "cogito-2.1:671b", "qwen3-coder-next", "nemotron-3-super", "deepseek-v4-pro", "minimax-m2.5", "deepseek-v3.2", "kimi-k2-thinking", "devstral-small-2:24b", "kimi-k2:1t"], "cached_at": 1778432623.8839386}
+{"models": ["minimax-m2.7", "gpt-oss:20b", "kimi-k2.5", "glm-4.7", "gemma4:31b", "gpt-oss:120b", "qwen3.5:397b", "deepseek-v3.1:671b", "glm-5", "qwen3-vl:235b-instruct", "gemini-3-flash-preview", "ministral-3:14b", "minimax-m2", "qwen3-next:80b", "qwen3-vl:235b", "rnj-1:8b", "minimax-m2.1", "glm-5.1", "mistral-large-3:675b", "ministral-3:8b", "qwen3-coder:480b", "kimi-k2.6", "nemotron-3-nano:30b", "deepseek-v4-flash", "glm-4.6", "ministral-3:3b", "devstral-2:123b", "cogito-2.1:671b", "qwen3-coder-next", "nemotron-3-super", "deepseek-v4-pro", "minimax-m2.5", "deepseek-v3.2", "kimi-k2-thinking", "devstral-small-2:24b", "kimi-k2:1t"], "cached_at": 1778488957.6501825}

sessions/20260511_075702_b931aa20.jsonl

@@ -7,7 +7,7 @@
 {"role": "assistant", "content": "Oui, le changement de modèle a fonctionné. Je suis maintenant en cours d'exécution sur `gemini-2.5-flash`.\n\nComment puis-je vous aider, Louis ?", "reasoning": "**Confirming the Model Change**\n\nI understand the user's question and will respond in French, confirming the successful model switch. Currently, I am running on `gemini-2.5-flash`, which is indeed a different model than before, so the change is evident.\n\n\n**Acknowledging the User's Query**\n\nI've understood the French inquiry and will formulate a response in the same language. I'm verifying the successful model shift by confirming I'm now utilizing `gemini-2.5-flash`, a departure from the prior model. This information allows me to confidently assure the user that the transition was completed. My plan is to use `send_message`.\n\n\n", "finish_reason": "stop", "reasoning_content": "**Confirming the Model Change**\n\nI understand the user's question and will respond in French, confirming the successful model switch. Currently, I am running on `gemini-2.5-flash`, which is indeed a different model than before, so the change is evident.\n\n\n**Acknowledging the User's Query**\n\nI've understood the French inquiry and will formulate a response in the same language. I'm verifying the successful model shift by confirming I'm now utilizing `gemini-2.5-flash`, a departure from the prior model. This information allows me to confidently assure the user that the transition was completed. My plan is to use `send_message`.\n\n\n", "timestamp": "2026-05-11T08:19:35.611770"}
 {"role": "user", "content": "non c'est gemini-2.0-flash-exp. que je veux", "timestamp": "2026-05-11T08:20:05.852787"}
 {"role": "assistant", "content": "Je comprends que vous souhaitez que j'utilise `gemini-2.0-flash-exp`.\n\nMalheureusement, je ne peux pas changer mon propre modèle directement au cours de notre conversation. La modification du modèle que j'utilise nécessite une configuration au niveau de mon déploiement sur Hugging Face Space/Endpoint, ou de contacter son mainteneur.\n\nCependant, si vous souhaitez utiliser `gemini-2.0-flash-exp` pour des tâches spécifiques comme des jobs planifiés (`cronjob`) ou des tâches déléguées (`delegate_task`), vous pouvez spécifier ce modèle lors de la création de ces tâches.", "reasoning": "**Investigating Model Options**\n\nI'm currently trying to switch the model to `gemini-2.0-flash -exp`. It seems like I need to use either the `cronjob` or `delegate_task` tool to do this. Both have a `model` parameter, which is a key lead. I'm checking their specifics to see which will do the job.\n\n\n**Clarifying Current Limitations**\n\nI realize there's no direct tool to alter my own model during this session. Both `cronjob` and `delegate_task` let you specify a model for their specific tasks, but not for the current session. I'm deployed on Hugging Face, so changes may require adjusting the Space configuration. I'll inform Louis about this limitation and the options for setting specific models in those other tools.\n\n\n", "finish_reason": "stop", "reasoning_content": "**Investigating Model Options**\n\nI'm currently trying to switch the model to `gemini-2.0-flash -exp`. It seems like I need to use either the `cronjob` or `delegate_task` tool to do this. Both have a `model` parameter, which is a key lead. I'm checking their specifics to see which will do the job.\n\n\n**Clarifying Current Limitations**\n\nI realize there's no direct tool to alter my own model during this session. Both `cronjob` and `delegate_task` let you specify a model for their specific tasks, but not for the current session. I'm deployed on Hugging Face, so changes may require adjusting the Space configuration. I'll inform Louis about this limitation and the options for setting specific models in those other tools.\n\n\n", "timestamp": "2026-05-11T08:20:05.852787"}
-{"role": "user", "content": "allo", "timestamp": "2026-05-11T08:31:51.263968"}
-{"role": "assistant", "content": "Bonjour Louis ! Comment puis-je vous aider aujourd'hui ?", "reasoning": "**Acknowledge and Respond**\n\nI've registered the user's greeting (\"allo\") and interpreted it as \"hello\". I'm formulating a concise response, aiming to mirror prior exchanges and offer assistance. My aim is to be efficient and helpful.\n\n\n", "finish_reason": "stop", "reasoning_content": "**Acknowledge and Respond**\n\nI've registered the user's greeting (\"allo\") and interpreted it as \"hello\". I'm formulating a concise response, aiming to mirror prior exchanges and offer assistance. My aim is to be efficient and helpful.\n\n\n", "timestamp": "2026-05-11T08:31:51.263968"}
-{"role": "user", "content": "et maintenant sur quel modele tourne tu?", "timestamp": "2026-05-11T08:32:07.142047"}
-{"role": "assistant", "content": "Je tourne toujours sur le modèle `gemini-2.5-flash`.\n\nComme mentionné précédemment, je ne peux pas changer mon modèle en cours de conversation. Si vous souhaitez que j'utilise un modèle différent, cela nécessiterait une modification au niveau de mon d��ploiement sur Hugging Face.\n\nY a-t-il autre chose que je puisse faire pour vous aider ?", "reasoning": null, "finish_reason": "stop", "timestamp": "2026-05-11T08:32:07.142047"}
+{"role": "user", "content": "HELLO", "timestamp": "2026-05-11T08:39:41.973295"}
+{"role": "assistant", "content": "Hello Louis! How can I help you today?", "reasoning": null, "finish_reason": "stop", "timestamp": "2026-05-11T08:39:41.973295"}
+{"role": "user", "content": "et maintenant sur quel modele tourne tu?", "timestamp": "2026-05-11T08:40:00.695588"}
+{"role": "assistant", "content": "Je tourne actuellement sur le modèle `gemini-2.5-flash` fourni par `gemini`.", "reasoning": "**Identifying Current Model**\n\nI'm focusing on pinpointing the specific model and provider that's powering our current interaction. I've located the crucial data within the `Current Session Context`, so I can deliver the requested information precisely.\n\n\n", "finish_reason": "stop", "reasoning_content": "**Identifying Current Model**\n\nI'm focusing on pinpointing the specific model and provider that's powering our current interaction. I've located the crucial data within the `Current Session Context`, so I can deliver the requested information precisely.\n\n\n", "timestamp": "2026-05-11T08:40:00.695588"}

sessions/session_20260511_075702_b931aa20.json

@@ -3,9 +3,9 @@
   "model": "gemini-2.5-flash",
   "base_url": "https://generativelanguage.googleapis.com/v1beta",
   "platform": "telegram",
-  "session_start": "2026-05-11T08:31:49.013240",
-  "last_updated": "2026-05-11T08:32:07.099918",
-  "system_prompt": "# Hermes Agent Persona\n\n<!--\nThis file defines the agent's personality and tone.\nThe agent will embody whatever you write here.\nEdit this to customize how Hermes communicates with you.\n\nExamples:\n  - \"You are a warm, playful assistant who uses kaomoji occasionally.\"\n  - \"You are a concise technical expert. No fluff, just facts.\"\n  - \"You speak like a friendly coworker who happens to know everything.\"\n\nThis file is loaded fresh each message -- no restart needed.\nDelete the contents (or this file) to use the default personality.\n-->\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Google model operational directives\nFollow these operational rules strictly:\n- **Absolute paths:** Always construct and use absolute file paths for all file system operations. Combine the project root with relative paths.\n- **Verify first:** Use read_file/search_files to check file contents and project structure before making changes. Never guess at file contents.\n- **Dependency checks:** Never assume a library is available. Check package.json, requirements.txt, Cargo.toml, etc. before importing.\n- **Conciseness:** Keep explanatory text brief — a few sentences, not paragraphs. Focus on actions and results over narration.\n- **Parallel tool calls:** When you need to perform multiple independent operations (e.g. reading several files), make all the tool calls in a single response rather than sequentially.\n- **Non-interactive commands:** Use flags like -y, --yes, --non-interactive to prevent CLI tools from hanging on prompts.\n- **Keep going:** Work autonomously until the task is fully resolved. Don't stop with a plan — execute it.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [10% — 226/2,200 chars]\n══════════════════════════════════════════════\nI am deployed on Hugging Face and currently lack the `web_search` tool. It cannot be enabled from within our conversation; it requires modification of the Hugging Face Space/Endpoint configuration or contacting its maintainer.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [15% — 212/1,375 chars]\n══════════════════════════════════════════════\nThe user's name is Louis.\n§\nLouis wants me to be his \"right-hand man\" for his daily projects.\n§\nLouis wants me to learn from each of our conversations.\n§\nLouis prefers concise responses to manage API token usage.\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n<available_skills>\n  autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n    - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n    - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n    - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n    - opencode: Delegate coding to OpenCode CLI (features, PR review).\n  creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n    - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n    - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n    - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n    - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n    - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n    - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n    - comfyui: Generate images, video, and audio with ComfyUI — install,...\n    - design-md: Author/validate/export Google's DESIGN.md token spec files.\n    - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n    - humanizer: Humanize text: strip AI-isms and add real voice.\n    - ideation: Generate project ideas via creative constraints.\n    - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n    - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n    - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n    - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n    - pretext: Use when building creative browser demos with @chenglou/p...\n    - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n    - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n    - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n  data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n    - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n  devops:\n    - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n    - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n    - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n  dogfood:\n    - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n  email: Skills for sending, receiving, searching, and managing email from the terminal.\n    - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n  gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n    - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n    - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n  github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n    - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n    - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n    - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n    - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n    - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n    - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n  mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n    - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n  media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n    - gif-search: Search/download GIFs from Tenor via curl + jq.\n    - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n    - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n    - spotify: Spotify: play, search, queue, manage playlists and devices.\n    - youtube-content: YouTube transcripts to summaries, threads, blogs.\n  mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n    - gemini-key-rotator: Automatically rotates Gemini API keys on quota errors by ...\n    - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n  mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n    - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n    - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n  mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n    - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n    - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n    - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n    - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n  mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n    - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n    - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n  mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n    - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n  mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n    - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n    - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n    - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n  note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n    - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n  productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n    - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n    - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n    - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n    - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n    - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n    - notion: Notion API via curl: pages, databases, blocks, search.\n    - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n    - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n    - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n  red-teaming:\n    - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n  research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n    - arxiv: Search arXiv papers by keyword, author, category, or ID.\n    - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n    - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n    - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n  smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n    - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n  social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n    - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n  software-development:\n    - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n    - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n    - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n    - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n    - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n    - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n    - spike: Throwaway experiments to validate an idea before build.\n    - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n    - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n    - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n    - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n  yuanbao:\n    - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n</available_skills>\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nConversation started: Monday, May 11, 2026 08:31 AM\nModel: gemini-2.5-flash\nProvider: gemini\n\nHost: Linux (6.12.79-101.147.amzn2023.x86_64)\nUser home directory: /opt/data\nCurrent working directory: /opt/hermes\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.",
+  "session_start": "2026-05-11T08:39:40.026787",
+  "last_updated": "2026-05-11T08:40:00.655630",
+  "system_prompt": "# Hermes Agent Persona\n\n<!--\nThis file defines the agent's personality and tone.\nThe agent will embody whatever you write here.\nEdit this to customize how Hermes communicates with you.\n\nExamples:\n  - \"You are a warm, playful assistant who uses kaomoji occasionally.\"\n  - \"You are a concise technical expert. No fluff, just facts.\"\n  - \"You speak like a friendly coworker who happens to know everything.\"\n\nThis file is loaded fresh each message -- no restart needed.\nDelete the contents (or this file) to use the default personality.\n-->\n\nIf the user asks about configuring, setting up, or using Hermes Agent itself, load the `hermes-agent` skill with skill_view(name='hermes-agent') before answering. Docs: https://hermes-agent.nousresearch.com/docs\n\nYou have persistent memory across sessions. Save durable facts using the memory tool: user preferences, environment details, tool quirks, and stable conventions. Memory is injected into every turn, so keep it compact and focused on facts that will still matter later.\nPrioritize what reduces future user steering — the most valuable memory is one that prevents the user from having to correct or remind you again. User preferences and recurring corrections matter more than procedural task details.\nDo NOT save task progress, session outcomes, completed-work logs, or temporary TODO state to memory; use session_search to recall those from past transcripts. Specifically: do not record PR numbers, issue numbers, commit SHAs, 'fixed bug X', 'submitted PR Y', 'Phase N done', file counts, or any artifact that will be stale in 7 days. If a fact will be stale in a week, it does not belong in memory. If you've discovered a new way to do something, solved a problem that could be necessary later, save it as a skill with the skill tool.\nWrite memories as declarative facts, not instructions to yourself. 'User prefers concise responses' ✓ — 'Always respond concisely' ✗. 'Project uses pytest with xdist' ✓ — 'Run tests with pytest -n 4' ✗. Imperative phrasing gets re-read as a directive in later sessions and can cause repeated work or override the user's current request. Procedures and workflows belong in skills, not memory. When the user references something from a past conversation or you suspect relevant cross-session context exists, use session_search to recall it before asking them to repeat themselves. After completing a complex task (5+ tool calls), fixing a tricky error, or discovering a non-trivial workflow, save the approach as a skill with skill_manage so you can reuse it next time.\nWhen using a skill and finding it outdated, incomplete, or wrong, patch it immediately with skill_manage(action='patch') — don't wait to be asked. Skills that aren't maintained become liabilities.\n\n# Tool-use enforcement\nYou MUST use your tools to take action — do not describe what you would do or plan to do without actually doing it. When you say you will perform an action (e.g. 'I will run the tests', 'Let me check the file', 'I will create the project'), you MUST immediately make the corresponding tool call in the same response. Never end your turn with a promise of future action — execute it now.\nKeep working until the task is actually complete. Do not stop with a summary of what you plan to do next time. If you have tools available that can accomplish the task, use them instead of telling the user what you would do.\nEvery response should either (a) contain tool calls that make progress, or (b) deliver a final result to the user. Responses that only describe intentions without acting are not acceptable.\n\n# Google model operational directives\nFollow these operational rules strictly:\n- **Absolute paths:** Always construct and use absolute file paths for all file system operations. Combine the project root with relative paths.\n- **Verify first:** Use read_file/search_files to check file contents and project structure before making changes. Never guess at file contents.\n- **Dependency checks:** Never assume a library is available. Check package.json, requirements.txt, Cargo.toml, etc. before importing.\n- **Conciseness:** Keep explanatory text brief — a few sentences, not paragraphs. Focus on actions and results over narration.\n- **Parallel tool calls:** When you need to perform multiple independent operations (e.g. reading several files), make all the tool calls in a single response rather than sequentially.\n- **Non-interactive commands:** Use flags like -y, --yes, --non-interactive to prevent CLI tools from hanging on prompts.\n- **Keep going:** Work autonomously until the task is fully resolved. Don't stop with a plan — execute it.\n\n══════════════════════════════════════════════\nMEMORY (your personal notes) [10% — 226/2,200 chars]\n══════════════════════════════════════════════\nI am deployed on Hugging Face and currently lack the `web_search` tool. It cannot be enabled from within our conversation; it requires modification of the Hugging Face Space/Endpoint configuration or contacting its maintainer.\n\n══════════════════════════════════════════════\nUSER PROFILE (who the user is) [15% — 212/1,375 chars]\n══════════════════════════════════════════════\nThe user's name is Louis.\n§\nLouis wants me to be his \"right-hand man\" for his daily projects.\n§\nLouis wants me to learn from each of our conversations.\n§\nLouis prefers concise responses to manage API token usage.\n\n## Skills (mandatory)\nBefore replying, scan the skills below. If a skill matches or is even partially relevant to your task, you MUST load it with skill_view(name) and follow its instructions. Err on the side of loading — it is always better to have context you don't need than to miss critical steps, pitfalls, or established workflows. Skills contain specialized knowledge — API endpoints, tool-specific commands, and proven workflows that outperform general-purpose approaches. Load the skill even if you think you could handle the task with basic tools like web_search or terminal. Skills also encode the user's preferred approach, conventions, and quality standards for tasks like code review, planning, and testing — load them even for tasks you already know how to do, because the skill defines how it should be done here.\nWhenever the user asks you to configure, set up, install, enable, disable, modify, or troubleshoot Hermes Agent itself — its CLI, config, models, providers, tools, skills, voice, gateway, plugins, or any feature — load the `hermes-agent` skill first. It has the actual commands (e.g. `hermes config set …`, `hermes tools`, `hermes setup`) so you don't have to guess or invent workarounds.\nIf a skill has issues, fix it with skill_manage(action='patch').\nAfter difficult/iterative tasks, offer to save as a skill. If a skill you loaded was missing steps, had wrong commands, or needed pitfalls you discovered, update it before finishing.\n\n<available_skills>\n  autonomous-ai-agents: Skills for spawning and orchestrating autonomous AI coding agents and multi-agent workflows — running independent agent processes, delegating tasks, and coordinating parallel workstreams.\n    - claude-code: Delegate coding to Claude Code CLI (features, PRs).\n    - codex: Delegate coding to OpenAI Codex CLI (features, PRs).\n    - hermes-agent: Configure, extend, or contribute to Hermes Agent.\n    - opencode: Delegate coding to OpenCode CLI (features, PR review).\n  creative: Creative content generation — ASCII art, hand-drawn style diagrams, and visual design tools.\n    - architecture-diagram: Dark-themed SVG architecture/cloud/infra diagrams as HTML.\n    - ascii-art: ASCII art: pyfiglet, cowsay, boxes, image-to-ascii.\n    - ascii-video: ASCII video: convert video/audio to colored ASCII MP4/GIF.\n    - baoyu-comic: Knowledge comics (知识漫画): educational, biography, tutorial.\n    - baoyu-infographic: Infographics: 21 layouts x 21 styles (信息图, 可视化).\n    - claude-design: Design one-off HTML artifacts (landing, deck, prototype).\n    - comfyui: Generate images, video, and audio with ComfyUI — install,...\n    - design-md: Author/validate/export Google's DESIGN.md token spec files.\n    - excalidraw: Hand-drawn Excalidraw JSON diagrams (arch, flow, seq).\n    - humanizer: Humanize text: strip AI-isms and add real voice.\n    - ideation: Generate project ideas via creative constraints.\n    - manim-video: Manim CE animations: 3Blue1Brown math/algo videos.\n    - p5js: p5.js sketches: gen art, shaders, interactive, 3D.\n    - pixel-art: Pixel art w/ era palettes (NES, Game Boy, PICO-8).\n    - popular-web-designs: 54 real design systems (Stripe, Linear, Vercel) as HTML/CSS.\n    - pretext: Use when building creative browser demos with @chenglou/p...\n    - sketch: Throwaway HTML mockups: 2-3 design variants to compare.\n    - songwriting-and-ai-music: Songwriting craft and Suno AI music prompts.\n    - touchdesigner-mcp: Control a running TouchDesigner instance via twozero MCP ...\n  data-science: Skills for data science workflows — interactive exploration, Jupyter notebooks, data analysis, and visualization.\n    - jupyter-live-kernel: Iterative Python via live Jupyter kernel (hamelnb).\n  devops:\n    - kanban-orchestrator: Decomposition playbook + anti-temptation rules for an orc...\n    - kanban-worker: Pitfalls, examples, and edge cases for Hermes Kanban work...\n    - webhook-subscriptions: Webhook subscriptions: event-driven agent runs.\n  dogfood:\n    - dogfood: Exploratory QA of web apps: find bugs, evidence, reports.\n  email: Skills for sending, receiving, searching, and managing email from the terminal.\n    - himalaya: Himalaya CLI: IMAP/SMTP email from terminal.\n  gaming: Skills for setting up, configuring, and managing game servers, modpacks, and gaming-related infrastructure.\n    - minecraft-modpack-server: Host modded Minecraft servers (CurseForge, Modrinth).\n    - pokemon-player: Play Pokemon via headless emulator + RAM reads.\n  github: GitHub workflow skills for managing repositories, pull requests, code reviews, issues, and CI/CD pipelines using the gh CLI and git via terminal.\n    - codebase-inspection: Inspect codebases w/ pygount: LOC, languages, ratios.\n    - github-auth: GitHub auth setup: HTTPS tokens, SSH keys, gh CLI login.\n    - github-code-review: Review PRs: diffs, inline comments via gh or REST.\n    - github-issues: Create, triage, label, assign GitHub issues via gh or REST.\n    - github-pr-workflow: GitHub PR lifecycle: branch, commit, open, CI, merge.\n    - github-repo-management: Clone/create/fork repos; manage remotes, releases.\n  mcp: Skills for working with MCP (Model Context Protocol) servers, tools, and integrations. Documents the built-in native MCP client — configure servers in config.yaml for automatic tool discovery.\n    - native-mcp: MCP client: connect servers, register tools (stdio/HTTP).\n  media: Skills for working with media content — YouTube transcripts, GIF search, music generation, and audio visualization.\n    - gif-search: Search/download GIFs from Tenor via curl + jq.\n    - heartmula: HeartMuLa: Suno-like song generation from lyrics + tags.\n    - songsee: Audio spectrograms/features (mel, chroma, MFCC) via CLI.\n    - spotify: Spotify: play, search, queue, manage playlists and devices.\n    - youtube-content: YouTube transcripts to summaries, threads, blogs.\n  mlops: Knowledge and Tools for Machine Learning Operations - tools and frameworks for training, fine-tuning, deploying, and optimizing ML/AI models\n    - gemini-key-rotator: Automatically rotates Gemini API keys on quota errors by ...\n    - huggingface-hub: HuggingFace hf CLI: search/download/upload models, datasets.\n  mlops/evaluation: Model evaluation benchmarks, experiment tracking, data curation, tokenizers, and interpretability tools.\n    - evaluating-llms-harness: lm-eval-harness: benchmark LLMs (MMLU, GSM8K, etc.).\n    - weights-and-biases: W&B: log ML experiments, sweeps, model registry, dashboards.\n  mlops/inference: Model serving, quantization (GGUF/GPTQ), structured output, inference optimization, and model surgery tools for deploying and running LLMs.\n    - llama-cpp: llama.cpp local GGUF inference + HF Hub model discovery.\n    - obliteratus: OBLITERATUS: abliterate LLM refusals (diff-in-means).\n    - outlines: Outlines: structured JSON/regex/Pydantic LLM generation.\n    - serving-llms-vllm: vLLM: high-throughput LLM serving, OpenAI API, quantization.\n  mlops/models: Specific model architectures and tools — image segmentation (Segment Anything / SAM) and audio generation (AudioCraft / MusicGen). Additional model skills (CLIP, Stable Diffusion, Whisper, LLaVA) are available as optional skills.\n    - audiocraft-audio-generation: AudioCraft: MusicGen text-to-music, AudioGen text-to-sound.\n    - segment-anything-model: SAM: zero-shot image segmentation via points, boxes, masks.\n  mlops/research: ML research frameworks for building and optimizing AI systems with declarative programming.\n    - dspy: DSPy: declarative LM programs, auto-optimize prompts, RAG.\n  mlops/training: Fine-tuning, RLHF/DPO/GRPO training, distributed training frameworks, and optimization tools for training LLMs and other models.\n    - axolotl: Axolotl: YAML LLM fine-tuning (LoRA, DPO, GRPO).\n    - fine-tuning-with-trl: TRL: SFT, DPO, PPO, GRPO, reward modeling for LLM RLHF.\n    - unsloth: Unsloth: 2-5x faster LoRA/QLoRA fine-tuning, less VRAM.\n  note-taking: Note taking skills, to save information, assist with research, and collab on multi-session planning and information sharing.\n    - obsidian: Read, search, create, and edit notes in the Obsidian vault.\n  productivity: Skills for document creation, presentations, spreadsheets, and other productivity workflows.\n    - airtable: Airtable REST API via curl. Records CRUD, filters, upserts.\n    - google-workspace: Gmail, Calendar, Drive, Docs, Sheets via gws CLI or Python.\n    - linear: Linear: manage issues, projects, teams via GraphQL + curl.\n    - maps: Geocode, POIs, routes, timezones via OpenStreetMap/OSRM.\n    - nano-pdf: Edit PDF text/typos/titles via nano-pdf CLI (NL prompts).\n    - notion: Notion API via curl: pages, databases, blocks, search.\n    - ocr-and-documents: Extract text from PDFs/scans (pymupdf, marker-pdf).\n    - powerpoint: Create, read, edit .pptx decks, slides, notes, templates.\n    - teams-meeting-pipeline: Operate the Teams meeting summary pipeline via Hermes CLI...\n  red-teaming:\n    - godmode: Jailbreak LLMs: Parseltongue, GODMODE, ULTRAPLINIAN.\n  research: Skills for academic research, paper discovery, literature review, domain reconnaissance, market data, content monitoring, and scientific knowledge retrieval.\n    - arxiv: Search arXiv papers by keyword, author, category, or ID.\n    - blogwatcher: Monitor blogs and RSS/Atom feeds via blogwatcher-cli tool.\n    - llm-wiki: Karpathy's LLM Wiki: build/query interlinked markdown KB.\n    - polymarket: Query Polymarket: markets, prices, orderbooks, history.\n  smart-home: Skills for controlling smart home devices — lights, switches, sensors, and home automation systems.\n    - openhue: Control Philips Hue lights, scenes, rooms via OpenHue CLI.\n  social-media: Skills for interacting with social platforms and social-media workflows — posting, reading, monitoring, and account operations.\n    - xurl: X/Twitter via xurl CLI: post, search, DM, media, v2 API.\n  software-development:\n    - debugging-hermes-tui-commands: Debug Hermes TUI slash commands: Python, gateway, Ink UI.\n    - hermes-agent-skill-authoring: Author in-repo SKILL.md: frontmatter, validator, structure.\n    - node-inspect-debugger: Debug Node.js via --inspect + Chrome DevTools Protocol CLI.\n    - plan: Plan mode: write markdown plan to .hermes/plans/, no exec.\n    - python-debugpy: Debug Python: pdb REPL + debugpy remote (DAP).\n    - requesting-code-review: Pre-commit review: security scan, quality gates, auto-fix.\n    - spike: Throwaway experiments to validate an idea before build.\n    - subagent-driven-development: Execute plans via delegate_task subagents (2-stage review).\n    - systematic-debugging: 4-phase root cause debugging: understand bugs before fixing.\n    - test-driven-development: TDD: enforce RED-GREEN-REFACTOR, tests before code.\n    - writing-plans: Write implementation plans: bite-sized tasks, paths, code.\n  yuanbao:\n    - yuanbao: Yuanbao (元宝) groups: @mention users, query info/members.\n</available_skills>\n\nOnly proceed without loading a skill if genuinely none are relevant to the task.\n\nConversation started: Monday, May 11, 2026 08:19 AM\nModel: gemini-2.5-flash\nProvider: gemini\n\nHost: Linux (6.12.79-101.147.amzn2023.x86_64)\nUser home directory: /opt/data\nCurrent working directory: /opt/hermes\n\nYou are on a text messaging communication platform, Telegram. Standard markdown is automatically converted to Telegram format. Supported: **bold**, *italic*, ~~strikethrough~~, ||spoiler||, `inline code`, ```code blocks```, [links](url), and ## headers. Telegram has NO table syntax — prefer bullet lists or labeled key: value pairs over pipe tables (any tables you do emit are auto-rewritten into row-group bullets, which you can produce directly for cleaner output). You can send media files natively: to deliver a file to the user, include MEDIA:/absolute/path/to/file in your response. Images (.png, .jpg, .webp) appear as photos, audio (.ogg) sends as voice bubbles, and videos (.mp4) play inline. You can also include image URLs in markdown format ![alt](url) and they will be sent as native photos.",
   "tools": [
     {
       "type": "function",
@@ -1079,13 +1079,11 @@
     },
     {
       "role": "user",
-      "content": "allo"
+      "content": "HELLO"
     },
     {
       "role": "assistant",
-      "content": "Bonjour Louis ! Comment puis-je vous aider aujourd'hui ?",
-      "reasoning": "**Acknowledge and Respond**\n\nI've registered the user's greeting (\"allo\") and interpreted it as \"hello\". I'm formulating a concise response, aiming to mirror prior exchanges and offer assistance. My aim is to be efficient and helpful.\n\n\n",
-      "reasoning_content": "**Acknowledge and Respond**\n\nI've registered the user's greeting (\"allo\") and interpreted it as \"hello\". I'm formulating a concise response, aiming to mirror prior exchanges and offer assistance. My aim is to be efficient and helpful.\n\n\n",
+      "content": "Hello Louis! How can I help you today?",
       "finish_reason": "stop"
     },
     {
@@ -1094,9 +1092,10 @@
     },
     {
       "role": "assistant",
-      "content": "Je tourne toujours sur le modèle `gemini-2.5-flash`.\n\nComme mentionné précédemment, je ne peux pas changer mon modèle en cours de conversation. Si vous souhaitez que j'utilise un modèle différent, cela nécessiterait une modification au niveau de mon déploiement sur Hugging Face.\n\nY a-t-il autre chose que je puisse faire pour vous aider ?",
-      "reasoning": null,
-      "finish_reason": "stop"
+      "content": "Je tourne actuellement sur le modèle `gemini-2.5-flash` fourni par `gemini`.",
+      "reasoning": "**Identifying Current Model**\n\nI'm focusing on pinpointing the specific model and provider that's powering our current interaction. I've located the crucial data within the `Current Session Context`, so I can deliver the requested information precisely.\n\n\n",
+      "finish_reason": "stop",
+      "reasoning_content": "**Identifying Current Model**\n\nI'm focusing on pinpointing the specific model and provider that's powering our current interaction. I've located the crucial data within the `Current Session Context`, so I can deliver the requested information precisely.\n\n\n"
     }
   ]
 }

sessions/sessions.json

@@ -3,7 +3,7 @@
     "session_key": "agent:main:telegram:dm:7904792459",
     "session_id": "20260511_075702_b931aa20",
     "created_at": "2026-05-11T07:57:02.819521",
-    "updated_at": "2026-05-11T08:32:07.145645",
+    "updated_at": "2026-05-11T08:40:00.698572",
     "display_name": "Louis",
     "platform": "telegram",
     "chat_type": "dm",
@@ -12,7 +12,7 @@
     "cache_read_tokens": 0,
     "cache_write_tokens": 0,
     "total_tokens": 0,
-    "last_prompt_tokens": 16465,
+    "last_prompt_tokens": 16462,
     "estimated_cost_usd": 0.0,
     "cost_status": "unknown",
     "expiry_finalized": false,

state.db

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:5e08e99274758177ee1155cc9dfa10ac265747d6d2af2b136c88aa7cf8a15768
-size 1044480
+oid sha256:f2fa3641fb6a75a8787df8bf220483d71050afc0a045fcaf3664157882b64025
+size 1040384