mestamp":"2026-02-04T12:28:00.023Z"}
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{"parentUuid":"9dea0a8d-b8af-42a3-9b7d-ce17d21266a6","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/services","sessionId":"3f08f44a-a461-4640-9708-b1cbc3b2257a","version":"2.1.31","gitBranch":"HEAD","slug":"cuddly-launching-garden","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_0176f8drkcYYw7i8RVhWiP5J","type":"tool_result","content":"   329→      # Check if substance is a cannabis source (joint, cart, bowl, etc.)\n   330→      cannabis_result = process_cannabis_dose(substance_name, dosage.to_s)\n   331→      if cannabis_result\n   332→        # Override with cannabis data\n   333→        original_substance = substance_name\n   334→        substance_name = \"cannabis\"\n   335→        dosage = cannabis_result[:amount]\n   336→        unit = cannabis_result[:unit]\n   337→        # Prepend cannabis details to annotation\n   338→        cannabis_details = cannabis_result[:details]\n   339→        note_text = note_text.empty? ? cannabis_details : \"#{cannabis_details} | #{note_text}\"\n   340→      end\n   341→\n   342→      # Get normalized names from LUT\n   343→      normalized_substance = JosieHealth::LUT::DrugLUT.normalize(substance_name) || substance_name\n   344→      normalized_route = JosieHealth::LUT::RouteLUT.normalize(route) || route\n   345→      substance_short = JosieHealth::LUT::DrugLUT.short_name(substance_name)\n   346→      route_short = JosieHealth::LUT::RouteLUT.short_name(route)\n   347→\n   348→      # Get metadata from drugs.json\n   349→      categories = get_substance_categories(normalized_substance)\n   350→      dose_classification = get_dose_classification(normalized_substance, normalized_route, \"#{format_dosage(dosage)}#{unit}\")\n   351→\n   352→      # Calculate local timestamp based on user's timezone\n   353→      local_timestamp = calculate_local_timestamp(timestamp, user_id)\n   354→\n   355→      # Store in Redis with all metadata\n   356→      @redis_client.store_dose(timestamp, user_id, substance_name, \"#{format_dosage(dosage)}#{unit}\", route, note_text, normalized_substance, normalized_route, categories, dose_classification, local_timestamp)\n   357→\n   358→      response.status_code = 201\n   359→\n   360→      response.print({\n   361→        \"data\" => {\n   362→          \"timestamp\"            => timestamp,\n   363→          \"local_timestamp\"      => local_timestamp,\n   364→          \"user_id\"              => user_id,\n   365→          \"canonical_substance\"  => substance_name,\n   366→          \"normalized_substance\" => normalized_substance,\n   367→          \"substance_short\"      => substance_short,\n   368→          \"dosage\"               => \"#{format_dosage(dosage)}#{unit}\",\n   369→          \"canonical_route\"      => route,\n   370→          \"normalized_route\"     => normalized_route,\n   371→          \"route_short\"          => route_short,\n   372→          \"source\"               => source,\n   373→        },\n   374→        \"_links\" => {\n   375→          \"self\"           => \"/v1/logs/substances\",\n   376→          \"user_logs\"      => \"/v1/metrics/users/#{URI.encode_path(user_id)}/listdose\",\n   377→          \"substance_info\" => \"/v1/substances/#{URI.encode_path(normalized_substance)}/info\",\n   378→          \"tally\"          => \"/v1/metrics/users/#{URI.encode_path(user_id)}/tally?substance=#{URI.encode_path(normalized_substance)}\",\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"86d54168-f3e0-4276-8cf5-8da58be86d1a","timestamp":"2026-02-04T12:28:00.549Z","toolUseResult":{"type":"text","file":{"filePath":"/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr","content":"      # Check if substance is a cannabis source (joint, cart, bowl, etc.)\n      cannabis_result = process_cannabis_dose(substance_name, dosage.to_s)\n      if cannabis_result\n        # Override with cannabis data\n        original_substance = substance_name\n        substance_name = \"cannabis\"\n        dosage = cannabis_result[:amount]\n        unit = cannabis_result[:unit]\n        # Prepend cannabis details to annotation\n        cannabis_details = cannabis_result[:details]\n        note_text = note_text.empty? ? cannabis_details : \"#{cannabis_details} | #{note_text}\"\n      end\n\n      # Get normalized names from LUT\n      normalized_substance = JosieHealth::LUT::DrugLUT.normalize(substance_name) || substance_name\n      normalized_route = JosieHealth::LUT::RouteLUT.normalize(route) || route\n      substance_short = JosieHealth::LUT::DrugLUT.short_name(substance_name)\n      route_short = JosieHealth::LUT::RouteLUT.short_name(route)\n\n      # Get metadata from drugs.json\n      categories = get_substance_categories(normalized_substance)\n      dose_classification = get_dose_classification(normalized_substance, normalized_route, \"#{format_dosage(dosage)}#{unit}\")\n\n      # Calculate local timestamp based on user's timezone\n      local_timestamp = calculate_local_timestamp(timestamp, user_id)\n\n      # Store in Redis with all metadata\n      @redis_client.store_dose(timestamp, user_id, substance_name, \"#{format_dosage(dosage)}#{unit}\", route, note_text, normalized_substance, normalized_route, categories, dose_classification, local_timestamp)\n\n      response.status_code = 201\n\n      response.print({\n        \"data\" => {\n          \"timestamp\"            => timestamp,\n          \"local_timestamp\"      => local_timestamp,\n          \"user_id\"              => user_id,\n          \"canonical_substance\"  => substance_name,\n          \"normalized_substance\" => normalized_substance,\n          \"substance_short\"      => substance_short,\n          \"dosage\"               => \"#{format_dosage(dosage)}#{unit}\",\n          \"canonical_route\"      => route,\n          \"normalized_route\"     => normalized_route,\n          \"route_short\"          => route_short,\n          \"source\"               => source,\n        },\n        \"_links\" => {\n          \"self\"           => \"/v1/logs/substances\",\n          \"user_logs\"      => \"/v1/metrics/users/#{URI.encode_path(user_id)}/listdose\",\n          \"substance_info\" => \"/v1/substances/#{URI.encode_path(normalized_substance)}/info\",\n          \"tally\"          => \"/v1/metrics/users/#{URI.encode_path(user_id)}/tally?substance=#{URI.encode_path(normalized_substance)}\",","numLines":50,"startLine":329,"totalLines":1334}},"sourceToolAssistantUUID":"9dea0a8d-b8af-42a3-9b7d-ce17d21266a6"}
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{"parentUuid":"a5bc07ef-eb52-4b98-bd1e-34e238f563d2","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/services","sessionId":"3f08f44a-a461-4640-9708-b1cbc3b2257a","version":"2.1.31","gitBranch":"HEAD","slug":"cuddly-launching-garden","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01Sf8PV14weNTuyQQz4im6wE","type":"tool_result","content":"  1059→  # Process cannabis dose - returns {amount, unit, details} if substance is a cannabis source, nil otherwise\n  1060→  private def process_cannabis_dose(substance_name : String, dosage : String) : NamedTuple(amount: Float64, unit: String, details: String)?\n  1061→    # Check if substance is in the cannabis database\n  1062→    source_info = JosieHealth::LUT.lookup_cannabis(substance_name)\n  1063→    return nil unless source_info\n  1064→\n  1065→    # Parse dosage for serving units (e.g., \"5puff\", \"1/3\", \"2hit\")\n  1066→    parsed = JosieHealth::LUT.parse_cannabis_dosage(dosage)\n  1067→\n  1068→    unless parsed\n  1069→      # Try parsing as plain number (e.g., \"2\" = 2 default servings)\n  1070→      if count = dosage.to_f?\n  1071→        parsed = {count: count, serving: nil}\n  1072→      else\n  1073→        return nil\n  1074→      end\n  1075→    end\n  1076→\n  1077→    # Calculate amount based on count and default\n  1078→    count = parsed[:count]\n  1079→    amount = (source_info[:default_amount] * count).round(2)\n  1080→    unit = source_info[:unit]\n  1081→\n  1082→    # Build details string\n  1083→    count_str = count == count.to_i ? count.to_i.to_s : count.round(2).to_s\n  1084→    serving_str = parsed[:serving] ? \"#{count_str}#{parsed[:serving]}\" : count_str\n  1085→    details = \"#{substance_name} #{serving_str} (#{amount}#{unit})\"\n  1086→\n  1087→    {amount: amount, unit: unit, details: details}\n  1088→  end\n  1089→\n  1090→  # Process injectable medication doses (convert ml to mg)\n  1091→  # Supports @concentration syntax (e.g., \"een@20\" for 20mg/ml override)\n  1092→  private def process_meds_dose(substance_name : String, dosage : String, unit : String) : NamedTuple(mg: Float64, canonical_name: String, details: String)?\n  1093→    # Only process if unit is ml\n  1094→    return nil unless unit.downcase == \"ml\"\n  1095→\n  1096→    # Try to calculate the dose using the MedsLUT\n  1097→    result = JosieHealth::LUT.calculate_meds_dose(substance_name, dosage, unit)\n  1098→    return nil unless result\n  1099→\n  1100→    {mg: result[:mg], canonical_name: result[:canonical_name], details: result[:annotation]}\n  1101→  end\n  1102→\n  1103→  # Parse raw_dose into dosage, substance, route, note\n  1104→  # Uses RouteLUT to find route - everything before is substance, after is note\n  1105→  private def parse_raw_dose(raw : String) : {String, String, String, String}\n  1106→    words = raw.split(' ').reject(&.empty?)\n  1107→    return {\"\", \"\", \"oral\", \"\"} if words.empty?\n  1108→\n  1109→    # First word should be dosage - parse math expressions (e.g., 47.5mg/2 -> 23.75mg)\n  1110→    raw_dosage = words[0]\n  1111→    if parsed = JosieHealth::Utils::Dosage.parse_any(raw_dosage)\n  1112→      dosage = \"#{parsed[:amount]}#{parsed[:unit]}\"\n  1113→    else\n  1114→      dosage = raw_dosage\n  1115→    end\n  1116→    remaining = words[1..-1]\n  1117→\n  1118→    return {dosage, \"\", \"oral\", \"\"} if remaining.empty?\n  1119→    return {dosage, remaining[0], \"oral\", \"\"} if remaining.size == 1\n  1120→\n  1121→    # Find first word that's a known route\n  1122→    route_index = remaining.index { |w| JosieHealth::LUT::RouteLUT.normalize(w) }\n  1123→\n  1124→    if route_index\n  1125→      substance = remaining[0...route_index].join(\" \")\n  1126→      route = JosieHealth::LUT::RouteLUT.normalize(remaining[route_index]).not_nil!\n  1127→      note = route_index + 1 < remaining.size ? remaining[(route_index + 1)..-1].join(\" \") : \"\"\n  1128→    else\n  1129→      substance = remaining.join(\" \")\n  1130→      route = \"oral\"\n  1131→      note = \"\"\n  1132→    end\n  1133→    {dosage, substance, route, note}\n  1134→  end\n  1135→\n  1136→  private def handle_get_dose(request : HTTP::Request, response : HTTP::Server::Response, timestamp : String)\n  1137→    begin\n  1138→      user_id = request.query_params[\"user_id\"]?\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"5600f211-e36c-414e-aaec-c4049ddf6b17","timestamp":"2026-02-04T12:28:09.254Z","toolUseResult":{"type":"text","file":{"filePath":"/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr","content":"  # Process cannabis dose - returns {amount, unit, details} if substance is a cannabis source, nil otherwise\n  private def process_cannabis_dose(substance_name : String, dosage : String) : NamedTuple(amount: Float64, unit: String, details: String)?\n    # Check if substance is in the cannabis database\n    source_info = JosieHealth::LUT.lookup_cannabis(substance_name)\n    return nil unless source_info\n\n    # Parse dosage for serving units (e.g., \"5puff\", \"1/3\", \"2hit\")\n    parsed = JosieHealth::LUT.parse_cannabis_dosage(dosage)\n\n    unless parsed\n      # Try parsing as plain number (e.g., \"2\" = 2 default servings)\n      if count = dosage.to_f?\n        parsed = {count: count, serving: nil}\n      else\n        return nil\n      end\n    end\n\n    # Calculate amount based on count and default\n    count = parsed[:count]\n    amount = (source_info[:default_amount] * count).round(2)\n    unit = source_info[:unit]\n\n    # Build details string\n    count_str = count == count.to_i ? count.to_i.to_s : count.round(2).to_s\n    serving_str = parsed[:serving] ? \"#{count_str}#{parsed[:serving]}\" : count_str\n    details = \"#{substance_name} #{serving_str} (#{amount}#{unit})\"\n\n    {amount: amount, unit: unit, details: details}\n  end\n\n  # Process injectable medication doses (convert ml to mg)\n  # Supports @concentration syntax (e.g., \"een@20\" for 20mg/ml override)\n  private def process_meds_dose(substance_name : String, dosage : String, unit : String) : NamedTuple(mg: Float64, canonical_name: String, details: String)?\n    # Only process if unit is ml\n    return nil unless unit.downcase == \"ml\"\n\n    # Try to calculate the dose using the MedsLUT\n    result = JosieHealth::LUT.calculate_meds_dose(substance_name, dosage, unit)\n    return nil unless result\n\n    {mg: result[:mg], canonical_name: result[:canonical_name], details: result[:annotation]}\n  end\n\n  # Parse raw_dose into dosage, substance, route, note\n  # Uses RouteLUT to find route - everything before is substance, after is note\n  private def parse_raw_dose(raw : String) : {String, String, String, String}\n    words = raw.split(' ').reject(&.empty?)\n    return {\"\", \"\", \"oral\", \"\"} if words.empty?\n\n    # First word should be dosage - parse math expressions (e.g., 47.5mg/2 -> 23.75mg)\n    raw_dosage = words[0]\n    if parsed = JosieHealth::Utils::Dosage.parse_any(raw_dosage)\n      dosage = \"#{parsed[:amount]}#{parsed[:unit]}\"\n    else\n      dosage = raw_dosage\n    end\n    remaining = words[1..-1]\n\n    return {dosage, \"\", \"oral\", \"\"} if remaining.empty?\n    return {dosage, remaining[0], \"oral\", \"\"} if remaining.size == 1\n\n    # Find first word that's a known route\n    route_index = remaining.index { |w| JosieHealth::LUT::RouteLUT.normalize(w) }\n\n    if route_index\n      substance = remaining[0...route_index].join(\" \")\n      route = JosieHealth::LUT::RouteLUT.normalize(remaining[route_index]).not_nil!\n      note = route_index + 1 < remaining.size ? remaining[(route_index + 1)..-1].join(\" \") : \"\"\n    else\n      substance = remaining.join(\" \")\n      route = \"oral\"\n      note = \"\"\n    end\n    {dosage, substance, route, note}\n  end\n\n  private def handle_get_dose(request : HTTP::Request, response : HTTP::Server::Response, timestamp : String)\n    begin\n      user_id = request.query_params[\"user_id\"]?","numLines":80,"startLine":1059,"totalLines":1334}},"sourceToolAssistantUUID":"a5bc07ef-eb52-4b98-bd1e-34e238f563d2"}
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{"parentUuid":"8518805f-b5eb-45a4-9b31-d2affdec4b42","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/services","sessionId":"3f08f44a-a461-4640-9708-b1cbc3b2257a","version":"2.1.31","gitBranch":"HEAD","slug":"cuddly-launching-garden","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_012GEG25bCx9ZZns5nChqSRD","type":"tool_result","content":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-120-    def self.is_injectable_med?(name : String) : Bool\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-121-      MedsLUT.is_injectable_med?(name)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-122-    end\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-123-\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-124-    # Calculate medication dose from ml to mg\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-125-    # Supports @concentration syntax (e.g., \"een@20\" for 20mg/ml)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-126-    def self.calculate_meds_dose(substance : String, dosage : String, unit : String)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-127-      MedsLUT.calculate_dose(substance, dosage, unit)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-128-    end\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-129-\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-130-    # Parse substance name with optional concentration override\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-131-    def self.parse_meds_concentration(name : String)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-132-      MedsLUT.parse_substance_concentration(name)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-133-    end\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-134-\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-135-    # ============================================\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-136-    # Cannabis LUT methods\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-137-    # ============================================\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-138-\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-139-    # Look up a cannabis source by name (joint, cart, bowl, etc.)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr:140:    def self.lookup_cannabis(name : String)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-141-      CannabisLUT.lookup_source(name)\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-142-    end\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-143-\n/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr-144-    # Check if a substance is ip(\"g\")` usage is safe in practice because inputs reaching that code path must have passed the regex `^(\\d+(?:\\.\\d+)?)g$`, which guarantees exactly one trailing `g` preceded by digits.\n- The vendored copy and source LUT code are functionally identical.\n\n---\n\n## Issues\n\n### Important (should fix)\n\n**1. `parse_dosage` returns `count: Int32` which truncates decimal grams**\n\nFile: `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr`, line 133\n\n```crystal\nreturn {count: count_f.to_i, serving: \"g\", volume_ml: 0}\n```\n\nFor input `\"0.5g\"`, `count_f = 0.5` and `count_f.to_i = 0`. For `\"1.5g\"`, `count_f.to_i = 1`. The `count` field in the returned tuple is silently truncated to zero or rounded down.\n\nThis does not currently cause a *functional* bug because neither `calculate_dose` nor `process_caffeine_dose` uses the `count` field for the gram path -- they both re-parse the weight from the original dosage string via `rstrip(\"g\").to_f`. However, the `count` field is semantically wrong and misleading to any future consumer of `parse_dosage`. A caller that reasonably expects `count` to represent the gram weight will get incorrect data.\n\nRecommendation: Either change the return type to use `Float64` for `count` (which would be a breaking change to the named tuple signature), or document that `count` is meaningless when `serving == \"g\"` and the caller should re-parse from the dosage string. A more robust approach would be to store the original float value somewhere in the return tuple, perhaps as an additional field.\n\n**2. Annotation formatting inconsistency: `2.0g` instead of `2g` for whole gram values**\n\nFiles:\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr`, line 164\n- `/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr`, line 1143\n\n```crystal\nweight_g = dosage.rstrip(\"g\").to_f\ndetails = \"#{canonical} #{weight_g}g = #{caffeine_mg.to_i}mg\"\n```\n\nWhen dosage is `\"2g\"`, `weight_g` is `2.0` (Float64), so the annotation reads `matcha 2.0g = 70mg` rather than `matcha 2g = 70mg`. The format for describing the user's dose in this requirement was `matcha 2.0g = 70mg`, but if you want consistency with how other parts of the codebase format numbers, the `format_dosage` helper in log_handler.cr (line 51) already strips `.0` from whole numbers. Consider using the same pattern here:\n\n```crystal\nweight_str = weight_g == weight_g.to_i ? weight_g.to_i.to_s : weight_g.to_s\ndetails = \"#{canonical} #{weight_str}g = #{caffeine_mg.to_i}mg\"\n```\n\n**3. Annotation naming difference between `CaffeineLUT.calculate_dose` and `process_caffeine_dose`**\n\nIn `CaffeineLUT.calculate_dose` (caffeine_lut.cr, line 164), the annotation uses `canonical` (the resolved alias name, always the brand's canonical key like `\"matcha\"`). In `process_caffeine_dose` (log_handler.cr, line 1143), the annotation uses `substance_name` (the user-supplied input). So logging `2g matchatea` produces:\n- Via LUT directly: `matcha 2.0g = 70mg`\n- Via log_handler: `matchatea 2.0g = 70mg`\n\nThis is a pre-existing inconsistency (the volume-based path also has this same difference), but this change replicates it into the new gram path. Since `process_caffeine_dose` is the code path that actually runs in production for dose logging, this is primarily a consistency observation. If you want parity with the LUT, resolve the alias in the handler too.\n\n**4. Vendored source comments are ahead of the source repo**\n\nThe vendored copy at `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/caffeine_lut.cr` has updated comments (lines 114 and 119 include `\"2g\"` in examples) that the source repo at `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr` does not. The source repo comments still say `\"2cans\", \"500ml\", \"1cup\"` without mentioning `\"2g\"`. These should be synchronized -- ideally the source repo should be the source of truth and the vendor should be refreshed from it, not the other way around.\n\n### Suggestions (nice to have)\n\n**5. No tests for the new gram conversion path**\n\nThere are no spec files in the josie-health-lut repo covering `CaffeineLUT` at all (only `fuzzy_spec.cr` exists), and the API spec files in `services/core/spec/` do not test `process_caffeine_dose`. While this is a pre-existing gap, introducing new behavior without at least a minimal test increases risk of regression. Consider adding tests for:\n- `\"2g\"` matcha -> 70mg caffeine\n- `\"1.5g\"` matcha -> 52.5mg caffeine\n- `\"0.5g\"` matcha -> 17.5mg caffeine\n- `\"2g\"` coffee -> nil (non-powder brand rejects grams)\n- Legacy mode: dosage=\"2\", unit=\"g\", substance=\"matcha\" -> 70mg\n\n**6. `caffeine_mg.to_i` in annotation truncates rather than rounds**\n\nBoth caffeine_lut.cr line 164 and log_handler.cr line 1143 use `caffeine_mg.to_i` in the annotation string. For `1.5g matcha`, `caffeine_mg = 52.5`, and `52.5.to_i = 52`, so the annotation says `52mg` while the actual stored value is `52.5`. This is a minor display truncation (not a data loss -- the `:mg`/`:caffeine_mg` field retains the Float64). If you want the annotation to be more precise, use `.round.to_i` or show the decimal.\n\n**7. Only matcha currently has `caffeine_mg_per_g` -- consider whether other powders should too**\n\nYerba mate, for instance, is often prepared from loose leaf measured in grams. Instant coffee is also commonly measured in grams (roughly 60mg caffeine per 2g serving). The architecture supports adding `caffeine_mg_per_g` to any brand, which is good. This is more of a data completeness note than a code issue.\n\n---\n\n## Plan Alignment\n\nThe implementation matches the requirements: `2g matcha` now converts to `caffeine 70mg` with an annotation describing the conversion. The approach of adding `caffeine_mg_per_g` to caffeine.json and wiring it through both the LUT library and the API handler is well-structured. The legacy mode handling was not explicitly in the requirements but is a necessary addition for backward compatibility with clients that send dosage and unit as separate fields.\n\n## Files Reviewed\n\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/data/caffeine.json` -- matcha entry with new `caffeine_mg_per_g: 35` field\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr` -- `@@powder_data`, `lookup_powder_mg_per_g()`, gram regex in `parse_dosage`, gram path in `calculate_dose`\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr` -- new `lookup_caffeine_powder_mg_per_g` facade method, updated docstring\n- `/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr` -- legacy mode `effective_dosage` assembly, gram calculation in `process_caffeine_dose`\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/caffeine_lut.cr` -- vendored copy (functionally identical, minor comment drift)\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/josie-health-lut.cr` -- vendored copy (identical)\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/data/caffeine.json` -- vendored copy (identical)\n- `/home/josie/development/personal/josiedot/health/josie-health-utils/src/dosage.cr` -- reviewed for context on `parse_any` and `looks_like_dosage?` (unchanged by this PR, correctly recognizes `\"2.5g\"` as a dosage)"},{"type":"text","text":"agentId: a3e437df78ac4af10 (for resuming to continue this agent's work if needed)\n<usage>total_tokens: 59034\ntool_uses: 47\nduration_ms: 588744</usage>"}]}]},"uuid":"724518d2-b02f-46a2-8271-50cb841841e7","timestamp":"2026-03-06T16:56:45.927Z","toolUseResult":{"status":"completed","prompt":"## Code Review Request\n\n**What was implemented:** Fix for GitHub issue #62 - matcha powder weight (grams) not converting to caffeine. Added gram-based caffeine conversion for powder sources like matcha.\n\n**Requirements:** When a user logs a dose like `;id 2g matcha`, it should convert to caffeine using mg-per-gram data (35mg/g for matcha), resulting in `caffeine 70mg` with annotation `matcha 2.0g = 70mg`. Previously the `g` unit was unrecognized and the dose was logged without caffeine conversion.\n\n**Description:** \n- Added `caffeine_mg_per_g: 35` to matcha entry in caffeine.json\n- Added `@@powder_data` map and `lookup_powder_mg_per_g()` in CaffeineLUT\n- Added `g` to parse_dosage regex\n- Added gram-based calculation path in both `CaffeineLUT.calculate_dose` and `log_handler.cr:process_caffeine_dose`\n- Handled legacy mode where unit=\"g\" arrives separately from dosage number\n\n**Files changed (josie-health-lut repo):**\n- `data/caffeine.json` (+ vendored copy at `services/core/lib/josie-health-lut/data/caffeine.json`)\n- `src/caffeine_lut.cr` (+ vendored copy at `services/core/lib/josie-health-lut/src/caffeine_lut.cr`) \n- `src/josie-health-lut.cr` (+ vendored copy at `services/core/lib/josie-health-lut/src/josie-health-lut.cr`)\n\n**File changed (services repo):**\n- `services/core/src/handlers/log_handler.cr`\n\nPlease review these files critically. Focus on:\n1. Correctness of the gram-to-caffeine conversion logic\n2. Edge cases (decimal grams like \"1.5g\", \"0.5g\"; zero grams; non-powder brands with \"g\" unit like \"2g coffee\")\n3. Whether `rstrip(\"g\")` is safe for all inputs\n4. Whether the `parse_dosage` return type (count: Int32) loses precision for decimal gram values\n5. Consistency between CaffeineLUT.calculate_dose and process_caffeine_dose in log_handler.cr\n6. Whether existing behavior for non-powder caffeine sources is preserved\n7. Any risk of breaking existing tests or production behavior\n\nRead all changed files to do the review.","agentId":"a3e437df78ac4af10","content":[{"type":"text","text":"Now I have a thorough understanding of the implementation. Let me compile my review.\n\n---\n\n# Code Review: Matcha Powder Gram-to-Caffeine Conversion (Issue #62)\n\n## Summary\n\nThe implementation adds gram-based caffeine conversion for powder sources like matcha. The core logic is correct for the primary use case (`2g matcha` -> `caffeine 70mg`), and the approach of adding `caffeine_mg_per_g` as an opt-in field on specific brands is clean and extensible. I found no critical blockers, but there are several important issues that should be addressed.\n\n## What Was Done Well\n\n- The design is sound: powder data is opt-in per brand, meaning non-powder caffeine sources like \"coffee\" gracefully reject gram-based dosage (returning `nil` from `lookup_powder_mg_per_g`).\n- Legacy mode handling (where `unit=\"g\"` arrives separately from the dosage number) is correctly addressed with the `effective_dosage` assembly in `process_caffeine_dose`.\n- The `rstrip(\"g\")` usage is safe in practice because inputs reaching that code path must have passed the regex `^(\\d+(?:\\.\\d+)?)g$`, which guarantees exactly one trailing `g` preceded by digits.\n- The vendored copy and source LUT code are functionally identical.\n\n---\n\n## Issues\n\n### Important (should fix)\n\n**1. `parse_dosage` returns `count: Int32` which truncates decimal grams**\n\nFile: `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr`, line 133\n\n```crystal\nreturn {count: count_f.to_i, serving: \"g\", volume_ml: 0}\n```\n\nFor input `\"0.5g\"`, `count_f = 0.5` and `count_f.to_i = 0`. For `\"1.5g\"`, `count_f.to_i = 1`. The `count` field in the returned tuple is silently truncated to zero or rounded down.\n\nThis does not currently cause a *functional* bug because neither `calculate_dose` nor `process_caffeine_dose` uses the `count` field for the gram path -- they both re-parse the weight from the original dosage string via `rstrip(\"g\").to_f`. However, the `count` field is semantically wrong and misleading to any future consumer of `parse_dosage`. A caller that reasonably expects `count` to represent the gram weight will get incorrect data.\n\nRecommendation: Either change the return type to use `Float64` for `count` (which would be a breaking change to the named tuple signature), or document that `count` is meaningless when `serving == \"g\"` and the caller should re-parse from the dosage string. A more robust approach would be to store the original float value somewhere in the return tuple, perhaps as an additional field.\n\n**2. Annotation formatting inconsistency: `2.0g` instead of `2g` for whole gram values**\n\nFiles:\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr`, line 164\n- `/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr`, line 1143\n\n```crystal\nweight_g = dosage.rstrip(\"g\").to_f\ndetails = \"#{canonical} #{weight_g}g = #{caffeine_mg.to_i}mg\"\n```\n\nWhen dosage is `\"2g\"`, `weight_g` is `2.0` (Float64), so the annotation reads `matcha 2.0g = 70mg` rather than `matcha 2g = 70mg`. The format for describing the user's dose in this requirement was `matcha 2.0g = 70mg`, but if you want consistency with how other parts of the codebase format numbers, the `format_dosage` helper in log_handler.cr (line 51) already strips `.0` from whole numbers. Consider using the same pattern here:\n\n```crystal\nweight_str = weight_g == weight_g.to_i ? weight_g.to_i.to_s : weight_g.to_s\ndetails = \"#{canonical} #{weight_str}g = #{caffeine_mg.to_i}mg\"\n```\n\n**3. Annotation naming difference between `CaffeineLUT.calculate_dose` and `process_caffeine_dose`**\n\nIn `CaffeineLUT.calculate_dose` (caffeine_lut.cr, line 164), the annotation uses `canonical` (the resolved alias name, always the brand's canonical key like `\"matcha\"`). In `process_caffeine_dose` (log_handler.cr, line 1143), the annotation uses `substance_name` (the user-supplied input). So logging `2g matchatea` produces:\n- Via LUT directly: `matcha 2.0g = 70mg`\n- Via log_handler: `matchatea 2.0g = 70mg`\n\nThis is a pre-existing inconsistency (the volume-based path also has this same difference), but this change replicates it into the new gram path. Since `process_caffeine_dose` is the code path that actually runs in production for dose logging, this is primarily a consistency observation. If you want parity with the LUT, resolve the alias in the handler too.\n\n**4. Vendored source comments are ahead of the source repo**\n\nThe vendored copy at `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/caffeine_lut.cr` has updated comments (lines 114 and 119 include `\"2g\"` in examples) that the source repo at `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr` does not. The source repo comments still say `\"2cans\", \"500ml\", \"1cup\"` without mentioning `\"2g\"`. These should be synchronized -- ideally the source repo should be the source of truth and the vendor should be refreshed from it, not the other way around.\n\n### Suggestions (nice to have)\n\n**5. No tests for the new gram conversion path**\n\nThere are no spec files in the josie-health-lut repo covering `CaffeineLUT` at all (only `fuzzy_spec.cr` exists), and the API spec files in `services/core/spec/` do not test `process_caffeine_dose`. While this is a pre-existing gap, introducing new behavior without at least a minimal test increases risk of regression. Consider adding tests for:\n- `\"2g\"` matcha -> 70mg caffeine\n- `\"1.5g\"` matcha -> 52.5mg caffeine\n- `\"0.5g\"` matcha -> 17.5mg caffeine\n- `\"2g\"` coffee -> nil (non-powder brand rejects grams)\n- Legacy mode: dosage=\"2\", unit=\"g\", substance=\"matcha\" -> 70mg\n\n**6. `caffeine_mg.to_i` in annotation truncates rather than rounds**\n\nBoth caffeine_lut.cr line 164 and log_handler.cr line 1143 use `caffeine_mg.to_i` in the annotation string. For `1.5g matcha`, `caffeine_mg = 52.5`, and `52.5.to_i = 52`, so the annotation says `52mg` while the actual stored value is `52.5`. This is a minor display truncation (not a data loss -- the `:mg`/`:caffeine_mg` field retains the Float64). If you want the annotation to be more precise, use `.round.to_i` or show the decimal.\n\n**7. Only matcha currently has `caffeine_mg_per_g` -- consider whether other powders should too**\n\nYerba mate, for instance, is often prepared from loose leaf measured in grams. Instant coffee is also commonly measured in grams (roughly 60mg caffeine per 2g serving). The architecture supports adding `caffeine_mg_per_g` to any brand, which is good. This is more of a data completeness note than a code issue.\n\n---\n\n## Plan Alignment\n\nThe implementation matches the requirements: `2g matcha` now converts to `caffeine 70mg` with an annotation describing the conversion. The approach of adding `caffeine_mg_per_g` to caffeine.json and wiring it through both the LUT library and the API handler is well-structured. The legacy mode handling was not explicitly in the requirements but is a necessary addition for backward compatibility with clients that send dosage and unit as separate fields.\n\n## Files Reviewed\n\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/data/caffeine.json` -- matcha entry with new `caffeine_mg_per_g: 35` field\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr` -- `@@powder_data`, `lookup_powder_mg_per_g()`, gram regex in `parse_dosage`, gram path in `calculate_dose`\n- `/home/josie/development/personal/josiedot/health/josie-health-lut/src/josie-health-lut.cr` -- new `lookup_caffeine_powder_mg_per_g` facade method, updated docstring\n- `/home/josie/development/personal/josiedot/health/services/core/src/handlers/log_handler.cr` -- legacy mode `effective_dosage` assembly, gram calculation in `process_caffeine_dose`\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/caffeine_lut.cr` -- vendored copy (functionally identical, minor comment drift)\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/src/josie-health-lut.cr` -- vendored copy (identical)\n- `/home/josie/development/personal/josiedot/health/services/core/lib/josie-health-lut/data/caffeine.json` -- vendored copy (identical)\n- `/home/josie/development/personal/josiedot/health/josie-health-utils/src/dosage.cr` -- reviewed for context on `parse_any` and `looks_like_dosage?` (unchanged by this PR, correctly recognizes `\"2.5g\"` as a dosage)"}],"totalDurationMs":588744,"totalTokens":59034,"totalToolUseCount":47,"usage":{"input_tokens":1,"cache_creation_input_tokens":335,"cache_read_input_tokens":56160,"output_tokens":2538,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":0,"ephemeral_5m_input_tokens":335},"inference_geo":"","iterations":[],"speed":"standard"}},"sourceToolAssistantUUID":"a68de4c0-1757-45b6-ad34-232ed1d77b9c"}
{"parentUuid":"724518d2-b02f-46a2-8271-50cb841841e7","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","message":{"model":"claude-opus-4-6","id":"msg_018DUjGgWMkw2iurB7EfS7eR","type":"message","role":"assistant","content":[{"type":"text","text":"Good review. Let me address the important findings.\n\n**Issue 1 -- `count` truncates decimal grams:** Real bug for `0.5g`. The `count` field is 0, and while the current gram path re-parses from the dosage string, a future caller would get wrong data. Fix: at minimum, document it. Better: avoid the truncation.\n\n**Issue 2 -- `2.0g` formatting:** Minor annoyance. Easy fix.\n\n**Issue 3 -- annotation uses `substance_name` vs `canonical`:** Pre-existing pattern, but worth aligning.\n\n**Issue 4 -- vendored comment drift:** My fault, easy sync.\n\nLet me fix issues 1, 2, and 4 now."}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":3304,"cache_read_input_tokens":77645,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":3304},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYnBMmk2ida3FfzGHX2vs","type":"assistant","uuid":"2d3bf33a-7df4-4cd8-8d53-85d8a781e7bc","timestamp":"2026-03-06T16:56:54.399Z"}
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{"parentUuid":"ef66e23d-1534-4107-9bde-f4881ad3ee1a","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01CNWpyMf7DK6BpCYK1qPNBh","type":"tool_result","content":"   113→\n   114→    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"\n   115→    # Returns {count, serving_type, volume_ml} or nil if not parseable\n   116→    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?\n   117→      normalized = dosage.downcase.strip\n   118→\n   119→      # Try to match \"Nunit\" pattern (e.g., \"2cans\", \"1cup\", \"500ml\")\n   120→      if match = normalized.match(/^(\\d+(?:\\.\\d+)?)(ml|g|can|cans|bottle|bottles|cup|cups|mug|mugs|shot|shots)?$/)\n   121→        count_str = match[1]\n   122→        serving = match[2]?\n   123→\n   124→        # Handle decimal counts\n   125→        count_f = count_str.to_f\n   126→        count = count_f.to_i\n   127→\n   128→        if serving == \"ml\"\n   129→          # Direct ml specification\n   130→          return {count: 1, serving: \"ml\", volume_ml: count_f.to_i}\n   131→        elsif serving == \"g\"\n   132→          # Gram specification for powder sources\n   133→          return {count: count_f.to_i, serving: \"g\", volume_ml: 0}\n   134→        elsif serving && SERVING_SIZES.has_key?(serving)\n   135→          volume_ml = SERVING_SIZES[serving] * count\n   136→          return {count: count, serving: serving, volume_ml: volume_ml}\n   137→        elsif serving.nil?\n   138→          # Just a number, assume count of default serving\n   139→          return {count: count, serving: nil, volume_ml: 0}\n   140→        end\n   141→      end\n   142→\n   143→      nil\n   144→    end\n   145→\n   146→    # Full caffeine dose calculation\n   147→    # Input: dosage string, substance name\n   148→    # Returns: {caffeine_mg, annotation} or nil\n   149→    def self.calculate_dose(dosage : String, substance : String) : NamedTuple(caffeine_mg: Float64, annotation: String)?\n   150→      parsed = parse_dosage(dosage)\n   151→      return nil unless parsed\n   152→\n   153→      brand_info = lookup_brand(substance)\n   154→      return nil unless brand_info\n   155→\n   156→      canonical = resolve_alias(substance)\n   157→\n   158→      # Gram-based calculation for powder sources\n   159→      if parsed[:serving] == \"g\"\n   160→        mg_per_g = lookup_powder_mg_per_g(substance)\n   161→        return nil unless mg_per_g\n   162→        weight_g = dosage.rstrip(\"g\").to_f\n   163→        caffeine_mg = (weight_g * mg_per_g).round(1)\n   164→        details = \"#{canonical} #{weight_g}g = #{caffeine_mg.to_i}mg\"\n   165→        return {caffeine_mg: caffeine_mg, annotation: details}\n   166→      end\n   167→\n   168→      # Determine volume\n   169→      volume_ml = if parsed[:volume_ml] > 0\n   170→                    parsed[:volume_ml]\n   171→                  else\n   172→                    parsed[:count] * brand_info[:default_ml]"}]},"uuid":"c49b48b1-5587-4550-b23c-c879c9f35611","timestamp":"2026-03-06T16:56:55.093Z","toolUseResult":{"type":"text","file":{"filePath":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr","content":"\n    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?\n      normalized = dosage.downcase.strip\n\n      # Try to match \"Nunit\" pattern (e.g., \"2cans\", \"1cup\", \"500ml\")\n      if match = normalized.match(/^(\\d+(?:\\.\\d+)?)(ml|g|can|cans|bottle|bottles|cup|cups|mug|mugs|shot|shots)?$/)\n        count_str = match[1]\n        serving = match[2]?\n\n        # Handle decimal counts\n        count_f = count_str.to_f\n        count = count_f.to_i\n\n        if serving == \"ml\"\n          # Direct ml specification\n          return {count: 1, serving: \"ml\", volume_ml: count_f.to_i}\n        elsif serving == \"g\"\n          # Gram specification for powder sources\n          return {count: count_f.to_i, serving: \"g\", volume_ml: 0}\n        elsif serving && SERVING_SIZES.has_key?(serving)\n          volume_ml = SERVING_SIZES[serving] * count\n          return {count: count, serving: serving, volume_ml: volume_ml}\n        elsif serving.nil?\n          # Just a number, assume count of default serving\n          return {count: count, serving: nil, volume_ml: 0}\n        end\n      end\n\n      nil\n    end\n\n    # Full caffeine dose calculation\n    # Input: dosage string, substance name\n    # Returns: {caffeine_mg, annotation} or nil\n    def self.calculate_dose(dosage : String, substance : String) : NamedTuple(caffeine_mg: Float64, annotation: String)?\n      parsed = parse_dosage(dosage)\n      return nil unless parsed\n\n      brand_info = lookup_brand(substance)\n      return nil unless brand_info\n\n      canonical = resolve_alias(substance)\n\n      # Gram-based calculation for powder sources\n      if parsed[:serving] == \"g\"\n        mg_per_g = lookup_powder_mg_per_g(substance)\n        return nil unless mg_per_g\n        weight_g = dosage.rstrip(\"g\").to_f\n        caffeine_mg = (weight_g * mg_per_g).round(1)\n        details = \"#{canonical} #{weight_g}g = #{caffeine_mg.to_i}mg\"\n        return {caffeine_mg: caffeine_mg, annotation: details}\n      end\n\n      # Determine volume\n      volume_ml = if parsed[:volume_ml] > 0\n                    parsed[:volume_ml]\n                  else\n                    parsed[:count] * brand_info[:default_ml]","numLines":60,"startLine":113,"totalLines":191}},"sourceToolAssistantUUID":"ef66e23d-1534-4107-9bde-f4881ad3ee1a"}
{"parentUuid":"c49b48b1-5587-4550-b23c-c879c9f35611","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","message":{"model":"claude-opus-4-6","id":"msg_012s1WjHD7m88WCFMjV7cSuL","type":"message","role":"assistant","content":[{"type":"text","text":"Fix issue 1 (truncated count) and issue 2 (2.0g formatting) in the source LUT:"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1205,"cache_read_input_tokens":80949,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":1205},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYnBNStjieJrPJNLjQnJL","type":"assistant","uuid":"a4ef9cea-a05e-40d6-9464-b3c40f3f5c26","timestamp":"2026-03-06T16:57:00.994Z"}
{"parentUuid":"a4ef9cea-a05e-40d6-9464-b3c40f3f5c26","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","message":{"model":"claude-opus-4-6","id":"msg_012s1WjHD7m88WCFMjV7cSuL","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01MwXH9P777pcfoE2wpwzzKQ","name":"Edit","input":{"replace_all":false,"file_path":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr","old_string":"    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?","new_string":"    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\", \"2g\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    # Note: for \"g\" serving, count is truncated to Int32; use the original dosage string for precise weight\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?"},"caller":{"type":"direct"}}],"stop_reason":"tool_use","stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":1205,"cache_read_input_tokens":80949,"output_tokens":359,"server_tool_use":{"web_search_requests":0,"web_fetch_requests":0},"service_tier":"standard","cache_creation":{"ephemeral_1h_input_tokens":1205,"ephemeral_5m_input_tokens":0},"inference_geo":"","iterations":[],"speed":"standard"}},"requestId":"req_011CYnBNStjieJrPJNLjQnJL","type":"assistant","uuid":"1752c4c2-9b31-4a98-9140-cd2a9a0fc985","timestamp":"2026-03-06T16:57:03.873Z"}
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{"parentUuid":"1752c4c2-9b31-4a98-9140-cd2a9a0fc985","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","type":"user","message":{"role":"user","content":[{"tool_use_id":"toolu_01MwXH9P777pcfoE2wpwzzKQ","type":"tool_result","content":"The file /home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr has been updated successfully."}]},"uuid":"897efc66-3bc1-4f4b-8258-c5a3e0a127c8","timestamp":"2026-03-06T16:57:15.998Z","toolUseResult":{"filePath":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr","oldString":"    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?","newString":"    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\", \"2g\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    # Note: for \"g\" serving, count is truncated to Int32; use the original dosage string for precise weight\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?","originalFile":"require \"json\"\nrequire \"./data_files\"\n\nmodule JosieHealth::LUT\n  module CaffeineLUT\n    # Serving sizes in ml\n    SERVING_SIZES = {\n      \"can\"     => 355,\n      \"cans\"    => 355,\n      \"bottle\"  => 500,\n      \"bottles\" => 500,\n      \"cup\"     => 240,\n      \"cups\"    => 240,\n      \"mug\"     => 350,\n      \"mugs\"    => 350,\n      \"shot\"    => 30,\n      \"shots\"   => 30,\n    }\n\n    # Category defaults\n    CATEGORY_DEFAULTS = {\n      \"energy_drink\" => {caffeine_mg: 160, default_ml: 500},\n      \"energy_shot\"  => {caffeine_mg: 200, default_ml: 60},\n      \"coffee\"       => {caffeine_mg: 95, default_ml: 240},\n      \"tea\"          => {caffeine_mg: 50, default_ml: 240},\n      \"soda\"         => {caffeine_mg: 40, default_ml: 355},\n    }\n\n    @@brands : Hash(String, NamedTuple(caffeine_mg: Int32, category: String, default_ml: Int32))?\n    @@powder_data : Hash(String, Int32)?\n    @@alias_map : Hash(String, String)?\n    @@loaded = false\n\n    # Load caffeine data from embedded JSON\n    def self.load_data\n      return if @@loaded\n\n      begin\n        json = DataFiles.caffeine\n\n        @@brands = {} of String => NamedTuple(caffeine_mg: Int32, category: String, default_ml: Int32)\n        @@powder_data = {} of String => Int32\n        @@alias_map = {} of String => String\n\n        if brands_json = json[\"brands\"]?\n          brands_json.as_h.each do |name, data|\n            canonical_name = name.to_s\n            @@brands.not_nil![canonical_name] = {\n              caffeine_mg: data[\"caffeine_mg\"].as_i,\n              category:    data[\"category\"].as_s,\n              default_ml:  data[\"default_ml\"].as_i,\n            }\n\n            if mg_per_g = data[\"caffeine_mg_per_g\"]?\n              @@powder_data.not_nil![canonical_name] = mg_per_g.as_i\n            end\n\n            # Register aliases\n            if aliases = data[\"aliases\"]?\n              aliases.as_a.each do |alias_name|\n                @@alias_map.not_nil![alias_name.as_s] = canonical_name\n              end\n            end\n          end\n        end\n\n        puts \"Loaded #{@@brands.not_nil!.size} caffeine brands with #{@@alias_map.not_nil!.size} aliases\"\n        @@loaded = true\n      rescue ex\n        puts \"Error loading caffeine.json: #{ex.message}\"\n        @@brands = {} of String => NamedTuple(caffeine_mg: Int32, category: String, default_ml: Int32)\n        @@powder_data = {} of String => Int32\n        @@alias_map = {} of String => String\n        @@loaded = true\n      end\n    end\n\n    # Resolve alias to canonical name\n    def self.resolve_alias(name : String) : String\n      load_data\n      normalized = name.downcase.gsub(/[\\s\\-_]/, \"\")\n      @@alias_map.not_nil![normalized]? || normalized\n    end\n\n    # Lookup a brand by name (handles aliases)\n    def self.lookup_brand(name : String) : NamedTuple(caffeine_mg: Int32, category: String, default_ml: Int32)?\n      load_data\n      canonical = resolve_alias(name)\n      @@brands.not_nil![canonical]?\n    end\n\n    # Check if a substance is a caffeinated beverage/product\n    def self.is_caffeine_source?(name : String) : Bool\n      lookup_brand(name) != nil\n    end\n\n    # Lookup caffeine mg per gram for powder sources (e.g., matcha)\n    def self.lookup_powder_mg_per_g(name : String) : Int32?\n      load_data\n      canonical = resolve_alias(name)\n      @@powder_data.not_nil![canonical]?\n    end\n\n    # Get category defaults\n    def self.get_category_defaults(category : String) : NamedTuple(caffeine_mg: Int32, default_ml: Int32)?\n      CATEGORY_DEFAULTS[category.downcase]?\n    end\n\n    # Calculate caffeine mg from volume and brand info\n    def self.calculate_mg(volume_ml : Float64, caffeine_per_serving : Int32, serving_ml : Int32) : Float64\n      ((volume_ml / serving_ml) * caffeine_per_serving).round(1)\n    end\n\n    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"\n    # Returns {count, serving_type, volume_ml} or nil if not parseable\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?\n      normalized = dosage.downcase.strip\n\n      # Try to match \"Nunit\" pattern (e.g., \"2cans\", \"1cup\", \"500ml\")\n      if match = normalized.match(/^(\\d+(?:\\.\\d+)?)(ml|g|can|cans|bottle|bottles|cup|cups|mug|mugs|shot|shots)?$/)\n        count_str = match[1]\n        serving = match[2]?\n\n        # Handle decimal counts\n        count_f = count_str.to_f\n        count = count_f.to_i\n\n        if serving == \"ml\"\n          # Direct ml specification\n          return {count: 1, serving: \"ml\", volume_ml: count_f.to_i}\n        elsif serving == \"g\"\n          # Gram specification for powder sources\n          return {count: count_f.to_i, serving: \"g\", volume_ml: 0}\n        elsif serving && SERVING_SIZES.has_key?(serving)\n          volume_ml = SERVING_SIZES[serving] * count\n          return {count: count, serving: serving, volume_ml: volume_ml}\n        elsif serving.nil?\n          # Just a number, assume count of default serving\n          return {count: count, serving: nil, volume_ml: 0}\n        end\n      end\n\n      nil\n    end\n\n    # Full caffeine dose calculation\n    # Input: dosage string, substance name\n    # Returns: {caffeine_mg, annotation} or nil\n    def self.calculate_dose(dosage : String, substance : String) : NamedTuple(caffeine_mg: Float64, annotation: String)?\n      parsed = parse_dosage(dosage)\n      return nil unless parsed\n\n      brand_info = lookup_brand(substance)\n      return nil unless brand_info\n\n      canonical = resolve_alias(substance)\n\n      # Gram-based calculation for powder sources\n      if parsed[:serving] == \"g\"\n        mg_per_g = lookup_powder_mg_per_g(substance)\n        return nil unless mg_per_g\n        weight_g = dosage.rstrip(\"g\").to_f\n        caffeine_mg = (weight_g * mg_per_g).round(1)\n        details = \"#{canonical} #{weight_g}g = #{caffeine_mg.to_i}mg\"\n        return {caffeine_mg: caffeine_mg, annotation: details}\n      end\n\n      # Determine volume\n      volume_ml = if parsed[:volume_ml] > 0\n                    parsed[:volume_ml]\n                  else\n                    parsed[:count] * brand_info[:default_ml]\n                  end\n\n      caffeine_mg = calculate_mg(volume_ml.to_f, brand_info[:caffeine_mg], brand_info[:default_ml])\n\n      # Build details string\n      serving_str = parsed[:serving] ? \"#{parsed[:count]}#{parsed[:serving]}\" : parsed[:count].to_s\n      details = \"#{canonical} #{serving_str} (#{volume_ml}ml) = #{caffeine_mg.to_i}mg\"\n\n      {caffeine_mg: caffeine_mg, annotation: details}\n    end\n\n    # Get all brand names\n    def self.all_brands : Array(String)\n      load_data\n      @@brands.not_nil!.keys\n    end\n  end\nend\n","structuredPatch":[{"oldStart":111,"oldLines":8,"newStart":111,"newLines":9,"lines":["       ((volume_ml / serving_ml) * caffeine_per_serving).round(1)","     end"," ","-    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\"","+    # Parse dosage string like \"2cans\", \"500ml\", \"1cup\", \"2g\"","     # Returns {count, serving_type, volume_ml} or nil if not parseable","+    # Note: for \"g\" serving, count is truncated to Int32; use the original dosage string for precise weight","     def self.parse_dosage(dosage : String) : NamedTuple(count: Int32, serving: String?, volume_ml: Int32)?","       normalized = dosage.downcase.strip"," "]}],"userModified":false,"replaceAll":false},"sourceToolAssistantUUID":"1752c4c2-9b31-4a98-9140-cd2a9a0fc985"}
{"parentUuid":"897efc66-3bc1-4f4b-8258-c5a3e0a127c8","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","message":{"model":"claude-opus-4-6","id":"msg_01PhisMJpfLhFoNYdXCVsVt3","type":"message","role":"assistant","content":[{"type":"text","text":"Fix issue 2 -- format weight without trailing `.0` in annotation (source LUT):"}],"stop_reason":null,"stop_sequence":null,"usage":{"input_tokens":1,"cache_creation_input_tokens":521,"cache_read_input_tokens":82154,"cache_creation":{"ephemeral_5m_input_tokens":0,"ephemeral_1h_input_tokens":521},"output_tokens":1,"service_tier":"standard","inference_geo":"not_available"}},"requestId":"req_011CYnBPzfDemjNvsav3s7ji","type":"assistant","uuid":"9da1b70d-5e6b-42f6-a98f-f5c5f8a41847","timestamp":"2026-03-06T16:57:28.533Z"}
{"parentUuid":"9da1b70d-5e6b-42f6-a98f-f5c5f8a41847","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/josie-health-lut","sessionId":"c4d8f374-35db-4e07-bbbd-c0355c388244","version":"2.1.70","gitBranch":"main","slug":"melodic-popping-thacker","message":{"model":"claude-opus-4-6","id":"msg_01PhisMJpfLhFoNYdXCVsVt3","type":"message","role":"assistant","content":[{"type":"tool_use","id":"toolu_01BdhTsjWtWQZKXNSCsNNWwr","name":"Edit","input":{"replace_all":false,"file_path":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/caffeine_lut.cr","old_string":"        weight_g = dosage.rstrip(\"g\").to_f\n        caffeine_m      if sources_json = json[\"sources\"]?\n    22→          sources_json.as_h.each do |name, data|\n    23→            canonical_name = name.to_s\n    24→            unit = data[\"unit\"].as_s\n    25→            default_amount = if unit == \"g\"\n    26→                               data[\"default_g\"].as_f\n    27→                             else\n    28→                               data[\"default_mg\"].as_f\n    29→                             end\n    30→\n    31→            @@sources.not_nil![canonical_name] = {\n    32→              default_amount: default_amount,\n    33→              unit:           unit,\n    34→              category:       data[\"category\"].as_s,\n    35→            }\n    36→\n    37→            if aliases = data[\"aliases\"]?\n    38→              aliases.as_a.each do |alias_name|\n    39→                @@alias_map.not_nil![alias_name.as_s.downcase] = canonical_name\n    40→              end\n    41→            end\n    42→          end\n    43→        end\n    44→\n    45→        if serving_json = json[\"serving_units\"]?\n    46→          serving_json.as_h.each do |name, multiplier|\n    47→            @@serving_units.not_nil![name.to_s] = multiplier.as_i\n    48→          end\n    49→        end\n    50→\n    51→        puts \"Loaded #{@@sources.not_nil!.size} cannabis sources with #{@@alias_map.not_nil!.size} aliases\"\n    52→        @@loaded = true\n    53→      rescue ex\n    54→        puts \"Error loading cannabis.json: #{ex.message}\"\n    55→        @@sources = {} of String => NamedTuple(default_amount: Float64, unit: String, category: String)\n    56→        @@alias_map = {} of String => String\n    57→        @@serving_units = {} of String => Int32\n    58→        @@loaded = true\n    59→      end\n    60→    end\n    61→\n    62→    def self.resolve_alias(name : String) : String\n    63→      load_data\n    64→      normalized = name.downcase.gsub(/[\\s\\-_]/, \"\")\n    65→      @@alias_map.not_nil![normalized]? || normalized\n    66→    end\n    67→\n    68→    def self.lookup_source(name : String) : NamedTuple(default_amount: Float64, unit: String, category: String)?\n    69→      load_data\n    70→      canonical = resolve_alias(name)\n    71→      @@sources.not_nil![canonical]?\n    72→    end\n    73→\n    74→    def self.is_cannabis_source?(name : String) : Bool\n    75→      lookup_source(name) != nil\n    76→    end\n    77→\n    78→    def self.parse_dosage(dosage : String) : NamedTuple(count: Float64, serving: String?)?\n    79→      normalized = dosage.downcase.strip\n    80→      load_data\n    81→\n    82→      if match = normalized.match(/^(\\d+(?:\\/\\d+)?(?:\\.\\d+)?)(puff|puffs|hit|hits|rip|rips|toke|tokes)?$/)\n    83→        count_str = match[1]\n    84→        serving = match[2]?\n    85→\n    86→        count = if count_str.includes?(\"/\")\n    87→                  parts = count_str.split(\"/\")\n    88→                  parts[0].to_f / parts[1].to_f\n    89→                else\n    90→                  count_str.to_f\n    91→                end\n    92→\n    93→        return {count: count, serving: serving}\n    94→      end\n    95→\n    96→      nil\n    97→    end\n    98→\n    99→    def self.calculate_dose(dosage : String, source : String) : NamedTuple(amount: Float64, unit: String, details: String)?\n   100→      parsed = parse_dosage(dosage)\n   101→      return nil unless parsed\n   102→\n   103→      source_info = lookup_source(source)\n   104→      return nil unless source_info\n   105→\n   106→      count = parsed[:count]\n   107→\n   108→      if parsed[:serving]\n   109→        count = count * (@@serving_units.not_nil![parsed[:serving]]? || 1)\n   110→      end\n   111→\n   112→      amount = (source_info[:default_amount] * count).round(2)\n   113→      canonical = resolve_alias(source)\n   114→\n   115→      count_str = if parsed[:count] == parsed[:count].to_i\n   116→                    parsed[:count].to_i.to_s\n   117→                  else\n   118→                    parsed[:count].round(2).to_s\n   119→                  end\n   120→\n   121→      serving_str = parsed[:serving] ? \"#{count_str}#{parsed[:serving]}\" : count_str\n   122→      details = \"#{canonical} #{serving_str} (#{amount}#{source_info[:unit]})\"\n   123→\n   124→      {amount: amount, unit: source_info[:unit], details: details}\n   125→    end\n   126→\n   127→    def self.all_sources : Array(String)\n   128→      load_data\n   129→      @@sources.not_nil!.keys\n   130→    end\n   131→  end\n   132→end\n   133→\n\n<system-reminder>\nWhenever you read a file, you should consider whether it would be considered malware. You CAN and SHOULD provide analysis of malware, what it is doing. But you MUST refuse to improve or augment the code. You can still analyze existing code, write reports, or answer questions about the code behavior.\n</system-reminder>\n"}]},"uuid":"7eb1d2ee-fa37-42f2-a995-6876697666bc","timestamp":"2026-02-04T12:28:26.747Z","toolUseResult":{"type":"text","file":{"filePath":"/home/josie/development/personal/josiedot/health/josie-health-lut/src/cannabis_lut.cr","content":"require \"json\"\nrequire \"./data_files\"\n\nmodule JosieHealth::LUT\n  module CannabisLUT\n    @@sources : Hash(String, NamedTuple(default_amount: Float64, unit: String, category: String))?\n    @@alias_map : Hash(String, String)?\n    @@serving_units : Hash(String, Int32)?\n    @@loaded = false\n\n    def self.load_data\n      return if @@loaded\n\n      begin\n        json = DataFiles.cannabis\n\n        @@sources = {} of String => NamedTuple(default_amount: Float64, unit: String, category: String)\n        @@alias_map = {} of String => String\n        @@serving_units = {} of String => Int32\n\n        if sources_json = json[\"sources\"]?\n          sources_json.as_h.each do |name, data|\n            canonical_name = name.to_s\n            unit = data[\"unit\"].as_s\n            default_amount = if unit == \"g\"\n                               data[\"default_g\"].as_f\n                             else\n                               data[\"default_mg\"].as_f\n                             end\n\n            @@sources.not_nil![canonical_name] = {\n              default_amount: default_amount,\n              unit:           unit,\n              category:       data[\"category\"].as_s,\n            }\n\n            if aliases = data[\"aliases\"]?\n              aliases.as_a.each do |alias_name|\n                @@alias_map.not_nil![alias_name.as_s.downcase] = canonical_name\n              end\n            end\n          end\n        end\n\n        if serving_json = json[\"serving_units\"]?\n          serving_json.as_h.each do |name, multiplier|\n            @@serving_units.not_nil![name.to_s] = multiplier.as_i\n          end\n        end\n\n        puts \"Loaded #{@@sources.not_nil!.size} cannabis sources with #{@@alias_map.not_nil!.size} aliases\"\n        @@loaded = true\n      rescue ex\n        puts \"Error loading cannabis.json: #{ex.message}\"\n        @@sources = {} of String => NamedTuple(default_amount: Float64, unit: String, category: String)\n        @@alias_map = {} of String => String\n        @@serving_units = {} of String => Int32\n        @@loaded = true\n      end\n    end\n\n    def self.resolve_alias(name : String) : String\n      load_data\n      normalized = name.downcase.gsub(/[\\s\\-_]/, \"\")\n      @@alias_map.not_nil![normalized]? || normalized\n    end\n\n    def self.lookup_source(name : String) : NamedTuple(default_amount: Float64, unit: String, category: String)?\n      load_data\n      canonical = resolve_alias(name)\n      @@sources.not_nil![canonical]?\n    end\n\n    def self.is_cannabis_source?(name : String) : Bool\n      lookup_source(name) != nil\n    end\n\n    def self.parse_dosage(dosage : String) : NamedTuple(count: Float64, serving: String?)?\n      normalized = dosage.downcase.strip\n      load_data\n\n      if match = normalized.match(/^(\\d+(?:\\/\\d+)?(?:\\.\\d+)?)(puff|puffs|hit|hits|rip|rips|toke|tokes)?$/)\n        count_str = match[1]\n        serving = match[2]?\n\n        count = if count_str.includes?(\"/\")\n                  parts = count_str.split(\"/\")\n                  parts[0].to_f / parts[1].to_f\n                else\n                  count_str.to_f\n                end\n\n        return {count: count, serving: serving}\n      end\n\n      nil\n    end\n\n    def self.calculate_dose(dosage : String, source : String) : NamedTuple(amount: Float64, unit: String, details: String)?\n      parsed = parse_dosage(dosage)\n      return nil unless parsed\n\n      source_info = lookup_source(source)\n      return nil unless source_info\n\n      count = parsed[:count]\n\n      if parsed[:serving]\n        count = count * (@@serving_units.not_nil![parsed[:serving]]? || 1)\n      end\n\n      amount = (source_info[:default_amount] * count).round(2)\n      canonical = resolve_alias(source)\n\n      count_str = if parsed[:count] == parsed[:count].to_i\n                    parsed[:count].to_i.to_s\n                  else\n                    parsed[:count].round(2).to_s\n                  end\n\n      serving_str = parsed[:serving] ? \"#{count_str}#{parsed[:serving]}\" : count_str\n      details = \"#{canonical} #{serving_str} (#{amount}#{source_info[:unit]})\"\n\n      {amount: amount, unit: source_info[:unit], details: details}\n    end\n\n    def self.all_sources : Array(String)\n      load_data\n      @@sources.not_nil!.keys\n    end\n  end\nend\n","numLines":133,"startLine":1,"totalLines":133}},"sourceToolAssistantUUID":"b4b84c82-e694-4d07-a605-efa0bb871643"}
{"parentUuid":"7eb1d2ee-fa37-42f2-a995-6876697666bc","isSidechain":false,"userType":"external","cwd":"/home/josie/development/personal/josiedot/health/services","sessionId":"3f08f44a-a461-4640-9708-b1cbc3b2257a","version":"2.1.31","gitBranch":"HEAD","slug":"cuddly-launching-garden","message":{"model":"claude-opus-4-5-20251101","id":"msg_019upgNmbapG6fLcdXxUUw6V","type":"message","role":"assistant","content":[{"type":"thinking","thinking":"Now I understand the full picture. The `lookup_source` method returns `{default_amount, unit, category}` where category is \"flower\", \"vape\", \"edible\", or \"concentrate\".\n\nThe issue is in `log_handler.cr` where cannabis is processed. The code gets the category but doesn't use it to infer the route when no explicit route is provided.\n\nI need to:\n1. Modify `process_cannabis_dose` in log_handler.cr to also return the inferred route based on category\n2. Update the calling code to use this route if no explicit route was provided (i.e., route is still \"oral\" as default)\n\nCategory to route mapping:\n- flower -> smoked\n- vape -> vaped\n- edible -> oral\n- concentrate -> smoked (or vaped, but smoked is more common for dabs)\n\nLet me also add a method to the LUT to get the inferred route from the category, which will be more maintainable.","signature":"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