|
|
@@ -45,6 +45,89 @@ def strip_scratchpad(text: str) -> str:
|
|
|
clean_text = re.sub(r'<scratchpad>.*?</scratchpad>', '', text, flags=re.DOTALL)
|
|
|
return clean_text.strip()
|
|
|
|
|
|
+def extract_allergens_from_json(data) -> list:
|
|
|
+ table_data = []
|
|
|
+
|
|
|
+ def add_item(aliment, allergens):
|
|
|
+ if not aliment or not allergens:
|
|
|
+ return
|
|
|
+ if isinstance(allergens, list):
|
|
|
+ cleaned = [str(alg).strip().title() for alg in allergens if alg]
|
|
|
+ if cleaned:
|
|
|
+ table_data.append({
|
|
|
+ "Aliment (Ingredient)": str(aliment).strip().title(),
|
|
|
+ "Allergen Kind(s)": ", ".join(cleaned)
|
|
|
+ })
|
|
|
+ elif isinstance(allergens, str) and allergens.strip():
|
|
|
+ table_data.append({
|
|
|
+ "Aliment (Ingredient)": str(aliment).strip().title(),
|
|
|
+ "Allergen Kind(s)": allergens.strip().title()
|
|
|
+ })
|
|
|
+
|
|
|
+ if isinstance(data, list):
|
|
|
+ for entry in data:
|
|
|
+ if isinstance(entry, dict):
|
|
|
+ aliment = entry.get('aliment') or entry.get('name') or entry.get('food')
|
|
|
+ allergens = entry.get('allergen') or entry.get('allergens') or entry.get('kinds') or []
|
|
|
+ if aliment and allergens:
|
|
|
+ add_item(aliment, allergens)
|
|
|
+ else:
|
|
|
+ for k, v in entry.items():
|
|
|
+ if isinstance(v, (list, str)):
|
|
|
+ add_item(k, v)
|
|
|
+ elif isinstance(entry, list) and len(entry) >= 2:
|
|
|
+ add_item(entry[0], entry[1])
|
|
|
+ elif isinstance(data, dict):
|
|
|
+ al_list = data.get('aliment') or data.get('aliments')
|
|
|
+ all_list = data.get('allergen') or data.get('allergens') or data.get('kinds')
|
|
|
+
|
|
|
+ if isinstance(al_list, list) and isinstance(all_list, list):
|
|
|
+ for item in all_list:
|
|
|
+ if isinstance(item, dict):
|
|
|
+ name = item.get('name') or item.get('aliment')
|
|
|
+ types = item.get('types') or item.get('type') or item.get('kinds') or item.get('allergen') or item.get('allergens')
|
|
|
+ if name and types:
|
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|
+ add_item(name, types)
|
|
|
+ elif isinstance(item, list) and len(item) >= 2:
|
|
|
+ add_item(item[0], item[1])
|
|
|
+ if not table_data and len(al_list) == len(all_list):
|
|
|
+ for a, alg in zip(al_list, all_list):
|
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|
+ add_item(a, alg)
|
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|
+
|
|
|
+ if not table_data:
|
|
|
+ for key, val in data.items():
|
|
|
+ if isinstance(val, list):
|
|
|
+ for entry in val:
|
|
|
+ if isinstance(entry, dict):
|
|
|
+ aliment = entry.get('aliment') or entry.get('name') or entry.get('food')
|
|
|
+ allergens = entry.get('allergen') or entry.get('allergens') or entry.get('kinds') or []
|
|
|
+ if aliment and allergens:
|
|
|
+ add_item(aliment, allergens)
|
|
|
+ else:
|
|
|
+ for k, v in entry.items():
|
|
|
+ if isinstance(v, (list, str)):
|
|
|
+ add_item(k, v)
|
|
|
+ elif isinstance(entry, list) and len(entry) >= 2:
|
|
|
+ add_item(entry[0], entry[1])
|
|
|
+ elif isinstance(entry, str):
|
|
|
+ if key not in ['aliment', 'aliments', 'allergen', 'allergens', 'kinds', 'types']:
|
|
|
+ add_item(key, val)
|
|
|
+ break
|
|
|
+ elif isinstance(val, dict):
|
|
|
+ for k, v in val.items():
|
|
|
+ if isinstance(v, (list, str)):
|
|
|
+ add_item(k, v)
|
|
|
+ elif isinstance(v, dict):
|
|
|
+ add_item(k, v.get('allergen') or v.get('allergens') or [])
|
|
|
+ elif isinstance(val, str):
|
|
|
+ if key not in ['aliment', 'aliments', 'allergen', 'allergens', 'kinds', 'types']:
|
|
|
+ add_item(key, val)
|
|
|
+ if not table_data:
|
|
|
+ for k, v in data.items():
|
|
|
+ if k not in ['aliment', 'aliments', 'allergen', 'allergens', 'kinds', 'types']:
|
|
|
+ add_item(k, v)
|
|
|
+ return table_data
|
|
|
+
|
|
|
@st.cache_data(show_spinner=False)
|
|
|
def query_plate_allergens(unique_aliments: list) -> list:
|
|
|
import ollama
|
|
|
@@ -64,34 +147,7 @@ def query_plate_allergens(unique_aliments: list) -> list:
|
|
|
)
|
|
|
res_content = response['message']['content'].strip()
|
|
|
data = json.loads(res_content)
|
|
|
-
|
|
|
- # Robust dictionary-or-list JSON parser
|
|
|
- aliments_array = []
|
|
|
- if isinstance(data, list):
|
|
|
- aliments_array = data
|
|
|
- elif isinstance(data, dict):
|
|
|
- for val in data.values():
|
|
|
- if isinstance(val, list):
|
|
|
- aliments_array = val
|
|
|
- break
|
|
|
-
|
|
|
- if aliments_array:
|
|
|
- for entry in aliments_array:
|
|
|
- if isinstance(entry, dict):
|
|
|
- aliment = entry.get('aliment')
|
|
|
- allergens = entry.get('allergen') or entry.get('allergens') or []
|
|
|
- if aliment:
|
|
|
- if isinstance(allergens, list) and allergens:
|
|
|
- cleaned_algs = [str(alg).strip().title() for alg in allergens if alg]
|
|
|
- table_data.append({
|
|
|
- "Aliment (Ingredient)": aliment.strip().title(),
|
|
|
- "Allergen Kind(s)": ", ".join(cleaned_algs)
|
|
|
- })
|
|
|
- elif isinstance(allergens, str) and allergens.strip():
|
|
|
- table_data.append({
|
|
|
- "Aliment (Ingredient)": aliment.strip().title(),
|
|
|
- "Allergen Kind(s)": allergens.strip().title()
|
|
|
- })
|
|
|
+ table_data = extract_allergens_from_json(data)
|
|
|
except Exception:
|
|
|
pass
|
|
|
return table_data
|
|
|
@@ -145,25 +201,11 @@ def detect_allergens_from_text(name: str, ingredients: str) -> set:
|
|
|
)
|
|
|
res_content = response['message']['content'].strip()
|
|
|
data = json.loads(res_content)
|
|
|
-
|
|
|
- # Robust dictionary-or-list JSON parser
|
|
|
- aliments_array = []
|
|
|
- if isinstance(data, list):
|
|
|
- aliments_array = data
|
|
|
- elif isinstance(data, dict):
|
|
|
- for val in data.values():
|
|
|
- if isinstance(val, list):
|
|
|
- aliments_array = val
|
|
|
- break
|
|
|
-
|
|
|
- if aliments_array:
|
|
|
- for entry in aliments_array:
|
|
|
- if isinstance(entry, dict):
|
|
|
- aliment = entry.get('aliment')
|
|
|
- allergens = entry.get('allergen') or entry.get('allergens') or []
|
|
|
- if aliment and allergens:
|
|
|
- if (isinstance(allergens, list) and len(allergens) > 0) or (isinstance(allergens, str) and allergens.strip()):
|
|
|
- detected.add(aliment.strip().title())
|
|
|
+ parsed = extract_allergens_from_json(data)
|
|
|
+ for item in parsed:
|
|
|
+ name = item.get("Aliment (Ingredient)")
|
|
|
+ if name:
|
|
|
+ detected.add(name)
|
|
|
except Exception:
|
|
|
pass
|
|
|
return detected
|
|
|
@@ -505,10 +547,15 @@ if cookies is None:
|
|
|
|
|
|
# If the cookie has auth_user, set/restore session state
|
|
|
cookie_user = cookie_manager.get(cookie="auth_user")
|
|
|
-if cookie_user:
|
|
|
- st.session_state["authenticated_user"] = cookie_user
|
|
|
-elif "authenticated_user" not in st.session_state:
|
|
|
+if st.session_state.get("logged_out"):
|
|
|
st.session_state["authenticated_user"] = None
|
|
|
+ if not cookie_user:
|
|
|
+ st.session_state["logged_out"] = False
|
|
|
+else:
|
|
|
+ if cookie_user:
|
|
|
+ st.session_state["authenticated_user"] = cookie_user
|
|
|
+ elif "authenticated_user" not in st.session_state:
|
|
|
+ st.session_state["authenticated_user"] = None
|
|
|
|
|
|
st.markdown("""
|
|
|
<style>
|
|
|
@@ -535,6 +582,7 @@ with st.sidebar:
|
|
|
if st.session_state["authenticated_user"]:
|
|
|
st.success(f"Logged in as: {st.session_state['authenticated_user']}")
|
|
|
if st.button("Logout"):
|
|
|
+ st.session_state["logged_out"] = True
|
|
|
st.session_state["authenticated_user"] = None
|
|
|
cookie_manager.delete("auth_user")
|
|
|
time.sleep(0.5)
|
|
|
@@ -913,7 +961,7 @@ with tab_explore:
|
|
|
for col in df_display.columns:
|
|
|
if 'image' in col.lower():
|
|
|
df_display[col] = df_display[col].apply(lambda x: x if is_valid_image_url(x) else "")
|
|
|
- df_display.replace(to_replace=[None, 'None', 'nan', 'NaN'], value=' ', inplace=True)
|
|
|
+ df_display.replace(to_replace=[None, 'None', 'nan', 'NaN'], value='\u00a0', inplace=True)
|
|
|
# Only fillna with empty string on object columns to avoid Arrow float64 conversion errors
|
|
|
for col in df_display.columns:
|
|
|
if df_display[col].dtype == 'object':
|
|
|
@@ -1188,20 +1236,37 @@ with tab_plate:
|
|
|
"Nutrition Image": r.get('image_nutrition_small_url') if is_valid_image_url(r.get('image_nutrition_small_url')) else "",
|
|
|
})
|
|
|
gallery_df = pd.DataFrame(df_rows)
|
|
|
- gallery_df.replace(to_replace=[None, 'None', 'nan', 'NaN'], value=' ', inplace=True)
|
|
|
+ gallery_df.replace(to_replace=[None, 'None', 'nan', 'NaN'], value='\u00a0', inplace=True)
|
|
|
gallery_df.index = range(1, len(gallery_df) + 1)
|
|
|
- st.dataframe(
|
|
|
+ event = st.dataframe(
|
|
|
gallery_df,
|
|
|
column_config={
|
|
|
"Image": st.column_config.ImageColumn("Image"),
|
|
|
"Ingredients Image": st.column_config.ImageColumn("Ingredients"),
|
|
|
"Nutrition Image": st.column_config.ImageColumn("Nutrition"),
|
|
|
},
|
|
|
- use_container_width=True
|
|
|
+ use_container_width=True,
|
|
|
+ on_select="rerun",
|
|
|
+ selection_mode="single_row",
|
|
|
+ key="product_preview_table"
|
|
|
)
|
|
|
|
|
|
+ selected_row_idx = None
|
|
|
+ if event and hasattr(event, "selection"):
|
|
|
+ sel = event.selection
|
|
|
+ if isinstance(sel, dict) and sel.get("rows"):
|
|
|
+ selected_row_idx = sel["rows"][0]
|
|
|
+ elif hasattr(sel, "get") and sel.get("rows"):
|
|
|
+ selected_row_idx = sel.get("rows")[0]
|
|
|
+
|
|
|
options = {f"{r['product_name']} ({r['code']})": r for r in search_res}
|
|
|
- selected_str = st.selectbox("Select Product", list(options.keys()))
|
|
|
+ options_list = list(options.keys())
|
|
|
+
|
|
|
+ default_idx = 0
|
|
|
+ if selected_row_idx is not None and selected_row_idx < len(options_list):
|
|
|
+ default_idx = selected_row_idx
|
|
|
+
|
|
|
+ selected_str = st.selectbox("Select Product", options_list, index=default_idx)
|
|
|
selected_product = options[selected_str]
|
|
|
|
|
|
add_amount_str = st.text_input("Portion Quantity (e.g., '100g', '2 tbsp', '1.5 cups', '1 pinch')", value="100g")
|
|
|
@@ -1244,6 +1309,10 @@ with tab_planner:
|
|
|
extra_notes = st.text_input("Any additional allergies or goals?")
|
|
|
|
|
|
if st.button("Generate Professional Menu"):
|
|
|
+ st.session_state.pop("generated_meal_plan", None)
|
|
|
+ st.session_state.pop("meal_plan_pdf_data", None)
|
|
|
+ st.session_state.pop("meal_plan_elapsed", None)
|
|
|
+
|
|
|
with st.spinner("Executing Lightning-Fast Context RAG..."):
|
|
|
user_eav = get_eav_profile(st.session_state["authenticated_user"])
|
|
|
profile_text = ", ".join([f"{p['name']}: {p['value']}" for p in user_eav]) if user_eav else "None"
|
|
|
@@ -1272,7 +1341,7 @@ with tab_planner:
|
|
|
- 1.5 cups of Cheese = X grams (density Y). Calories = A, Protein = B, Carbs = C, Fat = D.
|
|
|
- 2 tbsp of Peanut Butter = Z grams (density C). Calories = D, Protein = E, Carbs = F, Fat = G.
|
|
|
- Summation: Total Calories = A + D = Z kcal (vs target {target_cal}kcal). Total Protein = B + E = Fg.
|
|
|
- </scratchpad>
|
|
|
+ - </scratchpad>
|
|
|
| Meal Time | Exact Food | Portion Size | Calories | Protein | Carbs | Fat |
|
|
|
| --- | --- | --- | --- | --- | --- | --- |
|
|
|
...
|
|
|
@@ -1336,13 +1405,31 @@ with tab_planner:
|
|
|
total_pro += clean_num(cols[4])
|
|
|
total_carb += clean_num(cols[5])
|
|
|
total_fat += clean_num(cols[6])
|
|
|
- total_row = f"| **Total Summary** | **All Meals** | **-** | **{total_cal:.1f} kcal** | **{total_pro:.1f}g** | **{total_carb:.1f}g** | **{total_fat:.1f}g** |"
|
|
|
+ total_row = f"| Total Summary | All Meals | - | {total_cal:.1f} kcal | {total_pro:.1f}g | {total_carb:.1f}g | {total_fat:.1f}g |"
|
|
|
lines.insert(table_end + 1, total_row)
|
|
|
return "\n".join(lines)
|
|
|
|
|
|
final_reply = add_total_row_to_markdown_table(clean_reply)
|
|
|
- placeholder.markdown(final_reply)
|
|
|
- st.caption(f"⏱️ Execution Trace: Module=Ollama, MySQL | Time={time.time() - start_llm:.2f} seconds")
|
|
|
+
|
|
|
+ # Align numeric columns on the right
|
|
|
+ def align_markdown_table(text):
|
|
|
+ lines = text.split('\n')
|
|
|
+ for i, line in enumerate(lines):
|
|
|
+ line_s = line.strip()
|
|
|
+ if line_s.startswith('|') and line_s.endswith('|') and '---' in line_s:
|
|
|
+ parts = [p.strip() for p in line_s.strip('|').split('|')]
|
|
|
+ if len(parts) >= 7:
|
|
|
+ new_parts = []
|
|
|
+ for idx, part in enumerate(parts):
|
|
|
+ if idx < 3:
|
|
|
+ new_parts.append('---')
|
|
|
+ else:
|
|
|
+ new_parts.append('---:')
|
|
|
+ lines[i] = '| ' + ' | '.join(new_parts) + ' |'
|
|
|
+ break
|
|
|
+ return '\n'.join(lines)
|
|
|
+
|
|
|
+ final_reply = align_markdown_table(final_reply)
|
|
|
|
|
|
# PDF Generation
|
|
|
def generate_pdf(text):
|
|
|
@@ -1373,7 +1460,6 @@ with tab_planner:
|
|
|
pdf.set_font("Helvetica", 'B', 16)
|
|
|
pdf.cell(0, 10, "Strict Clinical Meal Plan", new_x="LMARGIN", new_y="NEXT", align='C')
|
|
|
pdf.ln(h=5)
|
|
|
- in_table = False
|
|
|
table_data = []
|
|
|
|
|
|
def flush_table():
|
|
|
@@ -1381,8 +1467,9 @@ with tab_planner:
|
|
|
pdf.set_font("Helvetica", size=9)
|
|
|
# Auto-calculate col_widths based on 5 columns if present
|
|
|
cw = (20, 40, 15, 10, 15) if len(table_data[0]) == 5 else (20, 30, 15, 10, 10, 10, 10) if len(table_data[0]) >= 7 else None
|
|
|
+ alignments = ("LEFT", "LEFT", "LEFT", "RIGHT", "RIGHT", "RIGHT", "RIGHT") if len(table_data[0]) >= 7 else ("LEFT", "LEFT", "LEFT", "RIGHT", "RIGHT") if len(table_data[0]) == 5 else "LEFT"
|
|
|
try:
|
|
|
- with pdf.table(text_align="LEFT", col_widths=cw) as table:
|
|
|
+ with pdf.table(text_align=alignments, col_widths=cw) as table:
|
|
|
for row_data in table_data:
|
|
|
row = table.row()
|
|
|
for datum in row_data:
|
|
|
@@ -1421,18 +1508,18 @@ with tab_planner:
|
|
|
|
|
|
flush_table()
|
|
|
|
|
|
- pdf_path = "/tmp/meal_plan.pdf"
|
|
|
+ current_dir = os.path.dirname(os.path.abspath(__file__))
|
|
|
+ tmp_dir = os.path.join(current_dir, "tmp")
|
|
|
+ os.makedirs(tmp_dir, exist_ok=True)
|
|
|
+ pdf_path = os.path.join(tmp_dir, "meal_plan.pdf")
|
|
|
pdf.output(pdf_path)
|
|
|
with open(pdf_path, "rb") as f:
|
|
|
return f.read()
|
|
|
-
|
|
|
- st.download_button(
|
|
|
- label="📄 Download PDF Export",
|
|
|
- data=generate_pdf(final_reply),
|
|
|
- file_name="Clinical_Meal_Plan.pdf",
|
|
|
- mime="application/pdf",
|
|
|
- type="primary"
|
|
|
- )
|
|
|
+
|
|
|
+ st.session_state['generated_meal_plan'] = final_reply
|
|
|
+ st.session_state['meal_plan_pdf_data'] = generate_pdf(final_reply)
|
|
|
+ st.session_state['meal_plan_elapsed'] = time.time() - start_llm
|
|
|
+ st.rerun()
|
|
|
|
|
|
except Exception as e:
|
|
|
error_msg = str(e).lower()
|
|
|
@@ -1441,4 +1528,19 @@ with tab_planner:
|
|
|
else:
|
|
|
st.error(f"AI Generation Failed: {e}")
|
|
|
|
|
|
+ # Outside the button, render the session state if exists
|
|
|
+ if 'generated_meal_plan' in st.session_state:
|
|
|
+ st.info("🧠 AI is analyzing nutritional synergies and generating your plan...")
|
|
|
+ st.markdown(st.session_state['generated_meal_plan'])
|
|
|
+ if st.session_state.get('meal_plan_elapsed'):
|
|
|
+ st.caption(f"⏱️ Execution Trace: Module=Ollama, MySQL | Time={st.session_state['meal_plan_elapsed']:.2f} seconds")
|
|
|
+
|
|
|
+ st.download_button(
|
|
|
+ label="📄 Download PDF Export",
|
|
|
+ data=st.session_state['meal_plan_pdf_data'],
|
|
|
+ file_name="Clinical_Meal_Plan.pdf",
|
|
|
+ mime="application/pdf",
|
|
|
+ type="primary"
|
|
|
+ )
|
|
|
+
|
|
|
if conn_reader: conn_reader.close()
|
