created for hugging face space

.idea/MentalHealthApi.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/.venv" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.12 (MentalHealthApi)" jdkType="Python SDK" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/MentalHealthApi.iml" filepath="$PROJECT_DIR$/.idea/MentalHealthApi.iml" />
+    </modules>
+  </component>
+</project>

.idea/vcs.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="VcsDirectoryMappings">
+    <mapping directory="$PROJECT_DIR$" vcs="Git" />
+  </component>
+</project>

.idea/workspace.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ChangeListManager">
+    <list default="true" id="28f98b15-03b6-46d3-96ff-cb09b54e30e9" name="Changes" comment="" />
+    <option name="SHOW_DIALOG" value="false" />
+    <option name="HIGHLIGHT_CONFLICTS" value="true" />
+    <option name="HIGHLIGHT_NON_ACTIVE_CHANGELIST" value="false" />
+    <option name="LAST_RESOLUTION" value="IGNORE" />
+  </component>
+  <component name="Git.Settings">
+    <option name="RECENT_GIT_ROOT_PATH" value="$PROJECT_DIR$" />
+  </component>
+  <component name="ProjectColorInfo"><![CDATA[{
+  "associatedIndex": 2
+}]]></component>
+  <component name="ProjectId" id="2vUl6kvbUHpwQdLCky5l3NhaUrr" />
+  <component name="ProjectLevelVcsManager" settingsEditedManually="true" />
+  <component name="ProjectViewState">
+    <option name="hideEmptyMiddlePackages" value="true" />
+    <option name="showLibraryContents" value="true" />
+  </component>
+  <component name="PropertiesComponent"><![CDATA[{
+  "keyToString": {
+    "RunOnceActivity.ShowReadmeOnStart": "true",
+    "git-widget-placeholder": "master"
+  }
+}]]></component>
+  <component name="SharedIndexes">
+    <attachedChunks>
+      <set>
+        <option value="bundled-python-sdk-1b1018131e27-aa17d162503b-com.jetbrains.pycharm.community.sharedIndexes.bundled-PC-243.22562.180" />
+      </set>
+    </attachedChunks>
+  </component>
+  <component name="SpellCheckerSettings" RuntimeDictionaries="0" Folders="0" CustomDictionaries="0" DefaultDictionary="application-level" UseSingleDictionary="true" transferred="true" />
+  <component name="TaskManager">
+    <task active="true" id="Default" summary="Default task">
+      <changelist id="28f98b15-03b6-46d3-96ff-cb09b54e30e9" name="Changes" comment="" />
+      <created>1744207365425</created>
+      <option name="number" value="Default" />
+      <option name="presentableId" value="Default" />
+      <updated>1744207365425</updated>
+    </task>
+    <servers />
+  </component>
+</project>

app.py

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+import gradio as gr
+import torch
+from transformers import (
+    AutoTokenizer,
+    AutoModelForSeq2SeqLM,
+    pipeline,
+    AutoModelForSequenceClassification,
+    AutoModelForCausalLM
+)
+
+# Hugging Face login token (only needed for private models or DeepSeek)
+import os
+from huggingface_hub import login
+
+hf_token = os.getenv("HF_TOKEN")
+login(hf_token)
+
+# Load PTSD summarization model
+model_name = "machinelearningzuu/ptsd-summarization"
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+summarizer = pipeline("summarization", model=model, tokenizer=tokenizer)
+
+# Sentiment analysis
+sentiment_analyzer = pipeline("sentiment-analysis")
+
+# Emotion classification
+clf_model = AutoModelForSequenceClassification.from_pretrained("nateraw/bert-base-uncased-emotion")
+clf_tokenizer = AutoTokenizer.from_pretrained("nateraw/bert-base-uncased-emotion")
+labels = ['sadness', 'joy', 'love', 'anger', 'fear', 'surprise']
+
+def classify_mental_state(text):
+    inputs = clf_tokenizer(text, return_tensors="pt", truncation=True, padding=True)
+    with torch.no_grad():
+        outputs = clf_model(**inputs)
+        logits = outputs.logits
+        probs = torch.nn.functional.softmax(logits, dim=1)
+        top_idx = torch.argmax(probs).item()
+        label = labels[top_idx]
+        confidence = probs[0][top_idx].item()
+        return f"{label.capitalize()} ({confidence:.2f})"
+
+# DeepSeek suggestion generator
+deepseek_model_id = "deepseek-ai/deepseek-llm-7b-chat"
+deepseek_tokenizer = AutoTokenizer.from_pretrained(deepseek_model_id)
+deepseek_model = AutoModelForCausalLM.from_pretrained(
+    deepseek_model_id,
+    torch_dtype=torch.float16,
+    device_map="auto",
+    token=True
+)
+deepseek_tokenizer.pad_token = deepseek_tokenizer.eos_token
+
+def generate_suggestion(summary_text):
+    prompt = (
+        f"Patient summary: {summary_text}\n"
+        f"Based on this, provide 3 specific coping suggestions for PTSD symptoms:\n"
+        f"1."
+    )
+    inputs = deepseek_tokenizer([prompt], return_tensors="pt", padding=True, truncation=True).to(deepseek_model.device)
+    outputs = deepseek_model.generate(
+        input_ids=inputs["input_ids"],
+        attention_mask=inputs["attention_mask"],
+        max_new_tokens=200,
+        do_sample=True,
+        temperature=0.7,
+        eos_token_id=deepseek_tokenizer.eos_token_id,
+        pad_token_id=deepseek_tokenizer.pad_token_id
+    )
+    generated = deepseek_tokenizer.decode(outputs[0], skip_special_tokens=True)
+    suggestion = generated.split("1.", 1)[-1].strip()
+    return "1. " + suggestion
+
+# Main logic for Gradio
+def analyze_input(text):
+    try:
+        summary = summarizer(text, max_length=100, min_length=10, do_sample=False)[0]['summary_text']
+        sentiment = sentiment_analyzer(text)[0]
+        sentiment_result = f"{sentiment['label']} ({sentiment['score']:.2f})"
+        classification_result = classify_mental_state(text)
+        suggestion = generate_suggestion(summary)
+        return summary, sentiment_result, classification_result, suggestion
+    except Exception as e:
+        return "Error: " + str(e), "Error", "Error", "Error"
+
+# Gradio UI
+demo = gr.Interface(
+    fn=analyze_input,
+    inputs=[gr.Textbox(lines=10, placeholder="Enter patient report...", label="Patient Report")],
+    outputs=[
+        gr.Textbox(label="Summary"),
+        gr.Textbox(label="Sentiment Analysis"),
+        gr.Textbox(label="Mental Health Indicator"),
+        gr.Textbox(label="Suggested Advice")
+    ],
+    title="Mental Health Assistant",
+    description="Summarizes PTSD-related text, detects emotional tone, classifies mental state, and generates non-clinical coping suggestions."
+)
+
+demo.launch()

requirements.txt

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+gradio
+transformers
+torch
+huggingface_hub
+accelerate