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interm.py

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+from smolagents import CodeAgent, DuckDuckGoSearchTool, HfApiModel
+from fpdf import FPDF
+import tempfile
+
+# Initialize Clinical AI Agent
+clinical_agent = CodeAgent(tools=[DuckDuckGoSearchTool()], model=HfApiModel())
+
+def generate_clinical_content(topic, audience):
+    """Generates medical content based on topic and audience."""
+    prompt = f"Write a detailed medical article on: {topic}.\nTarget Audience: {audience}.\nInclude latest medical research insights."
+    return clinical_agent.run(prompt)
+
+def generate_summary(content):
+    """Summarizes a given clinical document or research paper."""
+    summary_prompt = f"Summarize the following medical research:\n{content}"
+    return clinical_agent.run(summary_prompt)
+
+def generate_soap_note(symptoms, history):
+    """Generates a SOAP Note for clinicians based on symptoms and patient history."""
+    soap_prompt = (
+        f"Create a structured SOAP Note for a patient with:\n"
+        f"Symptoms: {symptoms}\n"
+        f"History: {history}\n"
+        f"Include Assessment & Plan."
+    )
+    return clinical_agent.run(soap_prompt)
+
+def save_as_text(content, filename):
+    """Saves AI-generated content as a TXT file."""
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".txt") as tmp_file:
+        tmp_file.write(content.encode())
+        return tmp_file.name, filename
+
+def save_as_pdf(content, filename):
+    """Saves AI-generated content as a PDF file."""
+    with tempfile.NamedTemporaryFile(delete=False, suffix=".pdf") as tmp_file:
+        pdf = FPDF()
+        pdf.add_page()
+        pdf.set_font("Arial", size=12)
+        pdf.multi_cell(0, 10, content)
+        pdf.output(tmp_file.name)
+        return tmp_file.name, filename

requirements.txt

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+streamlit
+fastapi
+transformers
+torch
+requests
+uvicorn
+pandas
+sqlalchemy
+openai  # For SQL query generation