To support Gradio Visualization and HuggingFace host

LICENSE

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+MIT License
+
+Copyright (c) 2026 KevinIsInCoding
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

app.py

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+from __future__ import annotations
+
+import datetime
+import json
+from typing import Generator
+
+import anthropic
+import gradio as gr
+from dotenv import load_dotenv
+
+from clinical_trials_guru import (
+    INTAKE_MODEL,
+    INTAKE_SYSTEM,
+    RESEARCH_MODEL,
+    RESEARCH_SYSTEM,
+    SEARCH_TRIALS_TOOL,
+    SUBMIT_PROFILE_TOOL,
+    PatientProfile,
+    _flatten_and_rank,
+    geocode_zip,
+    search_trials_api,
+)
+
+load_dotenv()
+
+
+def _intake_turn(
+    user_text: str, messages: list
+) -> tuple[str, list, PatientProfile | None]:
+    today = datetime.date.today().strftime("%B %d, %Y")
+    messages = messages + [{"role": "user", "content": user_text}]
+    client = anthropic.Anthropic()
+    response = client.messages.create(
+        model=INTAKE_MODEL,
+        max_tokens=1024,
+        system=f"Today's date is {today}.\n\n" + INTAKE_SYSTEM,
+        tools=[SUBMIT_PROFILE_TOOL],
+        messages=messages,
+    )
+    text = next((b.text for b in response.content if b.type == "text"), "")
+    tool_block = next(
+        (b for b in response.content if b.type == "tool_use" and b.name == "submit_profile"),
+        None,
+    )
+    messages = messages + [{"role": "assistant", "content": response.content}]
+
+    if tool_block:
+        data = tool_block.input
+        try:
+            lat, lon = geocode_zip(data["zip_code"], data.get("country_code", "US"))
+        except Exception:
+            lat, lon = 0.0, 0.0
+        profile = PatientProfile(
+            disease=data["disease"],
+            age=data["age"],
+            onset_months=data["onset_months"],
+            benchmarks=data.get("benchmarks") or {},
+            zip_code=data["zip_code"],
+            country_code=data.get("country_code", "US"),
+            lat=lat,
+            lon=lon,
+            radius_miles=data.get("radius_miles", 100),
+            phases=data.get("phases") or [],
+        )
+        return text or "Got it — searching for trials now…", messages, profile
+
+    return text, messages, None
+
+
+def _run_research(profile: PatientProfile) -> str:
+    client = anthropic.Anthropic()
+    messages: list[anthropic.types.MessageParam] = [
+        {
+            "role": "user",
+            "content": (
+                f"Find clinical trials for this patient:\n\n{profile.summary()}\n\n"
+                "Search within the specified radius and rank results by distance."
+            ),
+        }
+    ]
+    while True:
+        response = client.messages.create(
+            model=RESEARCH_MODEL,
+            max_tokens=8096,
+            system=RESEARCH_SYSTEM,
+            tools=[SEARCH_TRIALS_TOOL],
+            messages=messages,
+        )
+        messages.append({"role": "assistant", "content": response.content})
+        if response.stop_reason == "end_turn":
+            return next(
+                (b.text for b in response.content if b.type == "text"),
+                "No analysis produced.",
+            )
+        tool_results: list[anthropic.types.ToolResultBlockParam] = []
+        for block in response.content:
+            if block.type != "tool_use" or block.name != "search_clinical_trials":
+                continue
+            args = block.input
+            try:
+                studies = search_trials_api(
+                    condition=args["condition"],
+                    lat=args["lat"],
+                    lon=args["lon"],
+                    radius_miles=args.get("radius_miles", profile.radius_miles),
+                    phases=args.get("phases") or None,
+                    max_results=args.get("max_results", 20),
+                )
+                ranked = _flatten_and_rank(studies, profile.lat, profile.lon)
+                content = json.dumps(ranked)
+                is_error = False
+            except Exception as exc:
+                content = f"API request failed: {exc}"
+                is_error = True
+            tool_results.append(
+                {
+                    "type": "tool_result",
+                    "tool_use_id": block.id,
+                    "content": content,
+                    "is_error": is_error,
+                }
+            )
+        messages.append({"role": "user", "content": tool_results})
+
+
+def initialize():
+    text, msgs, _ = _intake_turn("Please begin.", [])
+    chat = [{"role": "assistant", "content": text}]
+    # Strip the seed "Please begin." turn so subsequent user messages append cleanly.
+    # msgs already includes both the seed user turn and the assistant turn; keep it.
+    return chat, msgs, None, "intake"
+
+
+def respond(
+    user_msg: str,
+    chat_history: list,
+    intake_msgs: list,
+    profile,
+    phase: str,
+) -> Generator:
+    if not user_msg.strip() or phase == "done":
+        yield chat_history, intake_msgs, profile, phase, gr.update(), gr.update()
+        return
+
+    chat_history = chat_history + [{"role": "user", "content": user_msg}]
+    yield chat_history, intake_msgs, profile, phase, gr.update(value=""), gr.update()
+
+    assistant_text, updated_msgs, new_profile = _intake_turn(user_msg, intake_msgs)
+
+    if new_profile:
+        status = (assistant_text + "\n\n" if assistant_text else "") + (
+            "*Searching ClinicalTrials.gov — this may take a minute…*"
+        )
+        chat_history = chat_history + [{"role": "assistant", "content": status}]
+        yield (
+            chat_history,
+            updated_msgs,
+            new_profile,
+            "researching",
+            gr.update(interactive=False, placeholder="Searching…"),
+            gr.update(visible=False),
+        )
+
+        analysis = _run_research(new_profile)
+        chat_history = chat_history + [{"role": "assistant", "content": analysis}]
+        yield (
+            chat_history,
+            updated_msgs,
+            new_profile,
+            "done",
+            gr.update(interactive=False, placeholder="Search complete."),
+            gr.update(visible=True),
+        )
+    else:
+        chat_history = chat_history + [{"role": "assistant", "content": assistant_text}]
+        yield (
+            chat_history,
+            updated_msgs,
+            profile,
+            "intake",
+            gr.update(),
+            gr.update(),
+        )
+
+
+with gr.Blocks(title="Beacon — Clinical Trial Finder") as demo:
+    gr.Markdown("# 🔦 Beacon — Rare Disease Clinical Trial Finder")
+
+    chatbot = gr.Chatbot(height=550, show_label=False)
+    with gr.Row():
+        msg_box = gr.Textbox(
+            placeholder="Type your message and press Enter…",
+            show_label=False,
+            scale=9,
+            autofocus=True,
+        )
+        send_btn = gr.Button("Send", scale=1, variant="primary")
+    new_search_btn = gr.Button("New Search", visible=False, variant="secondary")
+
+    # State
+    intake_msgs_state = gr.State([])
+    profile_state = gr.State(None)
+    phase_state = gr.State("intake")
+
+    outputs = [chatbot, intake_msgs_state, profile_state, phase_state, msg_box, new_search_btn]
+
+    demo.load(
+        initialize,
+        outputs=[chatbot, intake_msgs_state, profile_state, phase_state],
+    )
+
+    msg_box.submit(respond, [msg_box, chatbot, intake_msgs_state, profile_state, phase_state], outputs)
+    send_btn.click(respond, [msg_box, chatbot, intake_msgs_state, profile_state, phase_state], outputs)
+
+    new_search_btn.click(
+        initialize,
+        outputs=[chatbot, intake_msgs_state, profile_state, phase_state],
+    ).then(
+        lambda: (gr.update(interactive=True, placeholder="Type your message and press Enter…"), gr.update(visible=False)),
+        outputs=[msg_box, new_search_btn],
+    )
+
+
+if __name__ == "__main__":
+    demo.launch()

pyproject.toml

@@ -10,4 +10,5 @@ dependencies = [
     "openai>=1.0.0",
     "python-dotenv>=1.2.2",
     "rich>=13.0.0",
+    "gradio>=4.0.0",
 ]

requirements.txt

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+anthropic>=0.50.0
+gradio>=4.0.0
+langgraph>=1.2.0
+httpx
+python-dotenv
+openai>=1.0.0
+rich>=13.0.0