space

README.md

@@ -1,8 +1,8 @@
 ---
-title: Where Is Pharmacy
-emoji: 🔥
-colorFrom: purple
-colorTo: red
+title: Pharmacy Tool Calling
+emoji: 🏥
+colorFrom: green
+colorTo: gray
 sdk: gradio
 sdk_version: 6.21.0
 python_version: '3.12'
@@ -10,4 +10,11 @@ app_file: app.py
 pinned: false
 ---
 
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# Pharmacy Tool Calling Agent
+
+This repository implements a Tool-Calling / Function-Calling agent using the fine-tuned LoRA model `menesnas/gemma_4_pharmacy_lora` integrated with **SerpApi Google Maps API**.
+
+## Features
+- **Public API**: SerpApi Google Maps Engine
+- **Tool Calling**: Triggers `get_nearby_pharmacies` tool based on user query.
+- **Step Traceability**: Displays `Turn 1 (Tool Call)`, `Turn 2 (API Result)`, and `Turn 3 (Final Answer)`.

app.py

@@ -0,0 +1,322 @@
+import os
+import json
+import re
+import requests
+import torch
+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+# ---------------------------------------------------------------------------
+# 1. CONFIG & TOOLS SCHEMA
+# ---------------------------------------------------------------------------
+SERPAPI_KEY = os.getenv("SERPAPI_KEY", "")
+MODEL_ID = "menesnas/gemma_4_pharmacy_merged"
+
+TOOLS_SCHEMA = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_nearby_pharmacies",
+            "description": "Belirtilen ilçe, şehir veya adresteki en yakın eczaneleri arar.",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "Eczane aranacak konum adı (ör. 'Kadıköy, İstanbul', 'Karaköy')",
+                    }
+                },
+                "required": ["location"],
+            },
+        },
+    }
+]
+
+# ---------------------------------------------------------------------------
+# 2. API FUNCTION (SerpApi Google Maps + Fallback Mock Data)
+# ---------------------------------------------------------------------------
+def get_nearby_pharmacies(location: str, api_key: str = ""):
+    """SerpApi ile Google Maps üzerinden eczane arar. Key yoksa mock veri döner."""
+    key = api_key.strip() or SERPAPI_KEY
+    if not key:
+        # Fallback Mock Data (API Key girilmediyse veya boşsa ödev kontrolü için)
+        return {
+            "location": location,
+            "status": "DEMO_MOCK_DATA (SERPAPI_KEY Tanımlı Değil)",
+            "pharmacies": [
+                {"name": f"{location} Merkez Eczanesi", "address": f"{location} Cad. No:12", "rating": 4.8, "phone": "+90 216 555 0101", "open_state": "Açık"},
+                {"name": f"{location} Şifa Eczanesi", "address": f"{location} Sok. No:5", "rating": 4.6, "phone": "+90 216 555 0102", "open_state": "Nöbetçi"},
+                {"name": f"{location} Hayat Eczanesi", "address": f"{location} Meydan No:8", "rating": 4.5, "phone": "+90 216 555 0103", "open_state": "Açık"}
+            ]
+        }
+
+    url = "https://serpapi.com/search.json"
+    params = {
+        "engine": "google_maps",
+        "q": f"eczane {location}",
+        "type": "search",
+        "api_key": key,
+    }
+    try:
+        response = requests.get(url, params=params, timeout=10)
+        data = response.json()
+        results = []
+        for item in data.get("local_results", [])[:5]:
+            results.append({
+                "name": item.get("title", "Bilinmeyen Eczane"),
+                "address": item.get("address", "Adres yok"),
+                "rating": item.get("rating", "Puan yok"),
+                "phone": item.get("phone", "Telefon yok"),
+                "open_state": item.get("open_state", "Bilinmiyor"),
+            })
+        if not results:
+            return {"error": f"'{location}' konumunda eczane bulunamadı."}
+        return {"location": location, "pharmacies": results}
+    except Exception as e:
+        return {"error": f"API hatası: {str(e)}"}
+
+
+# ---------------------------------------------------------------------------
+# 3. MODEL LOADING
+# ---------------------------------------------------------------------------
+
+print("Model ve Tokenizer Yükleniyor...")
+
+tokenizer = AutoTokenizer.from_pretrained(MODEL_ID)
+
+try:
+    model = AutoModelForCausalLM.from_pretrained(
+        MODEL_ID,
+        torch_dtype=torch.float16,
+        device_map="auto",
+    )
+except Exception:
+    model = AutoModelForCausalLM.from_pretrained(
+        MODEL_ID,
+        torch_dtype=torch.float32,
+        device_map="cpu",
+    )
+
+model.eval()
+
+print("✓ Model başarıyla yüklendi.")
+print(type(tokenizer))
+print(tokenizer)
+
+
+def decode_tokens(output_tokens):
+    """Model çıktısı token id'lerini metne çevirir."""
+    return tokenizer.decode(
+        output_tokens,
+        skip_special_tokens=True,
+    ).strip()
+
+
+# ---------------------------------------------------------------------------
+# 4. AGENT DÖNGÜSÜ (TOOL CALLING PROCESS)
+# ---------------------------------------------------------------------------
+def run_pharmacy_agent(user_query: str, custom_api_key: str = ""):
+
+    execution_logs = []
+
+    system_prompt = f"""Sen sağlık ve eczane konusunda uzman bir asistansın.
+Sana verilen araçları (tools) kullanarak kullanıcı sorularına yanıt vermelisin.
+
+Mevcut Araçlar:
+{json.dumps(TOOLS_SCHEMA, ensure_ascii=False, indent=2)}
+
+ÇOK ÖNEMLİ:
+
+Kullanıcı;
+
+- eczane
+- nöbetçi eczane
+- en yakın eczane
+- hangi eczaneler
+- adres
+- telefon
+- konum
+
+ile ilgili herhangi bir soru sorarsa
+
+KESİNLİKLE doğrudan cevap verme.
+
+KESİNLİKLE aşağıdaki JSON dışında hiçbir şey yazma.
+
+{{
+  "name":"get_nearby_pharmacies",
+  "arguments":{{
+      "location":"..."
+  }}
+}}
+
+Doğrudan cevap vermek yasaktır.
+
+{{
+  "name": "get_nearby_pharmacies",
+  "arguments": {{
+    "location": "konum_adı"
+  }}
+}}
+"""
+
+    # -----------------------------
+    # TURN 1
+    # -----------------------------
+    messages = [
+        {
+            "role": "system",
+            "content": system_prompt,
+        },
+        {
+            "role": "user",
+            "content": user_query,
+        },
+    ]
+
+    text = tokenizer.apply_chat_template(
+        messages,
+        tokenize=False,
+        add_generation_prompt=True,
+    )
+
+    print(text)
+
+    inputs = tokenizer(
+        text=text,
+        return_tensors="pt",
+    ).to(model.device)
+
+    with torch.no_grad():
+        outputs = model.generate(
+            **inputs,
+            max_new_tokens=200,
+            do_sample=False,
+            temperature=0.2,
+        )
+
+    model_response = decode_tokens(outputs[0][inputs.input_ids.shape[1]:])
+
+    print(model_response)
+
+    json_match = re.search(r"\{.*\}", model_response, re.DOTALL)
+
+    if json_match and (
+        "get_nearby_pharmacies" in model_response
+        or "arguments" in model_response
+    ):
+
+        try:
+
+            tool_call = json.loads(json_match.group(0))
+
+            location = tool_call.get(
+                "arguments", {}
+            ).get("location", user_query)
+
+            execution_logs.append(
+                f"[Turn 1] Araç Çağrısı:\n"
+                f"-> get_nearby_pharmacies(location='{location}')"
+            )
+
+            api_result = get_nearby_pharmacies(
+                location,
+                custom_api_key,
+            )
+
+            execution_logs.append(
+                "\n[Turn 2] API Yanıtı:\n"
+                + json.dumps(
+                    api_result,
+                    ensure_ascii=False,
+                    indent=2,
+                )
+            )
+
+            # -----------------------------
+            # TURN 2
+            # -----------------------------
+            second_messages = [
+                {
+                    "role": "system",
+                    "content": system_prompt,
+                },
+                {
+                    "role": "assistant",
+                    "content": model_response,
+                },
+                {
+                    "role": "user",
+                    "content":
+                        f"""Tool sonucu:
+
+{json.dumps(api_result, ensure_ascii=False)}
+
+Bu bilgileri kullanıcıya anlaşılır ve maddeler halinde açıkla.
+""",
+                },
+            ]
+
+            second_text = tokenizer.apply_chat_template(
+                second_messages,
+                tokenize=False,
+                add_generation_prompt=True,
+            )
+
+            second_inputs = tokenizer(
+                text=second_text,
+                return_tensors="pt",
+            ).to(model.device)
+
+            with torch.no_grad():
+
+                second_outputs = model.generate(
+                    **second_inputs,
+                    max_new_tokens=400,
+                    do_sample=False,
+                    temperature=0.2,
+                )
+
+            final_answer = decode_tokens(second_outputs[0][second_inputs.input_ids.shape[1]:])
+
+            execution_logs.append(
+                "\n[Turn 3] Nihai Yanıt:\n"
+                + final_answer
+            )
+
+            return "\n".join(execution_logs)
+
+        except Exception as e:
+
+            execution_logs.append(
+                f"⚠️ Tool parse hatası: {e}"
+            )
+
+            execution_logs.append(model_response)
+
+            return "\n".join(execution_logs)
+
+    else:
+
+        execution_logs.append(
+            "[Turn 1] Tool çağrılmadı."
+        )
+
+        execution_logs.append(model_response)
+
+        return "\n".join(execution_logs)
+
+# ---------------------------------------------------------------------------
+# 5. GRADIO INTERFACE
+# ---------------------------------------------------------------------------
+demo = gr.Interface(
+    fn=run_pharmacy_agent,
+    inputs=[
+        gr.Textbox(label="Sorgu / Konum", placeholder="Örn: Kadıköy'deki en yakın eczaneleri bul", lines=2),
+    ],
+    outputs=gr.Textbox(label="Tool Call İşlem Adımları (Turn 1 -> Turn 2 -> Turn 3)", lines=18),
+    title="🏥 Pharmacy Tool-Calling Agent (`menesnas/gemma_4_pharmacy_merged`)",
+    description="Gemma 4 Merged modeli ile SerpApi Google Maps entegrasyonu."
+)
+
+if __name__ == "__main__":
+    demo.launch()

requirements.txt

@@ -0,0 +1,6 @@
+torch
+transformers>=4.55
+gradio
+requests
+accelerate
+sentencepiece