Update app.py

app.py

@@ -4,14 +4,12 @@ import requests
 
 # API Keys ophalen uit Hugging Face Secrets
 WEAVIATE_API_KEY = os.getenv("WEAVIATE_APIKEY")
-MISTRAL_API_KEY = os.getenv("MISTRAL_APIKEY")
+VLAM_API_KEY = os.getenv("VLAM_APIKEY")  # Nieuwe variabele voor VLAM.AI
 
-# Weaviate-instellingen
-WEAVIATE_URL = "https://ojk79flbtdqux0f4uua2qa.c0.europe-west3.gcp.weaviate.cloud/v1/graphql"
+# Weaviate-instellingen (update je Weaviate URL en cluster)
+WEAVIATE_URL = "https://k6hr14w1r8gwkdctkxha.c0.europe-west3.gcp.weaviate.cloud/v1/graphql"
 HEADERS = {
     "Authorization": f"Bearer {WEAVIATE_API_KEY}",
-    "X-Weaviate-Api-Key": WEAVIATE_API_KEY,
-    "X-Weaviate-Cluster-Url": "https://ojk79flbtdqux0f4uua2qa.c0.europe-west3.gcp.weaviate.cloud",
     "Content-Type": "application/json"
 }
 
@@ -30,7 +28,7 @@ def fetch_relevant_docs(user_query):
         "query": f"""
         {{
           Get {{
-            DigiD_Document_Vectorized(
+            DigiDDocument(  # Aangepast naar je nieuwe collection
               nearText: {{ concepts: ["{user_query}"] }},
               limit: 3
             ) {{
@@ -42,29 +40,23 @@ def fetch_relevant_docs(user_query):
         }}
         """
     }
-
     response = requests.post(WEAVIATE_URL, json=query, headers=HEADERS)
-
     if response.status_code == 200:
         data = response.json()
-        documents = data.get("data", {}).get("Get", {}).get("DigiD_Document_Vectorized", [])
-
+        documents = data.get("data", {}).get("Get", {}).get("DigiDDocument", [])
         if not documents:
             print(f"⚠️ Geen documenten gevonden voor de query: {user_query}")
             return None
-
         # Combineer de documentatie in een nette tekst
         combined_text = "\n\n".join(
             [f"**{doc['title']}**\n{doc['content']}\nBron: {doc['url']}" for doc in documents]
         )
-
         return combined_text
-
     else:
         print(f"❌ Fout bij ophalen documentatie: {response.status_code}, {response.text}")
         return None
 
-# **Functie om antwoord te genereren met Mistral**
+# **Functie om antwoord te genereren met VLAM.AI**
 def generate_answer(vraag, history=[]):
     messages = [{"role": "system", "content": SYSTEM_PROMPT}]
 
@@ -75,28 +67,34 @@ def generate_answer(vraag, history=[]):
     else:
         messages.append({"role": "system", "content": "Er is geen relevante documentatie gevonden. Probeer het opnieuw of neem contact op met Logius."})
 
-    # **Loop door de gespreksgeschiedenis en voeg alleen geldige entries toe**
+    # **Loop door de gespreksgeschiedenis**
     for turn in history:
-        if turn[0]:  
+        if turn[0]:
             messages.append({"role": "user", "content": turn[0]})
-        if turn[1]:  
+        if turn[1]:
             messages.append({"role": "assistant", "content": turn[1]})
 
     # Voeg de huidige gebruikersvraag toe
     messages.append({"role": "user", "content": vraag})
 
-    # **Mistral API instellingen**
-    MISTRAL_API_URL = "https://api.mistral.ai/v1/chat/completions"
-    MISTRAL_HEADERS = {
-        "Authorization": f"Bearer {MISTRAL_API_KEY}",
+    # **VLAM.AI API instellingen**
+    VLAM_API_URL = "https://api.demo.vlam.ai/v2.1/projects/poc/openai-compatible/v1/chat/completions"
+    VLAM_HEADERS = {
+        "Authorization": f"Bearer {VLAM_API_KEY}",
         "Content-Type": "application/json"
     }
+    VLAM_DATA = {
+        "model": "ubiops-deployment/logius-pc-mistralmedium-flexibel//chat-model",  # VLAM.AI model
+        "messages": messages,
+        "max_tokens": 512,
+        "temperature": 0.2
+    }
 
-    # **API-aanroep naar Mistral**
+    # **API-aanroep naar VLAM.AI**
     response = requests.post(
-        MISTRAL_API_URL,
-        headers=MISTRAL_HEADERS,
-        json={"model": "mistral-medium", "messages": messages, "max_tokens": 512, "temperature": 0.2}
+        VLAM_API_URL,
+        headers=VLAM_HEADERS,
+        json=VLAM_DATA
     )
 
     if response.status_code == 200:
@@ -106,7 +104,6 @@ def generate_answer(vraag, history=[]):
         return f"⚠️ Fout bij genereren antwoord: {response.status_code}, {response.text}"
 
 # **Gradio UI met gespreksgeschiedenis**
-demo = gr.ChatInterface(generate_answer, chatbot=gr.Chatbot(), title="DigiD Assistent")
-
+demo = gr.ChatInterface(generate_answer, chatbot=gr.Chatbot(), title="DigiD Assistent (VLAM.AI)")
 if __name__ == "__main__":
     demo.launch()