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modules_archives/ai_cloudflare.py

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+import os
+from openai import OpenAI
+from modules.logger import log_event
+
+def interroger_cloudflare(prompt_securise):
+    account_id = os.getenv("CLOUDFLARE_ACCOUNT_ID")
+    api_key = os.getenv("CLOUDFLARE_API_KEY")
+    if not account_id or not api_key: raise Exception("Identifiants Cloudflare manquants.")
+    client = OpenAI(base_url=f"https://api.cloudflare.com/client/v4/accounts/{account_id}/ai/v1", api_key=api_key)
+    modeles = ["@cf/meta/llama-3-8b-instruct"]
+    for modele in modeles:
+        try:
+            resp = client.chat.completions.create(
+                model=modele,
+                messages=[{"role": "system", "content": "Réponds en français en Markdown."}, {"role": "user", "content": prompt_securise}]
+            )
+            if resp and resp.choices:
+                log_event("INFO", f"CF-{modele}", "Succès.")
+                return resp.choices[0].message.content, "#f38ba8", "CLOUDFLARE", modele
+        except Exception as e:
+            log_event("WARNING", f"CF-{modele}", f"Erreur: {e}")
+    raise Exception("Tous les modèles Cloudflare ont échoué.")

modules_archives/ai_deepseek.py

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+import os
+from openai import OpenAI
+from modules.logger import log_event
+
+def interroger_deepseek(prompt_securise):
+    api_key = os.getenv("DEEPSEEK_API_KEY")
+    if not api_key: raise Exception("Clé API DeepSeek manquante.")
+    client = OpenAI(base_url="https://api.deepseek.com", api_key=api_key)
+    try:
+        resp = client.chat.completions.create(
+            model="deepseek-chat",
+            messages=[{"role": "system", "content": "Réponds en français en Markdown."}, {"role": "user", "content": prompt_securise}]
+        )
+        if resp and resp.choices:
+            log_event("INFO", "DEEPSEEK-CHAT", "Succès de la requête.")
+            return resp.choices[0].message.content, "#4f46e5", "DEEPSEEK", "deepseek-chat"
+    except Exception as e:
+        log_event("WARNING", "DEEPSEEK", f"Erreur: {e}")
+        raise Exception("DeepSeek a échoué.")

modules_archives/ai_groq.py

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+import os
+from openai import OpenAI
+from modules.logger import log_event
+
+def interroger_groq(prompt_securise):
+    api_key = os.getenv("GROQ_API_KEY")
+    if not api_key: raise Exception("Clé API Groq manquante.")
+    client = OpenAI(base_url="https://api.groq.com/openai/v1", api_key=api_key)
+    modeles = ["llama-3.3-70b-versatile", "llama-3.1-8b-instant", "mixtral-8x7b-32768"]
+    for modele in modeles:
+        try:
+            resp = client.chat.completions.create(
+                model=modele,
+                messages=[{"role": "system", "content": "Réponds en français en Markdown."}, {"role": "user", "content": prompt_securise}]
+            )
+            if resp and resp.choices:
+                log_event("INFO", f"GROQ-{modele}", "Succès de la requête.")
+                return resp.choices[0].message.content, "#f97316", "GROQ", modele
+        except Exception as e:
+            log_event("WARNING", f"GROQ-{modele}", f"Erreur: {e}")
+    raise Exception("Tous les modèles Groq ont échoué.")

modules_archives/ai_huggingface.py

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+import os
+from openai import OpenAI
+from modules.logger import log_event
+
+def interroger_huggingface(prompt_securise):
+    api_key = os.getenv("HF_API_KEY")
+    if not api_key: raise Exception("Clé API HuggingFace manquante.")
+    client = OpenAI(base_url="https://api-inference.huggingface.co/v1/", api_key=api_key)
+    modeles = ["meta-llama/Meta-Llama-3-8B-Instruct", "mistralai/Mistral-7B-Instruct-v0.3"]
+    for modele in modeles:
+        try:
+            resp = client.chat.completions.create(
+                model=modele,
+                messages=[{"role": "system", "content": "Réponds en français en Markdown."}, {"role": "user", "content": prompt_securise}],
+                max_tokens=1500
+            )
+            if resp and resp.choices:
+                log_event("INFO", f"HF-{modele}", "Succès.")
+                return resp.choices[0].message.content, "#fbbf24", "HUGGINGFACE", modele
+        except Exception as e:
+            log_event("WARNING", f"HF-{modele}", f"Erreur: {e}")
+    raise Exception("Tous les modèles HuggingFace ont échoué.")

modules_archives/ai_mistral.py

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+import os
+from openai import OpenAI
+from modules.logger import log_event
+
+def interroger_mistral(prompt_securise):
+    api_key = os.getenv("MISTRAL_API_KEY")
+    if not api_key: raise Exception("Clé API Mistral manquante.")
+    client = OpenAI(base_url="https://api.mistral.ai/v1", api_key=api_key)
+    modeles = ["mistral-large-latest", "open-mistral-nemo"]
+    for modele in modeles:
+        try:
+            resp = client.chat.completions.create(
+                model=modele,
+                messages=[{"role": "system", "content": "Réponds en français en Markdown."}, {"role": "user", "content": prompt_securise}]
+            )
+            if resp and resp.choices:
+                log_event("INFO", f"MISTRAL-{modele}", "Succès.")
+                return resp.choices[0].message.content, "#f59e0b", "MISTRAL", modele
+        except Exception as e:
+            log_event("WARNING", f"MISTRAL-{modele}", f"Erreur: {e}")
+    raise Exception("Tous les modèles Mistral ont échoué.")