Update main.py

main.py

@@ -12,6 +12,7 @@ from dotenv import load_dotenv
 from starlette.responses import StreamingResponse
 from openai import OpenAI
 from typing import List, Optional, Dict, Any
+import copy
 
 load_dotenv()
 
@@ -47,6 +48,12 @@ app.add_middleware(
     allow_headers=["*"],
 )
 
+# Client OpenAI
+def get_openai_client():
+    ''' Client OpenAI passando in modo RANDOM le Chiavi API. In questo modo posso aggirare i limiti "Quota Exceeded" '''
+    api_key = random.choice(API_KEYS)
+    return OpenAI(api_key=api_key, base_url=BASE_URL)
+
 # Validazione API       
 api_key_header = APIKeyHeader(name=API_KEY_NAME, auto_error=False)
 def verify_api_key(api_key: str = Depends(api_key_header)):
@@ -57,17 +64,119 @@ def verify_api_key(api_key: str = Depends(api_key_header)):
         raise HTTPException(status_code=403, detail="API key non valida")
     return api_key
 
-# Client OpenAI
-def get_openai_client():
-    ''' Client OpenAI passando in modo RANDOM le Chiavi API. In questo modo posso aggirare i limiti "Quota Exceeded" '''
-    api_key = random.choice(API_KEYS)
-    return OpenAI(api_key=api_key, base_url=BASE_URL)
+# Correzione payload con content=None
+def sanitize_messages(messages):
+    """Convert None content to empty string to avoid Gemini API errors"""
+    if not messages:
+        return messages
+    for message in messages:
+        if message.get('content') is None:
+            message['content'] = " "
+    return messages
+
+# Funzione per conversione Payload OpenAI to GEMINI (anomalia per ACTION) AnyOf, e property: {}
+def convert_openai_schema_for_gemini(tools_schema):
+    if isinstance(tools_schema, str):
+        try:
+            tools_schema = json.loads(tools_schema)
+        except json.JSONDecodeError:
+            raise ValueError("Stringa JSON non valida fornita")
+    converted_schema = []
+    for tool in tools_schema:
+        if tool.get("type") != "function":
+            converted_schema.append(tool)
+            continue
+        converted_tool = {"type": "function", "function": {}}
+        func_def = tool.get("function", {})
+        if not func_def:
+            continue
+        converted_tool["function"]["name"] = func_def.get("name", "")
+        converted_tool["function"]["description"] = func_def.get("description", "")
+        if "parameters" in func_def:
+            params = func_def["parameters"]
+            converted_params = {"type": "object"}
+            if "properties" in params:
+                converted_properties = {}
+                for prop_name, prop_value in params["properties"].items():
+                    cleaned = clean_schema_property(prop_value)
+                    if cleaned:  # Aggiungi solo se il dizionario non è vuoto
+                        converted_properties[prop_name] = cleaned
+                if converted_properties:
+                    converted_params["properties"] = converted_properties
+            if "required" in params:
+                converted_params["required"] = params["required"]
+            converted_tool["function"]["parameters"] = converted_params
+        converted_schema.append(converted_tool)
+    return converted_schema
+
+def clean_schema_property(prop):
+    if not isinstance(prop, dict):
+        return prop
+    result = {}
+    for key, value in prop.items():
+        if key in ("title", "default"):
+            continue
+        elif key == "anyOf":
+            if isinstance(value, list):
+                for item in value:
+                    if isinstance(item, dict) and item.get("type") != "null":
+                        cleaned_item = clean_schema_property(item)
+                        for k, v in cleaned_item.items():
+                            if k not in result:
+                                result[k] = v
+                        break
+        elif key == "oneOf":
+            if isinstance(value, list) and len(value) > 0:
+                cleaned_item = clean_schema_property(value[0])
+                for k, v in cleaned_item.items():
+                    if k not in result:
+                        result[k] = v
+            elif isinstance(value, dict):
+                cleaned_item = clean_schema_property(value)
+                for k, v in cleaned_item.items():
+                    if k not in result:
+                        result[k] = v
+        elif key == "properties" and isinstance(value, dict):
+            new_props = {}
+            for prop_name, prop_value in value.items():
+                cleaned_prop = clean_schema_property(prop_value)
+                if cleaned_prop:
+                    new_props[prop_name] = cleaned_prop
+            if not new_props:  # Se vuoto, sostituisci con dummy
+                new_props = {"dummy": {"type": "string"}}
+            result[key] = new_props
+        elif key == "items" and isinstance(value, dict):
+            result[key] = clean_schema_property(value)
+        elif isinstance(value, list):
+            result[key] = [clean_schema_property(item) if isinstance(item, dict) else item for item in value]
+        else:
+            result[key] = value
+    if "type" not in result and "properties" in result and result["properties"]:
+        result["type"] = "object"
+    return result
+
+def convert_payload_for_gemini(payload: ChatCompletionRequest):
+    if hasattr(payload, "model_dump"):
+        payload_converted = json.loads(payload.model_dump_json())
+    elif isinstance(payload, dict):
+        payload_converted = payload.copy()
+    else:
+        raise ValueError("Formato payload non supportato")
+    if "tools" in payload_converted:
+        payload_converted["tools"] = convert_openai_schema_for_gemini(payload_converted["tools"])
+    new_payload = ChatCompletionRequest.model_validate(payload_converted)
+    return new_payload
 
+# ---------------------------------- Funzioni per Chat Completion ---------------------------------------
 # Chiama API (senza Streaming)
 def call_api_sync(params: ChatCompletionRequest):
     ''' Chiamata API senza streaming. Se da errore 429 lo rifa'''
     try:
         client = get_openai_client()
+        if params.messages:
+            params.messages = sanitize_messages(params.messages)       
+        params = convert_payload_for_gemini(params)
+        print(params)
         response_format = getattr(params, 'response_format', None)
         if response_format and getattr(response_format, 'type', None) == 'json_schema':    
             response = client.beta.chat.completions.parse(**params.model_dump())
@@ -87,6 +196,9 @@ async def _resp_async_generator(params: ChatCompletionRequest):
     client = get_openai_client()
     try:
         response = client.chat.completions.create(**params.model_dump())
+        if params.messages:
+            params.messages = sanitize_messages(params.messages)     
+        params = convert_payload_for_gemini(params)
         for chunk in response:
             chunk_data = chunk.to_dict() if hasattr(chunk, "to_dict") else chunk
             yield f"data: {json.dumps(chunk_data)}\n\n"
@@ -112,7 +224,6 @@ async def health_check():
 
 @app.post("/v1/chat/completions", dependencies=[Depends(verify_api_key)])
 async def chat_completions(req: ChatCompletionRequest):
-    print(req)
     try:    
         if not req.messages:
             raise HTTPException(status_code=400, detail="Nessun messaggio fornito")