More LLMs

trustgraph-flow/trustgraph/model/text_completion/azure/llm.py

@@ -55,7 +55,9 @@ class Processor(LlmService):
         self.max_output = max_output
         self.default_model = model
 
-    def build_prompt(self, system, content):
+    def build_prompt(self, system, content, temperature=None):
+        # Use provided temperature or fall back to default
+        effective_temperature = temperature if temperature is not None else self.temperature
 
         data =  {
             "messages": [
@@ -67,7 +69,7 @@ class Processor(LlmService):
                 }
             ],
             "max_tokens": self.max_output,
-            "temperature": self.temperature,
+            "temperature": effective_temperature,
             "top_p": 1
         }
 
@@ -100,18 +102,22 @@ class Processor(LlmService):
 
         return result
 
-    async def generate_content(self, system, prompt, model=None):
+    async def generate_content(self, system, prompt, model=None, temperature=None):
 
         # Use provided model or fall back to default
         model_name = model or self.default_model
+        # Use provided temperature or fall back to default
+        effective_temperature = temperature if temperature is not None else self.temperature
 
         logger.debug(f"Using model: {model_name}")
+        logger.debug(f"Using temperature: {effective_temperature}")
 
         try:
 
             prompt = self.build_prompt(
                 system,
-                prompt
+                prompt,
+                effective_temperature
             )
 
             response = self.call_llm(prompt)

trustgraph-flow/trustgraph/model/text_completion/azure_openai/llm.py

@@ -62,12 +62,15 @@ class Processor(LlmService):
             azure_endpoint = endpoint,
         )
 
-    async def generate_content(self, system, prompt, model=None):
+    async def generate_content(self, system, prompt, model=None, temperature=None):
 
         # Use provided model or fall back to default
         model_name = model or self.default_model
+        # Use provided temperature or fall back to default
+        effective_temperature = temperature if temperature is not None else self.temperature
 
         logger.debug(f"Using model: {model_name}")
+        logger.debug(f"Using temperature: {effective_temperature}")
 
         prompt = system + "\n\n" + prompt
 
@@ -86,7 +89,7 @@ class Processor(LlmService):
                         ]
                     }
                 ],
-                temperature=self.temperature,
+                temperature=effective_temperature,
                 max_tokens=self.max_output,
                 top_p=1,
             )

trustgraph-flow/trustgraph/model/text_completion/googleaistudio/llm.py

@@ -86,12 +86,18 @@ class Processor(LlmService):
 
         logger.info("GoogleAIStudio LLM service initialized")
 
-    def _get_or_create_config(self, model_name):
+    def _get_or_create_config(self, model_name, temperature=None):
-        """Get cached generation config or create new one"""
+        """Get or create generation config with dynamic temperature"""
-        if model_name not in self.generation_configs:
+        # Use provided temperature or fall back to default
-            logger.info(f"Creating generation config for '{model_name}'")
+        effective_temperature = temperature if temperature is not None else self.temperature
-            self.generation_configs[model_name] = types.GenerateContentConfig(
+
-                temperature = self.temperature,
+        # Create cache key that includes temperature to avoid conflicts
+        cache_key = f"{model_name}:{effective_temperature}"
+
+        if cache_key not in self.generation_configs:
+            logger.info(f"Creating generation config for '{model_name}' with temperature {effective_temperature}")
+            self.generation_configs[cache_key] = types.GenerateContentConfig(
+                temperature = effective_temperature,
                 top_p = 1,
                 top_k = 40,
                 max_output_tokens = self.max_output,
@@ -99,16 +105,19 @@ class Processor(LlmService):
                 safety_settings = self.safety_settings,
             )
 
-        return self.generation_configs[model_name]
+        return self.generation_configs[cache_key]
 
-    async def generate_content(self, system, prompt, model=None):
+    async def generate_content(self, system, prompt, model=None, temperature=None):
 
         # Use provided model or fall back to default
         model_name = model or self.default_model
+        # Use provided temperature or fall back to default
+        effective_temperature = temperature if temperature is not None else self.temperature
 
         logger.debug(f"Using model: {model_name}")
+        logger.debug(f"Using temperature: {effective_temperature}")
 
-        generation_config = self._get_or_create_config(model_name)
+        generation_config = self._get_or_create_config(model_name, effective_temperature)
         # Set system instruction per request (can't be cached)
         generation_config.system_instruction = system
 

trustgraph-flow/trustgraph/model/text_completion/vllm/llm.py

@@ -52,12 +52,15 @@ class Processor(LlmService):
         logger.info(f"Using vLLM service at {base_url}")
         logger.info("vLLM LLM service initialized")
 
-    async def generate_content(self, system, prompt, model=None):
+    async def generate_content(self, system, prompt, model=None, temperature=None):
 
         # Use provided model or fall back to default
         model_name = model or self.default_model
+        # Use provided temperature or fall back to default
+        effective_temperature = temperature if temperature is not None else self.temperature
 
         logger.debug(f"Using model: {model_name}")
+        logger.debug(f"Using temperature: {effective_temperature}")
 
         headers = {
             "Content-Type": "application/json",
@@ -67,7 +70,7 @@ class Processor(LlmService):
             "model": model_name,
             "prompt": system + "\n\n" + prompt,
             "max_tokens": self.max_output,
-            "temperature": self.temperature,
+            "temperature": effective_temperature,
         }            
 
         try: