Implemented timestamp injection at multiple levels to ensure AI always has access to current date/time

core/coordinator.py

@@ -123,7 +123,14 @@ Your role is to: 1. Provide immediate, concise responses using available informa
         try:
             # Get conversation history
             session = session_manager.get_session(user_id)
-            conversation_history = session.get("conversation", []).copy()
+
+            # Inject current time into context
+            current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+            time_context = {
+                "role": "system",
+                "content": f"[Current Date & Time: {current_time}]"
+            }
+            conversation_history = [time_context] + session.get("conversation", []).copy()
 
             yield {
                 'type': 'coordination_status',
@@ -253,6 +260,14 @@ Your role is to: 1. Provide immediate, concise responses using available informa
             # Prepare enhanced conversation for HF with hierarchical context
             enhanced_history = history.copy()
 
+            # Inject current time into HF context too
+            current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+            time_context = {
+                "role": "system",
+                "content": f"[Current Date & Time: {current_time}]"
+            }
+            enhanced_history = [time_context] + enhanced_history
+
             # Add system instructions for HF
             enhanced_history.insert(0, {
                 "role": "system",
@@ -310,6 +325,14 @@ Your role is to: 1. Provide immediate, concise responses using available informa
             # Prepare conversation with hierarchical context
             enhanced_history = history.copy()
 
+            # Inject current time into Ollama context too
+            current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+            time_context = {
+                "role": "system",
+                "content": f"[Current Date & Time: {current_time}]"
+            }
+            enhanced_history = [time_context] + enhanced_history
+
             # Add system instruction for Ollama's role
             enhanced_history.insert(0, {
                 "role": "system",

core/providers/huggingface.py

@@ -1,5 +1,6 @@
 import time
 import logging
+from datetime import datetime
 from typing import List, Dict, Optional, Union
 from core.providers.base import LLMProvider
 from utils.config import config
@@ -13,18 +14,18 @@ except ImportError:
 
 class HuggingFaceProvider(LLMProvider):
     """Hugging Face LLM provider implementation"""
-    
+
     def __init__(self, model_name: str, timeout: int = 30, max_retries: int = 3):
         super().__init__(model_name, timeout, max_retries)
         logger.info(f"Initializing HuggingFaceProvider with:")
         logger.info(f" HF_API_URL: {config.hf_api_url}")
         logger.info(f" HF_TOKEN SET: {bool(config.hf_token)}")
-        
+
         if not HUGGINGFACE_SDK_AVAILABLE:
             raise ImportError("Hugging Face provider requires 'openai' package")
         if not config.hf_token:
             raise ValueError("HF_TOKEN not set - required for Hugging Face provider")
-        
+
         # Make sure NO proxies parameter is included
         try:
             self.client = OpenAI(
@@ -66,10 +67,15 @@ class HuggingFaceProvider(LLMProvider):
 
     def _generate_impl(self, prompt: str, conversation_history: List[Dict]) -> str:
         """Implementation of synchronous generation with proper configuration"""
+        # Inject current time as first message
+        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
+        enhanced_history = [time_context] + conversation_history
+
         try:
             response = self.client.chat.completions.create(
                 model=self.model_name,
-                messages=conversation_history,
+                messages=enhanced_history,
                 max_tokens=8192,  # Set to 8192 as requested
                 temperature=0.7,
                 top_p=0.9,
@@ -85,7 +91,7 @@ class HuggingFaceProvider(LLMProvider):
                 # Retry once after waiting
                 response = self.client.chat.completions.create(
                     model=self.model_name,
-                    messages=conversation_history,
+                    messages=enhanced_history,
                     max_tokens=8192,  # Set to 8192 as requested
                     temperature=0.7,
                     top_p=0.9,
@@ -98,10 +104,15 @@ class HuggingFaceProvider(LLMProvider):
 
     def _stream_generate_impl(self, prompt: str, conversation_history: List[Dict]) -> List[str]:
         """Implementation of streaming generation with proper configuration"""
+        # Inject current time as first message
+        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
+        enhanced_history = [time_context] + conversation_history
+
         try:
             response = self.client.chat.completions.create(
                 model=self.model_name,
-                messages=conversation_history,
+                messages=enhanced_history,
                 max_tokens=8192,  # Set to 8192 as requested
                 temperature=0.7,
                 top_p=0.9,
@@ -109,13 +120,13 @@ class HuggingFaceProvider(LLMProvider):
                 presence_penalty=0.1,
                 stream=True  # Enable streaming
             )
-            
+
             chunks = []
             for chunk in response:
                 content = chunk.choices[0].delta.content
                 if content:
                     chunks.append(content)
-            
+
             return chunks
         except Exception as e:
             # Handle scale-to-zero behavior
@@ -125,7 +136,7 @@ class HuggingFaceProvider(LLMProvider):
                 # Retry once after waiting
                 response = self.client.chat.completions.create(
                     model=self.model_name,
-                    messages=conversation_history,
+                    messages=enhanced_history,
                     max_tokens=8192,  # Set to 8192 as requested
                     temperature=0.7,
                     top_p=0.9,
@@ -133,13 +144,13 @@ class HuggingFaceProvider(LLMProvider):
                     presence_penalty=0.1,
                     stream=True  # Enable streaming
                 )
-                
+
                 chunks = []
                 for chunk in response:
                     content = chunk.choices[0].delta.content
                     if content:
                         chunks.append(content)
-                
+
                 return chunks
             else:
                 raise

core/providers/ollama.py

@@ -1,6 +1,7 @@
 import requests
 import logging
 import re
+from datetime import datetime
 from typing import List, Dict, Optional, Union
 from core.providers.base import LLMProvider
 from utils.config import config
@@ -9,7 +10,7 @@ logger = logging.getLogger(__name__)
 
 class OllamaProvider(LLMProvider):
     """Ollama LLM provider implementation"""
-    
+
     def __init__(self, model_name: str, timeout: int = 60, max_retries: int = 3):  # Increased timeout from 30 to 60
         super().__init__(model_name, timeout, max_retries)
         self.host = self._sanitize_host(config.ollama_host or "http://localhost:11434")
@@ -77,6 +78,12 @@ class OllamaProvider(LLMProvider):
         """Implementation of synchronous generation"""
         url = f"{self.host}/api/chat"
         messages = conversation_history.copy()
+        
+        # Inject current time as first message
+        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
+        messages = [time_context] + messages
+
         # Add the current prompt if not already in history
         if not messages or messages[-1].get("content") != prompt:
             messages.append({"role": "user", "content": prompt})
@@ -99,6 +106,12 @@ class OllamaProvider(LLMProvider):
         """Implementation of streaming generation"""
         url = f"{self.host}/api/chat"
         messages = conversation_history.copy()
+        
+        # Inject current time as first message
+        current_time = datetime.now().strftime("%A, %B %d, %Y at %I:%M %p")
+        time_context = {"role": "system", "content": f"[Current Date & Time: {current_time}]"}
+        messages = [time_context] + messages
+
         # Add the current prompt if not already in history
         if not messages or messages[-1].get("content") != prompt:
             messages.append({"role": "user", "content": prompt})