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Browse files- modules/analyzer.py +11 -17
modules/analyzer.py
CHANGED
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@@ -20,7 +20,7 @@ class Analyzer:
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# Connect to Redis cache
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self.cache = RedisServerStatusCache()
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-
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def is_server_ready(self):
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# Check cache first
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cached_status = self.cache.get(self.cache_key)
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@@ -61,7 +61,7 @@ class Analyzer:
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self.cache.set(self.cache_key, is_ready, ttl=60) # Cache for 1 minute
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log_server_status(self.cache_key, is_ready)
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return is_ready
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-
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def wait_for_server(self, timeout=300, interval=15): # Increased timeout to 5 minutes
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"""Wait for server to be ready with user feedback"""
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if self.is_server_ready():
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@@ -81,7 +81,7 @@ class Analyzer:
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logging.warning("⏰ Server initialization timeout reached")
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return False
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def analyze_stream(self, query, search_results):
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""" Analyze search results using the custom LLM with streaming output
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Yields chunks of the response as they arrive """
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@@ -92,8 +92,7 @@ class Analyzer:
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for result in search_results[:5] # Limit to top 5 for context
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])
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prompt = f"""
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You are an expert research analyst. Analyze the following query and information to provide a comprehensive summary.
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Query: {query}
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Information: {context}
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@@ -105,8 +104,7 @@ Please provide:
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4. Potential implications or future directions
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5. Any controversies or conflicting viewpoints
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Structure your response clearly with these sections. If there is insufficient information, state that clearly.
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"""
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try:
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# First check if server is ready with extended timeout and user feedback
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@@ -134,14 +132,12 @@ Structure your response clearly with these sections. If there is insufficient in
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stream=True # Enable streaming
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)
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# Yield chunks as they arrive
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accumulated_response = ""
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for chunk in response:
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if chunk.choices[0].delta.content:
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content = chunk.choices[0].delta.content
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yield accumulated_response
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logging.info("Analysis streaming completed successfully")
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@@ -157,7 +153,7 @@ Structure your response clearly with these sections. If there is insufficient in
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yield "⚠️ The AI model endpoint was not found. Please check the configuration."
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else:
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yield f"Analysis failed: {str(e)}"
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def analyze(self, query, search_results):
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""" Non-streaming version for compatibility """
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@@ -167,8 +163,7 @@ Structure your response clearly with these sections. If there is insufficient in
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for result in search_results[:5] # Limit to top 5 for context
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])
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prompt = f"""
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You are an expert research analyst. Analyze the following query and information to provide a comprehensive summary.
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Query: {query}
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Information: {context}
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@@ -180,8 +175,7 @@ Please provide:
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4. Potential implications or future directions
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5. Any controversies or conflicting viewpoints
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Structure your response clearly with these sections. If there is insufficient information, state that clearly.
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"""
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try:
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# First check if server is ready with extended timeout
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# Connect to Redis cache
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self.cache = RedisServerStatusCache()
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+
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def is_server_ready(self):
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# Check cache first
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cached_status = self.cache.get(self.cache_key)
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self.cache.set(self.cache_key, is_ready, ttl=60) # Cache for 1 minute
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log_server_status(self.cache_key, is_ready)
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return is_ready
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def wait_for_server(self, timeout=300, interval=15): # Increased timeout to 5 minutes
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"""Wait for server to be ready with user feedback"""
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if self.is_server_ready():
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logging.warning("⏰ Server initialization timeout reached")
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return False
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def analyze_stream(self, query, search_results):
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""" Analyze search results using the custom LLM with streaming output
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Yields chunks of the response as they arrive """
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for result in search_results[:5] # Limit to top 5 for context
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])
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prompt = f"""You are an expert research analyst. Analyze the following query and information to provide a comprehensive summary.
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Query: {query}
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Information: {context}
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4. Potential implications or future directions
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5. Any controversies or conflicting viewpoints
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Structure your response clearly with these sections. If there is insufficient information, state that clearly."""
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try:
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# First check if server is ready with extended timeout and user feedback
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stream=True # Enable streaming
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)
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# Yield chunks as they arrive
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for chunk in response:
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if chunk.choices[0].delta.content:
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content = chunk.choices[0].delta.content
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# Yield only the new content, not the accumulated response
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yield content
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logging.info("Analysis streaming completed successfully")
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yield "⚠️ The AI model endpoint was not found. Please check the configuration."
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else:
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yield f"Analysis failed: {str(e)}"
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def analyze(self, query, search_results):
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""" Non-streaming version for compatibility """
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for result in search_results[:5] # Limit to top 5 for context
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])
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prompt = f"""You are an expert research analyst. Analyze the following query and information to provide a comprehensive summary.
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Query: {query}
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Information: {context}
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4. Potential implications or future directions
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5. Any controversies or conflicting viewpoints
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Structure your response clearly with these sections. If there is insufficient information, state that clearly."""
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try:
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# First check if server is ready with extended timeout
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