ciyidogan commited on
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899e37d
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1 Parent(s): 07dfca1

Update llm/llm_spark.py

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Files changed (1) hide show
  1. llm/llm_spark.py +115 -115
llm/llm_spark.py CHANGED
@@ -1,116 +1,116 @@
1
- """
2
- Spark LLM Implementation
3
- """
4
- import os
5
- import httpx
6
- import json
7
- from typing import Dict, List, Any, AsyncIterator
8
- from llm_interface import LLMInterface
9
- from utils.logger import log_info, log_error, log_warning, log_debug
10
-
11
- # Get timeout from environment
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- DEFAULT_LLM_TIMEOUT = int(os.getenv("LLM_TIMEOUT_SECONDS", "60"))
13
- MAX_RESPONSE_LENGTH = int(os.getenv("LLM_MAX_RESPONSE_LENGTH", "4096"))
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-
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- class SparkLLM(LLMInterface):
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- """Spark LLM integration with improved error handling"""
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-
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- def __init__(self, spark_endpoint: str, spark_token: str, provider_variant: str = "cloud", settings: Dict[str, Any] = None):
19
- super().__init__(settings)
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- self.spark_endpoint = spark_endpoint.rstrip("/")
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- self.spark_token = spark_token
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- self.provider_variant = provider_variant
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- self.timeout = self.settings.get("timeout", DEFAULT_LLM_TIMEOUT)
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- log_info(f"πŸ”Œ SparkLLM initialized", endpoint=self.spark_endpoint, timeout=self.timeout)
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-
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- async def generate(self, system_prompt: str, user_input: str, context: List[Dict]) -> str:
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- """Generate response with improved error handling and streaming support"""
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- headers = {
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- "Authorization": f"Bearer {self.spark_token}",
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- "Content-Type": "application/json"
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- }
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-
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- # Build context messages
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- messages = []
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- if system_prompt:
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- messages.append({
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- "role": "system",
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- "content": system_prompt
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- })
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-
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- for msg in context[-10:]: # Last 10 messages for context
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- messages.append({
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- "role": msg.get("role", "user"),
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- "content": msg.get("content", "")
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- })
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-
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- messages.append({
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- "role": "user",
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- "content": user_input
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- })
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-
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- payload = {
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- "messages": messages,
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- "mode": self.provider_variant,
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- "max_tokens": self.settings.get("max_tokens", 2048),
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- "temperature": self.settings.get("temperature", 0.7),
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- "stream": False # For now, no streaming
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- }
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-
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- try:
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- async with httpx.AsyncClient(timeout=self.timeout) as client:
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- with LogTimer(f"Spark LLM request"):
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- response = await client.post(
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- f"{self.spark_endpoint}/generate",
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- json=payload,
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- headers=headers
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- )
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-
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- # Check for rate limiting
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- if response.status_code == 429:
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- retry_after = response.headers.get("Retry-After", "60")
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- log_warning(f"Rate limited by Spark", retry_after=retry_after)
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- raise httpx.HTTPStatusError(
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- f"Rate limited. Retry after {retry_after}s",
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- request=response.request,
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- response=response
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- )
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-
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- response.raise_for_status()
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- result = response.json()
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-
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- # Extract response
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- content = result.get("model_answer", "")
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-
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- # Check response length
86
- if len(content) > MAX_RESPONSE_LENGTH:
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- log_warning(f"Response exceeded max length, truncating",
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- original_length=len(content),
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- max_length=MAX_RESPONSE_LENGTH)
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- content = content[:MAX_RESPONSE_LENGTH] + "..."
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-
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- return content
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-
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- except httpx.TimeoutException:
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- log_error(f"Spark request timed out", timeout=self.timeout)
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- raise
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- except httpx.HTTPStatusError as e:
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- log_error(f"Spark HTTP error",
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- status_code=e.response.status_code,
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- response=e.response.text[:500])
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- raise
102
- except Exception as e:
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- log_error("Spark unexpected error", error=str(e))
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- raise
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-
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- def get_provider_name(self) -> str:
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- return f"spark-{self.provider_variant}"
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-
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- def get_model_info(self) -> Dict[str, Any]:
110
- return {
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- "provider": "spark",
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- "variant": self.provider_variant,
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- "endpoint": self.spark_endpoint,
114
- "max_tokens": self.settings.get("max_tokens", 2048),
115
- "temperature": self.settings.get("temperature", 0.7)
116
  }
 
1
+ """
2
+ Spark LLM Implementation
3
+ """
4
+ import os
5
+ import httpx
6
+ import json
7
+ from typing import Dict, List, Any, AsyncIterator
8
+ from .llm_interface import LLMInterface
9
+ from utils.logger import log_info, log_error, log_warning, log_debug
10
+
11
+ # Get timeout from environment
12
+ DEFAULT_LLM_TIMEOUT = int(os.getenv("LLM_TIMEOUT_SECONDS", "60"))
13
+ MAX_RESPONSE_LENGTH = int(os.getenv("LLM_MAX_RESPONSE_LENGTH", "4096"))
14
+
15
+ class SparkLLM(LLMInterface):
16
+ """Spark LLM integration with improved error handling"""
17
+
18
+ def __init__(self, spark_endpoint: str, spark_token: str, provider_variant: str = "cloud", settings: Dict[str, Any] = None):
19
+ super().__init__(settings)
20
+ self.spark_endpoint = spark_endpoint.rstrip("/")
21
+ self.spark_token = spark_token
22
+ self.provider_variant = provider_variant
23
+ self.timeout = self.settings.get("timeout", DEFAULT_LLM_TIMEOUT)
24
+ log_info(f"πŸ”Œ SparkLLM initialized", endpoint=self.spark_endpoint, timeout=self.timeout)
25
+
26
+ async def generate(self, system_prompt: str, user_input: str, context: List[Dict]) -> str:
27
+ """Generate response with improved error handling and streaming support"""
28
+ headers = {
29
+ "Authorization": f"Bearer {self.spark_token}",
30
+ "Content-Type": "application/json"
31
+ }
32
+
33
+ # Build context messages
34
+ messages = []
35
+ if system_prompt:
36
+ messages.append({
37
+ "role": "system",
38
+ "content": system_prompt
39
+ })
40
+
41
+ for msg in context[-10:]: # Last 10 messages for context
42
+ messages.append({
43
+ "role": msg.get("role", "user"),
44
+ "content": msg.get("content", "")
45
+ })
46
+
47
+ messages.append({
48
+ "role": "user",
49
+ "content": user_input
50
+ })
51
+
52
+ payload = {
53
+ "messages": messages,
54
+ "mode": self.provider_variant,
55
+ "max_tokens": self.settings.get("max_tokens", 2048),
56
+ "temperature": self.settings.get("temperature", 0.7),
57
+ "stream": False # For now, no streaming
58
+ }
59
+
60
+ try:
61
+ async with httpx.AsyncClient(timeout=self.timeout) as client:
62
+ with LogTimer(f"Spark LLM request"):
63
+ response = await client.post(
64
+ f"{self.spark_endpoint}/generate",
65
+ json=payload,
66
+ headers=headers
67
+ )
68
+
69
+ # Check for rate limiting
70
+ if response.status_code == 429:
71
+ retry_after = response.headers.get("Retry-After", "60")
72
+ log_warning(f"Rate limited by Spark", retry_after=retry_after)
73
+ raise httpx.HTTPStatusError(
74
+ f"Rate limited. Retry after {retry_after}s",
75
+ request=response.request,
76
+ response=response
77
+ )
78
+
79
+ response.raise_for_status()
80
+ result = response.json()
81
+
82
+ # Extract response
83
+ content = result.get("model_answer", "")
84
+
85
+ # Check response length
86
+ if len(content) > MAX_RESPONSE_LENGTH:
87
+ log_warning(f"Response exceeded max length, truncating",
88
+ original_length=len(content),
89
+ max_length=MAX_RESPONSE_LENGTH)
90
+ content = content[:MAX_RESPONSE_LENGTH] + "..."
91
+
92
+ return content
93
+
94
+ except httpx.TimeoutException:
95
+ log_error(f"Spark request timed out", timeout=self.timeout)
96
+ raise
97
+ except httpx.HTTPStatusError as e:
98
+ log_error(f"Spark HTTP error",
99
+ status_code=e.response.status_code,
100
+ response=e.response.text[:500])
101
+ raise
102
+ except Exception as e:
103
+ log_error("Spark unexpected error", error=str(e))
104
+ raise
105
+
106
+ def get_provider_name(self) -> str:
107
+ return f"spark-{self.provider_variant}"
108
+
109
+ def get_model_info(self) -> Dict[str, Any]:
110
+ return {
111
+ "provider": "spark",
112
+ "variant": self.provider_variant,
113
+ "endpoint": self.spark_endpoint,
114
+ "max_tokens": self.settings.get("max_tokens", 2048),
115
+ "temperature": self.settings.get("temperature", 0.7)
116
  }