quick prompt handling

Author: alizenhom

src/examples/openai_example/embeddings_create.py

@@ -16,5 +16,6 @@ def embeddings_create():
     result = client.embeddings.create(
         model="text-embedding-ada-002",
         input="Once upon a time, there was a pirate.",
+        encoding_format="float",
     )
     return result

src/examples/openai_example/images_edit.py

@@ -23,8 +23,8 @@ def image_edit():
 
     response = client.images.edit(
         model="dall-e-2",
-        image=open("./resources/lounge_flamingo.png", "rb"),
-        mask=open("./resources/mask.png", "rb"),
+        image=open("src/examples/openai_example/resources/lounge_flamingo.png", "rb"),
+        mask=open("src/examples/openai_example/resources/mask.png", "rb"),
         prompt="A sunlit indoor lounge area with a pool and duck standing in side with flamingo.",
         n=1,
         size="1024x1024",

src/langtrace_python_sdk/instrumentation/ollama/patch.py

@@ -1,6 +1,4 @@
 from langtrace_python_sdk.constants.instrumentation.ollama import APIS
-from importlib_metadata import version as v
-from langtrace_python_sdk.constants import LANGTRACE_SDK_NAME
 from langtrace_python_sdk.utils import set_span_attribute
 from langtrace_python_sdk.utils.llm import (
     get_extra_attributes,
@@ -10,11 +8,7 @@
     set_event_completion,
 )
 from langtrace_python_sdk.utils.silently_fail import silently_fail
-from langtrace_python_sdk.constants.instrumentation.common import (
-    LANGTRACE_ADDITIONAL_SPAN_ATTRIBUTES_KEY,
-    SERVICE_PROVIDERS,
-)
-from opentelemetry import baggage
+from langtrace_python_sdk.constants.instrumentation.common import SERVICE_PROVIDERS
 from langtrace.trace_attributes import LLMSpanAttributes, Event
 from opentelemetry.trace import SpanKind
 import json
@@ -28,7 +22,7 @@ def traced_method(wrapped, instance, args, kwargs):
         service_provider = SERVICE_PROVIDERS["OLLAMA"]
         span_attributes = {
             **get_langtrace_attributes(version, service_provider),
-            **get_llm_request_attributes(kwargs),
+            **get_llm_request_attributes(kwargs, prompts=kwargs.get("messages", [])),
             **get_llm_url(instance),
             SpanAttributes.LLM_PATH: api["ENDPOINT"],
             SpanAttributes.LLM_RESPONSE_FORMAT: kwargs.get("format"),
@@ -146,18 +140,6 @@ def _set_input_attributes(span, kwargs, attributes):
     for field, value in attributes.model_dump(by_alias=True).items():
         set_span_attribute(span, field, value)
 
-    if "messages" in kwargs:
-        set_span_attribute(
-            span,
-            SpanAttributes.LLM_PROMPTS,
-            json.dumps(kwargs.get("messages", [])),
-        )
-    if "prompt" in kwargs:
-        set_span_attribute(
-            span,
-            SpanAttributes.LLM_PROMPTS,
-            json.dumps([{"role": "user", "content": kwargs.get("prompt", "")}]),
-        )
     if "options" in kwargs:
         set_span_attribute(
             span,

src/langtrace_python_sdk/instrumentation/openai/patch.py

@@ -41,6 +41,7 @@
     is_streaming,
     set_event_completion,
     StreamWrapper,
+    set_span_attributes,
 )
 from openai._types import NOT_GIVEN
 
@@ -67,8 +68,7 @@ def traced_method(wrapped, instance, args, kwargs):
             kind=SpanKind.CLIENT.value,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
-            for field, value in attributes.model_dump(by_alias=True).items():
-                set_span_attribute(span, field, value)
+            set_span_attributes(span, attributes)
             try:
                 # Attempt to call the original method
                 result = wrapped(*args, **kwargs)
@@ -131,8 +131,7 @@ async def traced_method(wrapped, instance, args, kwargs):
             kind=SpanKind.CLIENT.value,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
-            for field, value in attributes.model_dump(by_alias=True).items():
-                set_span_attribute(span, field, value)
+            set_span_attributes(span, attributes)
             try:
                 # Attempt to call the original method
                 result = await wrapped(*args, **kwargs)
@@ -197,9 +196,7 @@ def traced_method(wrapped, instance, args, kwargs):
             kind=SpanKind.CLIENT.value,
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
-            for field, value in attributes.model_dump(by_alias=True).items():
-                if value is not None:
-                    span.set_attribute(field, value)
+            set_span_attributes(span, attributes)
             try:
                 # Attempt to call the original method
                 result = wrapped(*args, **kwargs)
@@ -463,8 +460,7 @@ def traced_method(wrapped, instance, args, kwargs):
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
 
-            for field, value in attributes.model_dump(by_alias=True).items():
-                set_span_attribute(span, field, value)
+            set_span_attributes(span, attributes)
             try:
                 # Attempt to call the original method
                 result = wrapped(*args, **kwargs)
@@ -521,8 +517,7 @@ async def traced_method(wrapped, instance, args, kwargs):
             context=set_span_in_context(trace.get_current_span()),
         ) as span:
 
-            for field, value in attributes.model_dump(by_alias=True).items():
-                set_span_attribute(span, field, value)
+            set_span_attributes(span, attributes)
             try:
                 # Attempt to call the original method
                 result = await wrapped(*args, **kwargs)

src/langtrace_python_sdk/utils/llm.py

@@ -95,8 +95,12 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None):
 
     user = kwargs.get("user", None)
     if prompts is None:
-        prompts = [{"role": user, "content": kwargs.get("prompt", [])}]
-
+        prompts = (
+            [{"role": user or "user", "content": kwargs.get("prompt")}]
+            if "prompt" in kwargs
+            else None
+        )
+    print("PRMPT", prompts)
     top_k = (
         kwargs.get("n", None)
         or kwargs.get("k", None)
@@ -105,21 +109,21 @@ def get_llm_request_attributes(kwargs, prompts=None, model=None):
     )
 
     top_p = kwargs.get("p", None) or kwargs.get("top_p", None)
-
+    tools = kwargs.get("tools", None)
     return {
         SpanAttributes.LLM_REQUEST_MODEL: model or kwargs.get("model"),
         SpanAttributes.LLM_IS_STREAMING: kwargs.get("stream"),
         SpanAttributes.LLM_REQUEST_TEMPERATURE: kwargs.get("temperature"),
         SpanAttributes.LLM_TOP_K: top_k,
-        SpanAttributes.LLM_PROMPTS: json.dumps(prompts),
+        SpanAttributes.LLM_PROMPTS: json.dumps(prompts) if prompts else None,
         SpanAttributes.LLM_USER: user,
         SpanAttributes.LLM_REQUEST_TOP_P: top_p,
         SpanAttributes.LLM_REQUEST_MAX_TOKENS: kwargs.get("max_tokens"),
         SpanAttributes.LLM_SYSTEM_FINGERPRINT: kwargs.get("system_fingerprint"),
         SpanAttributes.LLM_PRESENCE_PENALTY: kwargs.get("presence_penalty"),
         SpanAttributes.LLM_FREQUENCY_PENALTY: kwargs.get("frequency_penalty"),
         SpanAttributes.LLM_REQUEST_SEED: kwargs.get("seed"),
-        SpanAttributes.LLM_TOOLS: json.dumps(kwargs.get("tools")),
+        SpanAttributes.LLM_TOOLS: json.dumps(tools) if tools else None,
         SpanAttributes.LLM_REQUEST_LOGPROPS: kwargs.get("logprobs"),
         SpanAttributes.LLM_REQUEST_LOGITBIAS: kwargs.get("logit_bias"),
         SpanAttributes.LLM_REQUEST_TOP_LOGPROPS: kwargs.get("top_logprobs"),