Merge pull request #53 from parea-ai/format-cookbook

update cookbooks

parea/client.py

@@ -1,3 +1,6 @@
+import asyncio
+import time
+
 from attrs import asdict, define, field
 
 from parea.api_client import HTTPClient
@@ -54,13 +57,15 @@ async def aget_prompt(self, data: UseDeployedPrompt) -> UseDeployedPromptRespons
         return UseDeployedPromptResponse(**r.json())
 
     def record_feedback(self, data: FeedbackRequest) -> None:
+        time.sleep(2)  # give logs time to update
         self._client.request(
             "POST",
             RECORD_FEEDBACK_ENDPOINT,
             data=asdict(data),
         )
 
     async def arecord_feedback(self, data: FeedbackRequest) -> None:
+        await asyncio.sleep(2)  # give logs time to update
         await self._client.request_async(
             "POST",
             RECORD_FEEDBACK_ENDPOINT,

parea/cookbook/tracing_with_Parea_sdk.ipynb

@@ -369,7 +369,7 @@
     "\n",
     "p.record_feedback(\n",
     "    FeedbackRequest(\n",
-    "        trace_id=result.trace_id,\n",
+    "        trace_id=result.inference_id,\n",
     "        score=0.5,\n",
     "        target=\"Moonshine is nice. Full stop.\",\n",
     "    )\n",

parea/cookbook/tracing_with_agent.py

@@ -1,6 +1,5 @@
 import os
 import random
-import time
 
 from dotenv import load_dotenv
 
@@ -105,6 +104,5 @@ def run_agent(main_objective: str, initial_task: str = "") -> tuple[list[dict[st
 
 if __name__ == "__main__":
     result, trace_id = run_agent("Become a machine learning expert.", "Learn about tensors.")
-    time.sleep(1)
-    p.record_feedback(FeedbackRequest(trace_id=trace_id, score=0.642))
     print(result)
+    p.record_feedback(FeedbackRequest(trace_id=trace_id, score=0.642))

parea/cookbook/tracing_with_deployed_prompt.py

@@ -1,5 +1,4 @@
 import os
-import time
 from datetime import datetime
 
 from dotenv import load_dotenv
@@ -105,26 +104,24 @@ def deployed_argument_chain3(query: str, additional_description: str = "") -> Co
         "Whether wine is good for you.",
         additional_description="Provide a concise, few sentence argument on why wine is good for you.",
     )
-    time.sleep(3)
+    print(result2)
     p.record_feedback(
         FeedbackRequest(
             trace_id=trace_id2,
             score=0.0,  # 0.0 (bad) to 1.0 (good)
             target="Moonshine is wonderful.",
         )
     )
-    print(result2)
 
     result3 = deployed_argument_chain3(
-        "Whether moonshine is good for you.",
-        additional_description="Provide a concise, few sentence argument on why moonshine is good for you.",
+        "Whether coffee is good for you.",
+        additional_description="Provide a concise, few sentence argument on why coffee is good for you.",
     )
-    time.sleep(3)
+    print(result3.content)
     p.record_feedback(
         FeedbackRequest(
             trace_id=result3.inference_id,
             score=0.7,  # 0.0 (bad) to 1.0 (good)
-            target="Moonshine is wonderful. End of story.",
+            target="Coffee is wonderful. End of story.",
         )
     )
-    print(result3.error or result3.content)

parea/cookbook/tracing_with_open_ai_endpoint_directly.py

@@ -5,97 +5,83 @@
 from dotenv import load_dotenv
 
 from parea import Parea
+from parea.schemas.models import FeedbackRequest
+from parea.utils.trace_utils import get_current_trace_id, trace
 
 load_dotenv()
 
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-p = Parea(api_key=os.getenv("PAREA_API_KEY"))
-
-
-def argument_generator(query: str, additional_description: str = "", date=datetime.now()) -> str:
-    return (
-        openai.ChatCompletion.create(
-            model="gpt-3.5-turbo-0613",
-            messages=[
-                {
-                    "role": "system",
-                    "content": f"""You are a debater making an argument on a topic.
-{additional_description}.
-The current time is {date}""",
-                },
-                {"role": "user", "content": f"""The discussion topic is {query}"""},
-            ],
-            temperature=0.0,
-        )
-        .choices[0]
-        .message["content"]
+p = Parea(api_key=os.getenv("DEV_API_KEY"))
+
+
+def call_openai(data: list[dict], model: str = "gpt-3.5-turbo-0613", temperature: float = 0.0) -> str:
+    return openai.ChatCompletion.create(model=model, messages=data, temperature=temperature).choices[0].message["content"]
+
+
+@trace
+def argument_generator(query: str, additional_description: str = "") -> str:
+    return call_openai(
+        data=[
+            {
+                "role": "system",
+                "content": f"""You are a debater making an argument on a topic. {additional_description}.
+            The current time is {datetime.now()}""",
+            },
+            {"role": "user", "content": f"""The discussion topic is {query}"""},
+        ]
     )
 
 
+@trace
 def critic(argument: str) -> str:
-    return (
-        openai.ChatCompletion.create(
-            model="gpt-3.5-turbo-0613",
-            messages=[
-                {
-                    "role": "system",
-                    "content": f"""You are a critic.
-What unresolved questions or criticism do you have after reading the following argument?
-Provide a concise summary of your feedback.""",
-                },
-                {"role": "user", "content": f"""{argument}"""},
-            ],
-            temperature=0.0,
-        )
-        .choices[0]
-        .message["content"]
+    return call_openai(
+        data=[
+            {
+                "role": "system",
+                "content": f"""You are a critic.
+                What unresolved questions or criticism do you have after reading the following argument?
+                Provide a concise summary of your feedback.""",
+            },
+            {"role": "user", "content": f"""{argument}"""},
+        ]
     )
 
 
-def refiner(query: str, additional_description: str, current_arg: str, criticism: str, date=datetime.now()) -> str:
-    return (
-        openai.ChatCompletion.create(
-            model="gpt-3.5-turbo-0613",
-            messages=[
-                {
-                    "role": "system",
-                    "content": f"""You are a debater making an argument on a topic.
-{additional_description}.
-The current time is {date}""",
-                },
-                {"role": "user", "content": f"""The discussion topic is {query}"""},
-                {"role": "assistant", "content": f"""{current_arg}"""},
-                {"role": "user", "content": f"""{criticism}"""},
-                {"role": "system", "content": f"""Please generate a new argument that incorporates the feedback from the user."""},
-            ],
-            temperature=0.0,
-        )
-        .choices[0]
-        .message["content"]
+@trace
+def refiner(query: str, additional_description: str, current_arg: str, criticism: str) -> str:
+    return call_openai(
+        data=[
+            {
+                "role": "system",
+                "content": f"""You are a debater making an argument on a topic. {additional_description}.
+                The current time is {datetime.now()}""",
+            },
+            {"role": "user", "content": f"""The discussion topic is {query}"""},
+            {"role": "assistant", "content": f"""{current_arg}"""},
+            {"role": "user", "content": f"""{criticism}"""},
+            {
+                "role": "system",
+                "content": f"""Please generate a new argument that incorporates the feedback from the user.""",
+            },
+        ]
     )
 
 
-def argument_chain(query: str, additional_description: str = "") -> str:
+@trace
+def argument_chain(query: str, additional_description: str = "") -> tuple[str, str]:
+    trace_id = get_current_trace_id()
     argument = argument_generator(query, additional_description)
     criticism = critic(argument)
-    return refiner(query, additional_description, argument, criticism)
+    return refiner(query, additional_description, argument, criticism), trace_id
 
 
 if __name__ == "__main__":
-    result = argument_chain(
-        "Whether caffeine is good for you.",
-        additional_description="Provide a concise, few sentence argument on why caffeine is good for you.",
+    result, trace_id = argument_chain(
+        "Whether sparkling water is good for you.",
+        additional_description="Provide a concise, few sentence argument on why sparkling water is good for you.",
     )
     print(result)
-
-    from parea.schemas.models import FeedbackRequest
-    from parea.utils.trace_utils import get_current_trace_id
-
-    p = Parea(api_key=os.getenv("PAREA_API_KEY"))
-
-    trace_id = get_current_trace_id()
-    print(f"trace_id: {trace_id}")
     p.record_feedback(
         FeedbackRequest(
             trace_id=trace_id,

parea/cookbook/tracing_without_deployed_prompt.py

@@ -1,5 +1,4 @@
 import os
-import time
 from datetime import datetime
 
 from dotenv import load_dotenv
@@ -136,26 +135,24 @@ def argument_chain3(query: str, additional_description: str = "") -> CompletionR
         "Whether wine is good for you.",
         additional_description="Provide a concise, few sentence argument on why wine is good for you.",
     )
-    time.sleep(3)
+    print(result2)
     p.record_feedback(
         FeedbackRequest(
             trace_id=trace_id2,
             score=0.0,  # 0.0 (bad) to 1.0 (good)
             target="Moonshine is wonderful.",
         )
     )
-    print(result2)
 
     result3 = argument_chain3(
         "Whether moonshine is good for you.",
         additional_description="Provide a concise, few sentence argument on why moonshine is good for you.",
     )
-    time.sleep(3)
+    print(result3.content)
     p.record_feedback(
         FeedbackRequest(
             trace_id=result3.inference_id,
             score=0.7,  # 0.0 (bad) to 1.0 (good)
             target="Moonshine is wonderful. End of story.",
         )
     )
-    print(result3.content)

parea/schemas/models.py

@@ -71,7 +71,6 @@ class CompletionResponse:
     status: str
     start_timestamp: str
     end_timestamp: str
-    trace_id: Optional[str] = None
     error: Optional[str] = None
 
 

parea/utils/trace_utils.py

@@ -34,7 +34,7 @@ def merge(old, new):
     return new
 
 
-def get_current_trace_id():
+def get_current_trace_id() -> str:
     return trace_context.get()[-1]