update cookbook

parea/api_client.py

@@ -3,10 +3,9 @@
 import httpx
 
 
-# http://127.0.0.1:8000/api/parea/v1/trace_log
 class HTTPClient:
     _instance = None
-    base_url = "http://127.0.0.1:8000/api/parea/v1"  # "https://parea-ai-backend-e2adf7624bcb3980.onporter.run/api/parea/v1"
+    base_url = "https://parea-ai-backend-e2adf7624bcb3980.onporter.run/api/parea/v1"
     api_key = None
 
     def __new__(cls, *args, **kwargs):

parea/cookbook/langchain/trace_langchain_RAG_evals.py

@@ -31,7 +31,7 @@
 load_dotenv()
 
 # Need to instantiate Parea for tracing and evals
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 
 class DocumentRetriever:
@@ -87,33 +87,45 @@ def __init__(self, retriever, model: str):
             | response_generator
         )
 
-    def get_chain(self):
-        return self.chain
-
     def get_context(self) -> str:
+        """Helper to get the context from a retrieval chain, so we can use it for evaluation metrics."""
         return self.context
 
     def _format_docs(self, docs) -> str:
         context = "\n\n".join(doc.page_content for doc in docs)
+        # set context as an attribute, so we can access it later
         self.context = context
         return context
 
+    def get_chain(self):
+        return self.chain
+
 
 # EXAMPLE EVALUATION TEST CASES
 eval_questions = [
-    # "What is the population of New York City as of 2020?",
+    "What is the population of New York City as of 2020?",
     "Which borough of New York City has the highest population? Only respond with the name of the borough.",
-    # "What is the economic significance of New York City?",
-    # "How did New York City get its name?",
-    # "What is the significance of the Statue of Liberty in New York City?",
+    "What is the economic significance of New York City?",
+    "How did New York City get its name?",
+    "What is the significance of the Statue of Liberty in New York City?",
 ]
 
 eval_answers = [
-    # "8,804,190",
+    "8,804,190",
     "Brooklyn",
-    # "New York City's economic significance is vast, as it serves as the global financial capital, housing Wall Street and major financial institutions. Its diverse economy spans technology, media, healthcare, education, and more, making it resilient to economic fluctuations. NYC is a hub for international business, attracting global companies, and boasts a large, skilled labor force. Its real estate market, tourism, cultural industries, and educational institutions further fuel its economic prowess. The city's transportation network and global influence amplify its impact on the world stage, solidifying its status as a vital economic player and cultural epicenter.",
-    # "New York City got its name when it came under British control in 1664. King Charles II of England granted the lands to his brother, the Duke of York, who named the city New York in his own honor.",
-    # "The Statue of Liberty in New York City holds great significance as a symbol of the United States and its ideals of liberty and peace. It greeted millions of immigrants who arrived in the U.S. by ship in the late 19th and early 20th centuries, representing hope and freedom for those seeking a better life. It has since become an iconic landmark and a global symbol of cultural diversity and freedom.",
+    """New York City's economic significance is vast, as it serves as the global financial capital, housing Wall
+    Street and major financial institutions. Its diverse economy spans technology, media, healthcare, education,
+    and more, making it resilient to economic fluctuations. NYC is a hub for international business, attracting
+    global companies, and boasts a large, skilled labor force. Its real estate market, tourism, cultural industries,
+    and educational institutions further fuel its economic prowess. The city's transportation network and global
+    influence amplify its impact on the world stage, solidifying its status as a vital economic player and cultural
+    epicenter.""",
+    """New York City got its name when it came under British control in 1664. King Charles II of England granted the
+    lands to his brother, the Duke of York, who named the city New York in his own honor.""",
+    """The Statue of Liberty in New York City holds great significance as a symbol of the United States and its
+    ideals of liberty and peace. It greeted millions of immigrants who arrived in the U.S. by ship in the late 19th
+    and early 20th centuries, representing hope and freedom for those seeking a better life. It has since become an
+    iconic landmark and a global symbol of cultural diversity and freedom.""",
 ]
 
 # set up evaluation functions we want to test, provide the name of the relevant fields needed for each eval function
@@ -160,7 +172,7 @@ def main():
         # build log component needed for evaluation metric functions
         log = create_log(model, question, context, output, answer)
 
-        # run evaluation metric functions in a thread to avoid blocking return of chain
+        # helper function to run evaluation metrics in a thread to avoid blocking return of chain
         run_evals_in_thread_and_log(trace_id=str(parent_trace_id), log=log, eval_funcs=EVALS, verbose=True)
 
 

parea/cookbook/langchain/trace_langchain_anthropic_function_calling.py

@@ -10,10 +10,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
-
-os.environ["LANGCHAIN_PROJECT"] = "rag-example"
-
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 model = AnthropicFunctions(model="claude-2")
 
@@ -44,9 +41,8 @@
     },
     "required": ["name", "height"],
 }
-inp = """
-Alex is 5 feet tall. Claudia is 1 feet taller Alex and jumps higher than him. Claudia is a brunette and Alex is blonde.
-        """
+inp = """Alex is 5 feet tall. Claudia is 1 feet taller Alex and jumps higher than him. Claudia is a brunette and Alex
+is blonde."""
 
 chain = create_extraction_chain(schema, model)
 

parea/cookbook/langchain/trace_langchain_rag_agents.py

@@ -13,10 +13,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
-
-os.environ["LANGCHAIN_PROJECT"] = "rag-example"
-
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 loader = TextLoader("../data/state_of_the_union.txt")
 

parea/cookbook/langchain/trace_langchain_rag_question_answering.py

@@ -16,9 +16,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
-
-os.environ["LANGCHAIN_PROJECT"] = "rag-example"
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 loader = WebBaseLoader(
     web_paths=("https://lilianweng.github.io/posts/2023-06-23-agent/",),

parea/cookbook/tracing_with_agent.py

@@ -12,7 +12,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 # Parea SDK makes it easy to use different LLMs with the same apis structure and standardized request/response schemas.
 LLM_OPTIONS = [("gpt-3.5-turbo", "openai"), ("gpt-4", "openai"), ("claude-instant-1", "anthropic"), ("claude-2", "anthropic")]

parea/cookbook/tracing_with_deployed_prompt.py

@@ -1,5 +1,3 @@
-from typing import Tuple
-
 import json
 import os
 from datetime import datetime
@@ -13,7 +11,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 
 def deployed_argument_generator(query: str, additional_description: str = "") -> str:

parea/cookbook/tracing_with_open_ai_endpoint_directly.py

@@ -12,7 +12,7 @@
 
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 
 def call_llm(data: list[dict], model: str = "gpt-3.5-turbo", temperature: float = 0.0) -> str:

parea/cookbook/tracing_with_openai_with_functions.py

@@ -15,7 +15,7 @@
 PLACES_URL = "https://maps.googleapis.com/maps/api/place/nearbysearch/json"
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 functions = [
     {

parea/cookbook/tracing_without_deployed_prompt.py

@@ -10,7 +10,7 @@
 
 load_dotenv()
 
-p = Parea(api_key=os.getenv("DEV_API_KEY"))
+p = Parea(api_key=os.getenv("PAREA_API_KEY"))
 
 
 @trace  # <--- If you want to log the inputs to the LLM call you can optionally add a trace decorator here

parea/evals/utils.py

@@ -1,4 +1,4 @@
-from typing import Callable, Dict, List, Union
+from typing import Callable, Union
 
 import json
 import warnings
@@ -106,7 +106,7 @@ def make_evaluations(trace_id: str, log: Log, eval_funcs: list[EvalFuncTuple], v
         for score in scores:
             print(score)
     parea_logger.update_log(data=UpdateLog(trace_id=trace_id, field_name_to_value_map={"scores": scores, "target": log.target}))
-    print(f"View trace at: http://localhost:3000/logs/detailed/{trace_id} \n")
+    print(f"View trace at: https://app.parea.ai/logs/detailed/{trace_id} \n")
 
 
 def run_evals_in_thread_and_log(trace_id: str, log: Log, eval_funcs: list[EvalFuncTuple], verbose: bool = False):

parea/parea_logger.py

@@ -59,14 +59,14 @@ def record_vendor_log(self, data: dict[str, Any], vendor: TraceIntegrations) ->
         self._client.request(
             "POST",
             VENDOR_LOG_ENDPOINT.format(vendor=vendor.value),
-            data=json.loads(json_dumps(data)),
+            data=json.loads(json_dumps(data)),  # uuid is not serializable
         )
 
     async def arecord_vendor_log(self, data: dict[str, Any], vendor: TraceIntegrations) -> None:
         await self._client.request_async(
             "POST",
             VENDOR_LOG_ENDPOINT.format(vendor=vendor.value),
-            data=json.loads(json_dumps(data)),
+            data=json.loads(json_dumps(data)),  # uuid is not serializable
         )
 
 

pyproject.toml

@@ -6,7 +6,7 @@ build-backend = "poetry.core.masonry.api"
 [tool.poetry]
 name = "parea-ai"
 packages = [{ include = "parea" }]
-version = "0.2.23"
+version = "0.2.24"
 description = "Parea python sdk"
 readme = "README.md"
 authors = ["joel-parea-ai <[email protected]>"]