regression URL parsing in PR #231

src/typeagent/aitools/model_adapters.py

@@ -188,6 +188,7 @@ def _make_azure_provider(
             azure_endpoint=azure_endpoint,
             api_version=api_version,
             api_key=raw_key,
+            default_headers={"Ocp-Apim-Subscription-Key": raw_key},
         )
     return AzureProvider(openai_client=client)
 

src/typeagent/aitools/utils.py

@@ -195,9 +195,12 @@ def parse_azure_endpoint(
             f"{endpoint_envvar}={azure_endpoint} doesn't contain valid api-version field"
         )
 
-    # Strip query string — AsyncAzureOpenAI expects a clean base URL and
-    # receives api_version as a separate parameter.
+    # Strip query string and deployment path — AsyncAzureOpenAI expects a
+    # clean base URL and builds the deployment path internally.
     clean_endpoint = azure_endpoint.split("?", 1)[0]
+    deployment_idx = clean_endpoint.find("/openai/deployments/")
+    if deployment_idx >= 0:
+        clean_endpoint = clean_endpoint[:deployment_idx]
 
     return clean_endpoint, m.group(1)
 
@@ -253,6 +256,7 @@ def create_async_openai_client(
             api_version=api_version,
             azure_endpoint=azure_endpoint,
             api_key=azure_api_key,
+            default_headers={"Ocp-Apim-Subscription-Key": azure_api_key},
         )
 
     else:
@@ -264,6 +268,7 @@ def create_async_openai_client(
 # The true return type is pydantic_ai.Agent[T], but that's an optional dependency.
 def make_agent[T](cls: type[T]):
     """Create Pydantic AI agent using hardcoded preferences."""
+    from openai import AsyncAzureOpenAI
     from pydantic_ai import Agent, NativeOutput, ToolOutput
     from pydantic_ai.models.openai import OpenAIChatModel
     from pydantic_ai.providers.azure import AzureProvider
@@ -285,9 +290,12 @@ def make_agent[T](cls: type[T]):
         model = OpenAIChatModel(
             "gpt-4o",
             provider=AzureProvider(
-                azure_endpoint=azure_endpoint,
-                api_version=api_version,
-                api_key=azure_api_key,
+                openai_client=AsyncAzureOpenAI(
+                    azure_endpoint=azure_endpoint,
+                    api_version=api_version,
+                    api_key=azure_api_key,
+                    default_headers={"Ocp-Apim-Subscription-Key": azure_api_key},
+                ),
             ),
         )
 

src/typeagent/knowpro/conversation_base.py

@@ -13,11 +13,13 @@
     answer_response_schema,
     answers,
     convknowledge,
-    knowledge_schema as kplib,
+)
+from . import (
     search_query_schema,
     searchlang,
     secindex,
 )
+from . import knowledge_schema as kplib
 from ..aitools import model_adapters, utils
 from ..storage.memory import semrefindex
 from .convsettings import ConversationSettings

src/typeagent/knowpro/knowledge.py

@@ -7,7 +7,8 @@
 
 from typechat import Result, TypeChatLanguageModel
 
-from . import convknowledge, knowledge_schema as kplib
+from . import convknowledge
+from . import knowledge_schema as kplib
 from ..aitools import model_adapters
 from .interfaces import IKnowledgeExtractor
 

src/typeagent/storage/memory/semrefindex.py

@@ -7,7 +7,9 @@
 
 from typechat import Failure
 
-from ...knowpro import convknowledge, knowledge_schema as kplib, secindex
+from ...knowpro import convknowledge
+from ...knowpro import knowledge_schema as kplib
+from ...knowpro import secindex
 from ...knowpro.convsettings import ConversationSettings, SemanticRefIndexSettings
 from ...knowpro.interfaces import (  # Interfaces.; Other imports.
     IConversation,

tests/benchmarks/test_benchmark_vectorbase.py

@@ -14,8 +14,11 @@
 import pytest
 
 from typeagent.aitools.model_adapters import create_test_embedding_model
-from typeagent.aitools.vectorbase import ScoredInt, TextEmbeddingIndexSettings, VectorBase
-
+from typeagent.aitools.vectorbase import (
+    ScoredInt,
+    TextEmbeddingIndexSettings,
+    VectorBase,
+)
 
 # -- Helpers ------------------------------------------------------------------
 
@@ -61,7 +64,9 @@ def test_1k_vectors(self, benchmark, vb_1k: tuple[VectorBase, np.ndarray]) -> No
         assert len(result) == 10
         assert all(isinstance(r, ScoredInt) for r in result)
 
-    def test_10k_vectors(self, benchmark, vb_10k: tuple[VectorBase, np.ndarray]) -> None:
+    def test_10k_vectors(
+        self, benchmark, vb_10k: tuple[VectorBase, np.ndarray]
+    ) -> None:
         vb, query = vb_10k
         result = benchmark(vb.fuzzy_lookup_embedding, query, max_hits=10, min_score=0.0)
         assert len(result) == 10

tests/test_knowledge.py

@@ -5,7 +5,8 @@
 
 from typechat import Failure, Result, Success
 
-from typeagent.knowpro import convknowledge, knowledge_schema as kplib
+from typeagent.knowpro import convknowledge
+from typeagent.knowpro import knowledge_schema as kplib
 from typeagent.knowpro.knowledge import (
     create_knowledge_extractor,
     extract_knowledge_from_text,

tests/test_online.py

@@ -3,36 +3,30 @@
 
 import pytest
 
-from typeagent.aitools.utils import create_async_openai_client
+from pydantic_ai.messages import ModelRequest, TextPart, UserPromptPart
+from pydantic_ai.models import ModelRequestParameters
+
+from typeagent.aitools.model_adapters import create_chat_model
 
 
 @pytest.mark.asyncio
 async def test_why_is_sky_blue(really_needs_auth: None):
-    """Test that chat agent responds correctly to 'why is the sky blue?'"""
-
-    # Create an async OpenAI client
-    try:
-        client = create_async_openai_client()
-    except RuntimeError as e:
-        if "Neither OPENAI_API_KEY nor AZURE_OPENAI_API_KEY was provided." in str(e):
-            pytest.skip("API keys not configured")
-        raise
-
-    # Send the user request
-    response = await client.chat.completions.create(
-        model="gpt-4o",
-        messages=[
-            {
-                "role": "user",
-                "content": "why is the sky blue?",
-            }
-        ],
-        temperature=0,
+    """Test that chat agent responds correctly to 'why is the sky blue?'
+
+    Uses create_chat_model (the pydantic-ai code path) so this test exercises
+    the same Azure provider wiring as the rest of the codebase.
+    """
+    model = create_chat_model()
+
+    response = await model._model.request(
+        [ModelRequest(parts=[UserPromptPart(content="why is the sky blue?")])],
+        None,
+        ModelRequestParameters(),
     )
 
-    # Get the response message
-    msg = response.choices[0].message.content
-    assert msg is not None, "Chat agent didn't respond"
+    text_parts = [p.content for p in response.parts if isinstance(p, TextPart)]
+    msg = "".join(text_parts)
+    assert msg, "Chat agent didn't respond"
 
     print(f"Chat agent response: {msg}")
 

tests/test_semrefindex.py

@@ -20,7 +20,12 @@
     ITermToSemanticRefIndex,
     Topic,
 )
-from typeagent.knowpro.knowledge_schema import Action, ConcreteEntity, Facet, KnowledgeResponse
+from typeagent.knowpro.knowledge_schema import (
+    Action,
+    ConcreteEntity,
+    Facet,
+    KnowledgeResponse,
+)
 from typeagent.storage import SqliteStorageProvider
 from typeagent.storage.memory import MemoryStorageProvider
 from typeagent.storage.memory.semrefindex import (

tests/test_utils.py

@@ -89,7 +89,7 @@ def test_api_version_after_question_mark(
         )
         endpoint, version = utils.parse_azure_endpoint("TEST_ENDPOINT")
         assert version == "2025-01-01-preview"
-        assert endpoint == "https://myhost.openai.azure.com/openai/deployments/gpt-4"
+        assert endpoint == "https://myhost.openai.azure.com"
 
     def test_api_version_after_ampersand(self, monkeypatch: pytest.MonkeyPatch) -> None:
         """api-version preceded by & (not the first query parameter)."""
@@ -121,13 +121,13 @@ def test_query_string_stripped_from_endpoint(
     def test_query_string_stripped_with_path(
         self, monkeypatch: pytest.MonkeyPatch
     ) -> None:
-        """Query string stripped even when endpoint includes a path."""
+        """Query string and deployment path stripped from endpoint."""
         monkeypatch.setenv(
             "TEST_ENDPOINT",
             "https://myhost.openai.azure.com/openai/deployments/gpt-4?api-version=2025-01-01-preview",
         )
         endpoint, version = utils.parse_azure_endpoint("TEST_ENDPOINT")
-        assert endpoint == "https://myhost.openai.azure.com/openai/deployments/gpt-4"
+        assert endpoint == "https://myhost.openai.azure.com"
         assert "?" not in endpoint
         assert version == "2025-01-01-preview"
 

tools/query.py

@@ -36,13 +36,15 @@
 from typeagent.knowpro import (
     answer_response_schema,
     answers,
-    knowledge_schema as kplib,
+)
+from typeagent.knowpro import (
     query,
     search,
     search_query_schema,
     searchlang,
     serialization,
 )
+from typeagent.knowpro import knowledge_schema as kplib
 from typeagent.knowpro.convsettings import ConversationSettings
 from typeagent.knowpro.interfaces import (
     IConversation,

tools/release.py

@@ -450,9 +450,15 @@ def main():
 
     if exit_code != 0:
         if args.force:
-            print("Warning: Failed to create PR -- you can create it yourself", file=sys.stderr)
+            print(
+                "Warning: Failed to create PR -- you can create it yourself",
+                file=sys.stderr,
+            )
         else:
-            print("Error: Failed to create PR -- but you can create it yourself", file=sys.stderr)
+            print(
+                "Error: Failed to create PR -- but you can create it yourself",
+                file=sys.stderr,
+            )
             return 1
 
     if args.dry_run: