diff --git a/hindsight-api/hindsight_api/engine/llm_wrapper.py b/hindsight-api/hindsight_api/engine/llm_wrapper.py index 3dea0444..b107c674 100644 --- a/hindsight-api/hindsight_api/engine/llm_wrapper.py +++ b/hindsight-api/hindsight_api/engine/llm_wrapper.py @@ -3,11 +3,13 @@ LLM wrapper for unified configuration across providers. """ import asyncio +import json import logging import os import time from typing import Any +import httpx from google import genai from google.genai import errors as genai_errors from google.genai import types as genai_types @@ -157,7 +159,6 @@ class LLMProvider: """ async with _global_llm_semaphore: start_time = time.time() - import json # Handle Gemini provider separately if self.provider == "gemini": @@ -165,6 +166,20 @@ class LLMProvider: messages, response_format, max_retries, initial_backoff, max_backoff, skip_validation, start_time ) + # Handle Ollama with native API for structured output (better schema enforcement) + if self.provider == "ollama" and response_format is not None: + return await self._call_ollama_native( + messages, + response_format, + max_completion_tokens, + temperature, + max_retries, + initial_backoff, + max_backoff, + skip_validation, + start_time, + ) + call_params = { "model": self.model, "messages": messages, @@ -324,6 +339,129 @@ class LLMProvider: raise last_exception raise RuntimeError("LLM call failed after all retries with no exception captured") + async def _call_ollama_native( + self, + messages: list[dict[str, str]], + response_format: Any, + max_completion_tokens: int | None, + temperature: float | None, + max_retries: int, + initial_backoff: float, + max_backoff: float, + skip_validation: bool, + start_time: float, + ) -> Any: + """ + Call Ollama using native API with JSON schema enforcement. + + Ollama's native API supports passing a full JSON schema in the 'format' parameter, + which provides better structured output control than the OpenAI-compatible API. + """ + # Get the JSON schema from the Pydantic model + schema = response_format.model_json_schema() if hasattr(response_format, "model_json_schema") else None + + # Build the base URL for Ollama's native API + # Default OpenAI-compatible URL is http://localhost:11434/v1 + # Native API is at http://localhost:11434/api/chat + base_url = self.base_url or "http://localhost:11434/v1" + if base_url.endswith("/v1"): + native_url = base_url[:-3] + "/api/chat" + else: + native_url = base_url.rstrip("/") + "/api/chat" + + # Build request payload + payload = { + "model": self.model, + "messages": messages, + "stream": False, + } + + # Add schema as format parameter for structured output + if schema: + payload["format"] = schema + + # Add optional parameters with optimized defaults for Ollama + # Benchmarking shows num_ctx=16384 + num_batch=512 is optimal + options = { + "num_ctx": 16384, # 16k context window for larger prompts + "num_batch": 512, # Optimal batch size for prompt processing + } + if max_completion_tokens: + options["num_predict"] = max_completion_tokens + if temperature is not None: + options["temperature"] = temperature + payload["options"] = options + + last_exception = None + + async with httpx.AsyncClient(timeout=300.0) as client: + for attempt in range(max_retries + 1): + try: + response = await client.post(native_url, json=payload) + response.raise_for_status() + + result = response.json() + content = result.get("message", {}).get("content", "") + + # Parse JSON response + try: + json_data = json.loads(content) + except json.JSONDecodeError as json_err: + content_preview = content[:500] if content else "" + if content and len(content) > 700: + content_preview = f"{content[:500]}...TRUNCATED...{content[-200:]}" + logger.warning( + f"Ollama JSON parse error (attempt {attempt + 1}/{max_retries + 1}): {json_err}\n" + f" Model: ollama/{self.model}\n" + f" Content length: {len(content) if content else 0} chars\n" + f" Content preview: {content_preview!r}" + ) + if attempt < max_retries: + backoff = min(initial_backoff * (2**attempt), max_backoff) + await asyncio.sleep(backoff) + last_exception = json_err + continue + else: + raise + + # Validate against Pydantic model or return raw JSON + if skip_validation: + return json_data + else: + return response_format.model_validate(json_data) + + except httpx.HTTPStatusError as e: + last_exception = e + if attempt < max_retries: + logger.warning( + f"Ollama HTTP error (attempt {attempt + 1}/{max_retries + 1}): {e.response.status_code}" + ) + backoff = min(initial_backoff * (2**attempt), max_backoff) + await asyncio.sleep(backoff) + continue + else: + logger.error(f"Ollama HTTP error after {max_retries + 1} attempts: {e}") + raise + + except httpx.RequestError as e: + last_exception = e + if attempt < max_retries: + logger.warning(f"Ollama connection error (attempt {attempt + 1}/{max_retries + 1}): {e}") + backoff = min(initial_backoff * (2**attempt), max_backoff) + await asyncio.sleep(backoff) + continue + else: + logger.error(f"Ollama connection error after {max_retries + 1} attempts: {e}") + raise + + except Exception as e: + logger.error(f"Unexpected error during Ollama call: {type(e).__name__}: {e}") + raise + + if last_exception: + raise last_exception + raise RuntimeError("Ollama call failed after all retries") + async def _call_gemini( self, messages: list[dict[str, str]], @@ -335,8 +473,6 @@ class LLMProvider: start_time: float, ) -> Any: """Handle Gemini-specific API calls.""" - import json - # Convert OpenAI-style messages to Gemini format system_instruction = None gemini_contents = [] diff --git a/hindsight-api/hindsight_api/engine/memory_engine.py b/hindsight-api/hindsight_api/engine/memory_engine.py index f5b3d514..cd55eee7 100644 --- a/hindsight-api/hindsight_api/engine/memory_engine.py +++ b/hindsight-api/hindsight_api/engine/memory_engine.py @@ -237,7 +237,8 @@ class MemoryEngine(MemoryEngineInterface): db_url = db_url or config.database_url memory_llm_provider = memory_llm_provider or config.llm_provider memory_llm_api_key = memory_llm_api_key or config.llm_api_key - if not memory_llm_api_key: + # Ollama doesn't require an API key + if not memory_llm_api_key and memory_llm_provider != "ollama": raise ValueError("LLM API key is required. Set HINDSIGHT_API_LLM_API_KEY environment variable.") memory_llm_model = memory_llm_model or config.llm_model memory_llm_base_url = memory_llm_base_url or config.get_llm_base_url() or None diff --git a/hindsight-api/tests/test_llm_provider.py b/hindsight-api/tests/test_llm_provider.py index f3b6d8f6..4f26606a 100644 --- a/hindsight-api/tests/test_llm_provider.py +++ b/hindsight-api/tests/test_llm_provider.py @@ -26,6 +26,9 @@ MODEL_MATRIX = [ ("gemini", "gemini-2.5-flash"), ("gemini", "gemini-2.5-flash-lite"), ("gemini", "gemini-3-pro-preview"), + # Ollama models (local) + ("ollama", "gemma3:12b"), + ("ollama", "gemma3:1b"), ] @@ -48,12 +51,18 @@ async def test_llm_provider_memory_operations(provider: str, model: str): All models must pass this test. """ api_key = get_api_key_for_provider(provider) - if not api_key: + + # Skip Ollama tests in CI (no models available) + if provider == "ollama" and os.getenv("CI"): + pytest.skip(f"Skipping {provider}/{model}: Ollama not available in CI") + + # Other providers need an API key + if provider != "ollama" and not api_key: pytest.skip(f"Skipping {provider}/{model}: no API key available") llm = LLMProvider( provider=provider, - api_key=api_key, + api_key=api_key or "", base_url="", model=model, ) diff --git a/hindsight-dev/benchmarks/common/benchmark_runner.py b/hindsight-dev/benchmarks/common/benchmark_runner.py index b3f6f57d..fbbf16bd 100644 --- a/hindsight-dev/benchmarks/common/benchmark_runner.py +++ b/hindsight-dev/benchmarks/common/benchmark_runner.py @@ -28,6 +28,10 @@ from typing import Any, Dict, List, Optional, Tuple import pydantic from hindsight_api import MemoryEngine +from hindsight_api.config import get_config + +# Configure logging from environment variable 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