fix: switch to non-streaming Ollama calls — streaming breaks thinking mode
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@@ -12,7 +12,6 @@ Requirements: 5.1, 5.2, 5.4
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from __future__ import annotations
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import asyncio
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import json
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import logging
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import time
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from dataclasses import dataclass, field
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@@ -227,30 +226,17 @@ class OllamaClient:
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{"role": "user", "content": prompts["user"]},
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],
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"format": json_schema,
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"stream": True,
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# NOTE: Do NOT set "think": False here. Ollama has a known bug
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# (issues #14645, #15260) where think=false silently disables
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# the format constraint for qwen3.5 and gemma4 models, causing
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# the model to output plain text instead of valid JSON.
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# Omitting "think" lets the model use thinking mode (slightly
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# slower but structured output actually works).
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"options": {
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# Ollama defaults num_predict to 4096 which is consumed
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# entirely by thinking tokens, leaving nothing for content.
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# Set high enough for thinking + JSON output.
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"num_predict": self._config.max_tokens,
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},
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"stream": False,
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}
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url = f"{self._config.base_url}/api/chat"
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logger.info(
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"Ollama POST %s model=%s input_chars=%d (streaming)",
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"Ollama POST %s model=%s input_chars=%d",
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url, self._config.model, len(prompts.get("user", "")),
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)
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try:
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req = self._http.build_request("POST", url, json=payload)
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resp = await self._http.send(req, stream=True)
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resp = await self._http.post(url, json=payload)
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resp.raise_for_status()
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except httpx.TimeoutException:
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attempt.error = "timeout"
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@@ -266,73 +252,16 @@ class OllamaClient:
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attempt.duration_ms = int((time.monotonic() - start) * 1000)
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return attempt
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# Stream and accumulate with guardrails
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chunks: list[str] = []
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token_count = 0
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last_chunk_time = time.monotonic()
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abort_reason: str | None = None
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try:
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async for line in resp.aiter_lines():
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if not line:
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continue
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try:
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frame = json.loads(line)
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except json.JSONDecodeError:
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continue
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if frame.get("done"):
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break
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msg = frame.get("message", {})
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token = msg.get("content", "") if isinstance(msg, dict) else ""
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# During thinking mode, the model emits tokens in msg.thinking
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# before msg.content. We don't accumulate thinking tokens but
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# must update last_chunk_time so the stall guard doesn't fire.
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thinking_token = msg.get("thinking", "") if isinstance(msg, dict) else ""
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if thinking_token:
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last_chunk_time = time.monotonic()
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if not token:
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continue
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chunks.append(token)
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token_count += 1
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last_chunk_time = time.monotonic()
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# Guard: max tokens
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if token_count > self._config.max_tokens:
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abort_reason = f"max_tokens_exceeded ({token_count})"
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break
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# Guard: repetition loop detection
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if token_count >= self._config.loop_window:
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window = chunks[-self._config.loop_window:]
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unique_ratio = len(set(window)) / len(window)
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if unique_ratio < self._config.loop_threshold:
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abort_reason = f"repetition_loop (unique_ratio={unique_ratio:.2f})"
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break
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# Guard: stall detection (check between chunks)
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elapsed_since_last = time.monotonic() - last_chunk_time
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if elapsed_since_last > self._config.stall_timeout:
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abort_reason = "stall_timeout"
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break
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except httpx.ReadTimeout:
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abort_reason = "read_timeout"
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finally:
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await resp.aclose()
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attempt.duration_ms = int((time.monotonic() - start) * 1000)
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if abort_reason:
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logger.warning(
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"Stream aborted after %d tokens: %s", token_count, abort_reason,
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)
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attempt.error = abort_reason
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attempt.raw_output = "".join(chunks)
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try:
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data = resp.json()
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except Exception:
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attempt.error = "invalid_response_json"
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attempt.raw_output = resp.text[:2000]
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return attempt
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content = "".join(chunks)
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content = data.get("message", {}).get("content", "")
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attempt.raw_output = content
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if not content:
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