fix: WYSIWYG editor, content generation, and writing assistant bug fixes
- Fix text selection menu not showing: wire contentRef via inputRef on multiline TextField - Fix blog title not truncating: add min-w-0 for flex item overflow - Fix outline generation 500: escape curly braces in f-string prompt template - Fix content generation 'NoneType not callable': replace SessionLocal() with get_session_for_user(), add db param to MediumBlogGenerator, fix signature mismatch in database_task_manager - Fix writing assistant suggest 500: add auth + user_id to API endpoint and service, replace sync requests with httpx.AsyncClient - Fix hallucination detector 404: explicitly include router in main.py and app.py - Fix missing error_data in task failure responses - Hide CopilotKit web inspector button - Remove hardcoded fallback suggestions from SmartTypingAssist - Fix stale closure refs in SmartTypingAssist handleTypingChange - Add two-column editor layout, stats bar, section hover menu - Various subscription, billing, and research module improvements
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ajaysi
@@ -133,9 +133,9 @@ def edit_image(
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raise
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except Exception as e:
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logger.error(f"[Image Editing] ❌ Unexpected error during pre-flight validation: {e}")
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# In podcast-only mode, allow the operation to continue on validation errors
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if os.getenv("ALWRITY_ENABLED_FEATURES") == "podcast":
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logger.warning(f"[Image Editing] ⚠️ Validation error in podcast mode - allowing operation to continue")
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# In feature-limited mode, allow the operation to continue on validation errors
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if os.getenv("ALWRITY_ENABLED_FEATURES", "").strip().lower() not in ("", "all"):
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logger.warning(f"[Image Editing] ⚠️ Validation error in feature-limited mode - allowing operation to continue")
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else:
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raise HTTPException(status_code=500, detail=f"Image editing validation failed: {str(e)}")
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finally:
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@@ -45,6 +45,7 @@ def llm_text_gen(
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preferred_hf_models: Optional[List[str]] = None,
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preferred_provider: Optional[str] = None,
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flow_type: Optional[str] = None,
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max_tokens: Optional[int] = None,
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) -> str:
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"""
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Generate text using Language Model (LLM) based on the provided prompt.
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@@ -75,7 +76,8 @@ def llm_text_gen(
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gpt_provider = "google" # Default to Google Gemini
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model = "gemini-2.0-flash-001"
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temperature = 0.7
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max_tokens = 4000
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if max_tokens is None:
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max_tokens = 4000
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top_p = 0.9
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n = 1
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fp = 16
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@@ -371,16 +373,27 @@ def llm_text_gen(
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system_prompt=system_instructions
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)
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elif gpt_provider == "wavespeed":
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from services.llm_providers.wavespeed_provider import wavespeed_text_response
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llm_start = time.time()
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response_text = wavespeed_text_response(
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prompt=prompt,
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model=model or "openai/gpt-oss-120b",
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=top_p,
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system_prompt=system_instructions
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)
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if json_struct:
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from services.llm_providers.wavespeed_provider import wavespeed_structured_json_response
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response_text = wavespeed_structured_json_response(
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prompt=prompt,
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schema=json_struct,
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model=model or "openai/gpt-oss-120b",
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temperature=temperature,
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max_tokens=max_tokens,
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system_prompt=system_instructions
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)
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else:
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from services.llm_providers.wavespeed_provider import wavespeed_text_response
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response_text = wavespeed_text_response(
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prompt=prompt,
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model=model or "openai/gpt-oss-120b",
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=top_p,
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system_prompt=system_instructions
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)
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llm_ms = (time.time() - llm_start) * 1000
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logger.warning(f"[llm_text_gen][{flow_tag}] LLM API call took {llm_ms:.0f}ms for user {user_id} (wavespeed)")
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else:
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@@ -179,6 +179,43 @@ def get_wavespeed_api_key() -> str:
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return api_key
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def _retry_with_increased_tokens(
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client: "OpenAI",
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messages: List[Dict[str, str]],
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model: str,
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fallback_models: Optional[List[str]],
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temperature: float,
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max_tokens: int,
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) -> Optional[str]:
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"""Retry the API call with increased max_tokens when JSON parsing fails due to truncation."""
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max_tokens = min(max_tokens, 16384)
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last_error = None
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for candidate_model in _fallback_model_sequence(model, fallback_models):
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try:
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response = client.chat.completions.create(
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model=candidate_model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens,
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)
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text = response.choices[0].message.content
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text = text.strip() if text else ""
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if text.startswith("```json"):
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text = text[7:]
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if text.startswith("```"):
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text = text[3:]
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if text.endswith("```"):
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text = text[:-3]
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return text.strip()
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except NotFoundError as nf_err:
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last_error = nf_err
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continue
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if last_error:
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logger.error(f"All fallback models failed on retry with increased tokens: {last_error}")
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return None
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@retry(
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retry=retry_if_exception(_should_retry_wavespeed_error),
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wait=wait_random_exponential(min=1, max=60),
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@@ -446,24 +483,69 @@ def wavespeed_structured_json_response(
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raise last_error or Exception("WaveSpeed structured generation failed: all fallback models failed")
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response_text = response.choices[0].message.content
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response_text = response_text.strip() if response_text else ""
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# If response_format returned empty content, retry without it
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if not response_text:
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logger.warning("WaveSpeed structured call returned empty content with response_format, retrying without it...")
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response = None
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last_error = None
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for candidate_model in _fallback_model_sequence(model, fallback_models):
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try:
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response = client.chat.completions.create(
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model=candidate_model,
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messages=messages,
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temperature=temperature,
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max_tokens=max_tokens
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)
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break
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except NotFoundError as nf_err:
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last_error = nf_err
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continue
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if response is not None:
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response_text = response.choices[0].message.content
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response_text = response_text.strip() if response_text else ""
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# Clean up response text if needed
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response_text = response_text.strip()
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if response_text.startswith("```json"):
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response_text = response_text[7:]
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if response_text.startswith("```"):
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response_text = response_text[3:]
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if response_text.endswith("```"):
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response_text = response_text[:-3]
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response_text = response_text.strip()
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try:
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parsed_json = json.loads(response_text)
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logger.info("✅ WaveSpeed structured JSON response parsed successfully")
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return parsed_json
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parsed_json = json.loads(response_text) if response_text else None
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if parsed_json is not None:
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logger.info("✅ WaveSpeed structured JSON response parsed successfully")
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return parsed_json
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except json.JSONDecodeError as json_err:
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logger.error(f"❌ JSON parsing failed: {json_err}")
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logger.error(f"Raw response: {response_text}")
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# Retry once with increased max_tokens — likely a truncation issue
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if max_tokens < 16384:
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logger.warning(f"Retrying with increased max_tokens ({max_tokens} → {max_tokens * 2}) due to JSON parse failure")
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response_text = _retry_with_increased_tokens(
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client=client,
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messages=messages,
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model=model,
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fallback_models=fallback_models,
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temperature=temperature,
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max_tokens=max_tokens * 2,
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)
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if response_text:
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try:
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parsed_json = json.loads(response_text)
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if parsed_json is not None:
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logger.info("✅ WaveSpeed structured JSON parsed successfully after max_tokens increase")
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return parsed_json
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except json.JSONDecodeError:
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logger.error("❌ JSON parsing failed even after max_tokens increase")
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# Try to extract JSON from the response using regex
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logger.error(f"Raw response: {response_text}")
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# Try to extract JSON from the response using regex
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if response_text:
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json_match = re.search(r'\{.*\}', response_text, re.DOTALL)
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if json_match:
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try:
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@@ -472,8 +554,8 @@ def wavespeed_structured_json_response(
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return extracted_json
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except json.JSONDecodeError:
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pass
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return {"error": "Failed to parse JSON response", "raw_response": response_text}
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return {"error": "Failed to parse JSON response", "raw_response": response_text}
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except Exception as e:
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logger.error(f"❌ WaveSpeed API call failed: {e}")
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@@ -501,14 +583,24 @@ def wavespeed_structured_json_response(
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if response is None:
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raise last_error or e
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response_text = response.choices[0].message.content
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# ... (same parsing logic would apply, simplified here for brevity)
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response_text = response_text.strip() if response_text else ""
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# Parse JSON with robust cleaning
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if response_text.startswith("```json"):
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response_text = response_text[7:]
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if response_text.startswith("```"):
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response_text = response_text[3:]
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if response_text.endswith("```"):
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response_text = response_text[:-3]
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response_text = response_text.strip()
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try:
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return json.loads(response_text)
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except:
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# Regex fallback
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return json.loads(response_text) if response_text else {"error": "Empty response"}
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except json.JSONDecodeError:
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json_match = re.search(r'\{.*\}', response_text, re.DOTALL)
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if json_match:
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return json.loads(json_match.group())
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try:
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return json.loads(json_match.group())
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except json.JSONDecodeError:
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pass
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return {"error": "Failed to parse JSON response", "raw_response": response_text}
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raise e
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