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AI Researcher and Video Studio implementation complete

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This commit is contained in:
ajaysi
2026-01-05 15:49:51 +05:30
parent b134e9dc7e
commit 0b63ae7fc1
200 changed files with 39535 additions and 1375 deletions
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15
backend/services/research/intent/research_intent_inference.py
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@@ -51,6 +51,7 @@ class ResearchIntentInference:
competitor_data: Optional[List[Dict]] = None,
industry: Optional[str] = None,
target_audience: Optional[str] = None,
user_id: Optional[str] = None,
) -> IntentInferenceResponse:
"""
Analyze user input and infer their research intent.
@@ -96,13 +97,15 @@ class ResearchIntentInference:
"perspective": {"type": "string"},
"time_sensitivity": {"type": "string"},
"confidence": {"type": "number"},
"confidence_reason": {"type": "string"},
"great_example": {"type": "string"},
"needs_clarification": {"type": "boolean"},
"clarifying_questions": {"type": "array", "items": {"type": "string"}},
"analysis_summary": {"type": "string"}
},
"required": [
"input_type", "primary_question", "purpose", "content_output",
"expected_deliverables", "depth", "confidence", "analysis_summary"
"expected_deliverables", "depth", "confidence", "confidence_reason", "analysis_summary"
]
}
@@ -112,7 +115,7 @@ class ResearchIntentInference:
result = llm_text_gen(
prompt=prompt,
json_struct=intent_schema,
user_id=None
user_id=user_id
)
if isinstance(result, dict) and "error" in result:
@@ -134,6 +137,8 @@ class ResearchIntentInference:
suggested_keywords=self._extract_keywords_from_input(user_input, keywords),
suggested_angles=result.get("focus_areas", []),
quick_options=quick_options,
confidence_reason=result.get("confidence_reason", ""),
great_example=result.get("great_example", ""),
)
logger.info(f"Intent inferred: purpose={intent.purpose}, confidence={intent.confidence}")
@@ -166,7 +171,7 @@ class ResearchIntentInference:
if not expected_deliverables:
expected_deliverables = self._infer_deliverables_from_purpose(purpose)
return ResearchIntent(
intent = ResearchIntent(
primary_question=result.get("primary_question", user_input),
secondary_questions=result.get("secondary_questions", []),
purpose=purpose.value,
@@ -179,9 +184,13 @@ class ResearchIntentInference:
input_type=input_type.value,
original_input=user_input,
confidence=float(result.get("confidence", 0.7)),
confidence_reason=result.get("confidence_reason"),
great_example=result.get("great_example"),
needs_clarification=result.get("needs_clarification", False),
clarifying_questions=result.get("clarifying_questions", []),
)
return intent
def _safe_enum(self, enum_class, value: str, default):
"""Safely convert string to enum, returning default if invalid."""