Add AI agents tentacles for Strategies and Trading

Agent/Evaluators/__init__.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+
+from .technical_analysis_agent import *
+from .sentiment_analysis_agent import *
+from .real_time_analysis_agent import *
+from .summarization_agent import *

Agent/Evaluators/real_time_analysis_agent/__init__.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+
+from .real_time_analysis_agent import (
+    RealTimeAnalysisAIAgentChannel,
+    RealTimeAnalysisAIAgentConsumer,
+    RealTimeAnalysisAIAgentProducer,
+)
+from .models import RealTimeAnalysisOutput
+
+__all__ = [
+    "RealTimeAnalysisAIAgentChannel",
+    "RealTimeAnalysisAIAgentConsumer",
+    "RealTimeAnalysisAIAgentProducer",
+    "RealTimeAnalysisOutput",
+]

Agent/Evaluators/real_time_analysis_agent/metadata.json

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+{
+    "version": "1.0.0",
+    "origin_package": "OctoBot-Default-Tentacles",
+    "tentacles": ["RealTimeAnalysisAgent"],
+    "tentacles-requirements": []
+}

Agent/Evaluators/real_time_analysis_agent/models.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+
+"""
+Pydantic models for real-time analysis agent outputs.
+"""
+from typing import List, Optional
+from pydantic import BaseModel, Field, field_validator
+
+
+class RealTimeAnalysisOutput(BaseModel):
+    """Output from the real-time analysis agent."""
+    eval_note: float = Field(
+        ge=-1.0,
+        le=1.0,
+        description="Evaluation score from -1 (strong selling pressure) to 1 (strong buying pressure)."
+    )
+    confidence: float = Field(
+        ge=0.0,
+        le=1.0,
+        description="Confidence level of the real-time analysis (0-1)."
+    )
+    description: str = Field(
+        description="Summary description of the real-time market analysis."
+    )
+    price_momentum: Optional[float] = Field(
+        default=None,
+        ge=-1.0,
+        le=1.0,
+        description="Price momentum indicator from -1 (strong downward) to 1 (strong upward). Leave empty if no momentum."
+    )
+    current_status: Optional[str] = Field(
+        default=None,
+        description="Current market status: 'bullish', 'bearish', 'neutral', 'volatile'. Leave empty if unclear."
+    )
+    volume_signal: Optional[str] = Field(
+        default=None,
+        description="Volume analysis: 'high', 'normal', 'low'. Leave empty if no volume data."
+    )
+    urgency_level: Optional[str] = Field(
+        default=None,
+        description="Action urgency: 'immediate', 'high', 'medium', 'low', 'none'. Leave empty if no urgency."
+    )
+    critical_events: Optional[List[str]] = Field(
+        default=None,
+        description="Any critical events or catalysts detected. Leave empty if none."
+    )
+    recommendations: Optional[List[str]] = Field(
+        default=None,
+        description="Real-time trading recommendations. Leave empty if none."
+    )
+
+    @field_validator("current_status")
+    def validate_status(cls, v: str) -> str:
+        if v is None:
+            return None
+        allowed_statuses = ["bullish", "bearish", "neutral", "volatile"]
+        v_lower = v.lower()
+        if v_lower not in allowed_statuses:
+            raise ValueError(f"Status must be one of {allowed_statuses}")
+        return v_lower
+
+    @field_validator("volume_signal")
+    def validate_volume(cls, v: str) -> str:
+        if v is None:
+            return None
+        allowed_volumes = ["high", "normal", "low"]
+        v_lower = v.lower()
+        if v_lower not in allowed_volumes:
+            raise ValueError(f"Volume signal must be one of {allowed_volumes}")
+        return v_lower
+
+    @field_validator("urgency_level")
+    def validate_urgency(cls, v: str) -> str:
+        if v is None:
+            return None
+        allowed_urgencies = ["immediate", "high", "medium", "low", "none"]
+        v_lower = v.lower()
+        if v_lower not in allowed_urgencies:
+            raise ValueError(f"Urgency level must be one of {allowed_urgencies}")
+        return v_lower

Agent/Evaluators/real_time_analysis_agent/real_time_analysis_agent.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+import json
+
+import octobot_agents as agent
+
+from .models import RealTimeAnalysisOutput
+
+
+class RealTimeAnalysisAIAgentChannel(agent.AbstractAgentChannel):
+    """Channel for RealTimeAnalysisAIAgentProducer."""
+    OUTPUT_SCHEMA = RealTimeAnalysisOutput
+
+
+class RealTimeAnalysisAIAgentConsumer(agent.AbstractAIAgentChannelConsumer):
+    """Consumer for RealTimeAnalysisAIAgentProducer."""
+    pass
+
+
+class RealTimeAnalysisAIAgentProducer(agent.AbstractAIAgentChannelProducer):
+    """Producer specialized in real-time market analysis."""
+
+    AGENT_NAME = "RealTimeAnalysisAgent"
+    AGENT_VERSION = "1.0.0"
+    AGENT_CHANNEL = RealTimeAnalysisAIAgentChannel
+    AGENT_CONSUMER = RealTimeAnalysisAIAgentConsumer
+
+    def __init__(self, channel, **kwargs):
+        super().__init__(channel, **kwargs)
+
+    def _get_default_prompt(self) -> str:
+        return (
+            "You are a Real-Time Market Analysis AI expert. Follow these steps to analyze the provided real-time evaluator signals:\n"
+            "1. Examine real-time data comprehensively: Review order book dynamics, recent trades, price velocity, and market depth.\n"
+            "2. Assess market momentum: Determine current buying/selling pressure, accumulation/distribution patterns, and directional bias.\n"
+            "3. Evaluate market microstructure: Consider bid-ask spreads, order book imbalance, and trade flow characteristics.\n"
+            "4. Calculate momentum eval_note: Use the full range from -1 (strong selling pressure) to 1 (strong buying pressure), but most real-time data shows neutral to mild momentum.\n"
+            "5. Assess confidence (0-1) based on data quality: Higher confidence for strong, consistent signals; lower for noisy or conflicting data.\n"
+            "6. Provide detailed description: Explain current market dynamics, momentum indicators, and short-term outlook.\n\n"
+            "Important: Real-time momentum is rarely extreme. Use extreme values (-1/1) only for very strong, sustained pressure.\n\n"
+            "MANDATORY FIELDS (always include):\n"
+            "- eval_note: float between -1 (strong selling pressure) to 1 (strong buying pressure)\n"
+            "- confidence: float between 0 (low confidence) to 1 (high confidence)\n"
+            "- description: detailed explanation of current market momentum and dynamics\n\n"
+            "OPTIONAL FIELDS (only include if available):\n"
+            "- price_momentum: float for price momentum strength (-1 to 1) - Leave empty if not clearly identifiable\n"
+            "- current_status: string like 'accumulating', 'distributing', 'consolidating' - Leave empty if unclear\n"
+            "- volume_signal: string describing volume patterns - Leave empty if no strong volume signals\n"
+            "- urgency_level: string like 'low', 'medium', 'high' - Leave empty if no clear urgency\n"
+            "- critical_events: list of critical market events affecting momentum - Leave empty if none\n"
+            "- recommendations: list of action recommendations based on real-time analysis - Leave empty if none\n\n"
+            "If you lack data for any optional field, omit it from the response (leave as null).\n"
+            "Output only valid JSON matching the RealTimeAnalysisOutput schema."
+        )
+
+    async def execute(self, input_data, ai_service) -> dict:
+        """Evaluate aggregated real-time market data."""
+        aggregated_data = input_data
+        if not aggregated_data:
+            return {
+                "eval_note": 0,
+                "eval_note_description": "No real-time market data available",
+                "confidence": 0,
+            }
+
+        data_str = json.dumps(aggregated_data, indent=2)
+
+        messages = [
+            ai_service.create_message("system", self.prompt),
+            ai_service.create_message(
+                "user",
+                f"Real-time market data:\n{data_str}\n\n"
+                "Provide evaluation as JSON matching the RealTimeAnalysisOutput schema. "
+                "Include mandatory fields (eval_note, confidence, description). "
+                "Include optional fields only if you have data for them.",
+            ),
+        ]
+
+        try:
+            # Uses RealTimeAnalysisAIAgentChannel.OUTPUT_SCHEMA by default
+            parsed = await self._call_llm(
+                messages,
+                ai_service,
+                json_output=True,
+            )
+            eval_note = float(parsed.get("eval_note", 0))
+            eval_note_description = parsed.get("description", "Real-time analysis")
+            confidence = float(parsed.get("confidence", 0))
+
+            # Clamp values
+            eval_note = max(-1, min(1, eval_note))
+            confidence = max(0, min(1, confidence))
+
+            return {
+                "eval_note": eval_note,
+                "eval_note_description": eval_note_description,
+                "confidence": int(confidence * 100),  # Convert to 0-100 range
+            }
+        except RuntimeError as e:
+            return {
+                "eval_note": 0,
+                "eval_note_description": f"Error in real-time analysis: {str(e)}",
+                "confidence": 0,
+            }

Agent/Evaluators/sentiment_analysis_agent/__init__.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+
+from .sentiment_analysis_agent import (
+    SentimentAnalysisAIAgentChannel,
+    SentimentAnalysisAIAgentConsumer,
+    SentimentAnalysisAIAgentProducer,
+)
+from .models import SentimentAnalysisOutput
+
+__all__ = [
+    "SentimentAnalysisAIAgentChannel",
+    "SentimentAnalysisAIAgentConsumer",
+    "SentimentAnalysisAIAgentProducer",
+    "SentimentAnalysisOutput",
+]

Agent/Evaluators/sentiment_analysis_agent/metadata.json

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+{
+    "version": "1.0.0",
+    "origin_package": "OctoBot-Default-Tentacles",
+    "tentacles": ["SentimentAnalysisAgent"],
+    "tentacles-requirements": []
+}

Agent/Evaluators/sentiment_analysis_agent/models.py

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+#  Drakkar-Software OctoBot-Tentacles
+#  Copyright (c) Drakkar-Software, All rights reserved.
+#
+#  This library is free software; you can redistribute it and/or
+#  modify it under the terms of the GNU Lesser General Public
+#  License as published by the Free Software Foundation; either
+#  version 3.0 of the License, or (at your option) any later version.
+#
+#  This library is distributed in the hope that it will be useful,
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+#  Lesser General Public License for more details.
+#
+#  You should have received a copy of the GNU Lesser General Public
+#  License along with this library.
+
+"""
+Pydantic models for sentiment analysis agent outputs.
+"""
+from typing import List, Optional
+from pydantic import BaseModel, Field, field_validator
+
+
+class SentimentMetrics(BaseModel):
+    """Sentiment analysis metrics."""
+    sentiment_score: float = Field(
+        ge=-1.0,
+        le=1.0,
+        description="Sentiment score from -1 (very negative) to 1 (very positive)."
+    )
+
+    @field_validator("sentiment_score")
+    def validate_score(cls, v: float) -> float:
+        return max(-1.0, min(1.0, v))
+
+
+class SentimentAnalysisOutput(BaseModel):
+    """Output from the sentiment analysis agent."""
+    eval_note: float = Field(
+        ge=-1.0,
+        le=1.0,
+        description="Evaluation score from -1 (very negative) to 1 (very positive)."
+    )
+    confidence: float = Field(
+        ge=0.0,
+        le=1.0,
+        description="Confidence level of the sentiment analysis (0-1)."
+    )
+    description: str = Field(
+        description="Summary description of the sentiment analysis."
+    )
+    sentiment_score: float = Field(
+        ge=-1.0,
+        le=1.0,
+        description="Detailed sentiment score from -1 to 1. Same as eval_note."
+    )
+    sources_analyzed: Optional[List[str]] = Field(
+        default=None,
+        description="Data sources used for sentiment analysis. Leave empty if none identified."
+    )
+    key_mentions: Optional[List[str]] = Field(
+        default=None,
+        description="Key mentions or topics driving sentiment. Leave empty if none."
+    )
+    market_implications: Optional[str] = Field(
+        default=None,
+        description="Implications of sentiment for market direction. Leave empty if unclear."
+    )
+    recommendations: Optional[List[str]] = Field(
+        default=None,
+        description="Trading recommendations based on sentiment. Leave empty if none."
+    )