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fix(gtm): Resolve f-string SyntaxError and helpers.py incompatibility in orchestrator

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Floke
2025-12-31 14:20:30 +00:00
parent 9ee73f6229
commit 5c1f77ddbe
2 changed files with 41 additions and 19 deletions
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12
BUILDER_APPS_MIGRATION.md
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@@ -50,7 +50,19 @@ Das Projekt nutzt ein geteiltes `helpers.py`, das auf der alten OpenAI Python Li
```text ```text
openai==0.28.1 openai==0.28.1
# weitere deps... # weitere deps...
### 1.5 Python Syntax & F-Strings
Multi-Line f-Strings mit JSON-Beispielen (`{...}`) sind extrem fehleranfällig (Escaping, Einrückung).
* **Best Practice:** Komplexe JSON-Daten oder Strings **vorher** in Variablen speichern und dann einfügen.
```python
# Schlecht:
prompt = f"""Daten: {json.dumps(data.get('nested'))}"""
# Gut:
nested_json = json.dumps(data.get('nested'))
prompt = f"""Daten: {nested_json}"""
``` ```
* **Signaturen prüfen:** Shared Libraries (`helpers.py`) haben oft ältere Signaturen.
* Beispiel: `call_openai_chat` unterstützt oft kein `system_message` Argument. Stattdessen Prompt manuell zusammenbauen (`sys_instr + "\n\n" + prompt`).
--- ---

46
gtm_architect_orchestrator.py
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@@ -154,14 +154,17 @@ Output JSON format ONLY.
""" """
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_extraction_prompt = sys_instr + "\n\n" + extraction_prompt full_extraction_prompt = sys_instr + "\n\n" + extraction_prompt
extraction_response = call_openai_chat(full_extraction_prompt, json_mode=True) extraction_response = call_openai_chat(full_extraction_prompt, response_format_json=True)
extraction_data = json.loads(extraction_response) extraction_data = json.loads(extraction_response)
features_json = json.dumps(extraction_data.get('features'))
constraints_json = json.dumps(extraction_data.get('constraints'))
conflict_prompt = f""" conflict_prompt = f"""
PHASE 1-B: PORTFOLIO CONFLICT CHECK PHASE 1-B: PORTFOLIO CONFLICT CHECK
New Product Features: {json.dumps(extraction_data.get('features'))} New Product Features: {features_json}
New Product Constraints: {json.dumps(extraction_data.get('constraints'))} New Product Constraints: {constraints_json}
Existing Portfolio: Existing Portfolio:
1. "Indoor Scrubber 50": Indoor cleaning, hard floor, supermarkets. 1. "Indoor Scrubber 50": Indoor cleaning, hard floor, supermarkets.
@@ -174,8 +177,8 @@ Output JSON format ONLY.
""" if lang == 'en' else f""" """ if lang == 'en' else f"""
PHASE 1-B: PORTFOLIO CONFLICT CHECK PHASE 1-B: PORTFOLIO CONFLICT CHECK
Neue Produkt-Features: {json.dumps(extraction_data.get('features'))} Neue Produkt-Features: {features_json}
Neue Produkt-Constraints: {json.dumps(extraction_data.get('constraints'))} Neue Produkt-Constraints: {constraints_json}
Existierendes Portfolio: Existierendes Portfolio:
1. "Indoor Scrubber 50": Innenreinigung, Hartboden, Supermärkte. 1. "Indoor Scrubber 50": Innenreinigung, Hartboden, Supermärkte.
@@ -188,7 +191,7 @@ Output JSON format ONLY.
""" """
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_conflict_prompt = sys_instr + "\n\n" + conflict_prompt full_conflict_prompt = sys_instr + "\n\n" + conflict_prompt
conflict_response = call_openai_chat(full_conflict_prompt, json_mode=True) conflict_response = call_openai_chat(full_conflict_prompt, response_format_json=True)
conflict_data = json.loads(conflict_response) conflict_data = json.loads(conflict_response)
final_result = {{**extraction_data, **conflict_data}} final_result = {{**extraction_data, **conflict_data}}
@@ -199,10 +202,13 @@ def discover_icps(data):
lang = data.get('language', 'de') lang = data.get('language', 'de')
sys_instr = get_system_instruction(lang) sys_instr = get_system_instruction(lang)
features_json = json.dumps(phase1_result.get('features'))
constraints_json = json.dumps(phase1_result.get('constraints'))
prompt = f""" prompt = f"""
PHASE 2: ICP DISCOVERY & DATA PROXIES PHASE 2: ICP DISCOVERY & DATA PROXIES
Based on the product features: {json.dumps(phase1_result.get('features'))} Based on the product features: {features_json}
And constraints: {json.dumps(phase1_result.get('constraints'))} And constraints: {constraints_json}
Output JSON format ONLY: Output JSON format ONLY:
{{ {{
@@ -211,8 +217,8 @@ Output JSON format ONLY:
}} }}
""" if lang == 'en' else f""" """ if lang == 'en' else f"""
PHASE 2: ICP DISCOVERY & DATA PROXIES PHASE 2: ICP DISCOVERY & DATA PROXIES
Basierend auf Features: {json.dumps(phase1_result.get('features'))} Basierend auf Features: {features_json}
Und Constraints: {json.dumps(phase1_result.get('constraints'))} Und Constraints: {constraints_json}
Output JSON format ONLY: Output JSON format ONLY:
{{ {{
@@ -222,17 +228,18 @@ Output JSON format ONLY:
""" """
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_prompt = sys_instr + "\n\n" + prompt full_prompt = sys_instr + "\n\n" + prompt
response = call_openai_chat(full_prompt, json_mode=True) response = call_openai_chat(full_prompt, response_format_json=True)
print(response) print(response)
def hunt_whales(data): def hunt_whales(data):
phase2_result = data.get('phase2Result') phase2_result = data.get('phase2Result')
lang = data.get('language', 'de') lang = data.get('language', 'de')
sys_instr = get_system_instruction(lang) sys_instr = get_system_instruction(lang)
prompt = f"PHASE 3: WHALE HUNTING for {json.dumps(phase2_result.get('icps'))}. Identify 3-5 concrete DACH companies per industry and buying center roles. Output JSON ONLY." icps_json = json.dumps(phase2_result.get('icps'))
prompt = f"PHASE 3: WHALE HUNTING for {icps_json}. Identify 3-5 concrete DACH companies per industry and buying center roles. Output JSON ONLY."
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_prompt = sys_instr + "\n\n" + prompt full_prompt = sys_instr + "\n\n" + prompt
response = call_openai_chat(full_prompt, json_mode=True) response = call_openai_chat(full_prompt, response_format_json=True)
print(response) print(response)
def develop_strategy(data): def develop_strategy(data):
@@ -240,16 +247,18 @@ def develop_strategy(data):
phase1_result = data.get('phase1Result') phase1_result = data.get('phase1Result')
lang = data.get('language', 'de') lang = data.get('language', 'de')
sys_instr = get_system_instruction(lang) sys_instr = get_system_instruction(lang)
prompt = f"PHASE 4: STRATEGY Matrix for {json.dumps(phase3_result)}. Apply Hybrid logic. Output JSON ONLY." phase3_json = json.dumps(phase3_result)
prompt = f"PHASE 4: STRATEGY Matrix for {phase3_json}. Apply Hybrid logic. Output JSON ONLY."
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_prompt = sys_instr + "\n\n" + prompt full_prompt = sys_instr + "\n\n" + prompt
response = call_openai_chat(full_prompt, json_mode=True) response = call_openai_chat(full_prompt, response_format_json=True)
print(response) print(response)
def generate_assets(data): def generate_assets(data):
lang = data.get('language', 'de') lang = data.get('language', 'de')
sys_instr = get_system_instruction(lang) sys_instr = get_system_instruction(lang)
prompt = f"PHASE 5: GTM STRATEGY REPORT Markdown. Use facts, TCO, ROI. Data: {json.dumps(data)}" data_json = json.dumps(data)
prompt = f"PHASE 5: GTM STRATEGY REPORT Markdown. Use facts, TCO, ROI. Data: {data_json}"
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_prompt = sys_instr + "\n\n" + prompt full_prompt = sys_instr + "\n\n" + prompt
response = call_openai_chat(full_prompt) response = call_openai_chat(full_prompt)
@@ -258,10 +267,11 @@ def generate_assets(data):
def generate_sales_enablement(data): def generate_sales_enablement(data):
lang = data.get('language', 'de') lang = data.get('language', 'de')
sys_instr = get_system_instruction(lang) sys_instr = get_system_instruction(lang)
prompt = f"PHASE 6: Battlecards and MJ Prompts. Data: {json.dumps(data)}. Output JSON ONLY." data_json = json.dumps(data)
prompt = f"PHASE 6: Battlecards and MJ Prompts. Data: {data_json}. Output JSON ONLY."
# Fix: Prepend system instruction manually # Fix: Prepend system instruction manually
full_prompt = sys_instr + "\n\n" + prompt full_prompt = sys_instr + "\n\n" + prompt
response = call_openai_chat(full_prompt, json_mode=True) response = call_openai_chat(full_prompt, response_format_json=True)
print(response) print(response)
def main(): def main():